Various combinations of three bases in the coding strand of DNA are used to code for individual amino acids - shown by their three letter abbreviation
\r\n\tAt the same time, predicting and designing smarter, sustainable, resilient and livable cities is the desire of many governments and policy makers all over the world. However, there is not enough discussion around connecting the concept of smart and the concepts of desirable future cities including ‘sustainability, resilience and livability’. The concept “smart” can address intelligent transport systems for modelling and simulation, autonomous urban mobility, smart infrastructure, urban mobility, urban farms and sponge cities concepts. This book intends to provide an overview of emerging trends such as machine learning, artificial intelligence, internet of things and automation incorporated into powerful systems including online GIS to make a smarter, more sustainable, livable and resilient city.
",isbn:"978-1-83880-200-4",printIsbn:"978-1-83880-199-1",pdfIsbn:null,doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,hash:"37ca01618d7f291efb11a4d115b9cb63",bookSignature:"Dr. Sara Shirowzhan and Dr. Kefeng Zhang",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/9431.jpg",keywords:"Digital disruption, Environmental change, Rapid population growth, Smart city, Sensing technology, Remote sensing, Advanced GIS applications, Urban growth, Urban planning&management, Computational intelligence, Human-centric services, Big data evaluation, City environment monitor, Analytics and prediction, Smart City architecture, Water sensitive city",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 28th 2019",dateEndSecondStepPublish:"May 15th 2019",dateEndThirdStepPublish:"September 15th 2019",dateEndFourthStepPublish:"November 4th 2019",dateEndFifthStepPublish:"December 30th 2019",remainingDaysToSecondStep:"7 months",secondStepPassed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!0,editors:[{id:"273838",title:"Dr.",name:"Sara",middleName:null,surname:"Shirowzhan",slug:"sara-shirowzhan",fullName:"Sara Shirowzhan",profilePictureURL:"https://mts.intechopen.com/storage/users/273838/images/system/273838.jpeg",biography:"Dr Sara Shirowzhan completed her PhD in Geomatic Engineering at UNSW and her strong capability in designing and conducting high quality multi-disciplinary research has been demonstrated by solving complex problems facing digital representation and analysis of the built environment and civil engineering infrastructures. Her areas of interest for research are automation, laser scanning technologies and robotics for construction, remote sensing and advanced GIS for Smart Cities and monitoring 3D urban growth, metric development for sustainability assessment and urban infrastructures. Some of her areas of expertise include lidar technology, machine learning algorithms and app development. She has taught and supervised students in architecture, urban planning and construction departments as a lecturer, and research supervisor in several universities for over 10 years.",institutionString:"University of New South Wales",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"UNSW Sydney",institutionURL:null,country:{name:"Australia"}}}],coeditorOne:{id:"300088",title:"Dr.",name:"Kefeng",middleName:null,surname:"Zhang",slug:"kefeng-zhang",fullName:"Kefeng Zhang",profilePictureURL:"https://mts.intechopen.com/storage/users/300088/images/system/300088.jpeg",biography:"Dr. Zhang graduated from PhD in Civil Engineering at Monash University. His research areas include stormwater quality monitoring and modelling, Water Sensitive Urban Design (WSUD) green technologies (e.g. green walls and biofilters) for stormwater/greywater management, WSUD treatment validation, advanced stormwater treatment methods and integrated urban water modelling. He is the research manager of the Sino-Australia Centre on Sponge City, a large international research centre that involves partnerships between UNSW, Monash University and Dajiang Environmental Corporation, working on research areas of green technology development, urban water modelling and novel technologies for stormwater management. He is also experienced with development of integrated urban water models, e.g. UrbanBEATS (a WSUD planning support tool) and Water Sensitive Cities Toolkit (a tool to quantify the multiple benefits associated with WSUD implementations based on multidisciplinary research).",institutionString:"University of New South Wales",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"UNSW Sydney",institutionURL:null,country:{name:"Australia"}}},coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"11",title:"Engineering",slug:"engineering"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"194667",firstName:"Marijana",lastName:"Francetic",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/194667/images/4752_n.jpg",email:"marijana@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"43857",title:"Decoding the Building Blocks of Life from the Perspective of Quantum Information",doi:"10.5772/55160",slug:"decoding-the-building-blocks-of-life-from-the-perspective-of-quantum-information",body:'\nPhysical theories often start out as theories which only embrace essential features of the macroscopic world, where their predictions depend on certain parameters that have to be either assumed or taken from experiments; as a result these parameters cannot be predicted by such theories. To understand why the parameters have the values they do, we have to go one level deeper—typically to smaller scales where the easiest processes to study are the ones at the lowest level. When the deeper level reduces the number of unknown parameters, we consider the theory to be complete and satisfactory. The level below conventional molecular biology is spanned by atomic and molecular structure and by quantum dynamics. However, it is also true that at the lowest level it becomes very difficult to grasp all the features of the molecular processes that occur in living systems such that the complexity of the numerous parameters that are involved make the endeavour a very intricate one. Information theory provides a powerful framework for extracting essential features of complicated processes of life, and then analyzing them in a systematic manner. In connection to the latter, quantum information biology is a new field of scientific inquiry in which information-theoretical tools and concepts are permitting to get insight into some of the most basic and yet unsolved questions of molecular biology.
\nChirality is often glossed over in theoretical or experimental discussions concerning the origin of life, but the ubiquity of homochiral building blocks in known biological systems demands explanation. Information theory can provide a quantitative framework for understanding the role of chirality in biology. So far it has been thought that the genetic code is “unknowable” by considering DNA as a string of letters only (... ATTGCAAGC...) and likewise by considering proteins as strings of identifiers (... DYRFQ...), we believe that this particular conclusion might be probably wrong because it entirely fails to consider the information content of the molecular structures themselves and their conformations.
\nOn the other hand, according to molecular biology, living systems consist of building blocks which are encoded in nucleic acids (DNA and RNA) and proteins, which possess complex patterns that control all biological functions. Despite the fact that natural processes select particular building blocks which possess chemical simplicity (for easy availability and quick synthesis) and functional ability (for implementing the desired tasks), the most intriguing question resides in the amino acid selectivity towards a specific codon/anticodon. The universal triplet genetic code has considerable and non-uniform degeneracy, with 64 codons carrying 21 signals (including Stop) as shown in Table 1. Although there is a rough rule of similar codons for similar amino acids, no clear pattern is obvious.
\nInformation theory of quantum many-body systems is at the borderline of the development of physical sciences, in which major areas of research are interconnected, i.e., physics, mathematics, chemistry, and biology. Therefore, there is an inherent interest for applying theoretic-information ideas and methodologies to chemical, mesoscopic and biological systems along with the processes they exert. On the other hand, in recent years there has been an increasing interest in applying complexity concepts to study physical, chemical and biological phenomena. Complexity measures are understood as general indicators of pattern, structure, and correlation in systems or processes. Several alternative mathematical notions have been proposed for quantifying the concepts of complexity and information, including the Kolmogorov–Chaitin or algorithmic information theory (Kolmogorov, 1965; Chaitin, 1966), the classical information theory of Shannon and Weaver (Shannon & Weaver, 1948), Fisher information (Fisher, 1925; Frieden, 2004), and the logical (Bennet, 1988) and the thermodynamical (Lloyd & Pagels, 1988) depths, among others. Some of them share rigorous connections with others as well as with Bayes and information theory (Vitanyi & Li, 2000). The term complexity has been applied with different meanings: algorithmic, geometrical, computational, stochastic, effective, statistical, and structural among others and it has been employed in many fields: dynamical systems, disordered systems, spatial patterns, language, multielectronic systems, cellular automata, neuronal networks, self-organization, DNA analyses, social sciences, among others (Shalizi et al., 2004; Rosso et al., 2003; Chatzisavvas et al., 2005; Borgoo et al., 2007).
