Literature DB >> 16250664

Enhancing the effectiveness of similarity-based virtual screening using nearest-neighbor information.

Jérôme Hert1, Peter Willett, David J Wilton, Pierre Acklin, Kamal Azzaoui, Edgar Jacoby, Ansgar Schuffenhauer.   

Abstract

We test the hypothesis that fusing the outputs of similarity searches based on a single bioactive reference structure and on its nearest neighbors (of unknown activity) is more effective (in terms of numbers of high-ranked active structures) than a similarity search involving just the reference structure. This turbo similarity searching approach provides a simple way to enhance the effectiveness of simulated virtual screening searches of the MDL Drug Data Report database.

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Year:  2005        PMID: 16250664     DOI: 10.1021/jm050316n

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  12 in total

1.  Ligand expansion in ligand-based virtual screening using relevance feedback.

Authors:  Ammar Abdo; Faisal Saeed; Hentabli Hamza; Ali Ahmed; Naomie Salim
Journal:  J Comput Aided Mol Des       Date:  2012-01-17       Impact factor: 3.686

2.  A CROC stronger than ROC: measuring, visualizing and optimizing early retrieval.

Authors:  S Joshua Swamidass; Chloé-Agathe Azencott; Kenny Daily; Pierre Baldi
Journal:  Bioinformatics       Date:  2010-04-07       Impact factor: 6.937

3.  Virtual screening applications: a study of ligand-based methods and different structure representations in four different scenarios.

Authors:  Dimitar P Hristozov; Tudor I Oprea; Johann Gasteiger
Journal:  J Comput Aided Mol Des       Date:  2007-11-16       Impact factor: 3.686

4.  Analysis and use of fragment-occurrence data in similarity-based virtual screening.

Authors:  Shereena M Arif; John D Holliday; Peter Willett
Journal:  J Comput Aided Mol Des       Date:  2009-06-18       Impact factor: 3.686

5.  Exploring ensembles of bioactive or virtual analogs of X-ray ligands for shape similarity searching.

Authors:  Tomoyuki Miyao; Jürgen Bajorath
Journal:  J Comput Aided Mol Des       Date:  2018-07-02       Impact factor: 3.686

6.  Combining 2D and 3D in silico methods for rapid selection of potential PDE5 inhibitors from multimillion compounds' repositories: biological evaluation.

Authors:  Tünde Tömöri; István Hajdú; László Barna; Zsolt Lorincz; Sándor Cseh; György Dormán
Journal:  Mol Divers       Date:  2011-09-27       Impact factor: 2.943

7.  Influence relevance voting: an accurate and interpretable virtual high throughput screening method.

Authors:  S Joshua Swamidass; Chloé-Agathe Azencott; Ting-Wan Lin; Hugo Gramajo; Shiou-Chuan Tsai; Pierre Baldi
Journal:  J Chem Inf Model       Date:  2009-04       Impact factor: 4.956

8.  Turbo prediction: a new approach for bioactivity prediction.

Authors:  Ammar Abdo; Maude Pupin
Journal:  J Comput Aided Mol Des       Date:  2022-01-21       Impact factor: 3.686

9.  Large scale study of multiple-molecule queries.

Authors:  Ramzi J Nasr; S Joshua Swamidass; Pierre F Baldi
Journal:  J Cheminform       Date:  2009-06-04       Impact factor: 5.514

10.  Identification of novel antimalarial chemotypes via chemoinformatic compound selection methods for a high-throughput screening program against the novel malarial target, PfNDH2: increasing hit rate via virtual screening methods.

Authors:  Raman Sharma; Alexandre S Lawrenson; Nicholas E Fisher; Ashley J Warman; Alison E Shone; Alasdair Hill; Alison Mbekeani; Chandrakala Pidathala; Richard K Amewu; Suet Leung; Peter Gibbons; David W Hong; Paul Stocks; Gemma L Nixon; James Chadwick; Joanne Shearer; Ian Gowers; David Cronk; Serge P Parel; Paul M O'Neill; Stephen A Ward; Giancarlo A Biagini; Neil G Berry
Journal:  J Med Chem       Date:  2012-03-22       Impact factor: 7.446

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