Literature DB >> 19150413

Molecular fields in drug discovery: getting old or reaching maturity?

Simon Cross1, Gabriele Cruciani.   

Abstract

With GRID first published 23 years ago, and CoMFA 20 years ago, the two most widely known methods that apply molecular fields to drug discovery are now into their third decade. Are molecular-field-based methods still applicable to modern drug discovery? Are they old and outdated? Or are they maturing into their full potential? Copyright 2008 Elsevier Ltd. All rights reserved.

Mesh：

Year:  2009        PMID： 19150413     DOI： 10.1016/j.drudis.2008.12.006

Source DB:  PubMed          Journal:  Drug Discov Today        ISSN： 1359-6446            Impact factor:   7.851


  12 in total

1.  Open3DQSAR: a new open-source software aimed at high-throughput chemometric analysis of molecular interaction fields.

Authors:  Paolo Tosco; Thomas Balle
Journal:  J Mol Model       Date:  2010-04-11       Impact factor: 1.810

2.  A novel approach for predicting P-glycoprotein (ABCB1) inhibition using molecular interaction fields.

Authors:  Fabio Broccatelli; Emanuele Carosati; Annalisa Neri; Maria Frosini; Laura Goracci; Tudor I Oprea; Gabriele Cruciani
Journal:  J Med Chem       Date:  2011-02-22       Impact factor: 7.446

3.  Computational ligand-based rational design: Role of conformational sampling and force fields in model development.

Authors:  Jihyun Shim; Alexander D Mackerell
Journal:  Medchemcomm       Date:  2011-05       Impact factor: 3.597

4.  Quinazoline clubbed 1,3,5-triazine derivatives as VEGFR2 kinase inhibitors: design, synthesis, docking, in vitro cytotoxicity and in ovo antiangiogenic activity.

Authors:  Prateek Pathak; Parjanya Kumar Shukla; Vikas Kumar; Ankit Kumar; Amita Verma
Journal:  Inflammopharmacology       Date:  2018-04-16       Impact factor: 4.473

5.  Application of Q2MM to predictions in stereoselective synthesis.

Authors:  Anthony R Rosales; Taylor R Quinn; Jessica Wahlers; Anna Tomberg; Xin Zhang; Paul Helquist; Olaf Wiest; Per-Ola Norrby
Journal:  Chem Commun (Camb)       Date:  2018-07-24       Impact factor: 6.222

6.  BDDCS class prediction for new molecular entities.

Authors:  Fabio Broccatelli; Gabriele Cruciani; Leslie Z Benet; Tudor I Oprea
Journal:  Mol Pharm       Date:  2012-02-07       Impact factor: 4.939

7.  Combining machine learning and quantum mechanics yields more chemically aware molecular descriptors for medicinal chemistry applications.

Authors:  Sara Tortorella; Emanuele Carosati; Giulia Sorbi; Giovanni Bocci; Simon Cross; Gabriele Cruciani; Loriano Storchi
Journal:  J Comput Chem       Date:  2021-08-19       Impact factor: 3.672

8.  The Effects of Ca2+ Concentration and E200K Mutation on the Aggregation Propensity of PrPC: A Computational Study.

Authors:  Alessandro Marrone; Nazzareno Re; Loriano Storchi
Journal:  PLoS One       Date:  2016-12-13       Impact factor: 3.240

9.  Effect of pomegranate peel extract on shelf life of strawberries: computational chemistry approaches to assess antifungal mechanisms involved.

Authors:  D Rongai; N Sabatini; P Pulcini; C Di Marco; L Storchi; A Marrone
Journal:  J Food Sci Technol       Date:  2018-04-30       Impact factor: 2.701

10.  Studies of new fused benzazepine as selective dopamine D3 receptor antagonists using 3D-QSAR, molecular docking and molecular dynamics.

Authors:  Jing Liu; Yan Li; Shuwei Zhang; Zhengtao Xiao; Chunzhi Ai
Journal:  Int J Mol Sci       Date:  2011-02-18       Impact factor: 5.923
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