\nThe definition of complexity is not unique, its quantitative characterization has been an important subject of research and it has received considerable attention (Feldman & Crutchfield, 1998; Lamberti et al., 2004). The usefulness of each definition depends on the type of system or process under study, the level of the description, and the scale of the interactions among either elementary particles, atoms, molecules, biological systems, etc.. Fundamental concepts such as uncertainty or randomness are frequently employed in the definitions of complexity, although some other concepts like clustering, order, localization or organization might be also important for characterizing the complexity of systems or processes. It is not clear how the aforementioned concepts might intervene in the definitions so as to quantitatively assess the complexity of the system. However, recent proposals have formulated this quantity as a product of two factors, taking into account order/disequilibrium and delocalization/uncertainty. This is the case of the definition of López-Mancini-Calbet (LMC) shape complexity [9-12] that, like others, satisfies the boundary conditions by reaching its minimal value in the extreme ordered and disordered limits. The LMC complexity measure has been criticized (Anteonodo & Plastino, 1996), modified (Catalán et al., 2002; Martin et al., 2003) and generalized (López-Ruiz, 2005) leading to a useful estimator which satisfies several desirable properties of invariance under scaling transfromations, translation, and replication (Yamano, 2004; Yamano, 1995). The utility of this improved complexity has been verified in many fields [8] and allows reliable detection of periodic, quasiperiodic, linear stochastic, and chaotic dynamics (Yamano, 2004; López-Ruiz et al., 1995; Yamano, 1995). The LMC measure is constructed as the product of two important information-theoretic quantities (see below): the so-called disequilibrium D (also known as self-similarity (Carbó-Dorca et al., 1980) or information energy Onicescu, 1996), which quantifies the departure of the probability density from uniformity (Catalán et al., 2002; Martinet al., 2003) (equiprobability) and the Shannon entropy S, which is a general measure of randomness/uncertainty of the probability density (Shannon & Weaver, 1948), and quantifies the departure of the probability density from localizability. Both global quantities are closely related to the measure of spread of a probability distribution.
\nThe Fisher-Shannon product FS has been employed as a measure of atomic correlation (Romera & Dehesa, 2004) and also defined as a statistical complexity measure (Angulo et al., 2008a; Sen et al., 2007a). The product of the power entropy J -explicitly defined in terms of the Shannon entropy (see below)- and the Fisher information measure, I, combine both the global character (depending on the distribution as a whole) and the local one (in terms of the gradient of the distribution), to preserve the general complexity properties. As compared to the LMC complexity, aside of the explicit dependence on the Shannon entropy which serves to measure the uncertainty (localizability) of the distribution, the Fisher-Shannon complexity replaces the disequilibrium global factor D by the Fisher local one to quantify the departure of the probability density from disorder (Fisher, 1925; Frieden, 2004) of a given system through the gradient of the distribution.
\nThe Fisher information I itself plays a fundamental role in different physical problems, such as the derivation of the non-relativistic quantum-mechanical equations by means of the minimum I principle (Fisher, 1925; Frieden, 2004), as well as the time-independent Kohn-Sham equations and the time-dependent Euler equation (Nagy, 2003; Nalewajski, 2003). More recently, the Fisher information has been employed also as an intrinsic accuracy measure for specific atomic models and densities (Nagy & Sen, 2006; Sen et al., 2007b)), as well as for general quantum-mechanical central potentials (Romera et al. 2006; Dehesa et al., 2007). The concept of phase-space Fisher information has been analyzed for hydrogenlike atoms and the isotropic harmonic oscillator (Hornyak & Nagy, 2007), where both position and momentum variables are included. Several applications concern atomic distributions in position and momentum spaces have been performed where the FS complexity is shown to provide relevant information on atomic shell structure and ionization processes (Angulo et al., 2008a; Sen et al., 2007a; Angulo & Antolín, 2008b; Antolín & Angulo, 2009).
\nIn line with the aforementioned developments we have undertaken multidisciplinary research projects so as to employ IT at different levels, classical (Shannon, Fisher, complexity, etc) and quantum (von Neumann and other entanglement measures) on a variety of chemical processes, organic and nanostructured molecules. Recently, significant advances in chemistry have been achieved by use of Shannon entropies through the localized/delocalized features of the electron distributions allowing a phenomenological description of the course of elementary chemical reactions by revealing important chemical regions that are not present in the energy profile such as the ones in which bond forming and bond breaking occur (Esquivel et al., 2009). Further, the synchronous reaction mechanism of a SN2 type chemical reaction and the non-synchronous mechanistic behavior of the simplest hydrogenic abstraction reaction were predicted by use of Shannon entropies analysis (Esquivel et al., 2010a). In addition, a recent study on the three-center insertion reaction of silylene has shown that the information-theoretical measures provide evidence to support the concept of a continuum of transient of Zewail and Polanyi for the transition state rather than a single state, which is also in agreement with other analyses (Esquivel et al., 2010b). While the Shannon entropy has remained the major tool in IT, there have been numerous applications of Fisher information through the “narrowness/disorder” features of electron densities in conjugated spaces. Thus, in chemical reactions the Fisher measure has been employed to analyze its local features (Esquivel et al., 2010c) and also to study the steric effect of the conformational barrier of ethane (\n \n Esquivel et al., 2011\n\n a). Complexity of the physical, chemical and biological systems is a topic of great contemporary interest. The quantification of complexity of real systems is a formidable task, although various single and composite information-theoretic measures have been proposed. For instance, Shannon entropy (S) and the Fisher information measure (I) of the probability distributions are becoming increasingly important tools of scientific analysis in a variety of disciplines. Overall, these studies suggest that both S and I can be used as complementary tools to describe the information behavior, pattern, or complexity of physical and chemical systems and the electronic processes involving them. Besides, the disequilibrium (D), defined as the expectation value of the probability density is yet another complementary tool to study complexity since it measures its departure from equiprobability. Thus, measuring the complexity of atoms and molecules represents an interesting area of contemporary research which has roots in information theory (Angulo et al., 2010d). In particular, complexity measures defined as products of S and D or S and I have proven useful to analyze complexity features such as order, uncertainty and pattern of molecular systems (Esquivel et al., 2010f) and chemical processes (\n Esquivel et al., 2011\n\n b). On the other hand, the most interesting technological implications of quantum mechanics are based on the notion of entanglement, which is the essential ingredient for the technological implementations that are foreseen in the XXI century. Up to now it remains an open question whether entanglement can be realized with molecules or not and hence it is evident that the new quantum techniques enter the sphere of chemical interest. Generally speaking, entanglement shows up in cases where a former unit dissociates into simpler sub-systems, the corresponding processes are known quite well in chemistry. Although information entropies have been employed in quantum chemistry, applications of entanglement measures in chemical systems are very scarce. Recently, von Neumann measures in Hilbert space have been proposed and applied to small chemical systems (Carrera et al. 2010, Flores-Gallegos and Esquivel, 2008), showing than entanglement can be realized in molecules. For nanostructures, we have been able to show that IT measures can be successfully employed to analyse the growing behaviour of PAMAM dendrimers supporting the dense-core model against the hollow-core one (Esquivel et al., 2009b, 2010g, \n 2011\n c).
\nIn the Chapter we will present arguments based on the information content of L- and D-aminoacids to explain the biological preference toward homochirality. Besides, we present benchmark results for the information content of codons and aminoacids based on information-theoretical measures and statistical complexity factors which allow to elucidate the coding links between these building blocks and their selectivity.
\nIn the independent-particle approximation, the total density distribution in a molecule is a sum of contribution from the electrons in each of the occupied orbitals. This is the case in both r-space and p-space, position and momentum respectively. In momentum space, the total electron density, \n
Standard procedures for the Fourier transformation of position space orbitals generated by ab-initio methods have been described (Rawlings & Davidson, 1985). The orbitals employed in ab-initio methods are linear combinations of atomic basis functions and since analytic expressions are known for the Fourier transforms of such basis functions (Kaijser & Smith, 1997), the transformation of the total molecular electronic wavefunction from position to momentum space is computationally straightforward (Kohout, 2007).
\nAs we mentioned in the introduction, the LMC complexity is defined through the product of two relevant information-theoretic measures. So that, for a given probability density in position space, \n
where Dr is the disequilibrium (Carbó-Dorca et al., 1980; Onicescu, 1966)
\nand S is the Shannon entropy (Shannon & Weaver, 1949)
\nfrom which the exponential entropy \n
It is important to mention that the LMC complexity of a system must comply with the following lower bound (López-Rosa et al., 2009):
\nThe FS complexity in position space, Cr(FS), is defined in terms of the product of the Fisher information (Fisher, 1925; Frieden, 2004)
\nand the power entropy (Angulo et al. 2008a; Sen et al., 2007a) in position space, Jr\n
\nwhich depends on the Shannon entropy defined above. So that, the FS complexity in position space is given by
\nand similarly
\nin momentum space.
\nLet us remark that the factors in the power Shannon entropy J are chosen to preserve the invariance under scaling transformations, as well as the rigorous relationship (Dembo et al., 1991).
\nwith n being the space dimensionality, thus providing a universal lower bound to FS complexity. The definition in Eq. (8) corresponds to the particular case n=3, the exponent containing a factor 2/n for arbitrary dimensionality.
\nIt is worthwhile noting that the aforementioned inequalities remain valid for distributions normalized to unity, which is the choice that it is employed throughout this work for the 3-dimensional molecular case.
