Literature DB >> 23651486

Assessing the performance of 3D pharmacophore models in virtual screening: how good are they?

Rodolpho C Braga1, Carolina H Andrade.   

Abstract

Pharmacophore approaches have evolved to be one of the most successful tools in drug discovery, especially since the past two decades. 3D pharmacophore methods are now commonly used as part of more complex workflows in drug discovery campaigns, and have been successfully and extensively applied in virtual screening (VS) approaches. This review provides a perspective of how to assess the performance of 3D pharmacophore models to be used in VS. Since 3D VS protocols are in general assessed by their ability to discriminate between active and inactive compounds, we summarize the impact of the composition and preparation of modeling and external sets on the outcome of evaluations. Moreover, we highlight the significance of both classic enrichment parameters and advanced descriptors for the performance of 3D pharmacophore-based virtual screening methods.

Mesh:

Year:  2013        PMID: 23651486     DOI: 10.2174/1568026611313090010

Source DB:  PubMed          Journal:  Curr Top Med Chem        ISSN: 1568-0266            Impact factor:   3.295


  27 in total

1.  Receptor pharmacophore ensemble (REPHARMBLE): a probabilistic pharmacophore modeling approach using multiple protein-ligand complexes.

Authors:  Sivakumar Prasanth Kumar
Journal:  J Mol Model       Date:  2018-09-15       Impact factor: 1.810

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Authors:  Janay Stefany Carneiro Araujo; Bruno Cruz de Souza; David Bacelar Costa Junior; Larissa de Mattos Oliveira; Isis Bugia Santana; Angelo Amâncio Duarte; Pedro Sousa Lacerda; Manoelito Coelho Dos Santos Junior; Franco Henrique Andrade Leite
Journal:  J Mol Model       Date:  2018-07-28       Impact factor: 1.810

3.  Pharmacophore modeling, docking and molecular dynamics to identify Leishmania major farnesyl pyrophosphate synthase inhibitors.

Authors:  Larissa de Mattos Oliveira; Janay Stefany Carneiro Araújo; David Bacelar Costa Junior; Isis Bugia Santana; Angelo Amâncio Duarte; Franco Henrique Andrade Leite; Raquel Guimarães Benevides; Manoelito Coelho Dos Santos Junior
Journal:  J Mol Model       Date:  2018-10-16       Impact factor: 1.810

4.  Benchmarking methods and data sets for ligand enrichment assessment in virtual screening.

Authors:  Jie Xia; Ermias Lemma Tilahun; Terry-Elinor Reid; Liangren Zhang; Xiang Simon Wang
Journal:  Methods       Date:  2014-12-03       Impact factor: 3.608

5.  Identification of Nitazoxanide as a Group I Metabotropic Glutamate Receptor Negative Modulator for the Treatment of Neuropathic Pain: An In Silico Drug Repositioning Study.

Authors:  Ni Ai; Richard D Wood; William J Welsh
Journal:  Pharm Res       Date:  2015-03-12       Impact factor: 4.200

6.  Maximal Unbiased Benchmarking Data Sets for Human Chemokine Receptors and Comparative Analysis.

Authors:  Jie Xia; Terry-Elinor Reid; Song Wu; Liangren Zhang; Xiang Simon Wang
Journal:  J Chem Inf Model       Date:  2018-05-08       Impact factor: 4.956

Review 7.  Modern approaches to accelerate discovery of new antischistosomal drugs.

Authors:  Bruno Junior Neves; Eugene Muratov; Renato Beilner Machado; Carolina Horta Andrade; Pedro Vitor Lemos Cravo
Journal:  Expert Opin Drug Discov       Date:  2016-05-03       Impact factor: 6.098

8.  Integrating sampling techniques and inverse virtual screening: toward the discovery of artificial peptide-based receptors for ligands.

Authors:  Germán M Pérez; Luis A Salomón; Luis A Montero-Cabrera; José M García de la Vega; Marcello Mascini
Journal:  Mol Divers       Date:  2015-11-09       Impact factor: 2.943

9.  Molecular docking of alpha-enolase to elucidate the promising candidates against Streptococcus pneumoniae infection.

Authors:  Muhammad Hassan; Atif Amin Baig; Syed Awais Attique; Shafqat Abbas; Fizza Khan; Sara Zahid; Qurat Ul Ain; Muhammad Usman; Nordin Bin Simbak; Mohammad Amjad Kamal; Hanani Ahmad Yusof
Journal:  Daru       Date:  2021-02-03       Impact factor: 3.117

10.  Hybrid In Silico and TR-FRET-Guided Discovery of Novel BCL-2 Inhibitors.

Authors:  Kader Sahin; Muge Didem Orhan; Timucin Avsar; Serdar Durdagi
Journal:  ACS Pharmacol Transl Sci       Date:  2021-04-15
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