Retention time, formation enthalpy and fractal dimensions for chlorogenic acids.
Caffeoyl‐, feruloyl‐ and dicaffeoylquinic (chlorogenic) acids in infusions from green and medium roasted coffee beans were identified and quantified by reverse phase liquid chromatography. The chromatographic retention times of chlorogenic acids in coffee are modeled by structure‐property relationships. Bioplastic evolution is a view in evolution that conjugates the result of acquired features, and relationships that come out between the principles of evolutionary indeterminacy, morphological determination, and natural selection. Here, it is used to invent the coordination index, which is utilized to typify chlorogenic acids chromatographic retention times. The factors utilized to compute the co‐ordination index are the standard molar formation enthalpy, molecular bare, and hydrophobic solvent‐accessible surface areas, as well as fractal dimensions. The morphological and coordination indices provide strong correlations. Effect of different types of features is analyzed: thermodynamic, geometric, fractal, etc. Properties are molar formation enthalpy, bare molecular surface area, etc., in linear correlation models. Formation enthalpy, etc. distinguish chlorogenic acids molecular structures.
- biological plastic evolution
- morphological index
- co‐ordination index
- formation enthalpy
- molecular surface
- hydrophobic accessible surface
- fractal dimension
- solvation parameter model
- chlorogenic acid
Coffee terpenoids, cafestol, kaweol and 16‐
Coffee contains chlorogenic acids (CGAs) with the amounts varying between green (GCBs) and roasted (RCBs) coffee beans [11, 12].
The model used in this work is an extension of solvent‐dependent conformational analysis program (SCAP) octanol‐water model to organic solvents . In earlier publications, SCAP was applied for partition coefficients of porphyrins, phthalocyanines, benzobisthiazoles, fullerenes, acetanilides, local anesthetics , lysozyme , barbiturates, hydrocarbons , polystyrene , Fe–S proteins , C‐nanotubes  and D‐glucopyranoses . Bioplastic evolution was applied to phenylalcohols, 4‐alkylanilines , valence‐isoelectronic series of aromatics , phenylurea herbicides [36, 37], pesticides [38, 39], methylxanthines and cotinine [40, 41]. Quantitative structure‐activity/property relationships (QSARs/QSPRs) were applied to isoflavonoids  and sesquiterpene lactones . Mucoadhesive polymer hyaluronan, as biodegradable cationic and zwitterionic‐drug delivery vehicle, favors transdermal penetration absorption of caffeine (Caff) [44, 45]. The present report describes QSPR analysis and estimation of CGAs chromatographic retention times. The goal of the study is to identify the properties that differentiate CGAs consistent with chromatographic retention times. The work uses the chemical index in CGAs. The aim of this research is the corroboration of the value of the index by its ability to distinguish CGAs, as well as its concern as a prognostic descriptor for retention time evaluated with regard to molar formation enthalpy, molecular bare, and hydrophobic solvent‐accessible surface areas, and fractal dimensions. Section 2 describes the computational method. Sections 3 and 4 illustrate and discuss the calculation results. Finally, Section 5 summarizes our conclusions.
2. Computational method
Biological plastic (bioplastic) evolution is a perspective of the process of the evolution of species. It conjugates the result of (1) the acquired characters and (2) relationships between the principles of evolutionary indeterminacy, morphological determination and natural selection in evolutionary biology. The relationship between morphology and functionality in organisms is that morphology is the substance prop of functionality, which is the dynamic result of the former in the circumstance of the interaction between physical environment and living matter. Morphology, functionality, energy outlay and vital viability are equally affected: When a morphology is functional, it accomplishes its work with minimum energy outlay, and the vital viability of the organ or organism is maximum. Counting these ideas includes defining the
The larger the work
Code SCAP is founded on a representation by Hopfinger, parametrized for 1‐octanol‐water solvents . The conjecture is that one is able to center a
at a certain temperature
The models were obtained
3. Calculation results
For nine CGAs,
The 3‐CQA was taken as
The use of the co‐ordination index in the chemical description of molecules needs to change variables
Indices variation for CGAs
Variations of (
, , , .