\nAside of the analysis of the position and momentum information measures, we have considered it useful to study these magnitudes in the product rp-space, characterized by the probability density\n
and
\nFrom the above two equations, it is clear that the features and patterns of both LMC and FS complexity measures in the product space will be determined by those of each conjugated space. However, the numerical analyses carried out in the next section, reveal that the the momentum space contribution plays a more relevant role as compared to the one in position space.
\nWe have also evaluated some reactivity parameters that may be useful to analyze the chemical reactivity of the aminoacids. So that, we have computed several reactivity properties such as the ionization potential (IP), the hardness (η) and the electrophilicity index (ω). These properties were obtained at the Hartree-Fock level of theory (HF) in order to employ the Koopmans\' theorem (Koopmans, 1933; Janak, 1978), for relating the first vertical ionization energy and the electron affinity to the HOMO and LUMO energies, which are necessary to calculate the conceptual DFT properties. Parr and Pearson, proposed a quantitative definition of hardness (η) within conceptual DFT (Parr & Yang, 1989):
\nwhere ε denotes the frontier molecular orbital energies and S stands for the softness of the system. It is worth mentioning that the factor 1/2 in Eq. (14) was put originally to make the hardness definition symmetrical with respect to the chemical potential (Parr & Pearson, 1983)
\nalthough it has been recently disowned (Ayer et al. 2006: Pearson, 1995). In general terms, the chemical hardness and softness are good descriptors of chemical reactivity. The former has been employed (Ayer et al. 2006: Pearson, 1995; Geerlings et al., 2003) as a measure of the reactivity of a molecule in the sense of the resistance to changes in the electron distribution of the system, i.e., molecules with larger values of η are interpreted as being the least reactive ones. In contrast, the S index quantifies the polarizability of the molecule (Ghanty & Ghosh, 1993; Roy et al., 1994; Hati & Datta, 1994; Simon-Manso & Fuentealba, 1998) and hence soft molecules are more polarizable and possess predisposition to acquire additional electronic charge (Chattaraj et al., 2006). The chemical hardness η is a central quantity for use in the study of reactivity through the hard and soft acids and bases principle (Pearson, 1963; Pearson, 1973; Pearson, 1997).
\nThe electrophilicity index (Parr et al., 1999), ω, allows a quantitative classification of the global electrophilic nature of a molecule within a relative scale. Electrophilicity index of a system in terms of its chemical potential and hardness is given by the expression
\nThe electrophilicity is also a good descriptor of chemical reactivity, which quantifies the global electrophilic power of the molecules -predisposition to acquire an additional electronic charge- (Parr & Yang, 1989).
\nThe exact origin of homochirality is one of the great unanswered questions in evolutionary science; such that, the homochirality in molecules has remained as a mystery for many years ago, since Pasteur. Any biological system is mostly composed of homochiral molecules; therefore, the most well-known examples of homochirality is the fact that natural proteins are composed of L-amino acids, whereas nucleic acids (RNA or DNA) are composed of D-sugars (Root-Bernstein, 2007; Werner, 2009; Viedma et al., 2008). The reason for this behavior continues to be a mystery. Until today not satisfactory explanations have been provided regarding the origin of the homochirality of biological systems; since, the homochirality of the amino acids is critical to their function in the proteins. If proteins (with L-aminoacids) had a non-homochiral behavior (with few D-enantiomers in random positions) they would not present biological functionality It is interesting to mention that L-aminoacids can be synthesized by use of specific enzymes, however, in prebiotic life these processes remain unknown. The same problem exists for sugars which have the D configuration. (Hein and Blackmond, 2011; Zehnacker et al., 2008; Nanda and DeGrado, 2004).
\nOn the other hand, the natural amino acids contain one or more asymmetric carbon atoms, except the glycine. Therefore, the molecules are two nonsuperposable mirror images of each other; i.e., representing right-handed (D enantiomer) and left-handed (L enantiomer) structures. It is considered that the equal amounts of D- and L- amino acids existed on primal earth before the emergence of life. Although the chemical and physical properties of L-and D amino acids are extremely similar except for their optical character, the reason of the exclusion of D-amino acids and why all living organisms are now composed predominantly of L-amino acids are not well-known: however, the homochirality is essential for the development and maintenance of life (Breslow, 2011; Fujii et al., 2010; Tamura, 2008). The essential property of α-aminoacids is to form linear polymers capable of folding into 3-dimensional structures, which form catalytic active sites that are essential for life. In the procees, aminoacids behave as hetero bifunctional molecules, forming polymers via head to tail linkage. In contrast, industrial nylons are often prepared from pairs of homo-bifunctional molecules (such as diamines and dicarboxylic acids), the use of a single molecule containing both linkable functionalities is somewhat simpler (Cleaves, 2010; Weber and Miller, 1981; Hicks, 2002).
\nThe concept of chirality in chemistry is of paramount interest because living systems are formed of chiral molecules of biochemistry is chiral (Proteins, DNA, amino acids, sugars and many natural products such as steroids, hormones, and pheromones possess chirality). Indeed, amino acids are largely found to be homochiral (Stryer, 1995) in the L form. On the other hand, most biological receptors and membranes are chiral, many drugs, herbicides, pesticides and other biological agents must themselves possess chirality. Synthetic processes ordinarily produce a 50:50 (racemic) mixture of left-handed and right-handed molecules (so-called enantiomers), and often the two enantiomers behave differently in a biological system.
\nOn the other hand, a major topic of research has been to study the origin of homochirality. In this respect, biomembranes have played an important role for the homochiraility of biopolymers. One of the most intriguing problems in life sciences is the mechanism of symmetry breaking. Many theories have been proposed on these topics and in the attempt to explain the amplification of a first enantiomeric imbalance to the enantiopurity of biomolecules (Bombelli et al., 2004). In all theories on symmetry breaking and on enantiomeric excess amplification little attention has been paid to the possible role of biomembranes, or of simple self-aggregated systems that may have acted as primitive biomembranes. Nevertheless, it is possible that amphiphilic boundary systems, which are considered by many scientists as intimately connected to the emergence and the development of life (Avalos et al. 2000; Bachmann et al., 1992), had played a role in the history of homochirality in virtue of recognition and compartmentalization phenomena (Menger and Angelova, 1998). In general, the major reason for the different recognition of two enantiomers by biological cells is the homochirality of biomolecules such as L-amino acids and D-sugars. The diastereomeric interaction between the enantiomers of a bioactive compound and the receptor formed from a chiral protein can cause different physiological responses. The production technology of enantiomerically enriched bioactive compounds one of the most important topics in chemistry. There is great interest in how and when biomolecules achieved high enantioenrichment, including the origin of chirality from the standpoint of chiral chemistry (Zehnacker et al., 2008; Breslow, 2011; Fujii et al., 2010; Tamura, 2008; Arnett and Thompson, 1981)
\nFigure l illustrates a Venn diagram (Livingstone & Barton, 1993; Betts & Russell, 2003) which is contained within a boundary that symbolizes the universal set of 20 common amino acids (in one letter code). The amino acids that possess the dominant properties—hydrophobic, polar and small (< 60 Å3)—are defined by their set boundaries. Subsets contain amino acids with the properties aliphatic (branched sidechain non-polar), aromatic, charged, positive, negative and tiny (<35 Å 3). Shaded areas define sets of properties possessed by none of the common amino acids. For instance, cysteine occurs at two different positions in the Venn diagram. When participating in a disulphide bridge (CS-S), cysteine exhibits the properties \'hydrophobic\' and \'small\'. In addition to these properties, the reduced form (CS-H) shows polar character and fits the criteria for membership of the \'tiny\' set. Hence, the Venn diagram (Figure l) assigns multiple properties to each amino acid; thus lysine has the property hydrophobic by virtue of its long sidechain as well as the properties polar, positive and charged. Alternative property tables may also be defined. For example, the amino acids might simply be grouped into non-intersecting sets labelled, hydrophobic, charged and neutral.
\nVenn diagram (Livingstone & Barton, 1993; Betts & Russell, 2003) of boundaries that symbolizes the universal set of 20 common amino acids (b). The Venn diagram in Fig. (1a) may be simply encoded as the property table or index shown here where the rows define properties and the columns refer to each amino acid.
