This proposal focuses on incorporating protein flexibility into drug discovery by using ensembles of protein conformations (multiple protein structures, MPS) to represent inherent flexibility. This approach has been shown to overcome some limitations of traditional docking to rigid structures, resulting in higher hit rates and greater chemical diversity of identified inhibitors. More importantly, the current aims evolve the idea that a protein's conformational behavior can be used to identify new modes of inhibition. The long-term goal of this work is to improve the field of structure-based drug discovery (SBDD) by developing methods that more accurately model target proteins and incorporate the vast information available from structural proteomics. This study is well integrated, providing both methodological development and practical application to systems of critical biomedical importance to prove overall utility of the techniques.
The first aim (SA1) examines various improvements to the MPS methodology. Alternative sources of MPS will be used. Mixed solvent simulations are proposed to enhance mapping the protein surface. Benchmark data from multiple solvent crystal structures will identify which algorithmic strategies perform best across many proteins. Applicability to allosteric sites will be examined. SA2 and SA3 conduct computational studies of protein dynamics to drive the discovery of new inhibitors for HIV-1 protease (HIVp) and b-secretase (BACE1), respectively. Both proteins are aspartyl proteases, and their large degree of flexibility greatly affects ligand binding and inhibition. The MPS approach has proven advantageous for systems with large, exposed binding sites that are problematic for traditional docking. Targeting new modes of inhibition for HIVp has the promise of reducing drug resistance in AIDS treatment. Our pursuit of alternative modes of inhibiting BACE1 will focus on identifying smaller lead compounds that are more likely to cross the blood-brain barrier;this pharmacokinetic property is absolutely essential to treat Alzheimer's disease but is lacking in most inhibitors in the literature. Experimental verification of the MPS methodology is a key component of the later aims, including assaying potential inhibitors and performing key structural studies by deuterium exchange, crystallography, and NMR.

Public Health Relevance

Improved techniques for computer-aided drug discovery will be developed. Computers will be used to understand protein flexibility and find new ways to inhibit HIV-1 protease and b-secretase. Inhibitors with new mechanisms are needed to overcome drug resistance in AIDS and pharmacokinetic barriers in treating Alzheimer's disease, respectively.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Macromolecular Structure and Function D Study Section (MSFD)
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Preusch, Peter C
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University of Michigan Ann Arbor
Schools of Pharmacy
Ann Arbor
United States
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Graham, Sarah E; Smith, Richard D; Carlson, Heather A (2018) Predicting Displaceable Water Sites Using Mixed-Solvent Molecular Dynamics. J Chem Inf Model 58:305-314
Graham, Sarah E; Leja, Noah; Carlson, Heather A (2018) MixMD Probeview: Robust Binding Site Prediction from Cosolvent Simulations. J Chem Inf Model 58:1426-1433
Ghanakota, Phani; Carlson, Heather A (2017) Comparing pharmacophore models derived from crystallography and NMR ensembles. J Comput Aided Mol Des 31:979-993
Graham, Sarah E; Tweedy, Sara E; Carlson, Heather A (2016) Dynamic behavior of the post-SET loop region of NSD1: Implications for histone binding and drug development. Protein Sci 25:1021-9
Ghanakota, Phani; Carlson, Heather A (2016) Moving Beyond Active-Site Detection: MixMD Applied to Allosteric Systems. J Phys Chem B 120:8685-95
Ghanakota, Phani; Carlson, Heather A (2016) Driving Structure-Based Drug Discovery through Cosolvent Molecular Dynamics. J Med Chem 59:10383-10399
Ung, Peter M U; Ghanakota, Phani; Graham, Sarah E et al. (2016) Identifying binding hot spots on protein surfaces by mixed-solvent molecular dynamics: HIV-1 protease as a test case. Biopolymers 105:21-34
Xu, Hao; Majmudar, Jaimeen D; Davda, Dahvid et al. (2015) Substrate-Competitive Activity-Based Profiling of Ester Prodrug Activating Enzymes. Mol Pharm 12:3399-407
Lexa, Katrina W; Goh, Garrett B; Carlson, Heather A (2014) Parameter choice matters: validating probe parameters for use in mixed-solvent simulations. J Chem Inf Model 54:2190-9
Ung, Peter M-U; Dunbar Jr, James B; Gestwicki, Jason E et al. (2014) An allosteric modulator of HIV-1 protease shows equipotent inhibition of wild-type and drug-resistant proteases. J Med Chem 57:6468-78

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