, , .
where MAPE is 36.39% and AEV, 0.3472. The use of coordination index
, , , .
, , .
and AEV decays by 48%. The utilization of the standard molar formation enthalpy betters the fit:
, , , .
, , .
and AEV drops by 53%. The application of the bare molecular surface area
, , , .
, , .
and AEV decreases by 72%.
The inclusion of the hydrophobic solvent (water)‐accessible surface area HBAS improves the fit:
, , , .
, , .
and AEV decays by 93%. The fractal dimension averaged for
, , , .
, , .
and AEV decreases by 97%. The incorporation of the fractal dimension
, , , .
, , .
and AEV drops by 98%. The inclusion of the bare molecular surface area
, , , .
, , .
and AEV decays by 99%. The best non‐linear models do not improve the correlation. Additional fitting parameters were tested: molecular dipole moment, weight, volume, globularity, rugosity, hydrophilic and total solvent‐accessible surfaces, accessibility and fractal dimension for external atoms minus fractal index (
Food effects on health rightly worry consumers. Mass media tend to satisfy the permanent question, and physicians must face many queries from the persons that come to consult them. Information sources are scattered in many scientific journals, and a few domains exist that be so dispersed in different databases international journals. Information circulates badly, critical syntheses are rare, and an important passivity exists in knowledge transmission. Because of the great interest devoted to their health, consumers are receptive to all new accounts that concern food. Mass media know it and reply in a simplified way
One of the important applications of QSAR/QSPR models is to fill data gaps, by predicting a given response property or activity from known molecular features, or physicochemical and physiological properties of new compounds, which might not be experimentally tested. The performance of a model should be evaluated based on predictions quality from the test and not from the training set, in order to obviate any overfitting problem. The use of phenomenological methods, for example, QSAR/QSPR, is restricted by the insufficient accuracy of final digits. A quantum‐mechanical consideration of additive models showed that in most phenomenological approaches, systematic error is composed of two methodical errors: the same contribution of formally identical fragments and the inclusion of small molecules in training set. Two ways to improve models prognostic capabilities are: (1) compensation by introducing additional terms and (2) elimination of models systematic error. Building a model, Occam’s razor (principle of maximal parsimony) philosophical approach should be used, that is, fit the least complex (most parsimonious) model that could correctly describe training data. The simpler the model, the better the generalization one is going to find.
A study was made of the relations between retention times obtained by RP‐HPLC chromatography for a group of CGAs.
The QSPR linear models explaining the variation of chromatographic relative retention time
Thermodynamic indices were tried in order to improve the model. The molar formation enthalpy negatively correlates with the relative retention time and betters the fit [Eq. (13)].
Geometric descriptors were assayed in order to improve the fit. The molecular surface positively correlates with the relative retention time and betters the model [Eq. (14)]. The inclusion of the hydrophobic accessible surface presents a positive correlation with the relative retention time and improves the fit [Eq. (15)]. Notice that in this equation, index
Topological indices were tried in order to improve the model. The incorporation of the fractal dimension averaged for external (
From the present results and discussion, the following conclusions can be drawn.
The objective of this study was to develop structure‐property relationships for the qualitative and quantitative prediction of the reverse phase liquid chromatographic retention times of CGAs. It is hoped that the results of the present work increase scientific knowledge in the field of the relation prediction of chlorogenic acids in coffee. Program SCAP permits the Gibbs free energies of solvation (hydration) and partition coefficients that illustrate that for a certain atom, the solvation energies and partition coefficients result responsive to the occurrence in the molecule of some other atoms and groups.
The factors necessary to compute the co‐ordination index result in the standard molar formation enthalpy, molecular mass and surface area.
Linear correlation models resulted for chromatographic retention times. The morphological and coordination indices provided strong multivariable linear regression equations for chromatographic retention. The trend between the coordination index and molecular weight points not only to a homogeneous molecular structure of chlorogenic acids but also to the ability to predict and tailor their properties. The latter is non‐trivial in the analysis of chlorogenic acids and phenolic compounds in foods, beverages, human plasma, and urine because of the complex food, blood and urine matrixes.