In order to perform a theoretical-information analysis of L- and D-aminoacids we have employed the corresponfing L-enantiomers reported in the Protein Data Bank (PDB), which provide a standard representation for macromolecular structure data derived from X-ray diffraction and NMR studies. In a second stage, the D-type enantiomers were obtained from the L-aminoacids by interchanging the corresponding functional groups (carboxyl and amino) of the α-carbon so as to represent the D-configuration of the chiral center, provided that steric impediments are taken into account. The latter is achieved by employing the Ramachandran (Ramachandran et al, 1963) map, which represent the phi-psi torsion angles for all residues in the aminoacid structure to avoid the steric hindrance. Hence, the backbone of all of the studied aminoacids represent possible biological structures within the allowed regions of the Ramachandran. In the third stage, an electronic structure optimization of the geometry was performed on all the enantiomers for the twenty essential aminoacids so as to obtain structures of minimum energy which preserve the backbone (see above). In the last stage, all of the information-theoretic measures were calculated by use of a suite of programs which have been discussed elsewhere (Esquivel et al., 2012).
\nIn Figures 2 through 4 we have depicted some selected information-theoretical measures and complexities in position space versus the number of electrons and the energy. For instance, it might be observed from Fig. 2 that the Shannon entropy increases with the number of electrons so that interesting properties can be observed, e.g., the aromatic ones possess more delocalized densities as the rest of the aminoacids (see Figure 1B) which confer specific chemical properties. On the other hand, the disequilibrium diminishes as the number of electron increases (see Fig. 2), which can be related to the chemical stability of the aminoacids, e.g., cysteine and metionine show the larger values (see Fig. 2) which is in agreement with the biological evidence in that both molecules play mutiple functions in proteins, chemical as well as structural, conferring the higher reactivity that is recognized to both molecules. In contrast, aromatic aminoacids (see Fig 1B) are the least reactive, which is in agreement with the lower disequilibrium values that are observed form Fig 2.
\nShannon entropy (left) and disequilibrum (right), both in position space, versus the number of electrons, for the set of 20 aminoacids.
LMC- (left) and FS-complexities (right), both in position space, versus the number of electrons, for the set of 20 aminoacids.
LMC- (left) and FS-complexities (right), both in position space, versus the total energy, for the set of 20 aminoacids.
In Figures 3 we have plotted the LMC and FS complexities versus the number of electrons for the twenty aminoacids where we can observe that LMC complexity disntinguishes two different groups of aminoacids, where the more reactive (met and cys) hold larger values. In contrast, FS complexity behaves linearly with the number of electrons where the aromatic aminoacids possess the larger values and hence represent the more complex ones. Furthemore, the behavior of the LMC and FS complexities with respect to the total energy is analyzed in Figures 4, to note that LMC complexity characterizes two different groups of aminoacids where the most reactive (cys and met) possess the largest values, which incidentally hold the largest energies (negatively). A different behavior is observed for the FS complexity in that the smaller values correspond to the less energetic aminoacids. It is worthy to mention that the FS complexity is related to the Fisher information measure (Eq. 7) which depends on the local behavior of the position space density, i..e., simpler molecules present more ordered chemical structures, and hence these kind of aminoacids are expected to be less complex, e.g., the small and the tiny ones (Ser, Ala, Thr).
\nIn Figures 5 through 8 we have analyzed the homochiral behavior of all aminoacids by plotting the difference between the L and the D values of several physical properties (energy, ionization potential, hardness, electrophilicity) and some relevant information-theoretical measures (Shannon entropy, Fisher, LMC- and FS-complexity). From Figures 5 and 6 one can readily observe that none of the physical properties studied in this work show a uniform enantiomeric behavior, i.e., it is not possible to distinguish the L-aminoacids from the D-ones by using an specific physical property. In contrast, the L-aminoacids can be uniquely characterize d from the D-ones when informatic-theoretical measures are employed (see Figures 7 and 8) and this is perhaps the most interesting result obtained from our work. To the best of our kowledge no similar observations have been reported elsewhere, showing strong evidence of the utility of Information Theory tools for decoding the essential blocks of life.
\nDifferences (L-property – D-property) for the energy (in a.u., left) and the ionization potential (in a.u., right) for the set of 20 aminoacids.
Differences (L-property – D-property) for the hardness (in a.u., left, Eqn. 14) and the electrophilicity (in a.u., right, Eqn. 16) for the set of 20 aminoacids.
Differences (L-property – D-property) for the Shannon entropy (Eqn. 4, left) and the Fisher information (right, Eqn. 7), both in position space, for the set of 20 aminoacids.
Differences (L-property – D-property) for the LMC (left, Eqn. 2) and the FS-complexities (right, Eqn. 9), both in position space, for the set of 20 aminoacids.
The genetic code refers to a nearly universal assignment of codons of nucleotides to amino acids. The codon to amino acid assignment is realized through: (i) the code adaptor molecules of transfer RNAs (tRNAs) with a codon’s complementary replica (anticodon) and the corresponding amino acid attached to the 3’ end, and (ii) aminoacyl tRNA synthetases (aaRSs), the enzymes that actually recognize and connect proper amino acid and tRNAs. The origin of the genetic code is an inherently difficult problem (Crick, 1976). Taking into a count that the events determining the genetic code took place long time ago, and due to the relative compactness of the present genetic code. The degeneracy of the genetic code implies that one or more similar tRNA can recognize the same codon on a messenger mRNA. The number of amino acids and codons is fixed to 20 amino acids and 64 codons (4 nucleotides, A.C.U.G per three of each codon) but the number of tRNA genes varies widely 29 to 126 even between closely related organisms. The frequency of synonymous codon use differs between organisms, within genomes, and along genes, a phenomenon known as CUB (codon usage bias) (Thiele et al., 2011).
\nSequences of bases in the coding strand of DNA or in messenger RNA possess coded instructions for building protein chains out of amino acids. There are 20 amino acids used in making proteins, but only four different bases to be used to code for them. Obviously one base can\'t code for one amino acid. That would leave 16 amino acids with no codes. By taking two bases to code for each amino acid, that would still only give you 16 possible codes (TT, TC, TA, TG, CT, CC, CA and so on) – that is, still not enough. However, by taking three bases per amino acid, that gives you 64 codes (TTT, TTC, TTA, TTG, TCT, TCC and so on). That\'s enough to code for everything with lots to spare. You will find a full table of these below. A three base sequence in DNA or RNA is known as a codon.
\n\n | \n
Various combinations of three bases in the coding strand of DNA are used to code for individual amino acids - shown by their three letter abbreviation
The codes in the coding strand of DNA and in messenger RNA aren\'t, of course, identical, because in RNA the base uracil (U) is used instead of thymine (T). Table 1 shows how the various combinations of three bases in the coding strand of DNA are used to code for individual amino acids - shown by their three letter abbreviation. The table is arranged in such a way that it is easy to find any particular combination you want. It is fairly obvious how it works and, in any case, it doesn\'t take very long just to scan through the table to find what you want. The colours are to stress the fact that most of the amino acids have more than one code. Look, for example, at leucine in the first column. There are six different codons all of which will eventually produce a leucine (Leu) in the protein chain. There are also six for serine (Ser). In fact there are only two amino acids which have only one sequence of bases to code for them - methionine (Met) and tryptophan (Trp). Note that three codons don\'t have an amino acid but "stop" instead. For obvious reasons these are known as stop codons. The stop codons in the RNA table (UAA, UAG and UGA) serve as a signal that the end of the chain has been reached during protein synthesis. The codon that marks the start of a protein chain is AUG, that\'s the amino acid, methionine (Met). That ought to mean that every protein chain must start with methionine.
\nAn important goal of the present study is to characterize the biological units which codify aminoacids by means of information-theoretical properties. To accomplished the latter we have depicted in Figures 9 through 13 the Shannon entropy, Disequilibrium, Fisher and the LMC and FS complexities in position space as the number of electron increases, for the group of the 64 codons. A general observation is that all codons hold similar values for all these properties as judging for the small interval values of each graph. For instance, the Shannon entropy values for the aminoacids (see Figure 2) lie between 4.4 to 5.6, whereas the corresponding values for the codons (see Figure 9) lie between 6.66 to 6.82, therefore this information measure serves to characterize all these bilogical molecules, providing in this way the first benchmark informational results for the building blocks of life. Further, it is interesting to note from Figures 9 and 10 that entropy increases with the number of electrons (Fig. 9) whereas the opposite behavior is observed for the Disequilibrium measure. Besides, we may note from these Figures an interesting codification pattern within each isolelectronic group of codons where one may note that an exchange of one nucleotide seems to occur, e.g., as the entropy increases in the 440 electron group the following sequence is found: UUU to (UUC, UCU, CUU) to (UCC, CUC, CCU) to CCC. Similar observations can be obtained from Figures 10 and 11 for D and I, respectively. In particular, Fisher information deserves special analysis, see Figure 11, from which one may observe a more intricated behavior in which all codons seem to be linked across the plot, i.e., note that for each isoelectronic group codonds exchange only one nucleotide, e.g., in the 440 group codons change from UUU to (UUC, UCU, CUU) to (UCC, CUC, CCU) to CCC as the Fisher measure decreaes. Besides, as the Fisher measure and the number of electrons increase linearly a similar exchange is observed, eg., from AAA to (AAG, AGA, GAA) to (AGG, GAG, GGA) to GGG. We believe that the above observations deserve further studies since a codification pattern seems to be apparent.
