\r\n\tDiesel has a High Energy Density: Diesel engines are highly fuel-efficient, for one, because on a volume scale — gallon, liter, square foot, or meter — diesel has a much higher energy density than most other solid, liquid, and gas-state fossil fuels. Diesel certainly has a higher energy density than gasoline, natural gas (methane), and propane. \r\n\tDiesel has a High Energy Density: Higher energy density means there is more energy per volume unit of measure — more energy per liter. Diesel has a higher energy density than other fossil fuels because the hydrocarbons in diesel — the valuable components in every fossil fuel that ignites/burns/combusts — are made of long and complex molecules, molecules with very high carbon-to-hydrogen ratios. \r\n\tDiesel naturally has exceptional compressive resistance because it is a heavy fuel, stable fuel made of large, long hydrocarbon molecules.
\r\n
\r\n\tDiesel has High Compression Resistance: Diesel is highly efficient with respect to fuel efficiency is because it is a very heavy fossil fuel. Thus diesel is a very stable fuel. The stability of diesel is the reason diesel engines with high compression ratios are possible. Compression ratio plays into both fuel efficiency and emissions. The compression ratio is particularly important with respect to reducing emissions. The higher the compression ratio, the lower the emissions are.
\r\n
\r\n\tDiesel Engines are More Thermal Efficient than Other Fossil Fuel Engines: Diesel engines are more efficient than any other liquid fossil fuel engine in that of thermal efficiency. Thermal efficiency is the total amount of energy generated by an engine’s combustion of fuel that becomes mechanical energy, an energy that pushes a vehicle down the road. The thermal efficiency of diesel engines is far greater than that of any other type of liquid fossil fuel engine. \r\n\tDiesel Engines are More Thermal Efficient than Other Fossil Fuel Engines: The thermal efficiency of diesel engines is partly due to the energy density and compression resistance of diesel fuel.
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\n
1. Introduction
\n
A broad range of proteins and peptides, for various purposes of enhancement, such as human growth hormone (hGH), i.e., somatropin, can be obtained from the illicit market. These products are mainly marketed as lyophilized formulations in small glass containers often without labelling. The customers are exposed to a range of potential harms, besides from the active components, including bacterial and fungal or viral infections which may arise from the fact that they are administered parenterally.
\n
\n\nFigure 1A\n illustrates the total number of injection vials containing white lyophilized product cake being seized by the Swedish Customs during nine years in the past, i.e., 2010–2018. A large proportion of these samples, i.e., 64%, contained human growth hormone or melanotan II. About a third of the seized vials, i.e., 27%, did not contain any active peptide or protein, while the remaining 9% of the vials contained other compounds (\nFigure 1B\n).
\n
Figure 1.
Schematic illustration of the number of seized illicit products during 2010–2018 in Sweden (A), as well as the active peptides/proteins that have been identified in theses samples (B).
\n
The concept of a proteolytic peptide pattern, i.e., protein peptide mapping (PPM), being characteristic of a protein was first demonstrated by SDS-PAGE [1]. In 1989, peptide sequencing by automated Edman degradation had a cycle-time of nearly one hour per amino acid residue. Samples of interest often contained complex mixtures of proteins, which usually required separation by SDS-PAGE followed by electroblotting onto a polyvinylidene fluoride (PVDF) membrane [2]. However, a more rapid approach to peptide sequencing is “peptide mass fingerprinting” (PMF). By PMF, proteins are enzymatically cleaved in a predictable manner and the sizes of the generated peptide fragments are specific for different proteins. Subsequent analysis of the obtained peptides by mass spectrometry (MS) generates mass-to-charge ratio (m/z) values in the mass spectrum which in turn give rise to a characteristic “peptide mass fingerprint” of the protein [3, 4]. The fingerprint serves to identify the protein by comparison with in silico digests, i.e., search engines attempt to match peptides from in silico digested proteins to those measured by the mass spectrometer [5, 6, 7, 8, 9]. Peptide mass fingerprinting with MS, which was first demonstrated with fast atom bombardment ionization in 1981, provides the possibility of identifying a protein at nanogram-level [5, 10, 11, 12]. Trypsin is a commonly used proteolytic enzyme for PMF, since it is relatively cheap, highly selective, and generates peptides with an average size of about 8–10 amino acids which are ideally suited for analysis by MS. It cleaves principally on the C-terminal side of arginine and lysine with the exception of Arg-Pro and Lys-Pro [2]. Limitations to protein identification by PMF include; I) The protein sequence must be present in a database for a successful protein identification. II) Proteins with extensive post-translational modifications may fail to yield good matches [13]. III) Different isoforms of a protein or alternatively spliced proteins may not be distinguished if the unique sequence regions are not observed in the peptide map. IV) Incomplete proteolytic digestion and differences in peptide ionization provide an incomplete mass fingerprint of the protein. Therefore, a complementary approach to PMF for protein identification is the use of tandem mass spectrometry (MS/MS), whereby tryptic peptide ions from the first stage of MS are dissociated along the backbone and then separated and detected in a second stage of MS to identify primary amino acid sequences [14, 15, 16]. Tandem mass spectrometry in conjunction with PMF provides even more specificity, thereby facilitating the identification [17, 18].
\n
Since the innovation of sensitive commercial instrumentation based on MALDI-TOF MS in 1992, the technique has been widely used for protein identification due to its high sensitivity and mass accuracy, speed, extremely low material consumption, absence of multiple charge mass signals and relatively high tolerance toward additives and contaminants such as salts, matrix components and excipients [19, 20, 21, 22, 23, 24, 25, 26]. Furthermore, MALDI is a micro-destructive analytical technique and the remaining material on the MALDI target plate can be archived for later analysis. The high sensitivity of MALDI implies that only a small aliquot of the digested protein is required for mass analysis, and the remainder can be used for alternative measurements. MALDI provides additional information regarding the primary structure of the protein by sequencing of selected tryptic peptide ions in post source decay (PSD) mode [27, 28, 29, 30, 31, 32, 33, 34]. MALDI in-source decay (ISD) is another attractive method which generates partial sequence information of intact proteins with up to 20–50 amino acid residues [35] (\nFigure 2\n).
\n
Figure 2.
MALDI in source decay analysis of a suspected illegal somatropin sample. The blue marked amino acid asp (D) is the deamidated form of Asn (N).
\n
The sequence information from MALDI-PSD or MALDI-ISD analyses can be used to validate protein identification. The singly charged ions generated by MALDI-TOF-MS are a mixture of b-, y- and a-ions accompanied by ions resulting from neutral loss of ammonia or water [36, 37, 38, 39].
\n
PMF-based protein identification is accomplished by searching a protein sequence database using different search engines such as ProFound [40], Mascot [41], or SEQUEST [15]. A value-based scoring system has been developed that facilitates the identification without accompanying amino acid data [42, 43]. Parameters which are considered to be important for the identification include; molecular mass, protein sequence coverage and the number of matching peptides [42]. However, presence of a signature peptide, being unique for a protein, facilitates the PMF-based identifications [44]. Prior reports suggest that a minimum of four matching peptides and a sequence coverage of at least 20% is necessary for positive PMF-based protein identification [45, 46]. The other alternative strategy for protein identification is the top down approach, where intact molecule ions are subjected to gas-phase fragmentation [47].
\n
Proteins with posttranslational modifications, such as glycosylation, present additional challenges since the masses of the modified peptides are different and thus do not contribute to the identification. In such cases, the protein can be analyzed by capillary electrophoresis (CE), in order to explore the heterogeneity of the protein followed by comparison of its electropherogram with that of the corresponding reference standard [13, 48].
\n
\n
\n
2. Experimental
\n
\n
2.1 Sample preparation
\n
MALDI-TOF-MS is very tolerant to salts and sample matrices, hence it is seldom necessary to desalt the sample. However, sometimes it is necessary to use a C18 micro-column in order to fractionate a complex sample or enhance the target analyte concentration.