The effect of different types of features was analyzed: thermodynamic, geometric, fractal, etc. The molar formation enthalpy, bare molecular and hydrophobic solvent‐accessible surface areas, fractal dimensions, etc. distinguished chlorogenic acids in linear fits.
The authors acknowledge support from Generalitat Valenciana (Project No. PROMETEO/2016/094) and Universidad Católica de Valencia
Urgert R, Meyboom S, Kuilman M. Comparison of effect of cafetiere and filtered coffee on serum concentrations of liver aminotransferases and lipids: Six month randomised controlled trial. British Medical Journal. 1996; 313:1362–1366
Urgert R, Weusten‐van der Woum MP, Hovenier R. Diterpenes from coffee beans decrease serum levels of lipoprotein (a) in humans: Results from four randomised controlled trials. European Journal of Clinical Nutrition. 1997; 51:431–436
Urgert R, Katan MB. The cholesterol‐raising factor from coffee beans. Annual Review of Nutrition. 1997; 17:305–324
Urgert R, van Vliet T, Zock PL, Katan MB. Heavy coffee consumption and plasma homocysteine: A randomised controlled trial in healthy volunteers. The American Journal of Clinical Nutrition. 2000; 72:1107–1110
Verhoef P, Pasman WJ, van Vliet T, Urgert R, Katan MB. Contribution of caffeine to the homocysteine‐raising effect of coffee: A randomised controlled trial in humans. The American Journal of Clinical Nutrition. 2002; 76:1244–1248
Nagao M, Fujita Y, Wakabayashi K, Nukaya H, Kosuge T, Sugimura T. Mutagens in coffee and other beverages. Environmental Health Perspectives. 1986; 67:89–91
Itagaki SK, Kobayashi T, Kitagawa Y, Iwata S, Nukaya H, Tsuji K. Cytotoxicity of coffee in human intestinal cells in vitroand its inhibition by peroxidase. Toxicology In Vitro. 1992; 6:417–421
Stadler RH, Turesky RJ, Müller O, Markovic J, Leong‐Morgenthaler PM. The inhibitory effects of coffee on radical‐mediated oxidation and mutagenicity. Mutation Research. 1994; 308:177–190
Shah AM, Channon KM. Free radicals and redox signalling in cardiovascular disease. Heart. 2004; 90:486–487
Natella F, Nardini M, Giannetti I, Dattilo C, Scaccini C. Coffee drinking influences plasma antioxidant capacity in humans. Journal of Agricultural and Food Chemistry. 2002; 50:6211–6216
Clifford MN. Chlorogenic acids and other cinnamates: Nature, occurrence and dietary burden. Journal of the Science of Food and Agriculture. 1999; 79:362–372
Clifford MN. Chlorogenic acids and other cinnamates: Nature, occurrence, dietary burden, absorption and metabolism. Journal of the Science of Food and Agriculture. 2000; 80:1033–1043
Richelle M, Tavazzi I, Offord E. Comparison of the antioxidant activity of commonly consumed polyphenolic beverages (coffee, cocoa, and tea) prepared per cup serving. Journal of Agricultural and Food Chemistry. 2001; 49:3438–3442
Huang MT, Smart RC, Wong CQ, Connay AH. Inhibitory effect of curcumin, chlorogenic acid, caffeic acid and ferulic acid on tumor promotion in mouse skin by 12‐ O‐tetradecanoylphorbol‐13‐acetate. Cancer Research. 1988; 48:5941–5946
Tanaga T, Kojima T, Kawamori T, Wang A, Suzui M, Okamoto K, Mori H. Inhibition of 4-nitroquinoline-1-oxide‐induced rat tongue carcinogenesis by the naturally occurring plant phenolics caffeic, ellagic, chlorogenic and ferulic acids. Carcinogenesis. 1993; 14:1321–1325
Castelluccio C, Paganga G, Melikian N, Bolwell GP, Pridham J, Sampson J, Rice‐Evans C. Antioxidant potential of intermediates in phenylpropanoid metabolism in higher plants. FEBS Letters. 1995; 368:188–192