\nIn Figures 12 and 13 we have depicted the LMC and FS complexities, respectively, where we can note that as the number of electron increases the LMC complexity decreases and the opposite is observed for the FS complexity. It is worth mentioning that similar codification patternsm, as the ones above discussed, are observed for both complexities. Furthermore, we have found interesting to show similar plots in Figures 14 and 15 where the behavior of both complexities is shown with respect to the total energy. It is observed that as the energy increases (negatively) the LMC complexity decreases whereas the FS complexity increases. Note that similar codification patterns are observed in Figure 15 for the FS complexity.
\nShannon entropy values in position spaces as a function of the number of electrons for the set of 64 codons.
Disequilibrium in position spaces (Eqn. 3)as a function of the number of electrons for the set of 64 codons
Fisher information in position spaces (Eqn. 7) as a function of the number of electrons for the set of 64 codons
LMC-complexity in position spaces (Eqn.12) as a function of the number of electrons for the set of 64 codons
FS-complexity in position spaces (Eqn. 7) as a function of the number of electrons for the set of 64 codons
LMC-complexity in position spaces as a function of the total energy for the set of 64 codons.
FS-complexity in position space as a function of the total energy for the set of 64 codons.
We have shown throughout this Chapter that information-theoretical description of the fundamental biological pieces of the genetic code: aminoacids and codons, can be analysed in a simple fashion by employing Information Theory concepts such as local and global information measures and statistical complexity concepts. In particular, we have provided for the first time in the literature with benchmark information-theoretical values for the 20 essential aminacids and the 64 codons for the nucleotide triplets. Throughout these studies, we believe that information science may conform a new scientific language to explain essential aspects of biological phenomena. These new aspects are not accessible through any other standard methodology in quantum chemistry, allowing to reveal intrincated mechanisms in which chemical phenomena occur. This envisions a new area of research that looks very promising as a standalone and robust science. The purpose of this research is to provide fertile soil to build this nascent scientific area of chemical and biological inquiry through information-theoretical concepts towards the science of the so called Quantum Information Biology.
\nWe wish to thank José María Pérez-Jordá and Miroslav Kohout for kindly providing with their numerical codes. We acknowledge financial support through Mexican grants from CONACyT, PIFI, PROMEP-SEP and Spanish grants MICINN projects FIS2011-24540, FQM-4643 and P06-FQM-2445 of Junta de Andalucía. J.A., J.C.A., R.O.E. belong to the Andalusian researchs groups FQM-020 and J.S.D. to FQM-0207. R.O.E. wishes to acknowledge financial support from the CIE-2012. CSC., acknowledges financial support through PAPIIT-DGAPA, UNAM grant IN117311. Allocation of supercomputing time from Laboratorio de Supercómputo y Visualización at UAM, Sección de Supercomputacion at CSIRC Universidad de Granada, and Departamento de Supercómputo at DGSCA-UNAM is gratefully acknowledged.
\nBamboos are described as one of the most important renewable, easily obtained, and valuable of all forest resources. Bamboo species have been known and used by human kind since the beginning of civilization; its use as building materials can be traced back to the pre-ceramic period 9500 years ago, while relics from bamboo mats and baskets were dated at 3300-2800 BC [1]. In Asian countries, their leaves are used as a food wrapping material to prevent food deterioration since ancient times, besides using the culms as a construction material. In this region, bamboo leaves are described in the traditional medicine for treating hypertension, arteriosclerosis, cardiovascular disease, and certain forms of cancer. These therapeutic properties are most likely mediated by their antioxidant capacity.
These plants form a large subfamily of the grasses (Poaceae: Bambusoideae), comprising about 1662 species distributed in 121 genera. Bamboos present a large range of functional forms found over numerous biogeographic regions, including dwarf herbaceous species in temperate climates and giant tropical woody species that can reach up to 20 m height [2]. These species can adapt and propagate in inhospitable environments, such as humid and cold mountain tops as well as the ones dry and warm [3], naturally occurring in all continents except Europe [4]. Bamboos play an important role in South American forest diversity. Brazil is the country with the greatest number of native bamboo species in the New World [5]. This means that 89% of the genera and 65% of known bamboo species (36 genera and 254 species) are distributed among the Atlantic Forest, the Cerrado, and the Amazon [6].
Bamboos have a large ecological amplitude in response to canopy disturbances and can become super dominant species after opening in natural or anthropic origin. In addition, they have a very rapid growth from the stem base to the top of the plant [7]. Currently, bamboo species are considered as one of the most available forest resources. In tropical and subtropical areas, bamboos represent approximately 20–25% of the total biomass, which contributes to their status as one of the most important renewable resources [8]. Considered a rapid atmospheric carbon sink, bamboo has also physical and mechanical properties that make it suitable to be used in the development of products normally produced with native wood or from reforestation, such as construction components, furniture industry, cables for agricultural tools, panels, and plates, among others.
Bamboo species share some common characteristics of their phenolic composition with other grasses. They contain several glycosylated flavones whose aglycones are represented by apigenin, luteolin, and tricin [9, 10, 11]. This is also the case in, for example, durum wheat (Triticum durum) [12] and barley (Hordeum vulgare) [13]. Just as in other grass species, such as corn, wheat, and rice [14], most glycosides are conjugated via a C-linkage to the flavone aglycone. In China, their phenolic compounds are used to make a preparation, called antioxidant of bamboo leaves (AOB), to be applied as food antioxidant whose use is sanctioned by the local Health Ministry. The AOB is composed mainly by flavonoids, lactones, and phenolic acids. The main flavonoids found in AOB are the flavone C-glycosides such as orientin, homoorientin, vitexin, and isovitexin [15].
The production of reactive oxygen species (ROS) is a result of normal cell metabolism; however, once the oxidative processes start to be predominant over the antioxidant, the imbalance called “oxidative stress” can be harmful to human body [16]. Oxygen’s reactivity, which is under normal conditions, permits the high-energy electron transfer allowing the formation of big quantities of adenosine-5-triphosphate (ATP) by the oxidative phosphorylation and jeopardizes the cells of living organisms by attacking molecules such as proteins, lipids, or DNA [17]. Free radicals created in this process cause various genetic changes causing cancer, cardiovascular and neurological diseases, nephropathy, rheumatoid arthritis, and other disorders [18]. Plants provide an abundant source of the substances with biological activity. In case of antioxidant protection, flavonoids stand for one of the most efficient molecules combating the oxidative stress.
There are two terms describing the antioxidant efficacy: “antioxidant activity” and “antioxidant capacity,” and they have different meanings. The prior expresses the kinetics of a reaction between an antioxidant and the prooxidant or radical scavenging activity, and the latter one measures the thermodynamic conversion efficiency of the reaction. The analytical methods to evaluate antioxidant activity may be divided into electron transfer (ET)-based and hydrogen atom transfer (HAT)-based methods. ET-based methods utilize the process of the reduction in the oxidative component by the antioxidant, which leads to the change in color that can be observed [19]. Within this group, we can specify: DPPH (2,2-di(4-tert-octylphenyl)-1-picrylhydrazyl) method, ABTS (2,2′-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid), FRAP (ferric reducing antioxidant power), and CUPRAC (cupric reducing antioxidant capacity). HAT-based assays include for instance oxygen radical absorbance capacity (ORAC) reaction, detectable by the fluorescence loss of fluorescein. More “functional” analyses count the number of lipid oxidation products like thiobarbituric acid-reactive substances (TBARS) or evaluate a desired health effect of the product [19, 20].
The majority researchers working with bamboo-derived products use DPPH, ABTS, and FRAP methods or the combination of those to evaluate the antioxidant effect of their samples, when ORAC is less common. Values are expressed in the percentage of the radical inhibition, IC50, which is an inhibitory concentration (concentration needed to deactivate 50% of the radical formation) or Trolox equivalents. Table 1 demonstrates the results grouped by the method and unit used by the authors, and Table 2 shows IC50 against DPPH of the compounds isolated from the bamboo species.
