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      Predicting the side-chain dihedral angle distributions of nonpolar, aromatic, and polar amino acids using hard sphere models : Predicting Side-Chain Dihedral Angle Distributions

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      Proteins: Structure, Function, and Bioinformatics
      Wiley-Blackwell

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          Abstract

          The side-chain dihedral angle distributions of all amino acids have been measured from myriad high-resolution protein crystal structures. However, we do not yet know the dominant interactions that determine these distributions. Here, we explore to what extent the defining features of the side-chain dihedral angle distributions of different amino acids can be captured by a simple physical model. We find that a hard-sphere model for a dipeptide mimetic that includes only steric interactions plus stereochemical constraints is able to recapitulate the key features of the back-bone dependent observed amino acid side-chain dihedral angle distributions of Ser, Cys, Thr, Val, Ile, Leu, Phe, Tyr, and Trp. We find that for certain amino acids, performing the calculations with the amino acid of interest in the central position of a short α-helical segment improves the match between the predicted and observed distributions. We also identify the atomic interactions that give rise to the differences between the predicted distributions for the hard-sphere model of the dipeptide and that of the α-helical segment. Finally, we point out a case where the hard-sphere plus stereochemical constraint model is insufficient to recapitulate the observed side-chain dihedral angle distribution, namely the distribution P(χ₃) for Met.

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          Most cited references19

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          The Anatomy and Taxonomy of Protein Structure

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            PISCES: recent improvements to a PDB sequence culling server

            PISCES is a database server for producing lists of sequences from the Protein Data Bank (PDB) using a number of entry- and chain-specific criteria and mutual sequence identity. Our goal in culling the PDB is to provide the longest list possible of the highest resolution structures that fulfill the sequence identity and structural quality cut-offs. The new PISCES server uses a combination of PSI-BLAST and structure-based alignments to determine sequence identities. Structure alignment produces more complete alignments and therefore more accurate sequence identities than PSI-BLAST. PISCES now allows a user to cull the PDB by-entry in addition to the standard culling by individual chains. In this scenario, a list will contain only entries that do not have a chain that has a sequence identity to any chain in any other entry in the list over the sequence identity cut-off. PISCES also provides fully annotated sequences including gene name and species. The server allows a user to cull an input list of entries or chains, so that other criteria, such as function, can be used. Results from a search on the re-engineered RCSB's site for the PDB can be entered into the PISCES server by a single click, combining the powerful searching abilities of the PDB with PISCES's utilities for sequence culling. The server's data are updated weekly. The server is available at .
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              Bayesian statistical analysis of protein side-chain rotamer preferences.

              We present a Bayesian statistical analysis of the conformations of side chains in proteins from the Protein Data Bank. This is an extension of the backbone-dependent rotamer library, and includes rotamer populations and average chi angles for a full range of phi, psi values. The Bayesian analysis used here provides a rigorous statistical method for taking account of varying amounts of data. Bayesian statistics requires the assumption of a prior distribution for parameters over their range of possible values. This prior distribution can be derived from previous data or from pooling some of the present data. The prior distribution is combined with the data to form the posterior distribution, which is a compromise between the prior distribution and the data. For the chi 2, chi 3, and chi 4 rotamer prior distributions, we assume that the probability of each rotamer type is dependent only on the previous chi rotamer in the chain. For the backbone-dependence of the chi 1 rotamers, we derive prior distributions from the product of the phi-dependent and psi-dependent probabilities. Molecular mechanics calculations with the CHARMM22 potential show a strong similarity with the experimental distributions, indicating that proteins attain their lowest energy rotamers with respect to local backbone-side-chain interactions. The new library is suitable for use in homology modeling, protein folding simulations, and the refinement of X-ray and NMR structures.
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                Author and article information

                Journal
                Proteins: Structure, Function, and Bioinformatics
                Proteins
                Wiley-Blackwell
                08873585
                October 2014
                October 11 2014
                : 82
                : 10
                : 2574-2584
                Article
                10.1002/prot.24621
                24912976
                a546efcb-3bfb-48f1-8359-459c041ad73b
                © 2014

                http://doi.wiley.com/10.1002/tdm_license_1.1

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