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Multiple virtual screening approaches for finding new Hepatitis c virus RNA-dependent RNA polymerase inhibitors: Structure-based screens and molecular dynamics for the pursue of new poly…

Overview of attention for article published in BMC Bioinformatics, December 2012
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Title
Multiple virtual screening approaches for finding new Hepatitis c virus RNA-dependent RNA polymerase inhibitors: Structure-based screens and molecular dynamics for the pursue of new poly pharmacological inhibitors
Published in
BMC Bioinformatics, December 2012
DOI 10.1186/1471-2105-13-s17-s5
Pubmed ID
Authors

Mahmoud ElHefnawi, Mohammad ElGamacy, Mohamed Fares

Abstract

The RNA polymerase NS5B of Hepatitis C virus (HCV) is a well-characterised drug target with an active site and four allosteric binding sites. This work presents a workflow for virtual screening and its application to Drug Bank screening targeting the Hepatitis C Virus (HCV) RNA polymerase non-nucleoside binding sites. Potential polypharmacological drugs are sought with predicted active inhibition on viral replication, and with proven positive pharmaco-clinical profiles. The approach adopted was receptor-based. Docking screens, guided with contact pharmacophores and neural-network activity prediction models on all allosteric binding sites and MD simulations, constituted our analysis workflow for identification of potential hits. Steps included: 1) using a two-phase docking screen with Surflex and Glide Xp. 2) Ranking based on scores, and important H interactions. 3) a machine-learning target-trained artificial neural network PIC prediction model used for ranking. This provided a better correlation of IC50 values of the training sets for each site with different docking scores and sub-scores. 4) interaction pharmacophores-through retrospective analysis of protein-inhibitor complex X-ray structures for the interaction pharmacophore (common interaction modes) of inhibitors for the five non-nucleoside binding sites were constructed. These were used for filtering the hits according to the critical binding feature of formerly reported inhibitors. This filtration process resulted in identification of potential new inhibitors as well as formerly reported ones for the thumb II and Palm I sites (HCV-81) NS5B binding sites. Eventually molecular dynamics simulations were carried out, confirming the binding hypothesis and resulting in 4 hits.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
France 1 2%
Germany 1 2%
Unknown 56 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 20%
Researcher 11 19%
Student > Bachelor 9 15%
Student > Master 6 10%
Other 4 7%
Other 8 14%
Unknown 9 15%
Readers by discipline Count As %
Chemistry 7 12%
Engineering 7 12%
Computer Science 7 12%
Agricultural and Biological Sciences 6 10%
Medicine and Dentistry 5 8%
Other 13 22%
Unknown 14 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 May 2013.
All research outputs
#9,880,774
of 12,378,406 outputs
Outputs from BMC Bioinformatics
#3,787
of 4,542 outputs
Outputs of similar age
#185,221
of 265,428 outputs
Outputs of similar age from BMC Bioinformatics
#138
of 162 outputs
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