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Strategy to discover diverse optimal molecules in the small molecule universe.

ABSTRACT: The small molecule universe (SMU) is defined as a set of over 10(60) synthetically feasible organic molecules with molecular weight less than ∼500 Da. Exhaustive enumerations and evaluation of all SMU molecules for the purpose of discovering favorable structures is impossible. We take a stochastic approach and extend the ACSESS framework ( Virshup et al. J. Am. Chem. Soc. 2013 , 135 , 7296 - 7303 ) to develop diversity oriented molecular libraries that can generate a set of compounds that is representative of the small molecule universe and that also biases the library toward favorable physical property values. We show that the approach is efficient compared to exhaustive enumeration and to existing evolutionary algorithms for generating such libraries by testing in the NKp fitness landscape model and in the fully enumerated GDB-9 chemical universe containing 3 × 10(5) molecules.

SUBMITTER: Rupakheti C

PROVIDER: S-EPMC4372820 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

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Strategy to discover diverse optimal molecules in the small molecule universe.

Rupakheti Chetan C Virshup Aaron A Yang Weitao W Beratan David N DN

Journal of chemical information and modeling 20150219 3

The small molecule universe (SMU) is defined as a set of over 10(60) synthetically feasible organic molecules with molecular weight less than ∼500 Da. Exhaustive enumerations and evaluation of all SMU molecules for the purpose of discovering favorable structures is impossible. We take a stochastic approach and extend the ACSESS framework ( Virshup et al. J. Am. Chem. Soc. 2013 , 135 , 7296 - 7303 ) to develop diversity oriented molecular libraries that can generate a set of compounds that is rep ...[more]

PMID: 25594586

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Project description:The imputation from lower density SNP chip genotypes to whole-genome sequence level is an established approach to generate high density genotypes for many individuals. Imputation accuracy is dependent on many factors and for small cattle populations such as the endangered German Black Pied cattle (DSN), determining the optimal imputation strategy is especially challenging since only a low number of high density genotypes is available. In this paper, the accuracy of imputation was explored with regard to (1) phasing of the target population and the reference panel for imputation, (2) comparison of a 1-step imputation approach, where 50 k genotypes are directly imputed to sequence level, to a 2-step imputation approach that used an intermediate step imputing first to 700 k and subsequently to sequence level, (3) the software tools Beagle and Minimac, and (4) the size and composition of the reference panel for imputation. Analyses were performed for 30 DSN and 30 Holstein Frisian cattle available from the 1000 Bull Genomes Project. Imputation accuracy was assessed using a leave-one-out cross validation procedure. We observed that phasing of the target populations and the reference panels affects the imputation accuracy significantly. Minimac reached higher accuracy when imputing using small reference panels, while Beagle performed better with larger reference panels. In contrast to previous research, we found that when a low number of animals is available at the intermediate imputation step, the 1-step imputation approach yielded higher imputation accuracy compared to a 2-step imputation. Overall, the size of the reference panel for imputation is the most important factor leading to higher imputation accuracy, although using a larger reference panel consisting of a related but different breed (Holstein Frisian) significantly reduced imputation accuracy. Our findings provide specific recommendations for populations with a limited number of high density genotyped or sequenced animals available such as DSN. The overall recommendation when imputing a small population are to (1) use a large reference panel of the same breed, (2) use a large reference panel consisting of diverse breeds, or (3) when a large reference panel is not available, we recommend using a smaller same breed reference panel without including a different related breed.

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Strategy to discover diverse optimal molecules in the small molecule universe.

Publications

Strategy to discover diverse optimal molecules in the small molecule universe.

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