Literature DB >> 15602552

Virtual screening of chemical libraries.

Brian K Shoichet1.   

Abstract

Virtual screening uses computer-based methods to discover new ligands on the basis of biological structures. Although widely heralded in the 1970s and 1980s, the technique has since struggled to meet its initial promise, and drug discovery remains dominated by empirical screening. Recent successes in predicting new ligands and their receptor-bound structures, and better rates of ligand discovery compared to empirical screening, have re-ignited interest in virtual screening, which is now widely used in drug discovery, albeit on a more limited scale than empirical screening.

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Year:  2004        PMID: 15602552      PMCID: PMC1360234          DOI: 10.1038/nature03197

Source DB:  PubMed          Journal:  Nature        ISSN: 0028-0836            Impact factor:   49.962


  30 in total

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Authors:  Dina Schneidman-Duhovny; Ruth Nussinov; Haim J Wolfson
Journal:  Curr Med Chem       Date:  2004-01       Impact factor: 4.530

Review 2.  Virtual screening methods that complement HTS.

Authors:  Florence L Stahura; Jürgen Bajorath
Journal:  Comb Chem High Throughput Screen       Date:  2004-06       Impact factor: 1.339

3.  Molecular biology. NIH gears up for chemical genomics.

Authors:  Jocelyn Kaiser
Journal:  Science       Date:  2004-06-18       Impact factor: 47.728

4.  Allosteric inhibition through core disruption.

Authors:  James R Horn; Brian K Shoichet
Journal:  J Mol Biol       Date:  2004-03-05       Impact factor: 5.469

Review 5.  The many roles of computation in drug discovery.

Authors:  William L Jorgensen
Journal:  Science       Date:  2004-03-19       Impact factor: 47.728

6.  Rapid diversity-oriented synthesis in microtiter plates for in situ screening of HIV protease inhibitors.

Authors:  Ashraf Brik; John Muldoon; Ying-Chuan Lin; John H Elder; David S Goodsell; Arthur J Olson; Valery V Fokin; K Bary Sharpless; Chi-Huey Wong
Journal:  Chembiochem       Date:  2003-11-07       Impact factor: 3.164

7.  Compounds designed to fit a site of known structure in human haemoglobin.

Authors:  C R Beddell; P J Goodford; F E Norrington; S Wilkinson; R Wootton
Journal:  Br J Pharmacol       Date:  1976-06       Impact factor: 8.739

8.  Discovery of diverse thyroid hormone receptor antagonists by high-throughput docking.

Authors:  Matthieu Schapira; Bruce M Raaka; Sharmistha Das; Li Fan; Maxim Totrov; Zhiguo Zhou; Stephen R Wilson; Ruben Abagyan; Herbert H Samuels
Journal:  Proc Natl Acad Sci U S A       Date:  2003-05-30       Impact factor: 11.205

9.  Virtual screening for inhibitors of human aldose reductase.

Authors:  Oliver Kraemer; Isabelle Hazemann; Alberto D Podjarny; Gerhard Klebe
Journal:  Proteins       Date:  2004-06-01

10.  Automated docking of ligands to an artificial active site: augmenting crystallographic analysis with computer modeling.

Authors:  Robin J Rosenfeld; David S Goodsell; Rabi A Musah; Garrett M Morris; David B Goodin; Arthur J Olson
Journal:  J Comput Aided Mol Des       Date:  2003-08       Impact factor: 3.686

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  327 in total

1.  ElectroShape: fast molecular similarity calculations incorporating shape, chirality and electrostatics.

Authors:  M Stuart Armstrong; Garrett M Morris; Paul W Finn; Raman Sharma; Loris Moretti; Richard I Cooper; W Graham Richards
Journal:  J Comput Aided Mol Des       Date:  2010-07-08       Impact factor: 3.686

2.  Discovery of novel checkpoint kinase 1 inhibitors by virtual screening based on multiple crystal structures.

Authors:  Yan Li; Dong Joon Kim; Weiya Ma; Ronald A Lubet; Ann M Bode; Zigang Dong
Journal:  J Chem Inf Model       Date:  2011-10-12       Impact factor: 4.956

3.  Discovery of novel selective serotonin reuptake inhibitors through development of a protein-based pharmacophore.

Authors:  Sankar Manepalli; Laura M Geffert; Christopher K Surratt; Jeffry D Madura
Journal:  J Chem Inf Model       Date:  2011-09-02       Impact factor: 4.956

4.  Scoring and lessons learned with the CSAR benchmark using an improved iterative knowledge-based scoring function.

Authors:  Sheng-You Huang; Xiaoqin Zou
Journal:  J Chem Inf Model       Date:  2011-08-31       Impact factor: 4.956

5.  Incorporating specificity into optimization: evaluation of SPA using CSAR 2014 and CASF 2013 benchmarks.

Authors:  Zhiqiang Yan; Jin Wang
Journal:  J Comput Aided Mol Des       Date:  2016-02-15       Impact factor: 3.686

6.  Structure-Based Screening of Uncharted Chemical Space for Atypical Adenosine Receptor Agonists.

Authors:  David Rodríguez; Saibal Chakraborty; Eugene Warnick; Steven Crane; Zhan-Guo Gao; Robert O'Connor; Kenneth A Jacobson; Jens Carlsson
Journal:  ACS Chem Biol       Date:  2016-08-22       Impact factor: 5.100

7.  Shallow Representation Learning via Kernel PCA Improves QSAR Modelability.

Authors:  Stefano E Rensi; Russ B Altman
Journal:  J Chem Inf Model       Date:  2017-08-07       Impact factor: 4.956

8.  Drug Screening of Potential Multiple Target Inhibitors for Estrogen Receptor-α-positive Breast Cancer.

Authors:  Juan-Cheng Yang; Yang-Chang Wu; Yun-Hao Dai; Guan-Yu Chen; Chih-Hsin Tang; Wei-Chien Huang
Journal:  In Vivo       Date:  2021 Mar-Apr       Impact factor: 2.155

9.  DOCK 6: Impact of new features and current docking performance.

Authors:  William J Allen; Trent E Balius; Sudipto Mukherjee; Scott R Brozell; Demetri T Moustakas; P Therese Lang; David A Case; Irwin D Kuntz; Robert C Rizzo
Journal:  J Comput Chem       Date:  2015-06-05       Impact factor: 3.376

Review 10.  Computations of standard binding free energies with molecular dynamics simulations.

Authors:  Yuqing Deng; Benoît Roux
Journal:  J Phys Chem B       Date:  2009-02-26       Impact factor: 2.991

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