Virtual target screening to rapidly identify potential protein targets of natural products in drug discovery

Yuri Pevzner; Daniel N. Santiago; Jacqueline L. von Salm; Rainer S. Metcalf; Kenyon G. Daniel; Laurent Calcul; H. Lee Woodcock; Bill J. Baker; Wayne C. Guida; Wesley H. Brooks; Yuri Pevzner; Daniel N. Santiago; Jacqueline L. von Salm; Rainer S. Metcalf; Kenyon G. Daniel; Laurent Calcul; H. Lee Woodcock; Bill J. Baker; Wayne C. Guida; Wesley H. Brooks

doi:10.3934/molsci.2014.2.81

AIMS Molecular Science

2014, Volume 1, Issue 2: 81-98. doi: 10.3934/molsci.2014.2.81

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Research article Special Issues

Virtual target screening to rapidly identify potential protein targets of natural products in drug discovery

1.
Department of Chemistry, University of South Florida, Tampa, FL 33620, USA;
2.
Center for Molecular Diversity in Drug Design, Discovery and Delivery, University of South Florida, Tampa, FL 33620, USA;
3.
Virtual Screening and Molecular Modeling Core, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA;
4.
Department of Cell Biology, Microbiology, and Molecular Biology, University of South Florida, Tampa, FL 33620, USA;
5.
The Center for Drug Discovery and Innovation (CDDI), University of South Florida, Tampa, FL 33620, USA

Received: 17 March 2014 Accepted: 14 May 2014 Published: 21 May 2014

Inherent biological viability and diversity of natural products make them a potentially rich source for new therapeutics. However, identification of bioactive compounds with desired therapeutic effects and identification of their protein targets is a laborious, expensive process. Extracts from organism samples may show desired activity in phenotypic assays but specific bioactive compounds must be isolated through further separation methods and protein targets must be identified by more specific phenotypic and in vitro experimental assays. Still, questions remain as to whether all relevant protein targets for a compound have been identified. The desire is to understand breadth of purposing for the compound to maximize its use and intellectual property, and to avoid further development of compounds with insurmountable adverse effects. Previously we developed a Virtual Target Screening system that computationally screens one or more compounds against a collection of virtual protein structures. By scoring each compound-protein interaction, we can compare against averaged scores of synthetic drug-like compounds to determine if a particular protein would be a potential target of a compound of interest. Here we provide examples of natural products screened through our system as we assess advantages and shortcomings of our current system in regards to natural product drug discovery.
- natural products,
- virtual target screening,
- drug discovery
Citation: Yuri Pevzner, Daniel N. Santiago, Jacqueline L. von Salm, Rainer S. Metcalf, Kenyon G. Daniel, Laurent Calcul, H. Lee Woodcock, Bill J. Baker, Wayne C. Guida, Wesley H. Brooks. Virtual target screening to rapidly identify potential protein targets of natural products in drug discovery[J]. AIMS Molecular Science, 2014, 1(2): 81-98. doi: 10.3934/molsci.2014.2.81

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Abstract

Inherent biological viability and diversity of natural products make them a potentially rich source for new therapeutics. However, identification of bioactive compounds with desired therapeutic effects and identification of their protein targets is a laborious, expensive process. Extracts from organism samples may show desired activity in phenotypic assays but specific bioactive compounds must be isolated through further separation methods and protein targets must be identified by more specific phenotypic and in vitro experimental assays. Still, questions remain as to whether all relevant protein targets for a compound have been identified. The desire is to understand breadth of purposing for the compound to maximize its use and intellectual property, and to avoid further development of compounds with insurmountable adverse effects. Previously we developed a Virtual Target Screening system that computationally screens one or more compounds against a collection of virtual protein structures. By scoring each compound-protein interaction, we can compare against averaged scores of synthetic drug-like compounds to determine if a particular protein would be a potential target of a compound of interest. Here we provide examples of natural products screened through our system as we assess advantages and shortcomings of our current system in regards to natural product drug discovery.

References

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