SBIR/STTR Research Award

Rapid automated polarizable multipole-based force field parameterization for accurate drug-receptor binding affinity calculations.

Award identifier 81a6cee6cb89f1160531a5abd014ba6879ecdb5193c16cfb122e633394960da6Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$175,994

Program and phase

SBIR · Phase I

Award year

2018

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
DRUG DESIGN METHODOLOGIES, L.L.C.
Proposal award date
2018-02-15
Contract end date
2019-08-14
UEI
Not reported
Solicitation number
PA16-302
Topic code
500

Research abstract

PROJECT SUMMARY ABSTRACTDrug Design MethodologiesChris HoM DPh DThis SBIR will develop automated software to accurately estimate drug target binding affinity and selectivityThis capability is crucial to drug discoveryyet remains elusive in all current design toolsOur technology identifies favorable candidates and distinguishes problematic ones that could exhibit side effects due to weak or non selectiveoff target bindingThese compounds cause late phase attrition and the extraordinary costsandgt $ Band timeandgtyrsneeded to develop successful drugsLifesaving medications are often shelved due to costs and fear of litigationBy de risking pipelineswe lower costsand help companies bring more lifesaving treatments to marketCurrent tools utilize force fieldswhich are parameterized sets of equations that simulate chemical behaviorto calculate the free energy of receptor bindingHoweverthey all model electrostatic interactions poorlyusing simple point charges and Coulomb s lawwhich is inadequateInsteadwe utilize the AMOEBAAtomic Multipole Optimized Energetics for Biomolecular Applicationsforce field developed at Washington UniversityAMOEBA employs significantly more rigorous models for electrostaticsutilizing polarizable atomic multipoles to represent electrostatic potentials around the moleculeOur preliminary data and published studies have shown that the AMOEBA force field is much more accurate in predicting drug receptor binding free energies than current force fieldsUnfortunatelythe published academic protocol for deriving AMOEBA parameters for a desired drug is far too difficulttime consumingand technical to be commercially viableAs suchour hypothesis is that this procedure can be automated in a software product and executed by non experts in one person houraside from quantum mechanical calculation timerather than theperson hours currently required by a computational chemistThis is our first specific aimOur second aim is to develop automated software to then utilize these parameters to calculate binding free energies against the drug s receptor targetThe lower the receptor binding free energythe higher the binding affinity and potency of the compoundIn Phase II we will extend the software s functionality to optimize drugs by suggesting chemical modifications that will improve binding affinity to their targetsA market size and forecast report by Grand View Research states that theUS molecular modeling and virtual screening software market is about $M and growingin spite of current shortcomingsOur primary clients will be drug discovery groups at both pharmaceutical and biotech companiesas our technology is applicable to both small molecules and biologicsOur business model includes commercialization via software licensingconsultingcontract researchand IP evaluationBy developing this toolwe will accelerate drug development pipelines and diminish costsproviding significant benefit to both researchers as well as patients and clinical outcomes PROJECT NARRATIVEDrug Design MethodologiesChris HoM DPh DIn this Phase I SBIRDrug Design Methodologies will develop software to enable biotech and pharmaceutical researchers to accurately estimate drug target binding affinity and selectivityBy saving costsfocusing resourcesand de risking pipelinesour technology will accelerate both biologics and small molecule drug developmentThis will enable companies to bring more lifesaving treatments to marketincluding therapeutics against diseases whose druggability has been problematic

Technology keywords

Not reported

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Agency intelligence

Department of Health and Human Services

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