\n
The sample to be analyzed is mixed with a matrix solution (1:1, v:v), e.g. sinapinic acid (SA) or alpha-cyano-4-hydroxycinnamic acid (ACHCA). One μl of the mixture is deposited on the MALDI target plate and allowed to air-dry (i.e., the dried-droplet method) before being placed in the mass spectrometer [19, 49].
\n
\n
\n
2.2 Proteolysis
\n
The analyte to be digested is dissolved in ammonium bicarbonate (50 mM, pH 7.9). The intact sample is directly analyzed by MALDI in order to determine the molecular mass of the analyte. Then, 200 μl of the solution is digested by addition of 2–10 μl trypsin (200 μg/ml in 10 mM HCl). The reaction is carried out at room temperature or at 37°C for 30 minutes up to 24 hours, depending on peptide or protein in question. It has been found that 30 minutes digestion of somatropin at room temperature generated enough tryptic fragments for the MALDI analyses [50]. For more complex proteins, such as human chorionic gonadotropin, the required time period for proteolysis is found to be 24 hours at 37°C. Insulin porcine is digested at 37°C for 12 hours, while other peptides are digested at 37°C for 4 hours. In order to enable alkylation of the cysteine residues in a protein or peptide, it is reduced by using DTT or 2-mercaptoethanol (ME) followed by labelling of the free thiol groups with 2-iodoacetamide. The alkylation is carried out through the following procedure:
2.5 μl 100 mM ME is added to 10 μl of the protein solution.
The protein is then incubated at 50°C for 15 minutes to reduce the S-S linkages.
2.5 μl 2-iodoacetamide (100 mM) is added into the mixture to interact with free sulfide groups of the cysteine residues at +4°C for 15 to 60 minutes in darkness.
2.5 μl (10 μg/mL) trypsin is added to the mixture for the digestion. The reaction is performed at room temperature or at 37°C [13, 50].
\n\n
\n
\n
2.3 Apparatus and operating conditions
\n
MALDI-TOF analyses are performed using either an Autoflex or an Autoflex Max (Bruker Daltonics, Bremen, Germany) reflector type time-of-flight mass spectrometer, equipped with a pulsed nitrogen laser working at 337 nm and a smartbeam II laser working at 355 nm, respectively. The Autoflex instrument is operated in the positive ion mode with delayed extraction at an accelerating voltage of 20 kV and a variable voltage reflectron. The parameter settings are optimized to analyze peptides in reflectron mode. Before analysis, the instrument is externally calibrated with Bruker Daltonics standard peptide or protein mixtures. Peptide mass peaks occurring due to autolysis of trypsin (porcine) such as 842.51 and 2211.10 Da are also used for internal calibration. Mass spectra are obtained by averaging 250 laser shots (5× 50 shots) at different positions on the sample surface. All samples being used for post source decay (PSD) analysis are analyzed in the reflectron mode. The autoflex Max instrument TOF/TOF (2 kHz MS and 200 Hz MS/MS) operates in the positive ion mode. Metastable fragmentation is induced by laser (355 nm) without the further use of collision gas. The lyophilized samples are dissolved in 300 μL ammonium bicarbonate buffer (50 mM, pH 7.5). The liquid samples are diluted with same buffer. The wells of MALDI plate are spotted with 1 μl sample/matrix solution (1:1, v:v) and allowed to air dry before being placed in the mass spectrometer. ACHCA is used for analysis of peptides. About 20 mg of ACHCA is mixed in 1 ml of ethanol: acetonitrile (ACN) (1: 1 v/v) and 0.1% trifluoroacetic acid (TFA). SA is used for protein analysis. Two different solutions of SA in water and ethanol are made as follows: 1 - Saturated solution of SA in ethanol and 0.1% TFA; 2 - Saturated solution of SA in 50% acetonitrile (ACN) and 0.1% TFA. Solution 1 is first applied on the MALDI plate on which the sample mixed with SA in 50% ACN and 0.1% TFA (1: 1) is then applied.
\n
\n
\n
\n
3. Results and discussion
\n
Illegally distributed lyophilized or liquid products being suspected to contain pharmacologically active peptides were seized by the Swedish customs. The analyte to be identified is analyzed in both reflectron and linear modes in order to determine its molecular mass (\nFigure 3\n). Large peptides and proteins are then exposed to trypsin digestion in order to obtain peptide-mass map upon MALDI analysis in reflectron mode. Small peptides are, on the other hand, analyzed in reflectron mode and/or PSD mode directly. This strategy was applied to the identification of the following peptides and proteins (\nFigure 4\n and \nTable 1\n).
\n
Figure 3.
The sample to be identified is analyzed in both reflectron and linear modes in order to determine the molecular mass of the analyte. Depending on the size of the molecule it will be exposed to enzymatic digestion in order to be identified through PMF. Small peptides used to be identified by de novo sequencing in PSD mode.
\n
Figure 4.
The primary structure of the analyzed peptides. (A) Somatoliberin, (B) AOD, (C) GHRP-2, (D) glycine-GHRP-2, (E) GHRP-6, (F) glycine-GHRP-2, (G) Ipamorelin, (H) MGF, (I) long-R3-IGF (disulfide bridges: C6-C48; C47-C52 and C18-C61; asp at position 3 is replaced by Arg), (J) insulin Aspart, (K) insulin porcine, (L) DSIP, (M) Thymosine β4, (N) Melanotan II, (O) Bremelanotide, (P) Dermorphin and (Q) BPC 157. For molecular structures of somatropin and hCG see references [13, 50].
\n
\n
3.1 Identification of somatropin (hGH)
\n
Recombinant hGH or somatropin consists of 191 amino acids with two disulfide bridges (Cys53-Cys165 and Cys182-Cys189) and promotes proteinogenesis as well as fat mobilization and oxidation [51, 52, 53]. Recombinant hGH is used as a prescription drug to treat children’s growth disorders and adult growth hormone deficiency. In the belief that the beneficial impact of somatropin on the growth can be extrapolated to healthy individuals, it is abused by bodybuilders and athletes [54]. However, many users are unaware of the correct dosage and how to prepare the solution for giving an injection. It has been demonstrated that supra-physiological dosages can have fatal consequences [55]. Apart from the undesired consequences following the abuse of somatropin, our investigations have shown that the illegally marketed products contained high levels of impurities such as endotoxins [50]. Endotoxins are associated with Gram-negative bacteria which can cause severe immune response and diseases in humans [56, 57]. Somatropin was identified through PMF and MALDI-ISD (see \nFigure 2\n)[48, 58, 59]. The availability of a compendial reference standard has made it possible to apply double injection capillary zone electrophoresis (DICZE) for both identification and impurity determination of somatropin products [50, 58, 59]. The DICZE-method provided complementary information on the native protein, providing a side by side comparison between the electrophoretic patterns of the reference standard and the analyte to be identified [50].
\n
\n
\n
3.2 Identification of human somatoliberin
\n
Human somatoliberin, growth hormone-releasing hormone (GHRH), constitutes of 44 amino acids without any post-translational modification or disulfide bridge. Somatoliberin was first isolated from two pancreatic islet cell tumors, and subsequently from normal human hypothalamus [60, 61, 62]. The MALDI results from determination of the molecular mass, PMF and amino acid sequence revealed that the Asn8 (N), Gly15 (G) and Met27 (M) residues have, respectively, been replaced by Gln8 (Q), Ala15 (A) and Leu27 (L) during the synthesis (see \nFigures 4\n and \n5\n). The peptide was successfully identified by PMF and de-novo sequencing of three of the tryptic peptides.
\n
Figure 5.
MALDI-PMF (A) and MALDI-PSD (B) analysis of somatoliberin.
