Literature DB >> 12470286

Current state and perspectives of 3D-QSAR.

Miki Akamatsu1.   

Abstract

Quantitative structure-activity relationships (QSAR) have played an important role in the design of pharmaceuticals and agrochemicals. All QSAR techniques assume that all the compounds used in analyses bind to the same site of the same biological target. However, each method differs in how it describes structural properties of compounds and how it finds the quantitative relationships between the properties and activities. The Hansch-Fujita approach, the so-called classical QSAR, is a representative of QSAR methods. Despite the usefulness, classical QSAR techniques cannot be applied to all datasets due to the lack of availability of physicochemical parameters of the whole molecule or its substituents and often it is difficult to estimate those values. In addition, molecular properties based on the three dimensional (3D) structure of compounds may be useful in describing the ligand-receptor interactions. Recently, a variety of ligand-based 3D-QSAR methods such as Comparative Molecular Field Analysis (CoMFA) have been developed and widely used in medicinal chemistry. This review describes different 3D-QSAR techniques and indicates their advantages and disadvantages. Several studies about 3D-QSAR of ADME-toxicity and perspective of 3D-QSAR are also described in this review.

Entities:  

Mesh:

Year:  2002        PMID: 12470286     DOI: 10.2174/1568026023392887

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


  14 in total

Review 1.  In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling.

Authors:  S Ekins; J Mestres; B Testa
Journal:  Br J Pharmacol       Date:  2007-06-04       Impact factor: 8.739

2.  Computational approaches to shed light on molecular mechanisms in biological processes.

Authors:  Giorgio Moro; Laura Bonati; Maurizio Bruschi; Ugo Cosentino; Luca De Gioia; Pier Carlo Fantucci; Alessandro Pandini; Elena Papaleo; Demetrio Pitea; Gloria A A Saracino; Giuseppe Zampella
Journal:  Theor Chem Acc       Date:  2007-05-01       Impact factor: 1.702

3.  www.3d-qsar.com: a web portal that brings 3-D QSAR to all electronic devices-the Py-CoMFA web application as tool to build models from pre-aligned datasets.

Authors:  Rino Ragno
Journal:  J Comput Aided Mol Des       Date:  2019-10-08       Impact factor: 3.686

Review 4.  Recent advances in ligand-based drug design: relevance and utility of the conformationally sampled pharmacophore approach.

Authors:  Chayan Acharya; Andrew Coop; James E Polli; Alexander D Mackerell
Journal:  Curr Comput Aided Drug Des       Date:  2011-03       Impact factor: 1.606

5.  Construction of 4D-QSAR models for use in the design of novel p38-MAPK inhibitors.

Authors:  Nelilma Correia Romeiro; Magaly Girão Albuquerque; Ricardo Bicca de Alencastro; Malini Ravi; Anton J Hopfinger
Journal:  J Comput Aided Mol Des       Date:  2005-06       Impact factor: 3.686

Review 6.  Considerations and recent advances in QSAR models for cytochrome P450-mediated drug metabolism prediction.

Authors:  Haiyan Li; Jin Sun; Xiaowen Fan; Xiaofan Sui; Lan Zhang; Yongjun Wang; Zhonggui He
Journal:  J Comput Aided Mol Des       Date:  2008-06-24       Impact factor: 3.686

7.  Combinatorial Pharmacophore-Based 3D-QSAR Analysis and Virtual Screening of FGFR1 Inhibitors.

Authors:  Nannan Zhou; Yuan Xu; Xian Liu; Yulan Wang; Jianlong Peng; Xiaomin Luo; Mingyue Zheng; Kaixian Chen; Hualiang Jiang
Journal:  Int J Mol Sci       Date:  2015-06-11       Impact factor: 5.923

8.  Structural investigations of T854A mutation in EGFR and identification of novel inhibitors using structure activity relationships.

Authors:  Sukriti Goyal; Salma Jamal; Asheesh Shanker; Abhinav Grover
Journal:  BMC Genomics       Date:  2015-05-26       Impact factor: 3.969

9.  Combined 3D-QSAR modeling and molecular docking study on multi-acting quinazoline derivatives as HER2 kinase inhibitors.

Authors:  Sako Mirzaie; Majid Monajjemi; Mohammad Saeed Hakhamaneshi; Fardin Fathi; Mostafa Jamalan
Journal:  EXCLI J       Date:  2013-02-22       Impact factor: 4.068

10.  An index for characterization of natural and non-natural amino acids for peptidomimetics.

Authors:  Guizhao Liang; Yonglan Liu; Bozhi Shi; Jun Zhao; Jie Zheng
Journal:  PLoS One       Date:  2013-07-23       Impact factor: 3.240

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