Abstract
Purpose
We propose a framework with simple proxies to dissect the relative energy contributions responsible for standard drug discovery binding activity.
Methods
We explore a rule of thumb using hydrogen-bond donors, hydrogen-bond acceptors and rotatable bonds as relative proxies for the thermodynamic terms. We apply this methodology to several datasets (e.g., multiple small molecules profiled against kinases, Mycobacterium tuberculosis (Mtb) high throughput screening (HTS) and structure based drug design (SBDD) derived compounds, and FDA approved drugs).
Results
We found that Mtb active compounds developed through SBDD methods had statistically significantly larger PEnthalpy values than HTS derived compounds, suggesting these compounds had relatively more hydrogen bond donor and hydrogen bond acceptors compared to rotatable bonds. In recent FDA approved medicines we found that compounds identified via target-based approaches had a more balanced enthalpic relationship between these descriptors compared to compounds identified via phenotypic screens
Conclusions
As it is common to experimentally optimize directly for total binding energy, these computational methods provide alternative calculations and approaches useful for compound optimization alongside other common metrics in available software and databases.
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Abbreviations
- (FCFP):
-
Molecular function class fingerprints
- ADME/Tox:
-
Absorption, distribution, metabolism, excretion and toxicity
- AUC:
-
Area under the curve
- CDD:
-
Collaborative Drug Discovery
- FDA:
-
Food and Drug Administration
- GSK:
-
GlaxoSmithKline
- HAC:
-
heavy atom count
- HBA:
-
Hydrogen bond acceptors
- HBD:
-
Hydrogen bond donors
- HBT:
-
Total number of HBA and HBD
- HTS:
-
High-throughput screening
- Mtb :
-
Mycobacterium tuberculosis
- NCATS:
-
National Center for Advancing Translational Sciences
- NIH:
-
National Institute of Health
- PAINS:
-
Pan assay INterference compoundS
- PKIS:
-
Published kinase inhibitor set
- RB:
-
Rotatable bonds
- ROC:
-
Receiver operator Characteristic
- SBDD:
-
Structure based drug design
- XV:
-
Cross validated
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ACKNOWLEDGMENTS AND DISCLOSURES
We gratefully acknowledge colleagues at CDD for the development of the CDD Vault. The CDD TB DB has been developed thanks to funding from the Bill and Melinda Gates Foundation (Grant#49852 “Collaborative drug discovery for TB through a novel database of SAR data optimized to promote data archiving and sharing”). We also thank Dr. Peter Kenny for suggesting various papers, Dr. Matthew Soellner for discussions and Dr. Daniel Erlanson and the reviewers for critical comments. BAB is an employee and SE is a consultant of CDD Inc. CAL and NKL are on the scientific advisory board of CDD Inc.
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Ekins, S., Litterman, N.K., Lipinski, C.A. et al. Thermodynamic Proxies to Compensate for Biases in Drug Discovery Methods. Pharm Res 33, 194–205 (2016). https://doi.org/10.1007/s11095-015-1779-y
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DOI: https://doi.org/10.1007/s11095-015-1779-y