\n
\n
\n
3.3 Identification of an anti-obesity drug (AOD)
\n
The AOD peptide is a fragment of the C-terminus of human growth hormone (fragment 177–191) where a tyrosine is added at the N-terminus. It is a cyclic peptide consisting of 16 amino acids with a disulfide bridge between cysteine residues at positions 7 and 14 in the peptide chain [63] (\nFigure 4\n and \nTable 1\n). The fragment is the minimum length of the hGH sequence that retains the lipolytic and antilipogenic properties of hGH [63, 64, 65]. The molecular peptide masses of its tryptic peptides complied with the peptide map of hGH fragment 177–191. The existence of the disulfide bridge between C7 and C14 was confirmed upon analysis of the non-reduced tryptic sample (\nFigure 6\n). This peptide has also been employed as a signature peptide for the identification of hGH [48, 50]. The amino acid sequences of three selected tryptic peptides were also confirmed.
\n
Figure 6.
MALDI-PSD analysis of AOD.
\n
\n
\n
3.4 Identification of growth hormone releasing peptides (GHRP)
\n
GHRP, including GHRP-2, GHRP-6, Gly-GHRP-2, Gly-GHRP-6 and ipamorelin, as an agonist of the gut peptide ghrelin is an endogenous ligand for the growth hormone secretagogue receptor [66, 67]. Ghrelin strongly stimulates food intake and GH release in humans [68, 69, 70]. These peptides were identified through de-novo sequencing. The amino acid sequence of GHRP-6 differs slightly from that of GHRP-2, i.e., the amino acid residues dA and Naphthyl alanine (NalA) in GHRP2 are replaced by H and dW in GHRP-6 (\nFigure 4\n and \nTable 1\n) [70].
\n
Ipamorelin is a penta-peptide\n, being derived from GHRP-1 [71]. Ipamorelin like the other GHR-peptides, stimulates production of growth hormone [72]. Incorporation of aminoisobutyric acid (Aib) in the peptide chain increases the stability of the peptide (\nFigure 4\n) [73].
\n
\n
\n
3.5 Identification of mechano growth factor (MGF) and long-R3 insulin-like growth factor (IGF-1)
\n
MGF is a unique, spliced variant of IGF-1. MGF induces muscle cell proliferation in response to muscle stress and injury [74]. MGF and Long-R3-IGF1 were identified in several confiscated samples. Long-R3-IGF-1, an analogue of IGF-1, has 13 additional amino acids at its N-terminus (\nFigure 4\n and \nTable 1\n). IGF-1 mediates the anabolic and mitogenic activity of GH [75, 76, 77]. MGF and Long-R3-IGF1 were identified by sequence coverages of 100% and 43%, respectively (\nTable 2\n and \nFigure 7\n).
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n\n
\n
Peptide
\n
Mmass\n
\n
PMFa\n
\n
PSDb\n
\n
ISDc\n
\n
DICZEd\n
\n
NMR
\n
LC/MS
\n
\n\n\n
\n
Somatropin
\n
22115.07 22128.68e\n
\n
X
\n
—
\n
X
\n
X
\n
X
\n
X
\n
\n
\n
Human Somatoliberin
\n
3366.866
\n
X
\n
X
\n
—
\n
—
\n
—
\n
—
\n
\n
\n
AOD (Anti Obesity Drug) HGH fragment 177–191
\n
1813.850
\n
X
\n
X
\n
—
\n
—
\n
—
\n
—
\n
\n
\n
GHRP-2
\n
817.397
\n
—
\n
X
\n
—
\n
—
\n
—
\n
—
\n
\n
\n
Gly-GHRP-2
\n
874.419
\n
—
\n
X
\n
—
\n
—
\n
—
\n
—
\n
\n
\n
GHRP-6
\n
872.433
\n
—
\n
X
\n
—
\n
—
\n
—
\n
—
\n
\n
\n
Gly-GHRP-6
\n
929.455
\n
—
\n
X
\n
—
\n
—
\n
—
\n
—
\n
\n
\n
Ipamorelin
\n
711.385
\n
—
\n
X
\n
—
\n
—
\n
—
\n
—
\n
\n
\n
MGF
\n
2866.469
\n
X
\n
X
\n
—
\n
—
\n
—
\n
—
\n
\n
\n
Long-R3-IGF
\n
9105.385 9111.576e\n
\n
X
\n
X
\n
—
\n
—
\n
—
\n
—
\n
\n
\n
Insulin Porcine
\n
5772.766
\n
X
\n
X
\n
—
\n
X
\n
X
\n
X
\n
\n
\n
Insulin Aspart
\n
5821.611
\n
X
\n
X
\n
—
\n
X
\n
X
\n
X
\n
\n
\n
DSIP
\n
848.318
\n
—
\n
X
\n
—
\n
—
\n
—
\n
—
\n
\n
\n
Thymosin-β4\n
\n
4960.474
\n
X
\n
X
\n
—
\n
—
\n
—
\n
—
\n
\n
\n
hCG α - Chain β - Chain α + β
\n
13,431e\n 23,114e 36,341e\n
\n
X
\n
X
\n
—
\n
X
\n
—
\n
—
\n
\n
\n
Melanotan-II
\n
1023.502
\n
—
\n
X
\n
—
\n
—
\n
X
\n
—
\n
\n
\n
Bremelanotide
\n
1024.510
\n
—
\n
X
\n
—
\n
—
\n
X
\n
—
\n
\n
\n
Dermorphin
\n
802.337
\n
—
\n
X
\n
—
\n
—
\n
X
\n
X
\n
\n
\n
BPC-157
\n
1418.692
\n
—
\n
X
\n
—
\n
—
\n
X
\n
X
\n
\n
\n
Albumin bovinef\n
\n
> 66,000e\n
\n
X
\n
—
\n
—
\n
—
\n
—
\n
—
\n
\n\n
Table 1.
Illegally distributed peptides and proteins that have been analyzed by MALDI-ToF-MS and DICZE. The monoisotopic mass (Mmass) of the analytes and the employed analytical methodology is indicated.
Identification by peptide mass fingerprinting using enzymatic degradation as well as other modifications.
\nDe novo sequencing by MALDI- post source decay.
Protein sequencing by MALDI- in source decay.
Identification and/or impurity profiling by double injection capillary zone electrophoresis.
Average molecular mass.
Bovin albumin was detected in some of the samples.
\n
\n
\n
\n
\n\n
\n
Peptide fragments
\n
Theoretical m/z [M + H]+\n
\n
Determined m/z [M + H]+\n
\n
\n\n\n
\n
YQPPSTNKNTKSQRRKGSTFEERK
\n
2869.169
\n
2869.422
\n
\n
\n
Glu-C digestion of the peptidea:
\n
\n
\n
YQPPSTNKNTKSQRRKGSTFEE
\n
2584.809
\n
2584.816
\n
\n
\n
Trypsin digestion of the peptide:
\n
\n
\n
GSTFEERKb\n
\n
953.458
\n
953.574
\n
\n
\n
YQPPSTNKb\n
\n
934.453
\n
934.525
\n
\n
\n
GSTFEERb\n
\n
825.363
\n
825.469
\n
\n
\n
SQRb\n
\n
390.199
\n
390.186
\n
\n
\n
NTKb\n
\n
362.193
\n
362.302
\n
\n\n
Table 2.
MALDI peptide mass fingerprinting-data from analysis of mechano growth factor.
Glu-C cleaves at the C-terminus of either aspartic or glutamic acid residues.
The amino acid sequence of the peptide was determined.
\n
Figure 7.
MALDI analysis of intact long-R3-IGF and MALDI-PSD analysis of two tryptic peptides, i.e., m/z 1667.771 and m/z 1763.887.
\n
\n
\n
3.6 Identification of insulin porcine and insulin aspart
\n
Insulin regulates the cellular uptake, utilization, and storage of glucose, amino acids, and fatty acids and inhibits the breakdown of glycogen, protein, and fat. Since more than one decade ago the illegal use of insulin has been noticed [78]. However, the misuse and wrong administration of insulin could cause the, so called, dead in the bed syndrome [79]. In bodybuilding, insulin works such as testosterone or hGH to consolidate muscle tissue. Insulin also prevents breakdown of muscles and vanishes rapidly from the body, since it has a very short half-time (t\n1/2) [80].
