Literature DB >> 18061879

Multi-dimensional QSAR in drug discovery.

Markus A Lill1.   

Abstract

Quantitative structure-activity relationships (QSAR) is an area of computational research that builds virtual models to predict quantities such as the binding affinity or the toxic potential of existing or hypothetical molecules. Although a wealth of experimental data emphasizes the active role of the target protein in the binding process, QSAR studies are frequently restricted to the properties of the small-molecule ligand. This review aims at discussing recent QSAR concepts exploring higher dimensions (simulation of induced fit, simultaneous exploration of alternative binding modes, and solvation scenarios), and their benefit for the drug-discovery process.

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Year:  2007        PMID: 18061879     DOI: 10.1016/j.drudis.2007.08.004

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


  18 in total

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Review 5.  Translational Bioinformatics Approaches to Drug Development.

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7.  pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures.

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8.  A 3D-QSAR Study on the Antitrypanosomal and Cytotoxic Activities of Steroid Alkaloids by Comparative Molecular Field Analysis.

Authors:  Charles Okeke Nnadi; Julia Barbara Althaus; Ngozi Justina Nwodo; Thomas Jürgen Schmidt
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Review 9.  QSAR Modeling of Histamine H3R Antagonists/inverse Agonists as Future Drugs for Neurodegenerative Diseases.

Authors:  Michelle Fidelis Correa; Joao Paulo Dos Santos Fernandes
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10.  PL-PatchSurfer: a novel molecular local surface-based method for exploring protein-ligand interactions.

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Journal:  Int J Mol Sci       Date:  2014-08-27       Impact factor: 5.923

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