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Open AccessJournal ArticleDOI

The VSGB 2.0 model: A next generation energy model for high resolution protein structure modeling

TLDR
Given the precision and robustness of the calculations, it is believed that the VSGB 2.0 model is suitable to tackle “real” problems, such as biological function modeling and structure‐based drug discovery.
Abstract
A novel energy model (VSGB 2.0) for high resolution protein structure modeling is described, which features an optimized implicit solvent model as well as physics-based corrections for hydrogen bonding, π-π interactions, self-contact interactions and hydrophobic interactions. Parameters of the VSGB 2.0 model were fit to a crystallographic database of 2239 single side chain and 100 11–13 residue loop predictions. Combined with an advanced method of sampling and a robust algorithm for protonation state assignment, the VSGB 2.0 model was validated by predicting 115 super long loops up to 20 residues. Despite the dramatically increasing difficulty in reconstructing longer loops, a high accuracy was achieved: all of the lowest energy conformations have global backbone RMSDs better than 2.0 A from the native conformations. Average global backbone RMSDs of the predictions are 0.51, 0.63, 0.70, 0.62, 0.80, 1.41, and 1.59 A for 14, 15, 16, 17, 18, 19, and 20 residue loop predictions, respectively. When these results are corrected for possible statistical bias as explained in the text, the average global backbone RMSDs are 0.61, 0.71, 0.86, 0.62, 1.06, 1.67, and 1.59 A. Given the precision and robustness of the calculations, we believe that the VSGB 2.0 model is suitable to tackle “real” problems, such as biological function modeling and structure-based drug discovery.

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A Pilot Study of All-Computational Drug Design Protocol-From Structure Prediction to Interaction Analysis.

TL;DR: A protocol which integrates various in silico approaches, from de novo protein structure prediction to ligand-protein interaction simulation, which facilitates the acceleration of new drug discovery is proposed and applied to the drug design of structure unknown proteins.
Journal ArticleDOI

Pharmacophore generation, atom-based 3D-QSAR and molecular dynamics simulation analyses of pyridine-3-carboxamide-6-yl-urea analogues as potential gyrase B inhibitors.

TL;DR: Computational studies based on pharmacophore modelling, atom-based QSAR, molecular docking, free binding energy calculation and dynamics simulation were performed on a series of pyridine-3-carboxamide-6-yl-urea derivatives, revealing structural and chemical features necessary for these molecules to inhibit GyrB.
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An SH2 domain model of STAT5 in complex with phospho-peptides define “STAT5 Binding Signatures”

TL;DR: The results put in place the foundations to address STAT5 as a target for rational drug design, from sequence, structural and functional perspectives.
Journal ArticleDOI

Prediction of Long Loops with Embedded Secondary Structure using the Protein Local Optimization Program.

TL;DR: The applicability of the Protein Local Optimization Program is extended to loops up to 17 residues in length that contain either helical or hairpin segments and the effect of an imprecise surrounding environment is explored.
Journal ArticleDOI

Molecular Basis of Class B GPCR Selectivity for the Neuropeptides PACAP and VIP

TL;DR: In this article, the authors combined structural information and advanced simulation techniques to study PACAP/VIP binding selectivity, full-length receptor conformation ensembles and transitions of the PACAP and VIP receptor variants and subtypes, and a few key interactions in the orthosteric binding pocket.
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