Dataset Information


Reduction of false positives in structure-based virtual screening when receptor plasticity is considered.

ABSTRACT: Structure-based virtual screening for selecting potential drug candidates is usually challenged by how numerous false positives in a molecule library are excluded when receptor plasticity is considered. In this study, based on the binding energy landscape theory, a hypothesis that a true inhibitor can bind to different conformations of the binding site favorably was put forth, and related strategies to defeat this challenge were devised; reducing false positives when receptor plasticity is considered. The receptor in the study is the influenza A nucleoprotein, whose oligomerization is a requirement for RNA binding. The structural flexibility of influenza A nucleoprotein was explored by molecular dynamics simulations. The resultant distinctive structures and the crystal structure were used as receptor models in docking exercises in which two binding sites, the tail-loop binding pocket and the RNA binding site, were targeted with the Otava PrimScreen1 diversity-molecule library using the GOLD software. The intersection ligands that were listed in the top-ranked molecules from all receptor models were selected. Such selection strategy successfully distinguished high-affinity and low-affinity control molecules added to the molecule library. This work provides an applicable approach for reducing false positives and selecting true ligands from molecule libraries.


PROVIDER: S-EPMC6272817 | BioStudies | 2015-01-01

REPOSITORIES: biostudies

Similar Datasets

2017-01-01 | S-EPMC5543994 | BioStudies
2017-01-01 | S-EPMC5653793 | BioStudies
2014-01-01 | S-EPMC4178748 | BioStudies
1000-01-01 | S-EPMC2797012 | BioStudies
2001-01-01 | S-EPMC134593 | BioStudies
2019-01-01 | S-EPMC6791542 | BioStudies
2020-01-01 | S-EPMC7279658 | BioStudies
2012-01-01 | S-EPMC3522603 | BioStudies
1000-01-01 | S-EPMC3161832 | BioStudies
2016-01-01 | S-EPMC4939526 | BioStudies