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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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Identification of Ecdysone Hormone Receptor Agonists as a Therapeutic Approach for Treating Filarial Infections.

TL;DR: The studies validate the potential of the B. malayi ecdysone receptor as a drug target and provide a means to rapidly evaluate compounds for development of a new class of drugs against the human filarial parasites.
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Computational methods for high resolution prediction and refinement of protein structures.

TL;DR: Improvements in the generalized Born model and hydrophobicity term yield significantly more accurate energetics; specialized sampling algorithms allow complex local structures, such as a loop-helix-loop region, to be reliably predicted.
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Computational study of the binding orientation and affinity of PPARγ agonists: inclusion of ligand-induced fit by cross-docking

TL;DR: The docking of several potent agonists were performed inside the binding site of PPARγ and quantitative correlations between the obtained scoring energy functions and experimental biological activities were determined using the Glide and MM/GBSA methods.
References
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Improved protein-ligand docking using GOLD.

TL;DR: In terms of producing binding energy estimates, the Goldscore function appears to perform better than the Chemscore function and the two consensus protocols, particularly for faster search settings.
Journal ArticleDOI

Funnels, pathways, and the energy landscape of protein folding: A synthesis

TL;DR: The work unifies several previously proposed ideas concerning the mechanism protein folding and delimits the regions of validity of these ideas under different thermodynamic conditions.
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