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CMPB
2010

A ligand predication tool based on modeling and reasoning with imprecise probabilistic knowledge

11 years 6 months ago
A ligand predication tool based on modeling and reasoning with imprecise probabilistic knowledge
Ligand prediction has been driven by a fundamental desire to understand more about how biomolecules recognize their ligands and by the commercial imperative to develop new drugs. Most of the current available software systems are very complex and time consuming to use. Therefore, developing simple and efficient tools to perform initial screening of interesting compounds is an appealing idea. In this paper, we introduce our tool for very rapid screening for likely ligands (either substrates or inhibitors) based on reasoning with imprecise probabilistic knowledge elicited from past experiments. Probabilistic knowledge is input to the system via a userfriendly interface showing a base compound structure. A prediction of whether a particular compound is a substrate is queried against the acquired probabilistic knowledge base and a probability is returned as an indication of the prediction. This tool will be particularly useful in situations where a number of similar compounds have been s...
Weiru Liu, Anbu Yue, David J. Timson
Added 24 Jan 2011
Updated 24 Jan 2011
Type Journal
Year 2010
Where CMPB
Authors Weiru Liu, Anbu Yue, David J. Timson
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