\n
Several illegal products containing insulin porcine or aspart have been analyzed. Insulin is composed of two peptide chains, i.e., A and B, which are joined by two inter-chain disulfide bonds. The A chain also contains an intra-chain disulfide bond (\nFigure 4\n). The results summarized in \nTable 3\n, demonstrate the applied strategy for the identification of porcine and insulin aspart. The insulin molecules were reduced using a potent reducing agent, i.e., 2-mercaptoethanol (ME). MS-analysis of the reduced samples resulted in a mass spectrum consisting of several signals from both reduced A and B chains. The A and B chains generated three and four signals, respectively, corresponding to the ME-modified peptide as described in \nTable 3\n. It is to be noted that the amino acid residues P and A at positions 28 and 30 in the B-chain, respectively, have been replaced by D and T in insulin aspart. Therefore, these insulin molecules are distinguished upon these differences. The tryptic digestion of the B chain yielded three peptide fragments of different sizes (\nFigure 8\n and \nTable 3\n). The molecular masses of these peptides were determined accurately, and the amino acid sequence of the tryptic peptides were determined in PSD-mode.
\n
\n
\n
\n
\n\n
\n
Insulin
\n
Theoretical m/z [M + H]+\n
\n
Determined m/z [M + H]+\n
\n
\n\n\n
\n
Porcine (intact)
\n
5774.635
\n
5774.632
\n
\n
\n
Aspart (intact)
\n
5822.612
\n
5822.618
\n
\n
\n
Peptide chains from Insulin porcine:
\n
\n
\n
[A-chain + Na]+\n
\n
2404.990
\n
2404.758
\n
\n
\n
[A-chain +1ME + Na]+a\n
\n
2480.988
\n
2480.769
\n
\n
\n
[B-chain + H]+\n
\n
3398.682
\n
3398.460
\n
\n
\n
[B-chain +1ME + H]+a\n
\n
3474.680
\n
3474.486
\n
\n
\n
Peptide chain from Insulin aspart:b\n
\n
\n
\n
[B-chain + H]+\n
\n
3446.667
\n
3446.434
\n
\n
\n
[B-chain + Na]+
\n
3468.648
\n
3468.487
\n
\n
\n
[B-chain +1ME + H]+a\n
\n
3522.665
\n
3522.422
\n
\n
\n
[B-chain - (GFFYTDKT) + H]+c\n
\n
2487.228
\n
2487.030
\n
\n
\n
[B-chain - (GFFYTDKT) + 1ME + H]+a, c\n
\n
2563.226
\n
2563.302
\n
\n
\n
Tryptic peptides from Insulin aspart:
\n
\n
\n
[GFFYTDK + H]+\n
\n
877.399
\n
877.317
\n
\n
\n
[GFFYTDKT + H]+\n
\n
978.457
\n
978.446
\n
\n
\n
[B-chain - (GFFYTDKT) + H]+c, d\n
\n
2487.217
\n
2487.030
\n
\n
\n
Tryptic peptides from Insulin porcine:
\n
\n
\n
[GFFYTPK + H]+\n
\n
859.425
\n
859.345
\n
\n
\n
[GFFYTPKA + H]+\n
\n
930.462
\n
930.337
\n
\n
\n
[B-chain - (GFFYTPKA) + H]+c\n
\n
2487.228
\n
2487.234
\n
\n
\n
[B-chain-(GFFYTPKA) + 1ME + H]+ a, c\n
\n
2563.226
\n
2563.129
\n
\n\n
Table 3.
MALDI-TOF-MS analysis of insulin porcine and aspart.
Beta mercaptoethanol (ME) was used as reducing agent.
The A-chains of insulin aspart and Insulin porcine are identical.
Trypsinated B-chain.
These peptides originate from insulin aspart, see \nFigure 8\n.
\n
Figure 8.
MALDI analysis of insulin aspart; analysis of reduced B-chain (A), MALDI-PSD analysis of tryptic B-chain (B), see \nTable 3\n.
\n
Double-injection capillary electrophoresis has also been applied for the identification of insulin molecules [81].
\n
\n
\n
3.7 Identification of delta sleep-inducing peptide (DSIP)
\n
The nonapeptide delta DSIP was first isolated from the cerebral venous blood of rabbits in an induced state of sleep during the mid-70s [82]. It was primarily believed to be involved in sleep regulation due to its apparent ability to induce slow-wave sleep in rabbits. However, it has been demonstrated that short-term treatment of chronic insomnia with DSIP is not likely to be of major therapeutic benefit [83]. The peptide is marketed illegally presumably for the treatment of insomnia. The peptide was directly exposed to the PSD analysis in order to confirm its molecular mass and amino acid sequence (\nFigure 4\n and \nTable 1\n).
\n
\n
\n
3.8 Identification of thymosin β4\n
\n
Synthetic thymosin is a peptide consisting of 43 amino acids with artificial acetylation of the N-terminus (see \nFigure 4\n and \nTable 1\n). Thymosin has the potential of playing a significant role in tissue development, maintenance, repair, pathology and other important biological activities [84]. Some important biological activities of thymosin are related to the peptide sequence L17KKTET22 [85]. Illegally distributed thymosin products are claimed to promote a variety of beneficial biological functions, such as muscle building. The peptide was identified through PMF and de-novo sequencing of the tryptic peptides (\nTable 4\n).
\n
\n
\n
\n
\n\n
\n
Peptide fragments
\n
Theoretical m/z [M + H]+\n
\n
Determined m/z [M + H]+\n
\n
\n\n\n
\n
Ac-SDKPDMAEIEKFDKSKLKKTETQEKNPLPSKETI EQE-KQAGES
\n
4961.484
\n
4960.987
\n
\n
\n
KTETQEKNPLPSKETIEQEKQAGES
\n
2829.401
\n
2829.219
\n
\n
\n
Ac-SDKPDMAEIEKFDKSKLK
\n
2151.090
\n
2151.124
\n
\n
\n
Ac-SDKPDMAEIEKFDKSK
\n
1909.911
\n
1909.698
\n
\n
\n
Ac-SDKPDMAEIEKFDKa\n
\n
1694.784
\n
1694.765
\n
\n
\n
NPLPSKETIEQEK
\n
1512.780
\n
1512.768
\n
\n
\n
SKLKKTETQEK
\n
1319.743
\n
1319.729
\n
\n
\n
Ac-SDKPDMAEIEK
\n
1304.594
\n
1304.498
\n
\n
\n
ETIEQEK
\n
876.421
\n
876.356
\n
\n
\n
TETQEKa\n
\n
735.342
\n
735.356
\n
\n
\n
NPLPSKa\n
\n
655.367
\n
655.354
\n
\n
\n
FDKSK
\n
624.325
\n
N.D.b\n
\n
\n
\n
QAGES
\n
491.199
\n
N.D.b\n
\n
\n
\n
SKLK
\n
475.314
\n
N.D.b\n
\n
\n
\n
FDKa\n
\n
409.198
\n
409.196
\n
\n
\n
LKKa\n
\n
388.282
\n
388.286
\n
\n
\n
LKa\n
\n
260.187
\n
260.168
\n
\n
\n
SKa\n
\n
234.135
\n
234.151
\n
\n\n
Table 4.
MALDI peptide mass fingerprinting data from analysis of thymosin β4\n.
The amino acid sequence of the peptide was determined in the PSD mode.
N.D. = Not detected.
\n
\n
\n
3.9 Identification of human chorionic gonadotropin (hCG)
\n
Human chorionic gonadotropin (hCG) is a glycoprotein hormone consisting of α (92 amino acids) and β-subunits (145 amino acids) being noncovalently associated [86]. These subunits are, however, highly cross-linked internally through disulfide bridges, i.e., the α-subunit has five disulfide bridges [87], while the β-subunit has six [87, 88]. The protein is heavily glycosylated where oligosaccharides are attached to the protein backbone through asparagine and serine residues and constitute approximately 30% of the molecular mass [89]. The protein has been identified using MALDI-TOF-MS and DICZE [13, 50]. Approximately 40% of the amino acid sequence of hCG was confirmed upon PMF (\nTable 5\n) [13].
