Evidence map›Paper›PMID 24504704›Full record

ArticleJournal of computer-aided molecular design2014

Virtual screening of integrase inhibitors by large scale binding free energy calculations: the SAMPL4 challenge.

Emilio Gallicchio, Nanjie Deng, Peng He, Lauren Wickstrom, Alexander L Perryman, Daniel N Santiago, Stefano Forli, Arthur J Olson, Ronald M Levy

Abstract read
In one paragraph

Article in Journal of computer-aided molecular design, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

36 citing papers in PubMed.

  1. Article
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  8. Evaluation of log P, pKJournal of computer-aided molecular design · 2021
    Article
  9. Protein storytelling through physics.Science (New York, N.Y.) · 2020
    Review
  10. Best Practices for Alchemical Free Energy Calculations [Article v1.0].Living journal of computational molecular science · 2020
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
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  18. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Emilio GallicchioDepartment of Chemistry and Chemical Biology, Rutgers The State University of New Jersey, Piscataway, NJ, 08854, USA, egallicchio@brooklyn.cuny.edu.
Nanjie Deng
Peng He
Lauren Wickstrom
Alexander L Perryman
Daniel N Santiago
Stefano Forli
Arthur J Olson
Ronald M Levy

Funding

Project 9P50GM103368 · NIGMS · SCRIPPS RESEARCH INSTITUTE, THE · PI ARNOLD, EDWARD · 2012 to 2016
$20.0M
AutoDock Suite: Next Generation Environment for Drug DesignR01GM069832 · NIGMS · SCRIPPS RESEARCH INSTITUTE, THE · PI FORLI, STEFANO · 2004 to 2025
$10.9M
DYNAMICS OF PEPTIDES AND PROTEINSR01GM030580 · NIGMS · TEMPLE UNIV OF THE COMMONWEALTH · PI LEVY, RONALD · 1985 to 2018
$6.1M
Computer Cluster for Computational and Structural BiologyS10RR027444 · NCRR · RUTGERS, THE STATE UNIV OF N.J. · PI CASE, DAVID A · 2010 to 2010
$433k
Computer Cluster for Computational and Structural BiologyS10RR022375 · NCRR · RUTGERS, THE STATE UNIV OF N.J. · PI LEVY, RONALD · 2007 to 2007
$291k
NCRR NIH HHS 1 S10 RR022375NCRR NIH HHS 1 S10 RR027444NCRR NIH HHS S10 RR022375NCRR NIH HHS S10 RR027444NIGMS NIH HHS GM30580NIGMS NIH HHS P50 GM103368NIGMS NIH HHS R01 GM030580NIGMS NIH HHS R01 GM069832
6 · The paper itself

Abstract

As part of the SAMPL4 blind challenge, filtered AutoDock Vina ligand docking predictions and large scale binding energy distribution analysis method binding free energy calculations have been applied to the virtual screening of a focused library of candidate binders to the LEDGF site of the HIV integrase protein. The computational protocol leveraged docking and high level atomistic models to improve enrichment. The enrichment factor of our blind predictions ranked best among all of the computational submissions, and second best overall. This work represents to our knowledge the first example of the application of an all-atom physics-based binding free energy model to large scale virtual screening. A total of 285 parallel Hamiltonian replica exchange molecular dynamics absolute protein-ligand binding free energy simulations were conducted starting from docked poses. The setup of the simulations was fully automated, calculations were distributed on multiple computing resources and were completed in a 6-weeks period. The accuracy of the docked poses and the inclusion of intramolecular strain and entropic losses in the binding free energy estimates were the major factors behind the success of the method. Lack of sufficient time and computing resources to investigate additional protonation states of the ligands was a major cause of mispredictions. The experiment demonstrated the applicability of binding free energy modeling to improve hit rates in challenging virtual screening of focused ligand libraries during lead optimization.

Indexed as

Molecular Docking SimulationThermodynamicsComputer-Aided DesignDrug DesignHIVHIV InfectionsHIV IntegraseHumansIntegrase InhibitorsLigandsProtein BindingSoftwareHIV IntegraseIntegrase InhibitorsLigands

Identifiers

PMID24504704
PMCPMC4137862

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.