GLARE: a new approach for filtering large reagent lists in combinatorial library design using product properties.
We present a novel computer algorithm, called GLARE (Global Library Assessment of REagents), that addresses the issue of optimal reagent selection in combinatorial library design. This program reduces or eliminates the time a medicinal chemist spends examining reagents which a priori cannot be part of a "good" library. Our approach takes the large reagent sets returned by standard chemical database queries and produces often considerably reduced reagent sets that are well-behaved with respect to a specific template. The pruning enforces "goodness" constraints such as the Lipinski rule of five on the product properties such that any reagent selection from the resulting sets produces only "good" products. The algorithm we implemented has three important features: (i) As opposed to genetic algorithms or other stochastic algorithms, GLARE uses a deterministic greedy procedure that smoothly filters out nonviable reagents. (ii) The pruning method can be biased to produce reagent sets with a balanced size, conserving proportionally more reagents in smaller sets. (iii) For very large combinatorial libraries, a partitioning scheme allows libraries as large as 10(12) to be evaluated in 0.25 s on an IBM AMD Opteron processor. This algorithm is validated on a diverse set of 12 libraries. The results that we obtained show an excellent compliance to the product property requirements and very fast timings.
Truchon
Jean-François
JF
Merck Frosst Canada & Co., 16711 Trans Canada Hwy., Kirkland, Québec, Canada H9H 3L1. jeanfrancois_truchon@merck.com
Bayly
Christopher I
CI
D000465:Algorithms; D016000:Cluster Analysis; D020650:Combinatorial Chemistry Techniques; D004364:Pharmaceutical Preparations / Q000737:chemistry; D013269:Stochastic Processes
D004364:Pharmaceutical Preparations