\n
\n
\n
\n
\n
\n\n
\n
Peptide fragments
\n
Peptide position in the peptide chain
\n
Theoretical m/z [M + H]+\n
\n
Determined m/z [M + H]+\n
\n
\n\n\n
\n
AYPTPLR
\n
α-hCG; 36–42
\n
817.446
\n
817.482
\n
\n
\n
TMLVQK
\n
α-hCG; 46–51
\n
719.402
\n
719.414
\n
\n
\n
STNR
\n
α-hCG; 64–67
\n
477.231
\n
477.165
\n
\n
\n
VTVMGGFK
\n
α-hCG; 68–75
\n
838.439
\n
838.471
\n
\n
\n
SK
\n
β-hCG; 1–2
\n
234.135
\n
243.142
\n
\n
\n
PR
\n
β-hCG; 7–8
\n
272.161
\n
271.996
\n
\n
\n
EPLR
\n
β-hCG; 3–6
\n
514.288
\n
514.291
\n
\n
\n
EPLRPR
\n
β-hCG; 3–8
\n
767.442
\n
767.469
\n
\n
\n
DVR
\n
β-hCG; 61–63
\n
389.204
\n
389.228
\n
\n
\n
FESIR
\n
β-hCG; 64–68
\n
651.336
\n
651.359
\n
\n\n
Table 5.
MALDI-PMF and MALDI-PSD analysis of human chorionic gonadotropin. The identified peptides from the α and β subunits are presented in the table below.
\n
The identification was confirmed by DICZE analysis of illegal samples together with the corresponding reference standard [13, 50].
\n
\n
\n
3.10 Identification of melanotan II (MII) and bremelanotide
\n
Melanotan, a melanocortin receptor agonist, is a cyclic-lactam bridge heptapeptide which induces melanogenesis (i.e., tanning of the skin), by activation of the MC1 receptor, being an analogue to alpha melanocyte hormone (α-MSH) [90]. The cyclic, lactam bridged structure of MII induces increased lipophilicity (\nFigure 4\n) [91].
\n
Skin-tanning products that claim to contain MII are being advertised and sold on the illicit drug market. Injection of MII can result in systemic toxicity and rhabdomyolysis [90]. Bremelanotide (formerly PT-141) is an active metabolite of MII (\nTable 1\n).
\n
These peptides were identified through the top-down approach by MALDI in PSD mode as illustrated in \nFigure 9\n.
\n
Figure 9.
MALDI-PSD analysis of melanotan II.
\n
\n
\n
3.11 Identification of dermorphin
\n
Dermorphin is a μ-opioid receptor-binding peptide that causes both central and peripheral effects [92] (\nFigure 4\n and \nTable 1\n). This peptide, being originally isolated from the skin of the south American tree frog Phyllomedusa sauvagii, is classified as one of the strongest mammalian endogenous analgesic opioids [93, 94]. Dried frog skin containing dermorphin, has been used as a therapeutic agent by the Matses tribes of the upper Amazonian basin, to treat cuts during hunting expeditions [95]. The analgetic effects of dermorphin has been demonstrated in rat, horse, dog and white sea cod [92, 94]. It has been used illegally in horse racing as a pain killing agent, allowing horses to run even if injured.
\n
This peptide, which was detected in several samples, was identified by MALDI in the PSD mode (\nFigure 10\n). The molecular structure was confirmed by NMR spectroscopy.
\n
Figure 10.
MALDI-PSD analysis of dermorphin.
\n
\n
\n
3.12 Identification of body protecting compound 157 (BPC 157)
\n
BPC 157 being a partial sequence of body protecting compound (BPC) (Mmass = 40 kDa) is a synthetic peptide, which is composed of fifteen amino acids (\nFigure 4\n and \nTable 1\n). BPC was discovered and isolated from mouse gastric juice in response to stress stimuli in the gut mucosa [96]. BPC 157 is also known as Bepcin and PL. 14,736 or PL 10 [97]. This peptide fragment was speculated to be responsible for the BPC’s physiological and protective effects [96]. However, it is unclear whether this peptide is endogenous to humans. BPC 157 is suggested to aid in tendon, ligament and muscle healing, and therefore its use as a quick injury healing in the sporting world is appealing. However, no proper clinical trials in human subjects have yet been performed to investigate the healing capability and the harmful effects of this compound [97].
\n
BPC 157 was recently identified in several confiscated vials for injection. The identification was carried out by MALDI in both PSD and reflectron modes (\nFigure 11\n). The amino acid sequence of the peptide was confirmed by NMR spectroscopy and LC-QTOF-MS.
\n
Figure 11.
MALDI-PSD analysis of BPC 157.
\n
\n
\n
\n
4. Conclusions
\n
The proposed methods, based on PMF by MALDI-TOF-MS as well as analysis with DICZE, provided an efficient procedure for the identification of peptides and proteins in illegally distributed samples. The use of trypsin as a proteolytic enzyme generated peptide fragments which covered 40 to 80% of the amino acid sequences of the analyzed proteins. The presence of a signature peptide in the peptide map facilitated the analyte identification considerably. MALDI-TOF-MS was also applied in the PSD mode for the amino acid sequencing of selected tryptic peptides as well as small peptides, such as ipamorelin.
\n
The double-injection CE method provided complementary information on the native protein in the presence of a reference standard. This provided the possibility of performing a comparison between the electrophoretic patterns of the reference standard and the analyte to be identified. In addition, the double-injection based identifications were carried out by comparing the corrected migration time of the analyte and the observed migration time of the reference standard.
