Protein backbone sidechain1/30/2024 ![]() ![]() Many positions within a protein sequence can absorb a wide variety of substitutions. Such an understanding is especially important in explaining the less-than-straightforward plasticity found between sequence and structure space. These results help to explain the plasticity of amino acid substitutions on protein structure, and should help in protein design and structure evaluation.Ĭlassification of the 20 amino acids simplifies analysis and helps uncover relationships that are important to protein structure, folding and function. Effectively, this consistency across the secondary structure classes imply that side-chain steric effects strongly influence a residue’s backbone torsion angle conformation. Besides the expected uniqueness of the Gly and Pro distributions, the nonpolar/β-branched and AsX clusters were very consistent across all types of secondary structure. At the level of 4 types of secondary structure (helix, sheet, turn, and coil), these groups remain somewhat consistent, although there are a few significant variations. There were 7 general groups based on the clusters from the complete Ramachandran data: nonpolar/β-branched (Ile & Val), AsX (Asn & Asp), long (Met, Gln, Arg, Glu, Lys, & Leu), aromatic (Phe, Tyr, His, & Cys), small (Ala & Ser), bulky (Thr & Trp), and lastly the singletons of Gly and Pro. Based on this statistical modeling, a robust, hierarchical clustering was performed using a divergence score to measure the similarity between plots. To insure the precision of the Ramachandran plot comparisons, we applied a rigorous Bayesian density estimation method that produces continuous estimates of the backbone φ,ψ distributions. At this finer, more specific resolution, the torsion angle data is often sparse and discontinuous (especially for the non-helical classes) even though a comprehensive set of protein structures is used. We extend this approach to understand the effects that side-chains have upon backbone conformation and perform a knowledge-based classification of amino acids by comparing their backbone φ,ψ distributions in different types of secondary structure. Usually, this categorization is based on the biophysical and/or structural properties of a residue’s side-chain group. Our results provide a foundation for the development of spectroscopic markers based on the recently proposed Protein Charge Transfer Spectra (ProCharTS) which are relevant for the study of DNA-binding or intrinsically disordered proteins that are rich in charged amino acids.Grouping the 20 residues is a classic strategy to discover ordered patterns and insights about the fundamental nature of proteins, their structure, and how they fold. We find that photoinduced charge separation is more facile for the anionic amino acids (Asp, Glu, pSer, pThr and pTyr) relative to that for the cationic amino acids (Lys, Arg and Hsp). Photoinduced CT occurs in opposite directions for the anionic and cationic amino acids along the ground state dipole moment vector for the chromophores. The UV-visible spectral range of the backbone-sidechain CT transitions is determined by the chemical nature of the donor, bridge and acceptor groups within each amino acid, amino acid conformation and the protein secondary structure where the amino acids are located. We show that amino acids with charged sidechains present a directed electronic donor–bridge–acceptor paradigm, with the lowest energy optical excitations demonstrating peptide backbone-sidechain charge separations. Specifically, using time dependent density functional theory calculations, we examine the absorption spectra of naturally charged amino acids (Lys, Glu, Arg, Asp and His), extracted from solution phase protein structures generated by classical molecular dynamics simulations, and phosphorylated amino acids (Tyr, Thr and Ser) from experimentally determined protein structures. In this manuscript, we present a detailed computational study of new near UV-visible CT transitions that involve amino acids with charged side chains. Furthermore, the protein backbone also exhibits CT transitions in the far UV range. Metal–ligand complexes or active site prosthetic groups which absorb in the visible region exhibit prominent CT transitions. The absorption of light by proteins can induce charge transfer (CT) transitions in the UV-visible range of the electromagnetic spectrum. ![]()
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