Meyer AS, Donovan JL, Pearson DA, Waterhouse AL, Frankel EN. Fruit hydroxycinnamic acids inhibit human low‐density lipoprotein oxidation in‐vitro. Journal of Agricultural and Food Chemistry. 1998; 46:1783–1787
Moon JH, Terao J. Antioxidant activity of caffeic acid and dihydrocaffeic acid in lard and human low‐density lipoprotein. Journal of Agricultural and Food Chemistry. 1998; 46:5062–5065
Morton LW, Caccetta RAA, Puddey IB, Croft KD. Chemistry and biological effects of dietary phenolic compounds: Relevance to cardiovascular disease. Clinical and Experimental Pharmacology and Physiology. 2000; 27:152–159
Andreasen MF, Landbo AK, Christensen LP, Hansen Å, Meyer AS. Antioxidant effects of phenolic rye ( Secale cerealeL.) extracts, monomeric hydroxycinnamates, and ferulic acid dehydrodimers on human low‐density lipoproteins. Journal of Agricultural and Food Chemistry. 2001; 49:4090–4096
Stalmach A, Mullen W, Nagai C, Crozier, A. On‐line HPLC analysis of the antioxidant activity of phenolic compounds in brewed, paper‐filtered coffee. Brazilian Journal of Plant Physiology. 2006; 18:253–262
Thuong PT, Su ND, Ngoc TM, Hung TM, Dang NH, Thuan ND, Bae KH, Oh WK. Antioxidant activity and principles of Vietnam bitter tea Ilex kudingcha. Food Chemistry. 2009; 113:139–145
Wang QC, Zhang X, Zhang WQ, Sun XQ, Hu B, Sun Y, Zeng XX. Purification and HPLC analysis of caffeoylquinic acids from Kudingcha made from Ilex kudingchaC. J. Tseng. Journal of Food Science. 2013; 34:119–122
Che Y, Wang Z, Zhu Z, Ma Y, Zhang Y, Gu W, Zhang J, Rao G. Simultaneous qualitation and quantitation of chlorogenic acids in Kuding tea using ultra‐high‐performance liquid chromatography–diode array detection coupled with linear ion trap–Orbitrap mass spectrometer. Molecules 2016; 21:1728‐1–14
Liu, B, Cao, L, Zhang, L, Yuan, X, Zhao, B. Preparation, phytochemical investigation, and safety evaluation of chlorogenic acid products from Eupatorium adenophorum. Molecules 2017; 22:67‐1–12
Torrens F, Sánchez‐Marín J, Nebot‐Gil I. Universal model for the calculation of all organic solvent–water partition coefficients. Journal of Chromatography A. 1998; 827:345–358
Torrens F. Universal organic solvent‐water partition coefficient model. Journal of Chemical Information and Modeling. 2000; 40:236–240
Torrens F. Calculation of partition coefficient and hydrophobic moment of the secondary structure of lysozyme. Journal of Chromatography A. 2001; 908:215–221
Torrens F. Free energy of solvation and partition coefficients in methanol–water binary mixtures. Chromatographia. 2001; 53:S199‐S203
Torrens F, Soria V. Stationary‐mobile phase distribution coefficient for polystyrene standards. Separation Science and Technology. 2002; 37:1653–1665
Torrens F. Calculation of organic solvent–water partition coefficients of iron–sulfur protein models. Polyhedron. 2002; 21:1357–1361
Torrens F. Calculation of solvents and co-solvents of single‐wall carbon nanotubes: Cyclopyranoses. Nanotechnology. 2005; 16:S181‐S189
Torrens F, Castellano G. (Co-)solvent selection for single‐wall carbon nanotubes: Bestsolvents, acids, superacids and guest–host inclusion complexes. Nanoscale. 2011; 3:2494–2510
Torrens F. A new chemical index inspired by biological plastic evolution. Indian Journal of Chemistry Sec A. 2003; 42:1258–1263
Torrens F. A chemical index inspired by biological plastic evolution: Valence‐isoelectronic series of aromatics. Journal of Chemical Information and Modeling. 2004; 44:575–581
Torrens F, Castellano G. QSPR prediction of retention times of phenylurea herbicides by biological plastic evolution. Current Drug Safety. 2012; 7:262–268