\n
\n
Abbreviations
ACHCA
α-cyano-4-hydroxycinnamic acid
ACN
Acetonitrile
Aib
Aminobutyric acid
BPC
Body protecting compound
DICZE
Double-injection capillary electrophoresis
DSIP
Delta sleep-inducing peptide
GH
Growth hormone
GHRP
Growth hormone releasing peptide
GHRH
Growth hormone releasing hormone (somatoliberin)
hCG
Human chorionic gonadotropin
hGH
Human growth hormone
IGF-1
Insulin like growth factor 1
ISD
In source decay
Nle
Norleucine
PMF
Protein mass fingerprinting
PSD
Post source decay
SA
Sinapinic acid
TFA
Trifluoroacetic acid
\n',keywords:"matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, double-injection capillary electrophoresis, illegally distributed proteins and peptides",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/74510.pdf",chapterXML:"https://mts.intechopen.com/source/xml/74510.xml",downloadPdfUrl:"/chapter/pdf-download/74510",previewPdfUrl:"/chapter/pdf-preview/74510",totalDownloads:442,totalViews:0,totalCrossrefCites:0,totalDimensionsCites:0,totalAltmetricsMentions:0,impactScore:0,impactScorePercentile:46,impactScoreQuartile:2,hasAltmetrics:0,dateSubmitted:"September 28th 2020",dateReviewed:"December 2nd 2020",datePrePublished:"January 5th 2021",datePublished:"June 2nd 2021",dateFinished:"December 21st 2020",readingETA:"0",abstract:"An analytical strategy based on matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) mass spectrometry (MS) for identification of peptides and proteins in illegally distributed products is presented. The identified compounds include human growth hormone (hGH), human somatoliberin, anti-obesity drug (AOD), growth hormone releasing peptides (GHRP-2 and GHRP-6), Glycine-GHRP-2 and Glycine-GHRP-6, ipamorelin, insulin aspart and porcine, delta sleep-inducing peptide (DSIP), thymosin β4, insulin like growth factor (IGF), mechano growth factor (MGF), human chorionic gonadotropin (hCG), melanotan II, bremelanotide, dermorphin and body protecting compound (BPC 157). The identification of proteins was mainly based on peptide mass fingerprinting, i.e., bottom up approach, while the smaller peptides were identified through de-novo sequencing. In cases when a reference standard was available, complementary identification was performed by capillary electrophoresis in double-injection mode (DICE), where a suspicious product was compared with the reference standard through two consecutive injections within the same electrophoretic run.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/74510",risUrl:"/chapter/ris/74510",book:{id:"10387",slug:"mass-spectrometry-in-life-sciences-and-clinical-laboratory"},signatures:"Ahmad Amini, Torgny Rundlöf, Henrik Lodén, Johan A. Carlsson, Martin Lavén, Ezra Mulugeta, Karin Björk, Torbjörn Arvidsson, Iréne Agerkvist and Anette Perolari",authors:[{id:"333124",title:"Associate Prof.",name:"Ahmad",middleName:null,surname:"Amini",fullName:"Ahmad Amini",slug:"ahmad-amini",email:"ahmad.amini@mpa.se",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"333126",title:"Dr.",name:"Torgny",middleName:null,surname:"Rundlöf",fullName:"Torgny Rundlöf",slug:"torgny-rundlof",email:"torgny.rundlof@mpa.se",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"333127",title:"Dr.",name:"Henrik",middleName:null,surname:"Lodén",fullName:"Henrik Lodén",slug:"henrik-loden",email:"henrik.loden@farmbio.uu.se",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"333128",title:"Dr.",name:"Martin",middleName:null,surname:"Laven",fullName:"Martin Laven",slug:"martin-laven",email:"martin.laven@mpa.se",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"333129",title:"Dr.",name:"Johan",middleName:null,surname:"Carlsson",fullName:"Johan Carlsson",slug:"johan-carlsson",email:"johan.carlsson@mpa.se",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"333130",title:"Dr.",name:"Karin",middleName:null,surname:"Björk",fullName:"Karin Björk",slug:"karin-bjork",email:"karin.bjork@tullverket.se",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"333132",title:"Dr.",name:"Torbjörn",middleName:null,surname:"Arvidsson",fullName:"Torbjörn Arvidsson",slug:"torbjorn-arvidsson",email:"torbjorn.arvidsson@mpa.se",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"336680",title:"Dr.",name:"Ezra",middleName:null,surname:"Mulugeta",fullName:"Ezra Mulugeta",slug:"ezra-mulugeta",email:"ezra.mulugeta@lakemedelsverket.se",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"336681",title:"Dr.",name:"Iréne",middleName:null,surname:"Agerkvist",fullName:"Iréne Agerkvist",slug:"irene-agerkvist",email:"irene.agerkvist@lakemedelsverket.se",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"336682",title:"Dr.",name:"Anette",middleName:null,surname:"Perolari",fullName:"Anette Perolari",slug:"anette-perolari",email:"anette.perolari@lakemedelsverket.se",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Experimental",level:"1"},{id:"sec_2_2",title:"2.1 Sample preparation",level:"2"},{id:"sec_3_2",title:"2.2 Proteolysis",level:"2"},{id:"sec_4_2",title:"2.3 Apparatus and operating conditions",level:"2"},{id:"sec_6",title:"3. Results and discussion",level:"1"},{id:"sec_6_2",title:"3.1 Identification of somatropin (hGH)",level:"2"},{id:"sec_7_2",title:"3.2 Identification of human somatoliberin",level:"2"},{id:"sec_8_2",title:"3.3 Identification of an anti-obesity drug (AOD)",level:"2"},{id:"sec_9_2",title:"3.4 Identification of growth hormone releasing peptides (GHRP)",level:"2"},{id:"sec_10_2",title:"3.5 Identification of mechano growth factor (MGF) and long-R3 insulin-like growth factor (IGF-1)",level:"2"},{id:"sec_11_2",title:"3.6 Identification of insulin porcine and insulin aspart",level:"2"},{id:"sec_12_2",title:"3.7 Identification of delta sleep-inducing peptide (DSIP)",level:"2"},{id:"sec_13_2",title:"3.8 Identification of thymosin β4\n",level:"2"},{id:"sec_14_2",title:"3.9 Identification of human chorionic gonadotropin (hCG)",level:"2"},{id:"sec_15_2",title:"3.10 Identification of melanotan II (MII) and bremelanotide",level:"2"},{id:"sec_16_2",title:"3.11 Identification of dermorphin",level:"2"},{id:"sec_17_2",title:"3.12 Identification of body protecting compound 157 (BPC 157)",level:"2"},{id:"sec_19",title:"4. Conclusions",level:"1"},{id:"sec_22",title:"Abbreviations",level:"1"}],chapterReferences:[{id:"B1",body:'\nCleveland DW, Fischer SG, Kirschner MW, Laemmli UK. Peptide mapping by limited proteolysis in sodium dodecyl sulfate and analysis by gel electrophoresis. Journal of Biological Chemistry. 1977; 252: 1102-1106\n'},{id:"B2",body:'\nMatsudaira P. Sequence from picomole quantities of proteins electroblotted onto polyvinylidene difluoride membranes. Journal of Biological Chemistry. 1987;262:10035-10038\n'},{id:"B3",body:'\nDomon B, Aebersold R. Mass Spectrometry and protein analysis. Science. 2006;312:212-217. DOI: 10.1126/science.1124619\n'},{id:"B4",body:'\nHan X, Aslanian A, Yates III JR. Mass spectrometry for proteomics. Current Opinion in Chemical Biology. 2008;12:483-490. DOI: 10.1016/j.cbpa.2008.07.024\n'},{id:"B5",body:'\nYates III JR, Speicher S, Griffin PR, Hunkapiller T. Peptide mass maps: a highly informative approach to protein identification. 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Omega amino acids in peptide design: incorporation into helices. Biopolymers. 1996;39: 769-777. DOI: 10.1002/(SICI)1097-0282(199612)39:6%3C769::AID-BIP4%3E3.0.CO;2-T\n'},{id:"B74",body:'\nKandalla PK, Goldspink G, Butler-Browne G, Mouly V. Mechano Growth Factor E peptide (MGF-E), derived from an isoform of IGF-1, activates human muscle progenitor cells and induces an increase in their fusion potential at different ages. Mechanisms of Aging and Development. 2011;132:154-162. DOI:10.1016/j.mad.2011.02.007\n'},{id:"B75",body:'\nLaron Z. Biodrugs. Somatomedin-1 (recombinant insulin-like growth factor-1): clinical pharmacology and potential treatment of endocrine and metabolic disorders. 1999;11:55-70. DOI: 10.2165/00063030-199911010-00006\n'},{id:"B76",body:'\nGreen H, Morikawa M, Nixon T. A dual effector theory of growth-hormone action. Differentiation, 1985;29:195-198. DOI:org/10.1111/j.1432-0436.1985.tb00316.x\n'},{id:"B77",body:'\nDubaquié Y, Mortensen DL, Intintoli A, Hogue DA, Nakamura G, Rancatore P, Lester P, Sadick MD, Filvaroff E, Fielder PJ, Lowman HB. Selective Insulin-Like Growth Factor I Variants: Engineering, Biodistributions, and Clearance. Endocrinology. 