scholarly journals Improving Blind Docking in DOCK6 through an Automated Preliminary Fragment Probing Strategy

Molecules ◽  
2021 ◽  
Vol 26 (5) ◽  
pp. 1224
Author(s):  
Paula Jofily ◽  
Pedro G. Pascutti ◽  
Pedro H. M. Torres
Keyword(s):  
Binding Sites ◽  
Search Algorithm ◽  
Pose Prediction ◽  
Success Rates ◽  
Protein Surfaces ◽  
Cavity Detection ◽  
Docking Method ◽  
Potential Binding ◽  
Binding Pockets ◽  
Automated Pipeline

Probing protein surfaces to accurately predict the binding site and conformation of a small molecule is a challenge currently addressed through mainly two different approaches: blind docking and cavity detection-guided docking. Although cavity detection-guided blind docking has yielded high success rates, it is less practical when a large number of molecules must be screened against many detected binding sites. On the other hand, blind docking allows for simultaneous search of the whole protein surface, which however entails the loss of accuracy and speed. To bridge this gap, in this study, we developed and tested BLinDPyPr, an automated pipeline which uses FTMap and DOCK6 to perform a hybrid blind docking strategy. Through our algorithm, FTMap docked probe clusters are converted into DOCK6 spheres for determining binding regions. Because these spheres are solely derived from FTMap probes, their locations are contained in and specific to multiple potential binding pockets, which become the regions that are simultaneously probed and chosen by the search algorithm based on the properties of each candidate ligand. This method yields pose prediction results (45.2–54.3% success rates) comparable to those of site-specific docking with the classic DOCK6 workflow (49.7–54.3%) and is half as time-consuming as the conventional blind docking method with DOCK6.

Evaluation of Grey Wolf Optimization Algorithm on Rigid and Flexible Receptor Docking

2020 ◽  
Author(s):  
Kin Meng Wong ◽  
Shirley Siu
Keyword(s):  
Scoring Function ◽  
Ligand Docking ◽  
Receptor Protein ◽  
Pose Prediction ◽  
Grey Wolf ◽  
Success Rates ◽  
Autodock Vina ◽  
Grey Wolf Optimization ◽  
Structure Based Drug Design ◽  
Docking Program

Protein-ligand docking programs are indispensable tools for predicting the binding pose of a ligand to the receptor protein in current structure-based drug design. In this paper, we evaluate the performance of grey wolf optimization (GWO) in protein-ligand docking. Two versions of the GWO docking program – the original GWO and the modified one with random walk – were implemented based on AutoDock Vina. Our rigid docking experiments show that the GWO programs have enhanced exploration capability leading to significant speedup in the search while maintaining comparable binding pose prediction accuracy to AutoDock Vina. For flexible receptor docking, the GWO methods are competitive in pose ranking but lower in success rates than AutoDockFR. Successful redocking of all the flexible cases to their holo structures reveals that inaccurate scoring function and lack of proper treatment of backbone are the major causes of docking failures.

scholarly journals PepSite: prediction of peptide-binding sites from protein surfaces

2012 ◽  
Vol 40 (W1) ◽  
pp. W423-W427 ◽  
Author(s):  
L. G. Trabuco ◽  
S. Lise ◽  
E. Petsalaki ◽  
R. B. Russell
Keyword(s):  
Binding Sites ◽  
Peptide Binding ◽  
Protein Surfaces

Empirical rules facilitate the search for binding sites on protein surfaces

2007 ◽  
Vol 25 (5) ◽  
pp. 671-679 ◽  
Author(s):  
Henrik te Heesen ◽  
Anna Melissa Schlitter ◽  
Jürgen Schlitter
Keyword(s):  
Binding Sites ◽  
Protein Surfaces

scholarly journals Subunit stoichiometry and arrangement in a heteromeric glutamate-gated chloride channel

