Computational approaches to discover ligands with new chemotypes and functional properties

Active Project Grant Awarded Last action

Award ID
R35GM153437
Recipient
Awarding agency
Obligated
$968,334

Award facts

Assistance listing
93.859 Biomedical Research and Research Training
Completion date 42% complete
Place of performance
Los Angeles, CA 90089, USA

Award details come from USAspending.gov.

Description

Abstract
Discovery of selective and potent ligands for novel targets, as well as ligands with new functionalities remains a slow and expensive process, hampering pharmacological validation of targets and discovery of new treatments for many conditions like pain, substance abuse, alzheimer's disease and cancer. Our research aims at developing a scalable computational platform for ligand discovery, synergistically combining the advantages of structure-based and data-driven approaches. We will pursue three synergistic technological directions, combined with their experimental validation and application to clinically relevant targets. The first one builds upon our recently introduced highly scalable synthon-based approach, v-synthes, which performs hierarchical structure-based virtual screening of giga- and tera-scale on-demand chemical spaces. We will further improve the performance of the method by employing complementary machine learning approaches to ligand selection, and optimize v-synthes parameters to expand IT to tera-scale real libraries. The second research direction combines v-synthes screening with synergistic experimental HIT identification approaches like fragment- based, covalent screening and DNA-encoded library. Such hybrid methods build on complementary strengths of these tools, enabling ligand discovery for the most challenging targets like cryptic and allosteric pockets. Finally, building upon our extensive experience with the rational design of functionalized ligands, we will explore structure-based approaches to designing photoswitchable, irreversible, bitopic and bivalent ligands, based on both derivatives of known ligands and newly discovered chemotypes. Our broad network of experimental collaborators will allow rapid synthesis of predicted compounds, and their comprehensive experimental validating in biochemical, cellular and in vivo assays. Successful completion of this project will establish robust computational and hybrid platforms for structure-based ligand discovery in most classes of therapeutic targets, scaleable for rapidly growing real chemical spaces. The platform will be also thoroughly validated on a diverse set of clinical targets, yielding new chemical probes and potential leads for drug discovery.

Transactions

Action Obligated Date
Amendment $415,000
Amendment $415,000
Amendment $0
Amendment $0
Amendment $0
Amendment $69,167
Original award $69,167

Quick answers

Who received award R35GM153437?

R35GM153437 was awarded to University Of Southern California by National Institute of General Medical Sciences (National Institutes of Health) on September 22, 2024.

How much is award R35GM153437 worth?

$968,334 has been obligated on R35GM153437.

On GovTribe

See this award's full record

  • Every transaction and subaward
  • The recipient's other awards and teaming partners
  • Similar grant awards
  • Ask GovTribe AI about this award