2001;142: 165-173. DOI: org/10.1210/endo.142.1.7864\n'},{id:"B78",body:'\nSonksen PH. Insulin, growth hormone and sport. Journal of Endocrinology. 2001;170:13-25. DOI: 10-1677/joe.0.1700013\n'},{id:"B79",body:'\nWeston PJ. The dead in bed syndrome revisited: a review of the evidence. Diabetes Management. 2012;2:233-241\n'},{id:"B80",body:'\nDuckworth WC, Bennett RG, Hamel FG. Insulin Degradation: Progress and Potential. Endocrine Reviews. 1998;19:608-624. DOI:org/10.1210/edrv.19.5.0349\n\n'},{id:"B81",body:'\nAmini A. Double-injection capillary electrophoresis for the identification of analytes. Electrophoresis. 2014;35:2915-2921. DOI:org/10.1002/elps.201400229\n'},{id:"B82",body:'\nSchoenenberger GA, Maier PF, Tobler HJ, Monnier M. A naturally occurring delta-EEG-enhancing nonapeptide in rabbits. Pflügers Archiv -European Journal of Physics. 1977;369;99-109\n'},{id:"B83",body:'\nBes F, Hofman W, Schuur J,\nVan Boxtel C. Effects of Delta Sleep-Inducing Peptide on Sleep of Chronic Insomniac Patients. Neuropsychobiology. 1992;26:193-197. DOI:10.1159/000118919\n'},{id:"B84",body:'\nSosne G, QiuP, Goldstein AL, Wheater M. The biological activities of thymosin β4 defined by active sites in short peptide sequences. The FASEB Journal. 2010;24: 2144-2151. DOI:org/10.1096/fj.09-142307\n'},{id:"B85",body:'\nMannherz HG, Hannappel E. The beta-thymosins: intracellular and extracellular activities of a versatile actin binding protein family. Cell Motility and the Cytoskeleton. 2009;66:839-851. DOI: 10.1002/cm.20371\n'},{id:"B86",body:'\nStenman UH, Tiitinen A, Alfthan H, Valmu L. The classification, functions and clinical use of different isoforms of HCG. Human Reproduction Update 2006;12:769-784. DOI:org/10.1093/humupd/dml029\n'},{id:"B87",body:'\nMise T, Bahl OP. Assignment of disulfide bonds in the alpha subunit of human chorionic gonadotropin. Journal of biological Chemistry.1980;255:8516-8522\n'},{id:"B88",body:'\nMise T, Bahl OP. Assignment of disulfide bonds in b sub-unite of human chorionic gonadotropin. Journal of Biological Chemistry. 1981;256:6587-6592\n'},{id:"B89",body:'\nElliott MM, Kardana A, Lustbader JW, Cole LA. Carbohydrate and peptide structure of the alpha- and beta-subunits of human chorionic gonadotropin from normal and aberrant pregnancy and choriocarcinoma. Endocrine. 1997;7:15-32. DOI: 10.1007/BF02778058\n'},{id:"B90",body:'\nNelson ME, Bryant SM, Aks SE. Melanotan II injection resulting in systemic toxicity and rhabdomyolysis. Clinical Toxicology. 2012, 50,1169-1173. DOI: 10.3109/15563650.2012.740637.\n'},{id:"B91",body:'\nHadley ME. Discovery that a melanocortin regulates sexual functions in male and female humans. Peptides, 2005;26:1687-1689. DOI:org/10.1016/j.peptides.2005.01.023\n'},{id:"B92",body:'\nRobinson MA, Guan F, McDonnell S, Uboh CE, Soma LR. Pharmacokinetics and pharmacodynamics of dermorphin in the horse. Journal of Veterinary Pharmacology and Therapeutics, 2014;38:321-329. DOI:org/10.1111/jvp.12179\n'},{id:"B93",body:'\nBroccardo M, Usenko AB, Uranova MG, Guzevatykh LS, Kamensky AA, Andreeva LA, Alfeeva LY, Myasoedov NF, Giannini E, Improta G, Emel’yanova TG. In vitro and in vivo opioid activity of [DPro6]dermorphin, a new dermorphin analogue. Peptides, 2003;24:419-428. DOI:org/10.1016/S0196-9781(03)00057-3\n'},{id:"B94",body:'\nChervova LS, Lapshin DN, Kamenskii AA. Pain Sensitivity of Trout and Analgesia Induced by Intranasal Administration of Dermorphin. Doklady Biological Sciences.1994;338:424-425\n'},{id:"B95",body:'\nNegri L, Melchiorri P, Lattanzi R. Pharmacology of amphibian opiate peptides. Peptides, 2000;21:1639-1647. DOI: 10.1016/s0196-9781(00)00295-3\n'},{id:"B96",body:'\nSikirić, P Petek M, Ručman R, Seiwerth S, Grabarević Z, Rotkvić, I, Turković B, Jagić V, Mildner B, Duvnjak M, Lang N, Danilović Z, Cviko A, Kolega M, Sallmani A, Djačić S, Bura M, Brkić T, Banić M, Dodig M, Corić V, Šimičević V, Veljaca M, Erceg, D, Ježek D, Simunić-Banek L, Skroza N, Bulić K, Buljat G, Hanževački M, Orihovać V, Lučinger D, Culig J, Separović J, Marović, A, Miše S, Suchanek E, Matoz W, Perović D, Gjurašin M, Mikulandra S, Derniković K, Cuk V, Karakas I. A new gastric juice peptide, BPC. An overview of the stomach-stress-organoprotection hypothesis and beneficial effects of BPC. The Journal of Physiology. 1993;87: 313-327. DOI: org/10.1016/0928-4257(93)90038-U\n'},{id:"B97",body:'\nCox HD, Millera GD, Eichnera D. Detection and in vitro metabolism of the confiscated peptides BPC 157 and MGF R23H. Drug Testing and Analysis. 2017;9:1490-1498. DOI: 10.1002/dta.2152\n'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Ahmad Amini",address:"ahmad.amini@lakemedelsverket.se",affiliation:'
Swedish Medical Products Agency, Dag Hammarskjölds väg, Sweden
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All of our IntechOpen sponsors are in good company! The research in past IntechOpen books and chapters have been funded by:
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\r\n\tIn general, the harsher the environmental conditions in an ecosystem, the lower the biodiversity. Changes in the environment caused by human activity accelerate the impoverishment of biodiversity.
\r\n
\r\n\tBiodiversity refers to “the variability of living organisms from any source, including terrestrial, marine and other aquatic ecosystems and the ecological complexes of which they are part; it includes diversity within each species, between species, and that of ecosystems”.
\r\n
\r\n\tBiodiversity provides food security and constitutes a gene pool for biotechnology, especially in the field of agriculture and medicine, and promotes the development of ecotourism.
\r\n
\r\n\tCurrently, biologists admit that we are witnessing the first phases of the seventh mass extinction caused by human intervention. It is estimated that the current rate of extinction is between a hundred and a thousand times faster than it was when man first appeared. The disappearance of species is caused not only by an accelerated rate of extinction, but also by a decrease in the rate of emergence of new species as human activities degrade the natural environment. The conservation of biological diversity is "a common concern of humanity" and an integral part of the development process. Its objectives are “the conservation of biological diversity, the sustainable use of its components, and the fair and equitable sharing of the benefits resulting from the use of genetic resources”.
\r\n
\r\n\tThe following are the main causes of biodiversity loss:
\r\n
\r\n\t• The destruction of natural habitats to expand urban and agricultural areas and to obtain timber, minerals and other natural resources.
\r\n
\r\n\t• The introduction of alien species into a habitat, whether intentionally or unintentionally which has an impact on the fauna and flora of the area, and as a result, they are reduced or become extinct.
\r\n
\r\n\t• Pollution from industrial and agricultural products, which devastate the fauna and flora, especially those in fresh water.
\r\n
\r\n\t• Global warming, which is seen as a threat to biological diversity, and will become increasingly important in the future.
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\r\n\tThe environment is subject to severe anthropic effects. Among them are those associated with pollution, resource extraction and overexploitation, loss of biodiversity, soil degradation, disorderly land occupation and planning, and many others. These anthropic effects could potentially be caused by any inadequate management of the environment. However, ecosystems have a resilience that makes them react to disturbances which mitigate the negative effects. It is critical to understand how ecosystems, natural and anthropized, including urban environments, respond to actions that have a negative influence and how they are managed. It is also important to establish when the limits marked by the resilience and the breaking point are achieved and when no return is possible. The main focus for the chapters is to cover the subjects such as understanding how the environment resilience works, the mechanisms involved, and how to manage them in order to improve our interactions with the environment and promote the use of adequate management practices such as those outlined in the United Nations’ Sustainable Development Goals.