Torrens F, Castellano G. Molecular clustering of phenylurea herbicides: Comparison with sulphonylureas, pesticides and persistent organic pollutants. Evolving Trends in Engineering and Technology. 2014; 1:29–52
Torrens F, Castellano G. QSPR prediction of chromatographic retention times of pesticides: Partition and fractal indices. Journal of Environmental Science and Health, Part B. 2014; 49:400–407
Torrens F, Castellano G. Molecular classification of pesticides including persistent organic pollutants, phenylurea and sulphonylurea herbicides. Molecules. 2014; 19:7388–7414
Torrens F, Castellano G. QSPR prediction of retention times of methylxanthines and cotinine by bioplastic evolution. International Journal of Quantitative Structure‐Property Relationships. in press
Torrens F, Castellano G. Molecular classification of caffeine, its metabolites and nicotine metabolite. In: Ul‐Haq Z, Madura JD, editors. Frontiers in Computational Chemistry. Hilversum (Holland): Bentham; Vol. 4, in press
Castellano G, Torrens F. Quantitative structure–antioxidant activity models of isoflavonoids: A theoretical study. International Journal of Molecular Sciences. 2015; 16:12891–12906
Castellano G, Redondo L, Torrens F. QSAR of natural sesquiterpene lactones as inhibitors of Myb‐dependent gene expression. Phytochemistry, submitted for publication
Torrens F, Castellano G. Mucoadhesive polymer hyaluronan as biodegradable cationic/zwitterionic‐drug delivery vehicle. ADMET DMPK. 2014; 2:235–247
Torrens F, Castellano G. Computational study of nanosized drug delivery from cyclodextrins, crown ethers and hyaluronan in pharmaceutical formulations. Current Topics in Medicinal Chemistry. 2015; 15:1901–1913
Ruíz‐Bustos A. La Evolución Plástica. Granada (Spain): Andalucía; 1994
Hopfinger AJ. Polymer‐solvent interactions for homopolypeptides in aqueous solution. Macromolecules. 1971; 4:731–737
Hopfinger AJ, Battershell RD. Application of SCAP to drug design: 1. Prediction of octanol–water partition coefficients using solvent‐dependent conformational analyses. Journal of Medicinal Chemistry. 1976; 19:569–573
Gibson KD, Scheraga HA. Minimization of polypeptide energy. I. Preliminary structures of bovine pancreatic ribonuclease S‐peptide. Proceedings of the National Academy of Sciences of the United States of America. 1967; 58:420–427
Rekker RF. The Hydrophobic Fragmental Constant. Amsterdam (The Netherlands): Elsevier; 1976
Pascal P. Program SCAP. Nancy (France): Université Henry Poincaré‐Nancy I; 1991
Torrens F. Characterizing cavity‐like spaces in active‐site models of zeolites. Computational Materials Science. 2003; 27:96–101
Dewar MJS, Zoebisch EG, Healy EF, Stewart JJP. AM1: A new general purpose quantum mechanical model. Journal of the American Chemical Society. 1985; 107:3902–3909
Debry G. Le Café: Sa Composition, sa Consommation, ses Incidences sur la Santé. Centre de Nutrition Humaine Monographie No. 1. Paris (France): Communications Economiques et Sociales; 1990
Johansson B, Halldner L, Dunwiddie TV, Masino SA, Poelchen W, Giménez‐Llort L, Escorihuela RM, Fernández‐Teruel A, Wiesenfeld‐Hallin Z, Xu XJ, Hårdemark A, Betsholtz C, Herlenius E, Fredholm BB. Hyperalgesia, anxiety, and decreased hypoxic neuroprotection in mice lacking the adenosine A1 receptor. Proceedings of the National Academy of Sciences of the United States of America. 2001; 98:9407–9412
Aguilar A. L’abús de cafè ens torna més dèbils. Presència (Barcelona). Nov. 23–29, 2001; 2001:22–23