# Addressing biomedical challenges with computational mechanics and big data

> **NIH NIH R35** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2020 · $383,163

## Abstract

PROJECT SUMMARY
The objective of this project is to develop better algorithms for molecular
mechanics and flexible docking, incorporate new data, and use the methods to
expand the set of three-dimensional atomic models of bio-macromolecules and
their ligand complexes with predicted parts and homology models. These
models will be used to identify new therapeutic candidates and predict
mechanism of action of drugs. Since 2007 we collaborated and published with
over sixty research laboratories and used structural models to understand
biological function and therapeutic action. We will work in close collaboration
with several laboratories at Skaggs School of Pharmacy and Pharmaceutical
Sciences, UCSD, UCSD Medical School, Bioinformatics and Systems Biology
Program at UCSD and several US Institutions. The SSPPS collaborators include
Tracy Handel (chemokine receptors), James McKerrow (head of CDIPD center),
Larissa Podust (crystallography, CDIPD), Conor Caffrey (schistosomiasis,
hookworms), Jair L. Siqueira-Neto (HTS core, trypanosomiasis, leishmaniasis,
antivirals), Anjan Debnath (amebiasis), Carlo Ballatore and Dionicio Siegel
(medicinal chemistry) . Nuno Bandeira and Pieter Dorrestein (NIH/NCRR Center
for Computational Mass Spectrometry), will help with incorporating or generating
mass spectrometry data. We will also work on new treatments for several
diseases, molecular mechanisms of action, and probes for new disease related
pathways with the laboratories from UCSD Health Sciences Departments (Silvio
Gutkind, Joseph Califano, Don Durden, Nunzio Bottini, Olivier Harismendy -
oncogenomics, Pavel Pevzner, Lev Tsimring) and several US laboratories (Mark
Yeager, UVa, Irina Artsimovich, OHSU, Andrei Osterman, SBP-
Med.Res.Institute, Eric Debler, Jefferson Uni.). Better methods, better models,
better data will help with new probes for disease-related pathways, drug
repurposing and designing new drug combinations, understanding drug-
resistance mutations, and understanding multi-target drug pharmacology. We
will make all the data and programs produced during the project publicly
available.

## Key facts

- **NIH application ID:** 9918928
- **Project number:** 5R35GM131881-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** RUBEN ABAGYAN
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $383,163
- **Award type:** 5
- **Project period:** 2019-05-01 → 2024-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9918928

## Citation

> US National Institutes of Health, RePORTER application 9918928, Addressing biomedical challenges with computational mechanics and big data (5R35GM131881-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9918928. Licensed CC0.

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