\r\n\tPollution is caused by a wide variety of human activities and occurs in diverse forms, for example biological, chemical, et cetera. In recent years, significant efforts have been made to ensure that the environment is clean, that rigorous rules are implemented, and old laws are updated to reduce the risks towards humans and ecosystems. However, rapid industrialization and the need for more cultivable sources or habitable lands, for an increasing population, as well as fewer alternatives for waste disposal, make the pollution control tasks more challenging. Therefore, this topic will focus on assessing and managing environmental pollution. It will cover various subjects, including risk assessment due to the pollution of ecosystems, transport and fate of pollutants, restoration or remediation of polluted matrices, and efforts towards sustainable solutions to minimize environmental pollution.
\r\n\tWater is not only a crucial substance needed for biological life on Earth, but it is also a basic requirement for the existence and development of the human society. Owing to the importance of water to life on Earth, early researchers conducted numerous studies and analyses on the liquid form of water from the perspectives of chemistry, physics, earth science, and biology, and concluded that Earth is a "water polo". Water covers approximately 71% of Earth's surface. However, 97.2% of this water is seawater, 21.5% is icebergs and glaciers, and only 0.65% is freshwater that can be used directly by humans. As a result, the amount of water reserves available for human consumption is limited. The development, utilization, and protection of freshwater resources has become the focus of water science research for the continued improvement of human livelihoods and society.
\r\n
\r\n\tWater exists as solid, liquid, and gas within Earth’s atmosphere, lithosphere, and biosphere. Liquid water is used for a variety of purposes besides drinking, including power generation, ecology, landscaping, and shipping. Because water is involved in various environmental hydrological processes as well as numerous aspects of the economy and human society, the study of various phenomena in the hydrosphere, the laws governing their occurrence and development, the relationship between the hydrosphere and other spheres of Earth, and the relationship between water and social development, are all part of water science. Knowledge systems for water science are improving continuously. Water science has become a specialized field concerned with the identification of its physical, chemical, and biological properties. In addition, it reveals the laws of water distribution, movement, and circulation, and proposes methods and tools for water development, utilization, planning, management, and protection. Currently, the field of water science covers research related to topics such as hydrology, water resources and water environment. It also includes research on water related issues such as safety, engineering, economy, law, culture, information, and education.
",coverUrl:"https://cdn.intechopen.com/series_topics/covers/41.jpg",keywords:"Water, Water resources, Freshwater, Hydrological processes, Utilization, Protection"}],annualVolumeBook:{},thematicCollection:[],selectedSeries:{title:"Environmental Sciences",id:"25"},selectedSubseries:null},seriesLanding:{item:{id:"11",title:"Biochemistry",doi:"10.5772/intechopen.72877",issn:"2632-0983",scope:"Biochemistry, the study of chemical transformations occurring within living organisms, impacts all areas of life sciences, from molecular crystallography and genetics to ecology, medicine, and population biology. Biochemistry examines macromolecules - proteins, nucleic acids, carbohydrates, and lipids – and their building blocks, structures, functions, and interactions. Much of biochemistry is devoted to enzymes, proteins that catalyze chemical reactions, enzyme structures, mechanisms of action and their roles within cells. Biochemistry also studies small signaling molecules, coenzymes, inhibitors, vitamins, and hormones, which play roles in life processes. Biochemical experimentation, besides coopting classical chemistry methods, e.g., chromatography, adopted new techniques, e.g., X-ray diffraction, electron microscopy, NMR, radioisotopes, and developed sophisticated microbial genetic tools, e.g., auxotroph mutants and their revertants, fermentation, etc. More recently, biochemistry embraced the ‘big data’ omics systems. Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. 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He completed his Ph.D. at MIT in Organic Chemistry; he followed up his Ph.D. with two postdoctoral study periods at Stanford University. Since 1983, he has been a faculty member of the RO Perelman Department of Dermatology, NYU School of Medicine, where he is codirector of a training grant in cutaneous biology. Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},subseries:[{id:"14",title:"Cell and Molecular Biology",keywords:"Omics (Transcriptomics; Proteomics; Metabolomics), Molecular Biology, Cell Biology, Signal Transduction and Regulation, Cell Growth and Differentiation, Apoptosis, Necroptosis, Ferroptosis, Autophagy, Cell Cycle, Macromolecules and Complexes, Gene Expression",scope:"The Cell and Molecular Biology topic within the IntechOpen Biochemistry Series aims to rapidly publish contributions on all aspects of cell and molecular biology, including aspects related to biochemical and genetic research (not only in humans but all living beings). We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics include, but are not limited to: Advanced techniques of cellular and molecular biology (Molecular methodologies, imaging techniques, and bioinformatics); Biological activities at the molecular level; Biological processes of cell functions, cell division, senescence, maintenance, and cell death; Biomolecules interactions; Cancer; Cell biology; Chemical biology; Computational biology; Cytochemistry; Developmental biology; Disease mechanisms and therapeutics; DNA, and RNA metabolism; Gene functions, genetics, and genomics; Genetics; Immunology; Medical microbiology; Molecular biology; Molecular genetics; Molecular processes of cell and organelle dynamics; Neuroscience; Protein biosynthesis, degradation, and functions; Regulation of molecular interactions in a cell; Signalling networks and system biology; Structural biology; Virology and microbiology.",annualVolume:11410,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"79367",title:"Dr.",name:"Ana Isabel",middleName:null,surname:"Flores",fullName:"Ana Isabel Flores",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRpIOQA0/Profile_Picture_1632418099564",institutionString:null,institution:{name:"Hospital Universitario 12 De Octubre",institutionURL:null,country:{name:"Spain"}}},{id:"328234",title:"Ph.D.",name:"Christian",middleName:null,surname:"Palavecino",fullName:"Christian Palavecino",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000030DhEhQAK/Profile_Picture_1628835318625",institutionString:null,institution:{name:"Central University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"186585",title:"Dr.",name:"Francisco Javier",middleName:null,surname:"Martin-Romero",fullName:"Francisco Javier Martin-Romero",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSB3HQAW/Profile_Picture_1631258137641",institutionString:null,institution:{name:"University of Extremadura",institutionURL:null,country:{name:"Spain"}}}]},{id:"15",title:"Chemical Biology",keywords:"Phenolic Compounds, Essential Oils, Modification of Biomolecules, Glycobiology, Combinatorial Chemistry, Therapeutic peptides, Enzyme Inhibitors",scope:"Chemical biology spans the fields of chemistry and biology involving the application of biological and chemical molecules and techniques. In recent years, the application of chemistry to biological molecules has gained significant interest in medicinal and pharmacological studies. This topic will be devoted to understanding the interplay between biomolecules and chemical compounds, their structure and function, and their potential applications in related fields. Being a part of the biochemistry discipline, the ideas and concepts that have emerged from Chemical Biology have affected other related areas. This topic will closely deal with all emerging trends in this discipline.",annualVolume:11411,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null,editorialBoard:[{id:"241413",title:"Dr.",name:"Azhar",middleName:null,surname:"Rasul",fullName:"Azhar Rasul",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRT1oQAG/Profile_Picture_1635251978933",institutionString:null,institution:{name:"Government College University, Faisalabad",institutionURL:null,country:{name:"Pakistan"}}},{id:"178316",title:"Ph.D.",name:"Sergey",middleName:null,surname:"Sedykh",fullName:"Sergey Sedykh",profilePictureURL:"https://mts.intechopen.com/storage/users/178316/images/system/178316.jfif",institutionString:null,institution:{name:"Novosibirsk State University",institutionURL:null,country:{name:"Russia"}}}]},{id:"17",title:"Metabolism",keywords:"Biomolecules Metabolism, Energy Metabolism, Metabolic Pathways, Key Metabolic Enzymes, Metabolic Adaptation",scope:"Metabolism is frequently defined in biochemistry textbooks as the overall process that allows living systems to acquire and use the free energy they need for their vital functions or the chemical processes that occur within a living organism to maintain life. Behind these definitions are hidden all the aspects of normal and pathological functioning of all processes that the topic ‘Metabolism’ will cover within the Biochemistry Series. 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Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. 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