This project accelerates the development of new drugs. Currently, the process of developing a new drug takes an average of 12 years and tens or hundreds of millions of dollars. Consequently, only a handful of new drugs enter the market every year. It is essential to bring the level of automation inherent in computing disciplines to the life sciences. The search space for possibly beneficial and life-saving biomolecules is enormous. The proposed approach will ensure that only biomolecules likely to satisfy the desired properties are enumerated and empirically evaluated. Accelerated growth in the pharmaceutical industry strengthens the US economy by creating desirable biotechnology jobs, and increases our overall global competitiveness in biotechnology.

This project applies program synthesis principles to automate the discovery of new drugs. The chemist is allowed to specify the characteristics of the desired drug using a domain-specific specification language. For example, a chemist developing a novel peptide drug (a sequence of amino-acids) may request that amino acids at specific positions have certain chemical properties, or that certain constant sequences of amino acids with known behaviors appear in specific locations in the peptide. The chemist can also specify the target proteins in the mix to which the peptide drug should or should not bind. The binding strength of a drug translates to its efficacy. Given a drug specification, the synthesis process automatically identifies a ligand that complies with the specification, can be safely synthesized and strongly binds to the desired proteins.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Project Start
Project End
Budget Start
2019-10-01
Budget End
2022-09-30
Support Year
Fiscal Year
2019
Total Cost
$500,000
Indirect Cost
Name
University of California Riverside
Department
Type
DUNS #
City
Riverside
State
CA
Country
United States
Zip Code
92521