2016 ◽  
Vol 113 (5) ◽  
pp. E644-E653 ◽  
Author(s):  
Nurit Degani-Katzav ◽  
Revital Gortler ◽  
Lilach Gorodetzki ◽  
Yoav Paas
Keyword(s):  
Binding Site ◽  
Binding Sites ◽  
Parasitic Diseases ◽  
Β Subunit ◽  
River Blindness ◽  
Subunit Stoichiometry ◽  
Binding Pockets ◽  
Extracellular Side ◽  
Electrophysiological Characterization

The invertebrate glutamate-gated chloride-selective receptors (GluClRs) are ion channels serving as targets for ivermectin (IVM), a broad-spectrum anthelmintic drug used to treat human parasitic diseases like river blindness and lymphatic filariasis. The native GluClR is a heteropentamer consisting of α and β subunit types, with yet unknown subunit stoichiometry and arrangement. Based on the recent crystal structure of a homomeric GluClαR, we introduced mutations at the intersubunit interfaces where Glu (the neurotransmitter) binds. By electrophysiological characterization of these mutants, we found heteromeric assemblies with two equivalent Glu-binding sites at β/α intersubunit interfaces, where the GluClβ and GluClα subunits, respectively, contribute the “principal” and “complementary” components of the putative Glu-binding pockets. We identified a mutation in the IVM-binding site (far away from the Glu-binding sites), which significantly increased the sensitivity of the heteromeric mutant receptor to both Glu and IVM, and improved the receptor subunits’ cooperativity. We further characterized this heteromeric GluClR mutant as a receptor having a third Glu-binding site at an α/α intersubunit interface. Altogether, our data unveil heteromeric GluClR assemblies having three α and two β subunits arranged in a counterclockwise β-α-β-α-α fashion, as viewed from the extracellular side, with either two or three Glu-binding site interfaces.

scholarly journals Connecting Structure with Kinetics of Single-Stranded DNA Fluctuations that Provide Potential Binding Sites for Replication Proteins

2021 ◽  
Vol 120 (3) ◽  
pp. 219a
Author(s):  
Claire Albrecht ◽  
Brett A. Israels ◽  
Chloe Chvatal ◽  
Peter H. von Hippel ◽  
Andrew H. Marcus
Keyword(s):  
Binding Sites ◽  
Replication Proteins ◽  
Single Stranded Dna ◽  
Potential Binding ◽  
Kinetics Of

scholarly journals NSiteMatch: Prediction of Binding Sites of Nucleotides by Identifying the Structure Similarity of Local Surface Patches

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Jie Sun ◽  
Ke Chen
Keyword(s):  
Binding Sites ◽  
Surface Patch ◽  
Energy Calculation ◽  
Local Similarity ◽  
Success Rates ◽  
Biologically Relevant ◽  
Surface Patches ◽  
Extensive Evaluation ◽  
Structure Similarity ◽  
Global Similarity

Nucleotides play a central role in life-form metabolism, by interacting with proteins and mediating the function of proteins. It is estimated that nucleotides constitute about 15% of the biologically relevant ligands included in PDB. Prediction of binding sites of nucleotides is useful in understanding the function of proteins and can facilitate the in silico design of drugs. In this study, we propose a nucleotide-binding site predictor, namely, NSiteMatch. The NSiteMatch algorithm integrates three different strategies: geometrical analysis, energy calculation, and template comparison. Unlike a traditional template-based predictor, which identifies global similarity between target structure and template, NSiteMatch concerns the local similarity between a surface patch of the target protein and the binding sites of template. To this end, NSiteMatch identifies more templates than traditional template-based predictors. The NSiteMatch predictor is compared with three representative methods, Findsite, Q-SiteFinder, and MetaPocket. An extensive evaluation demonstrates that NSiteMatch achieves higher success rates than Findsite, Q-SiteFinder, and MetaPocket, in prediction of binding sites of ATP, ADP, and AMP.

Architectural Repertoire of Ligand-Binding Pockets on Protein Surfaces

ChemBioChem ◽  
2010 ◽  
Vol 11 (4) ◽  
pp. 556-563 ◽  
Author(s):  
Martin Weisel ◽  
Jan M. Kriegl ◽  
Gisbert Schneider
Keyword(s):  
Ligand Binding ◽  
Protein Surfaces ◽  
Binding Pockets
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