# Combining systems biology and structural biology to find new therapeutics

> **NIH NIH R01** · STANFORD UNIVERSITY · 2021 · $96,200

## Abstract

Abstract
Abstract of funded award: Our accelerating ability to measure biological systems at the
molecular, cellular, organ and organism level promises a new generation of powerful and
improved drug therapies. However, drug failures continue to occur at high rates due to lack of
efficacy or unexpected toxicity—even when the drug binds its intended target with very high
affinity. We do not sufficiently understand the biological systems in which we are intervening,
suggesting that we are making fundamental assumptions that are wrong. Building on results
from our previous grant period, this renewal proposal proposes new assumptions: (a) when
drugs work it is because they interact not only with their target but with many other off-targets
that produce synergistic effects, (b) the actions of drugs can be best understand as the
interaction between protein networks that are dysfunctional in disease and drug response
networks that are modulated by the complete set of relevant targets, and (c) that evidence of
direct physical interaction is superior to complicated and integrative signals (such as gene
expression) in creating and analyzing drug response networks that can usefully be linked to
disease networks. Thus, we propose a plan to (1) develop and apply methods to predict drug
interactions on a proteome scale, and uses these to improve methods for creating interaction
networks relevant to drug response and disease biology, (2) devise methods to associate drug
response with disease biology, using the features of the associated protein networks, and (3)
collaborative apply these tools with collaborations from academia (U. Pennsylvania for NSAID
response & the Structural Genomics Consortium for target selection and triage), industry
(Genentech for cancer, Pfizer for autoimmune disease), and government (the U.S. FDA for
seeking biomarkers to predict efficacy and toxicity. With success, we will have created a
framework for drug discovery, repurposing, combination use and toxicity prediction that may
contribute to a higher rate of success in delivering new therapies to benefit public health.

## Key facts

- **NIH application ID:** 10385252
- **Project number:** 3R01GM102365-08S1
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** RUSS BIAGIO ALTMAN
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $96,200
- **Award type:** 3
- **Project period:** 2012-09-01 → 2022-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10385252

## Citation

> US National Institutes of Health, RePORTER application 10385252, Combining systems biology and structural biology to find new therapeutics (3R01GM102365-08S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10385252. Licensed CC0.

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