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A knowledge‐based approach for screening chemical structures within de novo molecular evolution
Author(s) -
Chu Chunmei,
Alsberg Bjørn Kåre
Publication year - 2010
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.1283
Subject(s) - chemical space , set (abstract data type) , computer science , filter (signal processing) , process (computing) , sampling (signal processing) , space (punctuation) , degrees of freedom (physics and chemistry) , evolutionary algorithm , algorithm , artificial intelligence , bioinformatics , drug discovery , physics , biology , computer vision , programming language , operating system , quantum mechanics
Despite the advantage of employing evolutionary algorithms (EAs) for de novo creation of novel molecular structures with optimal properties, the approach is hampered by sampling chemically undesirable structures. Such structures are undesirable for different reasons, such as a critical structural pattern may be ignored or too many rotational degrees of freedom exist for conformational search. A new method is presented which creates a user‐defined structure filter, here referred to as the bias filter (BF)b, generated from a set of molecules representing typical structure types that are allowed to evolve in the de novo process. The BF can be seen as constraining the chemical structure space according to external requirements given by the user. No explicit programming of structure rules is necessary which makes the proposed method much more intuitive and user friendly than other methods commonly used in de novo applications. We have tested the proposed method in the process of evolving a set of Factor Xa inhibitors where the aim is to create molecules with optimal log P values. The de novo GeneGear system developed in our group is responsible for the corresponding evolutionary computation and bias filtering. Copyright © 2010 John Wiley & Sons, Ltd.