A Statistical Mechanical Approach to Combinatorial Chemistry

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dc.creatorDeem, Michael W.
dc.date2000-09-16
dc.date.accessioned2026-07-25T21:40:15Z
dc.descriptionAn analogy between combinatorial chemistry and Monte Carlo computer simulation is pursued. Examples of how to design libraries for both materials discovery and protein molecular evolution are given. For materials discovery, the concept of library redesign, or the use previous experiments to guide the design of new experiments, is introduced. For molecular evolution, examples of how to use ``biased'' Monte Carlo to search the protein sequence space are given. Chemical information, whether intuition, theoretical calculations, or database statistics, can be naturally incorporated as an a priori bias in the Monte Carlo approach to library design in combinatorial chemistry. In this sense, combinatorial chemistry can be viewed as an extension of traditional chemical synthesis.
dc.description34 pages. 9 figures
dc.identifierhttps://arxiv.org/abs/cond-mat/0009243
dc.identifierhttp://arxiv.org/abs/cond-mat/0009243
dc.identifier.urihttps://dspace.dare.co.zw/handle/123456789/81732
dc.subjectStatistical Mechanics
dc.subjectMaterials Science
dc.subjectSoft Condensed Matter
dc.subjectQuantitative Biology
dc.titleA Statistical Mechanical Approach to Combinatorial Chemistry
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