Bamboo species | Sample | DPPH | ABTS | FRAP | ORAC | Ref. |
---|---|---|---|---|---|---|
Phyllostachys heterocycla cv. pubescens | Essential oil | 2.85* | [21] | |||
P. heterocycla cv. gracilis | Essential oil | 4.44* | ||||
P. heterocycla cv. heterocycla | Essential oil | 3.82* | ||||
P. kwangsiensis | Essential oil | 4.93* | ||||
Merostachys pluriflora Munro ex. C. G. Camus | Leaf ethanol | 119.51 | 25.65 | 92.08 | 5.79 | [22] |
Leaf hydromethanolic | 137.37 | 16.30 | 85.73 | 6.18 | ||
Leaf ethyl acetate | 117.68 | 19.66 | 51.88 | 2.73 | ||
Leaf dichloromethane | 190.73 | 37.21 | 89.69 | 6.05 | ||
Culm ethanol | 181.92 | 39.51 | 62.02 | 4.20 | ||
Culm hydromethanolic | 413.80 | 47.22 | 108.50 | 9.33 | ||
Culm ethyl acetate | 244.85 | 33.25 | 51.22 | 3.47 | ||
Culm dichloromethane | — | 60.69 | 27.92 | 1.22 | ||
Culm hexane | 296.94 | 94.77 | 145.80 | 9.10 | ||
P. pubescens (Pradelle) Mazel ex J. Houz | Leaf ethanol | — | [23] | |||
Branch ethanol | 350.60 | |||||
Inner culm at 1 m height ethanol | 373.80 | |||||
Inner culm at 5 m height ethanol | 88.50 | |||||
Rhizome ethanol | 171.50 | |||||
Leaf water | 306.70 | |||||
Branch water | 179.50 | |||||
Inner culm at 1 m height water | 231.90 | |||||
Inner culm at 5 m height water | 198.30 | |||||
Rhizome water | 266.70 | |||||
Shoot methanol | 3600.00 | [24] | ||||
Shoot chloroform | 4000.00 | |||||
Shoot ethyl acetate | 800.00 | |||||
Shoot butanolic | 700.00 | |||||
Shoot water | 4700.00 | |||||
Pseudosasa amabilis McClure | Essential oil | 5.29* | [25] | |||
Pleioblastus gramineus (Bean) Nakai | Essential oil | 6.50* | ||||
P. vivax f. aureocaulis N.X.Ma. | Essential oil | 7.53* | ||||
Indocalamus latifolius (Keng) McClure | Essential oil | 4.99* | ||||
P. nigra (Lodd. ex Lindl.) Munro | Shoot methanol | 3400.00 | [24] | |||
Shoot Chloroform | 2300.00 | |||||
Shoot ethyl acetate | 400.00 | |||||
Shoot butanolic | 800.00 | |||||
Shoot water | 5300.00 | |||||
Sasa borealis (Hack.) Makino and Shibata | Leaf butanolic | 51.00 | [9] |
Antioxidant activity of different bamboo species.
Values recalculated from μL/mL to μg/mL, assuming that the density of an essential oil is approximately 0.9 g/mL.
ABTS—scavenging ABTS(2,2′-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid) cation radical effect; DPPH—scavenging DPPH (2,2-di(4-tert-octylphenyl)-1-picrylhydrazyl)radical effect; FRAP—ferric reducing antioxidant power; all the values in the table are the—IC50 [μg/mL]—inhibitory concentration, concentration needed to diminish the production the radical/oxidized product by 50%; ORAC—oxygen radical absorbance capacity.
Bamboo species | Part of the plant | Isolated compound | DPPH (IC50) | Reference |
---|---|---|---|---|
Sasa borealis (Hack.) Makino and Shibata | Leaves | Isoorientin | 9.5 | [9] |
Isoorientin 2-O-α- | 34.5 | |||
Apigenin 6-C-β- | 161.5 | |||
Phyllostachys edulis (Carrière) J. Houz. | Leaves | 3-O-(3′-methylcaffeoyl) quinic acid | 16.00 | [26] |
5-O-caffeoyl-4-methylquinic acid | 8.8 | |||
3-O-caffeoyl-1-methylquinic acid | 6.9 |
Antioxidant activity of isolated compounds of bamboos.
DPPH—scavenging DPPH (2,2-di(4-tert-octylphenyl)-1-picrylhydrazyl) radical effect; IC50—inhibitory concentration, concentration needed to diminish the production of DPPH radical by 50% [μM].
The most popular method (also as per the number of results included in Table 1) is the certainty DPPH radical scavenging test. IC50 is a unit that is easy to compare because it gives an idea of the concentration, which is necessary to decrease the radical formation by 50%. The values obtained for different species of bamboo varied between 51 μg/mL for Sasa borealis (leaf butanolic fraction) [9] and 5300 μg/mL for Phyllostachys nigra (shoot water fraction) [24]. The highest antiradicalar activity was obtained in case of butanol, ethyl acetate, and ethanol fractions. Although leaf extracts seemed to be the part of the plant that provides reasonably good results, essential oils were efficient in much smaller concentrations. The essential oil from Phyllostachys heterocycla cv. pubescens had IC50 of only 2.85 μg/mL (value recalculated from μL/mL for comparison purposes if the density of an essential oil is approximately 0.9 g/mL) as reported by Jin et al. [21]. The worst in the group, but still with high activity, was an essential oil from Phyllostachys vivax f. aureocaulis
Two from the chosen authors [10, 26] described the results for two Asian bamboo species: Phyllostachys nigra v. henonis and Phyllostachys edulis in the percentage of DPPH inhibition. The 20 μg/mL ethanol extract from the first species managed to suppress 40.9% of the radical formation, whereas the second one, depending on the fraction, was able to decrease it from 30.4 to 79.1% (chloroform and butanol fractions, respectively) in the concentration of 100 μg/mL. Both authors investigated in parallel the influence of the bamboo samples on lipid peroxidation. It was confirmed that the P. nigra scavenging effect reduced the rate of liposome peroxidation and human LDL (low-density lipoprotein) oxidation suppressing DNA modifications [10]. 3-O-caffeoyl-1-methylquinic acid (shown in Table 2), isolated from P. edulis, exhibited 36% of the inhibition of superoxide generation in human promyelocytic leukemia HL-60 cells [26].
The results expressed in IC50 for the DPPH and other methods such as ABTS, FRAP, and ORAC varied due to different mechanisms of action between prooxidant and antioxidant molecules. An ethyl acetate fraction from a Brazilian bamboo, Merostachys pluriflora, defined as the most active fraction from this species against DPPH (IC50 = 117.68 μg/mL), the second most active against ABTS cation radical (IC50 = 19.66 μg/mL) was also quite potent ferric reducing (IC50 = 51.88 μg/mL) and oxygen radical scavenging (IC50 = 2.73 μg/mL) agent. On the other hand, dichloromethane culm fraction from the same plant, not so active against DPPH nor ABTS, reduced almost two times more the ferric cation in the FRAP method than the previous sample (IC50 = 27.92 μg/mL) and was an excellent scavenger of the oxygen radical in ORAC assay (IC50 = 1.22 μg/mL) [22]. No direct correlation between the results assessed by ABTS and ORAC was also found in another study, evaluating the antioxidant activity of different parts of P. pubescens [23].
Trolox equivalents received by two methods: DPPH and FRAP were also compared, and it was found that in case of P. heterocycla cv. pubescens, gracilis, Tao Kiang, and P. aureosulcata, leaf and shoots in both evaluations were very similar to the TE content. Additionally, the extract that was the richest in TE in DPPH assay (P. heterocycla leaf) had also the highest value of it in the FRAP method [27]. As per this author, the shoots of bamboo were the part of the plant with the poorest antioxidant activity.
In general, bamboos were classified as good antioxidants, which can be related to their high flavonoid and phenol contents [27]. The scavenging activity against superoxide anion and hydroxyl radical of some methanol and hot water extracts from a bamboo powder, used in Japan for different purposes, was higher than the ones received for the control—α-tocoferol and ascorbic acid [28]. A polysaccharide-rich extract from Bambusa rutila had hydroxyl radical scavenging activity equal to vitamin C [29], where an isoorientin and its ester, derived from a Chinese product called antioxidant of bamboo leaves (AOB), had their IC50 lower than vitamin E [30]. The acylation of isoorientin was performed to improve its solubility in lipidic media, however, the process did not have a positive impact on the antioxidant activity of the substance. A nutritional formulation developed from bamboo vinegar (5%) and maltodextrin (30%) had better in vitro antioxidant effect that tested commercial beverages [31]. In other study, it was proved that bamboo oil from P. bambusoides, when incubated for 20 h, had its linoleic acid scavenging rate similar to that of ascorbic acid [32].
