Abstract
Computer-aided drug design (CADD) methodologies have proven to be very effective, greatly enhancing the efficiency of small molecule drug discovery and development processes. These methods include quantitative structureactivity relationship and pharmacophore models, quantitative structure-property relationship models, as well as in silico docking studies. While docking studies very often correctly identify the binding mode of a ligand, they have reduced success in predicting binding affinities. Development of improved and more efficient strategies for scoring binding affinity is a very active area of research. Here we review the utility of computational intelligence approaches such as artificial neural networks, fuzzy logic, and evolutionary computation to the calculation of improved docking scores.
Keywords: Computational intelligence, evolutionary algorithms, artificial neural networks, fuzzy logic, docking scores, in silico docking, high-throughput screening, virtual screening
Current Computer-Aided Drug Design
Title: Computational Intelligence Methods for Docking Scores
Volume: 5 Issue: 1
Author(s): David Hecht and Gary B. Fogel
Affiliation:
Keywords: Computational intelligence, evolutionary algorithms, artificial neural networks, fuzzy logic, docking scores, in silico docking, high-throughput screening, virtual screening
Abstract: Computer-aided drug design (CADD) methodologies have proven to be very effective, greatly enhancing the efficiency of small molecule drug discovery and development processes. These methods include quantitative structureactivity relationship and pharmacophore models, quantitative structure-property relationship models, as well as in silico docking studies. While docking studies very often correctly identify the binding mode of a ligand, they have reduced success in predicting binding affinities. Development of improved and more efficient strategies for scoring binding affinity is a very active area of research. Here we review the utility of computational intelligence approaches such as artificial neural networks, fuzzy logic, and evolutionary computation to the calculation of improved docking scores.
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Cite this article as:
Hecht David and Fogel B. Gary, Computational Intelligence Methods for Docking Scores, Current Computer-Aided Drug Design 2009; 5 (1) . https://dx.doi.org/10.2174/157340909787580863
DOI https://dx.doi.org/10.2174/157340909787580863 |
Print ISSN 1573-4099 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-6697 |
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