Literature DB >> 18220761

Virtual screening and its integration with modern drug design technologies.

Rafael V C Guido1, Glaucius Oliva, Adriano D Andricopulo.   

Abstract

Drug discovery is a highly complex and costly process, which demands integrated efforts in several relevant aspects involving innovation, knowledge, information, technologies, expertise, R&D investments and management skills. The shift from traditional to genomics- and proteomics-based drug research has fundamentally transformed key R&D strategies in the pharmaceutical industry addressed to the design of new chemical entities as drug candidates against a variety of biological targets. Therefore, drug discovery has moved toward more rational strategies based on our increasing understanding of the fundamental principles of protein-ligand interactions. The combination of available knowledge of several 3D protein structures with hundreds of thousands of small-molecules have attracted the attention of scientists from all over the world for the application of structure- and ligand-based drug design approaches. In this context, virtual screening technologies have largely enhanced the impact of computational methods applied to chemistry and biology and the goal of applying such methods is to reduce large compound databases and to select a limited number of promising candidates for drug design. This review provides a perspective of the utility of virtual screening in drug design and its integration with other important drug discovery technologies such as high-throughput screening (HTS) and QSAR, highlighting the present challenges, limitations, and future perspectives in medicinal chemistry.

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Year:  2008        PMID: 18220761     DOI: 10.2174/092986708783330683

Source DB:  PubMed          Journal:  Curr Med Chem        ISSN: 0929-8673            Impact factor:   4.530


  35 in total

Review 1.  Virtual screening: an endless staircase?

Authors:  Gisbert Schneider
Journal:  Nat Rev Drug Discov       Date:  2010-04       Impact factor: 84.694

2.  A combined LS-SVM & MLR QSAR workflow for predicting the inhibition of CXCR3 receptor by quinazolinone analogs.

Authors:  Antreas Afantitis; Georgia Melagraki; Haralambos Sarimveis; Panayiotis A Koutentis; Olga Igglessi-Markopoulou; George Kollias
Journal:  Mol Divers       Date:  2009-05-30       Impact factor: 2.943

Review 3.  Fragment-based QSAR: perspectives in drug design.

Authors:  Lívia B Salum; Adriano D Andricopulo
Journal:  Mol Divers       Date:  2009-01-31       Impact factor: 2.943

4.  Predictive QSAR workflow for the in silico identification and screening of novel HDAC inhibitors.

Authors:  Georgia Melagraki; Antreas Afantitis; Haralambos Sarimveis; Panayiotis A Koutentis; George Kollias; Olga Igglessi-Markopoulou
Journal:  Mol Divers       Date:  2009-02-10       Impact factor: 2.943

5.  Improving scoring-docking-screening powers of protein-ligand scoring functions using random forest.

Authors:  Cheng Wang; Yingkai Zhang
Journal:  J Comput Chem       Date:  2016-11-17       Impact factor: 3.376

6.  Beyond picomolar affinities: quantitative aspects of noncovalent and covalent binding of drugs to proteins.

Authors:  Adam J T Smith; Xiyun Zhang; Andrew G Leach; K N Houk
Journal:  J Med Chem       Date:  2009-01-22       Impact factor: 7.446

7.  Structure-based discovery of low molecular weight compounds that stimulate neurite outgrowth and substitute for nerve growth factor.

Authors:  Britney Williams; Donard S Dwyer
Journal:  J Neurochem       Date:  2009-07-17       Impact factor: 5.372

Review 8.  Advancement of structure-activity relationship of multidrug resistance-associated protein 2 interactions.

Authors:  Li Xing; Yiding Hu; Yurong Lai
Journal:  AAPS J       Date:  2009-06-03       Impact factor: 4.009

Review 9.  Hit identification and optimization in virtual screening: practical recommendations based on a critical literature analysis.

Authors:  Tian Zhu; Shuyi Cao; Pin-Chih Su; Ram Patel; Darshan Shah; Heta B Chokshi; Richard Szukala; Michael E Johnson; Kirk E Hevener
Journal:  J Med Chem       Date:  2013-06-07       Impact factor: 7.446

10.  Analysis of HSP90-related folds with MED-SuMo classification approach.

Authors:  Olivia Doppelt-Azeroual; Fabrice Moriaud; François Delfaud; Alexandre G de Brevern
Journal:  Drug Des Devel Ther       Date:  2009-09-21       Impact factor: 4.162

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