Quantifying side-chain conformational variations in protein structure

Abstract

Protein side-chain conformation is closely related to their biological functions. The side-chain prediction is a key step in protein design, protein docking and structure optimization. However, side-chain polymorphism comprehensively exists in protein as various types and has been long overlooked by side-chain prediction. But such conformational variations have not been quantitatively studied and the correlations between these variations and residue features are vague. Here, we performed statistical analyses on large scale data sets and found that the side-chain conformational flexibility is closely related to the exposure to solvent, degree of freedom and hydrophilicity. These analyses allowed us to quantify different types of side-chain variabilities in PDB. The results underscore that protein side-chain conformation prediction is not a single-answer problem, leading us to reconsider the assessment approaches of side-chain prediction programs.

The Floquet Theory of the Two-Level System Revisited

“…Especially the seminal paper of J. H. Shirley [4] has until now been cited more than 11 000 times. Among the numerous applications of the theory of periodically driven two level systems are nuclear magnetic resonance [5], acdriven quantum dots [6], Josephson qubit circuits [7], and coherent destruction of tunneling [8]. On the theoretical level the methods of solving the RPL and related problems have been gradually refined and include power series approximations for Bloch-Siegert shifts [9] [10], perturbation theory and/or various limit cases [11] - [16] and the hybridized rotating wave approximation [17].…”

Protein phenotype diagnosis of autosomal dominant calmodulin mutations causing irregular heart rhythms

“…Our quantitative backbone atom analysis (in terms of RMSD) of protein structures reflected that CaM variants (Iso54, Leu90, Val/His96, Asn/Iso98, Val103, Gly/Val130, Val/Glu/HisD132, His134, Pro136, Gly141, and Leu142) are seen to have subtle structural changes at the mutant amino acid residue level. The degree of structure variation caused by individual amino acid residues, in general, corresponds to their biophysical and chemical properties like its size, charge, molecular weight, chemical side chains, and hydrophobic nature . These structural deviations may, in turn, affect ionic, H‐bond and Vander wall interactions helping to maintain the secondary (α‐helix, β‐sheets), tertiary (3D) and quaternary (biomolecular complexes) structural features of calmodulin protein.…”

PyRod Enables Rational Homology Model‐based Virtual Screening Against MCHR1

“…In such situation, researchers often employ homology modeling, a method that is generating an atomistic model of the target of interest based on a closely related macromolecule . However, performing structure‐based virtual screening using homology models increases the chance for modeling artifacts, since even small modeling errors, such as a wrong side chain conformation essential for ligand binding, can impair docking performance …”

“…The orthosteric pocket residues Q 3.36 , Q 5.42 and Q 6.55 are highly flexible allowing various conformations and interact with several neighboring residues in a complex hydrogen bonding network (Figure ). Such situations complicate docking studies, since their performance can already be affected by small changes in side chain conformations . Thus, this homology model was subjected to molecular dynamics simulations with Desmond 5.1 to explore side chain conformations.…”