Few studies of the functional antioxidant activity with correlated health effect were described in the literature as well. The lignophenol derivatives obtained from a wood mixture containing bamboo P. bambusoides demonstrated neuroprotective activity in cells influenced by hydrogen peroxide-induced apoptosis [33]. A short-term assay established that both Asp-Tyr identified and isolated from P. pubescens shoot fractions diminished significantly the systolic blood pressure of spontaneously hypertensive rats [34]. An extract from Sasa senanensis, named Absolutely Hemicellulose Senanensis (AHSS), had determined its in vivo activity, and it was shown that it inhibited the production of lipid peroxide by intestinal ischemia and subsequent reperfusion (I/R) injury model in rats [35].
Quality and safety of various products can be affected by the presence of microorganisms; therefore, antimicrobial substances are widely used in cosmetic, food, and pharmaceutical industries. In cosmetics, preservatives protect the formulation during the production and the use by the consumers [36]. In the food industry, these additives can improve organoleptic characteristics of food, such as color, smell, and taste, in addition to the protection of food during production, storage, and consumption [37]. The growing microbial resistance to existing drugs has generated the need for the pharmaceutical industry to search for new molecules that can be used as preservatives, antibiotics, and disinfectants [38]. This factor associated with the toxicity of certain additives [39] and the consumer appeals for the reduction in synthetic substances [40], encourage the search for alternative solutions. The complexity and molecular diversity of natural products make them an interesting source of new molecules [41].
The antimicrobial capacity of bamboo species was evaluated through several methodologies, resulting in different units for the presentation of the results. In Table 3, results are shown as minimal inhibitory concentration (MIC), which is the lowest concentration that is able to completely inhibit microbial growth.
Bamboo species | Product | Microorganism | MIC (μg/mL) | Ref. |
---|---|---|---|---|
P. heterocycla var. pubescens (Pradelle) Ohwi | 2,6-Dimethoxy-p-benzoquinone | Escherichia coli | 400 | [42] |
Bacillus subtilis | 200 | |||
Salmonella typhimurium | 400 | |||
Sarcina lutea | 400 | |||
Pseudomonas aeruginosa | 800 | |||
Staphylococcus aureus | 200 | |||
Candida albicans | 800 | [43] | ||
Saccharomyces cerevisiae | 25 | |||
10 | ||||
25 | ||||
800 | ||||
Aspergillus niger | 800 | |||
Chloroform/methanol extract (bark) | Escherichia coli | 10,000 | [44] | |
Bacillus subtilis | 5000 | |||
Salmonella typhimurium | 10,000 | |||
Sarcina lutea | 10,000 | |||
P. heterocycla var. pubescens (Pradelle) Ohwi | Chloroform/methanol extract (bark) | Pseudomonas aeruginosa | 50,000 | [44] |
Staphylococcus aureus | 2000 | |||
Essential oil | Escherichia coli | 31.76* | [21] | |
Staphylococcus aureus | 31.76* | |||
P. pubescens (Pradelle) Mazel ex J. Houz. | Ethanol extract (outer culm) | Staphylococcus aureus | 400 | [23] |
P. pubescens (Pradelle) Mazel ex J. Houz. | Hot water extract (leaf) | Staphylococcus aureus | 1200 | [23] |
Hot water extract (branch) | Staphylococcus aureus | 1400 | ||
Hot water extract (inner culm) | Staphylococcus aureus | >16,000 | ||
P. kwangsiensis W.Y. Hsiung, Q.H. Dai and J.K. Liu | Essential oil | Escherichia coli | 31.76* | [21] |
Staphylococcus aureus | 22.23* | |||
P. heterocycla fo. gracilis (W.Y. Hsiung ex Houz.) T.P. Yi | Essential oil | Escherichia coli | 31.76* | |
Staphylococcus aureus | 22.23* | |||
P. heterocycla (Carrière) Mitford cv heterocycla | Essential oil | Escherichia coli | 31.76* | |
Staphylococcus aureus | 45.24* |
Antimicrobial activity of bamboo extracts—MIC.
Concentration calculated considering the density value 0.9.
The lower the MIC values, the more potent the substance is. To be considered as promising antimicrobial agents, natural products must have MICs below 100 μg/mL [39]. Therefore, the essential oils of Phyllostachys kwangsiensis, P. heterocycla cv. gracilis, and P. heterocycla cv. Heterocycla are the most active extracts, with MIC values ranging from 22.23 to 45.24 μg/mL for S. aureus and 31.76 μg/mL for E coli. 2,6-Dimethoxy-p-benzoquinone presented lower values than the essential oils; however, it is an isolated compound and not an extract. It is possible to affirm that the essential oils evaluated have an intense antimicrobial activity because their MIC values are close to those of an isolated compound.
In Table 4, the species were evaluated using the disk diffusion method. Three different extracts of each species were compared. All of them presented similar inhibition zones, around 7 mm. The wider inhibition zones were presented by the ethanolic extract of Bambusa blumeana against E. coli (9.8 mm) and Bambusa vulgaris hot water extract (10.7 mm) against S. aureus. However, all the extracts can be considered inactive, comparing them with the inhibition zones in Table 5. It is important to say that during the measurement of the diameter of the inhibition zones, the diameter of the disk is considered.
Bamboo species | Product | Inhibition zone (mm) | Ref. | |
---|---|---|---|---|
E. coli | S. aureus | |||
B. blumeana var. luzonensis Hack. | Acetone extract | 7.2 | 9.3 | [44] |
Ethanol extract | 7.6 | 7.2 | ||
Hot water extract | 7.4 | 7.4 | ||
B. blumeana Schult. and Schult. f. | Acetone extract | 6.6 | 7.0 | |
Ethanol extract | 9.8 | 9.3 | ||
Hot water extract | 7.3 | 7.3 | ||
B. vulgaris Schrad. | Acetone extract | 7.5 | 6.9 | |
Ethanol extract | 7.5 | 7.8 | ||
Hot water extract | 7.2 | 10.7 |
Antimicrobial activity of bamboo extracts—inhibition zone.
Symbol | Diameter (mm) | Classification |
---|---|---|
− | <10 | No activity |
+ | 10–15 | Activity |
++ | 15–20 | Good activity |
+++ | >20 | Very good activity |
Interpretation of inhibition zones [47].
The search for bioactive compounds is not limited only to the compounds produced by a plant species. Microorganisms hosted in plant tissues and organs have become a new source of useful metabolites for the pharmaceutical, agricultural, and food industries [45, 46]. Found in various parts of plants (roots, stems, leaves, and barks), endophytic fungi colonize various species [47], and the relationship between the endophytic fungi and the host plant may be advantageous since many of them improve the growth and protect the plant against pathogens [46].
Using the agar diffusion method, some authors evaluated the antimicrobial activity of fungal strains isolated from bamboos. The antimicrobial potential of the strains was evaluated against human pathogens, and in Table 6, it is possible to find the main results. Isolate 130 from P. edulis culms and isolate B38 from the same species presented similar results, with activity ranging from good to very good for most pathogens evaluated. Nevertheless, the isolate FB16 from P. edulis presented the best result, with very good activity against a larger number of microorganisms.
Bamboo species | Isolate no. | S. aureus | B. subtilis | L. monocytogenes | S. bacteria | E. coli | P. vulgaris | C. albicans | R. rubra | Ref. |
---|---|---|---|---|---|---|---|---|---|---|
P. edulis (Carrière) J. Houz. (Culms) | 106 | + | + | − | − | NT | NT | ++ | − | [45] |
120 | +++ | +++ | + | − | NT | NT | +++ | ++ | ||
127 | − | + | + | + | NT | NT | + | − | ||
128 | + | + | − | − | NT | NT | + | + | ||
130 | +++ | +++ | ++ | ++ | NT | NT | +++ | + | ||
P. edulis (Carrière) J. Houz.(Seeds) | B09 | + | + | − | − | NT | NT | ++ | − | [47] |
B34 | − | + | + | + | NT | NT | + | − | ||
B35 | + | + | − | − | NT | NT | + | + | ||
B38 | +++ | +++ | ++ | ++ | NT | NT | +++ | + | ||
ZZZ816 | +++ | +++ | + | − | NT | NT | +++ | + | ||
P. heteroclada Oliv. | FB16 | NT | +++ | +++ | +++ | +++ | ++ | +++ | NT | [46] |
FB43 | NT | − | ++ | ++ | + | + | − | NT | ||
FB06 | NT | ++ | ++ | − | + | − | + | NT | ||
FB21 | NT | − | ++ | ++ | + | + | ++ | NT |
Antimicrobial activity of fungal isolates.
NT—not tested.
