Quantum-Chemical Description of the Propensity of Amino Acids of Formation of the Peptide Bond

Review Article

Austin J Comput Biol Bioinform. 2016; 3(1): 1014.

Quantum-Chemical Description of the Propensity of Amino Acids of Formation of the Peptide Bond

Kereselidze J* and Mikuchadze G

Department of Chemistry, Ivane Javakhishvili Tbilisi State University, Georgia

*Corresponding author: Jumber Kereselidze, Department of Chemistry, Ivane Javakhishvili Tbilisi State University, 0179 Tbilisi, Georgia

Received: May 20, 2016; Accepted: June 16, 2016; Published: June 20, 2016


With purpose of quantitative description of peptide bond formation the bond orders (PCO and PRNH), the bond lengths (RCO and RRNH), the charges on the carbon and nitrogen atoms (qC and qN) of carbonyl and amino groups, the activation energy (ΔE#) and the reaction Energy (ΔE) for 400 amino acid pairs by use the quantum - chemical method of Density Functional Theory (DFT) have been calculated. The formula of propensity of amino acids of peptide bonds formation (KP) by means these values were constructed.

Keywords: Amino acid; Peptide bond; Parameter of propensity; DFT calculations


The theoretical description of biochemical processes for the development of the main direction of natural science - biophysical chemistry is very actual. In recent years, for a quantitative description of complex biochemical processes the modern method of quantum chemistry - Density Functional Theory (DFT) is widely used. Including and for investigation of the mechanism of peptide bond formation too [1]. It is assumed that the inductive and steric effects of the R-groups of amino acids have an effect on propensity of peptide bond formation [2]. A quantum-mechanical study of different possible mechanisms of peptide synthesis in the ribosome has been carried out using density functional also [3]. Analysis of database of protein sequences for all possible binary patterns of polar and non-polar amino acid residues revealed that alternating patterns occur significantly less often than others with similar composition. To facilitate understanding of the information available for protein structures, has been constructed the structural classification of proteins (scop) database. This database provides a detailed and comprehensive description of the structural and evolutionary relationships of the proteins of the known structure [4]. Analysis of extant proteomes has the potential of revealing how the frequencies of amino acids within proteins have evolved over biological time. It was shown that presented here residues of cysteine, tyrosine and phenylalanine have substantially increased in frequency [5]. To understand more fully how amino acid composition of proteins has changed over the course of evolution, a method has been developed for estimating the composition of proteins in an ancestral genome. This method was used to infer the amino acid composition of a large protein set in the Last Universal Ancestor (LUA) of all extant species. It is proposed that the inferred amino acid composition of proteins in the LUA probably reflects historical events in the establishment of the genetic code [6]. Several different formal definitions of local complexity and probability are presented and are compared for their utility in algorithms for localization of such regions in amino acid sequences and sequence databases. The occurrence of all di- and tripeptide segments of proteins was counted in a large data base containing about 119 000 residues. Systematic conformational analysis study of the tripeptidic units (Gly-X-Pro) and (Gly-Pro-X), with X = Pro, Ala, Ser, Val, Leu, Ile, and Phe it has been reported. The low-energy conformers obtained by quantum computations are discussed with respect to other theoretical investigations [7]. Model building revealed that of the 210 possible amino acid pairs of the standard 20 amino acids, no more than 26 could be built to meet standard criteria for bonding. Of these 26, 14 were found to be genetically encoded when the codons are read as if they paired in a parallel manner [8].


DFT is a computational quantum mechanical method and used in physical, chemical and biological sciences for investigate the electronic structure of molecules [9]. The properties of a manyelectron system can be determined by using functionals, which in this case is the spatially dependent electron density. Hence the name density functional theory comes from the use of functionals of the electron density. DFT is among the most popular and versatile methods available in computational biology. Hybrid methods, as the name suggests, attempt to incorporate some of the more useful features from ab initio methods (specifically Hartree-Fock methods) with some of the improvements of DFT mathematics. Hybrid methods, such as B3LYP [10-13], tend to be the most commonly used methods for computational chemistry and Biology.

Results and Discussion

The purpose of this paper is a quantitative description of the propensity of amino acids of formation of peptide bonds by means of quantum - chemical modern method of Density Functional Theory (DFT). All 400 options of pairing of the 20 amino acids are shown in (Table 1).