A Scalable Approach to Combinatorial Library Design

Research output: Chapter in Book/Report/Conference proceedingChapter


In this chapter, we describe an algorithm for the design of lead-generation libraries required in combinatorial drug discovery. This algorithm addresses simultaneously the two key criteria of diversity and representativeness of compounds in the resulting library and is computationally efficient when applied to a large class of lead-generation design problems. At the same time, additional constraints on experimental resources are also incorporated in the framework presented in this chapter. A computationally efficient scalable algorithm is developed, where the ability of the deterministic annealing algorithm to identify clusters is exploited to truncate computations over the entire dataset to computations over individual clusters. An analysis of this algorithm quantifies the trade-off between the error due to truncation and computational effort. Results applied on test datasets corroborate the analysis and show improvement by factors as large as ten or more depending on the datasets.

Original languageEnglish (US)
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Number of pages19
StatePublished - 2011

Publication series

NameMethods in Molecular Biology
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029


  • Library design
  • combinatorial optimization
  • deterministic annealing

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics


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