One of the studies also evaluated the activity of fermentation products of fungal strains of P. edulis, and the results can be seen in Table 7. The product FB16 is the most active, with the biggest zones of inhibition. This behavior agrees with the results presented by the isolated fungus, as shown in Table 6. It is important to note that although the fermentation product FB16 presented the best result among the samples, its zones of inhibition are smaller than those presented by the isolated fungus.
Isolate no. | Inhibition zone (mm) | Ref. | |||||
---|---|---|---|---|---|---|---|
B. subtilis | L. monocytogenes | S. bacteria | E. coli | P. vulgaris | C. albicans | ||
FB16 | 13.2 | 11.8 | 10.29 | 12.46 | 8.8 | 16 | [46] |
FB43 | — | 10.6 | 8.95 | 7.6 | 7.52 | — | |
FB06 | 8.66 | 9.1 | — | 7.84 | — | 7.66 | |
FB21 | — | 8.7 | 8.64 | 7.52 | 7.77 | 8.69 |
Antimicrobial activity of fermentation products of fungal isolates from Phyllostachys heteroclada.
—: not active.
Despite the search for new substances with the ability to inhibit microbial growth, the presence of microorganisms is not always harmful. In some cases, certain microorganisms may contribute to human health, such as the human intestinal microbiota. It is composed of more than 400 bacterial species, and bifidobacteria and lactobacilli are the main ones [48]. They help in the digestion and synthesize bioactive compounds, besides preventing diseases, avoiding the growth of pathogenic microorganisms [49]. Through the consumption of probiotics and prebiotics, it is possible to maintain the balance of these intestinal bacteria. Probiotics are supplements containing the microorganisms of interest. Nondigestible carbohydrates that undergo fermentation by intestinal microbes are called prebiotics [48, 49].
Prebiotic activity was evaluated in bamboo shoots, since they are a rich source of polysaccharides and oligosaccharides [50]. The polysaccharides isolated from the shoots of Gigantochloa levis were able to stimulate the growth of Bifidobacterium animalis, Bifidobacterium longum, and Lactobacillus acidophilus. At the same time, they were able to reduce the growth of Salmonella sp., pathogenic bacteria [50]. Heteropolysaccharides-protein complexes from Phyllostachys praecox shoots were isolated, and the fractions containing these substances increased the Bifidobacterium adolescentis and Bifidobacterium bifidum counts [50]. These results suggest that bamboo shoots can be a source of probiotics.
Chinese traditional medicine has described the use of different parts of bamboos, such as leaves and rhizomes, to treat many diseases. Nowadays, scientific studies have demonstrated that bamboo extracts have excellent biological efficacy regarding their antioxidant activity. Theoretically, this activity might also be related for the treatment of diverse pathologies, such as resistance to free-radical, cardiovascular protection against neurodegenerative diseases, anticancer, and many others.
Bamboo shavings are a sort of Chinese traditional medicine that can be obtained from different bamboo species by scraping off the coating from bamboo stems, cutting the stems into slices, and binding them together by drying in shadowy places. A triterpenoid-rich extract of bamboo shavings was obtained from P. nigra var. henonis by superfluid carbon dioxide extraction and tested for antitumor activity. The extract showed a significant inhibitory activity against P388 and A549 cancer cell lines. The extract also presented an effective inhibitory effect on the sarcoma-loaded mice S180 model. Friedelin, the main compound in the extract, was also active on inhibiting the proliferation of four cancer lines, A375, L929, Hela, and THP-1 [51].
Bamboo extracts used as dietary supplement demonstrated a protective effect on the development of induced breast cancer by 7,12-dimethylbenz[a]anthracene (DMBA). A crude hydroethanolic extract from P. edulis was incorporated into a standard rodent diet at a concentration of 5 g/kg (0.5%), and it was able to delay the onset of mammary tumor by 1 week, decreasing the tumor incidence by 44% and tumor multiplicity by 67%. The biochemical analysis indicated that the activity might be related to an increased estrogen metabolism [52].
Bamboo vinegar, a natural liquid derived from the condensation produced during bamboo charcoal production, a pyrolyzate product, has been used in agriculture and used as a food additive. This liquid is composed mainly by water and acetic acid, but it also contains a variety of phenolic compounds. A vinegar preparation produced from P. pubescens reduced inducible nitric oxide synthase expression and nitric oxide levels and interleukin-6 secretion using lipopolysaccharide-activated macrophages. The mechanism proposed for the anti-inflammatory effect of the vinegar involved a decrease in reactive oxygen species production and protein kinase C-α/δ activation. The main component involved in the anti-inflammatory activity was creosol (2-methoxy-4-methylphenol) in in vivo tests [53]. Vinegars obtained from P pubescens, P. nigra, and P. bambusoides were tested for protective effect against N-methyl-
Besides the usual secondary metabolites, aqueous bamboo extracts contain many amino acids and polysaccharides that have not been investigated for their biological activities. Hypertension is associated with cardiovascular diseases such as arteriosclerosis, stroke, and myocardial infarction. Angiotensin converting enzyme (ACE, EC 3.4.15.1) is a dipeptidyl carboxypeptidase involved in different blood pressure regulating mechanisms. A peptide enriched P. pubescens shoot aqueous extract could significantly reduce systolic blood pressure, improve oxidant stress status (GSH-Px, SOD, TAC and MDA), and increase NO level in serum and NO synthase activity in kidney. This extract also decreased total cholesterol, triglyceride, and low-density lipoprotein cholesterol content and MDA level of hyperlipidemic rats. These activities were higher for crude extract rather than for the synthetic peptide used. This indicates a synergism with the phenolic compounds still present in the crude extract, such as p-coumaric acid, ferulic acid, caffeic acid, homoorientin, and orientin [55]. The antihyperlipidemic effect of these metabolites has been demonstrated later. The lipid metabolism was affected by phenolics and triterpenoids present in the inner culm water found from Dendrocalamus giganteus Wall. ex Munro. The freeze-dried powder obtained from this water was composed mainly of protocatechuic acid, p-hydroxybenzoic acid, syringic acid, friedelan-3-one, lup-20(29)-en-3-one, lup-20(29)-en-3-ol, and α-amyrin. The powder reduced the contents of triglycerides, total cholesterol, and free fatty acids in model assay with steatosis human liver cell L02 [56].
Most of the bamboo applications are related to the paper, textile, and construction industries, due to its high fiber contents. For this reason, scientists have been isolating and characterizing bamboo hemicelluloses since the 1970s. Hemicelluloses are polysaccharides found in plant cell walls that are characterized by being neither cellulose nor pectin and by having β-(1 → 4)-linked backbones with an equatorial configuration. Some of these polysaccharides are known to have an immunomodulatory activity. Hemicelluloses isolated from P. pubescens shavings showed in vitro immunomodulatory activity and significantly stimulated mouse splenocyte proliferation. All the isolated compounds markedly enhanced the phagocytosis activity and nitric oxide production of the murine macrophage RAW264 [57]. The total polysaccharide fraction of Sasa veitchii (Carrière) Rehder inhibited the production of interferon gamma (IFN-γ) by not only the toll like receptors (TLRs) but also the C-type lectin receptors (CLRs) dectin-1, and dectin-2 of BWMP also inhibited the autologous production of IFN-γ in the splenocyte culture mice splenocytes in the presence of immunostimulant fungal polysaccharides [58].
Although bamboo has been used for centuries by the Traditional Chinese Medicine, this is still a group of plant under investigated regarding its medicinal properties. In Asian countries, such as China, Korea, and Japan, among others, the most used species have already been studied regarding their biological properties and chemical composition. On the other hand, in Southern American countries, where a huge bamboo diversity is available, very little has been done to access its medicinal properties.
Several species have shown an important antioxidant potential demonstrating that they can be applied in the treatment of different diseases such as anti-inflammatory, antitumor, and several other ailments involving oxidative processes. Additionally, besides the usual secondary metabolites, bamboo extracts may contain biologically active peptides and polysaccharides. The combined effect of these macromolecules with polyphenols and other metabolites may lead to multiple biological effects, such as antifree radical, antiaging, antifatigue, antibacteria, antivirus, and as a functional dietary supplement, cosmetic ingredient, and food additive.
The authors wish to thank CAPES and CNPq for the scholarships granted.
The authors declare that there is no conflict of interest.
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I am also a member of the team in charge for the supervision of Ph.D. students in the fields of development of silicon based planar waveguide sensor devices, study of inelastic electron tunnelling in planar tunnelling nanostructures for sensing applications and development of organotellurium(IV) compounds for semiconductor applications. I am a specialist in data analysis techniques and nanosurface structure. 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