Literature DB >> 25262801

Virtual screening strategies in medicinal chemistry: the state of the art and current challenges.

Rodolpho C Braga, Vinicius M Alves, Arthur C Silva, Marilia N Nascimento, Flavia C Silva, Luciano M Liao, Carolina H Andrade1.   

Abstract

Virtual screening (VS) techniques are well-established tools in the modern drug discovery process, mainly used for hit finding in drug discovery. The availability of knowledge of structural information, which includes an increasing number of 3D protein structures and the readiness of free databases of commercially available smallmolecules, provides a broad platform for VS. This review summarizes the current developments in VS regarding chemical databases and highlights the achievements as well as the challenges with an emphasis on a recent example of the successful application for the identification of new hits for sterol 14α-demethylase (CYP51) of Trypanosoma cruzi.

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Year:  2014        PMID: 25262801     DOI: 10.2174/1568026614666140929120749

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


  19 in total

1.  Identification of steroid-like natural products as antiplasmodial agents by 2D and 3D similarity-based virtual screening.

Authors:  Elumalai Pavadai; Gurminder Kaur; Sergio Wittlin; Kelly Chibale
Journal:  Medchemcomm       Date:  2017-03-22       Impact factor: 3.597

2.  QSAR-driven design, synthesis and discovery of potent chalcone derivatives with antitubercular activity.

Authors:  Marcelo N Gomes; Rodolpho C Braga; Edyta M Grzelak; Bruno J Neves; Eugene Muratov; Rui Ma; Larry L Klein; Sanghyun Cho; Guilherme R Oliveira; Scott G Franzblau; Carolina Horta Andrade
Journal:  Eur J Med Chem       Date:  2017-05-10       Impact factor: 6.514

3.  Performance of a docking/molecular dynamics protocol for virtual screening of nutlin-class inhibitors of Mdmx.

Authors:  Nagakumar Bharatham; Kristin E Finch; Jaeki Min; Anand Mayasundari; Michael A Dyer; R Kiplin Guy; Donald Bashford
Journal:  J Mol Graph Model       Date:  2017-02-24       Impact factor: 2.518

4.  Tuning HERG out: antitarget QSAR models for drug development.

Authors:  Rodolpho C Braga; Vinicius M Alves; Meryck F B Silva; Eugene Muratov; Denis Fourches; Alexander Tropsha; Carolina H Andrade
Journal:  Curr Top Med Chem       Date:  2014       Impact factor: 3.295

5.  Convolutional neural network scoring and minimization in the D3R 2017 community challenge.

Authors:  Jocelyn Sunseri; Jonathan E King; Paul G Francoeur; David Ryan Koes
Journal:  J Comput Aided Mol Des       Date:  2018-07-10       Impact factor: 3.686

Review 6.  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

7.  Discovery of New Anti-Schistosomal Hits by Integration of QSAR-Based Virtual Screening and High Content Screening.

Authors:  Bruno J Neves; Rafael F Dantas; Mario R Senger; Cleber C Melo-Filho; Walter C G Valente; Ana C M de Almeida; João M Rezende-Neto; Elid F C Lima; Ross Paveley; Nicholas Furnham; Eugene Muratov; Lee Kamentsky; Anne E Carpenter; Rodolpho C Braga; Floriano P Silva-Junior; Carolina Horta Andrade
Journal:  J Med Chem       Date:  2016-07-22       Impact factor: 7.446

Review 8.  In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery.

Authors:  Lauro Ribeiro de Souza Neto; José Teófilo Moreira-Filho; Bruno Junior Neves; Rocío Lucía Beatriz Riveros Maidana; Ana Carolina Ramos Guimarães; Nicholas Furnham; Carolina Horta Andrade; Floriano Paes Silva
Journal:  Front Chem       Date:  2020-02-18       Impact factor: 5.221

9.  QSAR-Driven Discovery of Novel Chemical Scaffolds Active against Schistosoma mansoni.

Authors:  Cleber C Melo-Filho; Rafael F Dantas; Rodolpho C Braga; Bruno J Neves; Mario R Senger; Walter C G Valente; João M Rezende-Neto; Willian T Chaves; Eugene N Muratov; Ross A Paveley; Nicholas Furnham; Lee Kamentsky; Anne E Carpenter; Floriano P Silva-Junior; Carolina H Andrade
Journal:  J Chem Inf Model       Date:  2016-06-16       Impact factor: 4.956

10.  Deep Learning in Drug Design: Protein-Ligand Binding Affinity Prediction.

Authors:  Mohammad A Rezaei; Yanjun Li; Dapeng Wu; Xiaolin Li; Chenglong Li
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2022-02-03       Impact factor: 3.710

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