Literature DB >> 25171960

Virtual screening strategies: recent advances in the identification and design of anti-cancer agents.

Vikash Kumar1, Shagun Krishna1, Mohammad Imran Siddiqi2.   

Abstract

Virtual screening (VS) is a well-established technique, which is now routinely employed in computer aided drug designing process. VS can be broadly classified into two categories, i.e., ligand-based and structure-based approach. In recent years, VS has emerged as a time saving and cost effective technique, capable of screening millions of compounds in a user friendly manner. In the area of cancer drug design, VS methods have been widely used and helped in identifying novel molecules as potential anti-cancer agents. Both ligand-based VS (LBVS) structure-based VS (SBVS) methods have been highly useful in the identification of a number of potential anti-cancer agents exhibiting activities in nanomolar range. In tune with the rapid progress in the enhancement of computational power, VS has witnessed significant change in terms of speed and hit rate and in future it is expected that VS will be a preferential alternative to high throughput screening (HTS). This review, discusses recent trends and contribution of VS in the area of anti-cancer drug discovery.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Anti-cancer agents; Molecular docking; Pharmacophore; Virtual screening

Mesh:

Substances:

Year:  2014        PMID: 25171960     DOI: 10.1016/j.ymeth.2014.08.010

Source DB:  PubMed          Journal:  Methods        ISSN: 1046-2023            Impact factor:   3.608


  13 in total

1.  Theoretical and experimental study of polycyclic aromatic compounds as β-tubulin inhibitors.

Authors:  Fabian E Olazarán; Carlos A García-Pérez; Debasish Bandyopadhyay; Isaias Balderas-Rentería; Angel D Reyes-Figueroa; Lars Henschke; Gildardo Rivera
Journal:  J Mol Model       Date:  2017-02-18       Impact factor: 1.810

Review 2.  Small molecules as therapeutic agents for inborn errors of metabolism.

Authors:  Leslie Matalonga; Laura Gort; Antonia Ribes
Journal:  J Inherit Metab Dis       Date:  2016-12-13       Impact factor: 4.982

Review 3.  Role of Structural Bioinformatics in Drug Discovery by Computational SNP Analysis: Analyzing Variation at the Protein Level.

Authors:  David K Brown; Özlem Tastan Bishop
Journal:  Glob Heart       Date:  2017-03-13

4.  Discovery of new small molecules inhibiting 67 kDa laminin receptor interaction with laminin and cancer cell invasion.

Authors:  Ada Pesapane; Carmen Di Giovanni; Francesca Wanda Rossi; Daniela Alfano; Luigi Formisano; Pia Ragno; Carmine Selleri; Nunzia Montuori; Antonio Lavecchia
Journal:  Oncotarget       Date:  2015-07-20

5.  The ChemicalToolbox: reproducible, user-friendly cheminformatics analysis on the Galaxy platform.

Authors:  Simon A Bray; Xavier Lucas; Anup Kumar; Björn A Grüning
Journal:  J Cheminform       Date:  2020-06-01       Impact factor: 5.514

Review 6.  Machine and deep learning approaches for cancer drug repurposing.

Authors:  Naiem T Issa; Vasileios Stathias; Stephan Schürer; Sivanesan Dakshanamurthy
Journal:  Semin Cancer Biol       Date:  2020-01-03       Impact factor: 15.707

7.  Virtual screening-driven repositioning of etoposide as CD44 antagonist in breast cancer cells.

Authors:  Charmina Aguirre-Alvarado; Aldo Segura-Cabrera; Inés Velázquez-Quesada; Miguel A Hernández-Esquivel; Carlos A García-Pérez; Sandra L Guerrero-Rodríguez; Angel J Ruiz-Moreno; Andrea Rodríguez-Moreno; Sonia M Pérez-Tapia; Marco A Velasco-Velázquez
Journal:  Oncotarget       Date:  2016-04-26

8.  Drug Repositioning for Cancer Therapy Based on Large-Scale Drug-Induced Transcriptional Signatures.

Authors:  Haeseung Lee; Seungmin Kang; Wankyu Kim
Journal:  PLoS One       Date:  2016-03-08       Impact factor: 3.240

9.  Identification of Phytochemicals Targeting c-Met Kinase Domain using Consensus Docking and Molecular Dynamics Simulation Studies.

Authors:  Shima Aliebrahimi; Shideh Montasser Kouhsari; Seyed Nasser Ostad; Seyed Shahriar Arab; Leila Karami
Journal:  Cell Biochem Biophys       Date:  2017-08-29       Impact factor: 2.194

Review 10.  How Computational Chemistry and Drug Delivery Techniques Can Support the Development of New Anticancer Drugs.

Authors:  Mariangela Garofalo; Giovanni Grazioso; Andrea Cavalli; Jacopo Sgrignani
Journal:  Molecules       Date:  2020-04-10       Impact factor: 4.411

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