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Ligand-based virtual screening using bayesian inference network and reweighted fragments

Alfakiabdalla, Ali Ahmed and A., Abdo and N., Salim (2012) Ligand-based virtual screening using bayesian inference network and reweighted fragments. The Scientific World Journal . pp. 1-7. ISSN 1537-744X

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Abstract

Many of the similarity-based virtual screening approaches assume that molecular fragments that are not related to the biological activity carry the same weight as the important ones. This was the reason that led to the use of Bayesian networks as an alternative to existing tools for similarity-based virtual screening. In our recent work, the retrieval performance of the Bayesian inference network (BIN) was observed to improve significantly when molecular fragments were reweighted using the relevance feedback information. In this paper, a set of active reference structures were used to reweight the fragments in the reference structure. In this approach, higher weights were assigned to those fragments that occur more frequently in the set of active reference structures while others were penalized. Simulated virtual screening experiments with MDL Drug Data Report datasets showed that the proposed approach significantly improved the retrieval effectiveness of ligand-based virtual screening, especially when the active molecules being sought had a high degree of structural heterogeneity.

Item Type:Article
Uncontrolled Keywords:Bayesian networks, biological activity, heterogeneity
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System
ID Code:47160
Deposited By: Narimah Nawil
Deposited On:22 Jun 2015 05:56
Last Modified:29 Feb 2020 13:07

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