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J Chem Inf Model. 2016 May 23;56(5):843-53. doi: 10.1021/acs.jcim.5b00733. Epub 2016 Apr 18.

Probing the Druggability Limits for Enzymes of the NAD Biosynthetic Network in Glioma.

Author information

1
Department of Biochemistry, IISc, Bangalore 560012, India.
2
Supercomputer Education and Research Centre, IISc, Bangalore 560012, India.
3
Oxford Genomics Centre, Wellcome Trust Centre for Human Genetics, University of Oxford , Oxford OX37BN, United Kingdom.
4
Department of Microbiology, IISc, Bangalore 560012, India.

Abstract

The biosynthesis of NAD constitutes an important metabolic module in the cell, since NAD is an essential cofactor involved in several metabolic reactions. NAD concentrations are known to be significantly increased in several cancers, particularly in glioma, consistent with the observation of up-regulation of several enzymes of the network. Modulating NAD biosynthesis in glioma is therefore an attractive therapeutic strategy. Here we report reconstruction of a biochemical network of NAD biosynthesis consisting of 22 proteins, 36 metabolites, and 86 parameters, tuned to mimic the conditions in glioma. Kinetic simulations of the network provide comprehensive insights about the role of individual enzymes. Further, quantitative changes in the same network between different states of health and disease enable identification of drug targets, based on specific alterations in the given disease. Through simulations of enzyme inhibition titrations, we identify NMPRTase as a potential drug target, while eliminating other possible candidates NMNAT, NAPRTase, and NRK. We have also simulated titrations of both binding affinities as well as inhibitor concentrations, which provide insights into the druggability limits of the target, a novel aspect that can provide useful guidelines for designing inhibitors with optimal affinities. Our simulations suggest that an inhibitor affinity of 10 nM used in a concentration range of 0.1 to 10 μM achieves a near maximal inhibition response for NMPRTase and that increasing the affinity any further is not likely to have a significant advantage. Thus, the quantitative appreciation defines a maximal extent of inhibition possible for a chosen enzyme in the context of its network. Knowledge of this type enables an upper affinity threshold to be defined as a goal in lead screening and refinement stages in drug discovery.

PMID:
26958865
DOI:
10.1021/acs.jcim.5b00733
[Indexed for MEDLINE]

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