SBIR/STTR Research Award

Development and Deployment of the Movable Type Method for Drug Discovery and Desi

Award identifier 6f9543dd935517345031e1bd7facd3f837f296d3d71e9444904011407fb35dc9Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$1,131,845

Program and phase

SBIR · Phase II

Award year

2015

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
QUANTUMBIO INC
Proposal award date
2015-03-10
Contract end date
2018-02-28
UEI
SFCDUHJNHBM4
Solicitation number
PA13-234
Topic code
300

Research abstract

DESCRIPTION provided by applicant Our long term goal is to provide a solution to the protein ligand binding affinity and pose prediction problems The protein ligand docking and scoring problem is one of the central problems in computational biology because of its importance in understanding intermolecular interactions and because of its practical payoff The transformative impact molecular docking and scoring can have in the design of next generation medicines cannot be overstated If we could routinely and accurately design molecules using these approaches it would revolutionize drug discovery by winnowing out compounds with no activity while focusing more effort and scrutiny on highly active compounds In this proposal we describe a novel method we call Movable Type MT which addresses the protein ligand binding and scoring problem using fundamental statistical mechanics combined with a novel way to generate the ensemble of a ligand in a protein binding pocket Via a rapid assembly of the necessary partition functions we directly obtain binding free energies and the low free energy poses Conceptually the MT method is analogous to block and type set printing which allows us to efficiently evaluate partition functions describing regions or systems of interest In this approach we construct two databases that describe the probability of certain pairwise interactions as a function of r obtained from a knowledge base Protein Databank PDB or the Cambridge Structural Database CSD and the energetics of the pairwise interactions as a function of r obtained from empirical potentials which can be either derived from the probabilities or can utilize extant pairwise potentials like AMBER Overall the MT method is a general one and can use a broad range of two body potential functions and can be extended to higher order interactions if so desired In the present project we will extend and further validat the MT method and develop commercial quality software to deliver this methodology to users via the web and GUI This will involve collaboration between the academic laboratory and the industrial laboratory development of a new implementation of the method in order to commercially deploy the technology construction of a graphical user interface based on MOE along with a web based interface and finally use of this software in real life structure based drug discovery problems on site with our pharmaceutical collaborators see Letters of Support PUBLIC HEALTH RELEVANCE The successful completion of the SBIR grant will have a major impact on improving human health It will improve the quality of protein structures facilitate our understanding of bio molecular structure and function and will provide higher quality structural insights into protein ligand drug interactions which will enhance our ability o rationally design novel therapeutics for human diseases

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

19 SBIR/STTR records share this UEI (2005–2025). Reported award amounts total $9,699,824. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Health and Human Services, Department of Defense

Agency intelligence

Department of Health and Human Services

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