R35GM144042
Project Grant
Overview
Grant Description
Computational and Experimental Studies of Protein Structure and Design - Project Summary
The determination of three-dimensional protein structures is essential for revealing the molecular mechanism of disease processes, and also for structure-based drug design. Concomitantly, technological advances in protein design could revolutionize therapeutic treatment. With these advances, proteins and other molecules can be designed to act on today's undruggable proteins or tomorrow's drug-resistant diseases.
This proposed MIRA research project focuses on computational and experimental studies of protein structure and design (PS&D). The interlocking goals are to (a) determine protein structure and dynamics in systems of biomedical importance; and (b) design proteins, inhibitors, and their molecular interactions, especially to predict and overcome resistance. We develop novel algorithms in structural molecular biology. To surmount the challenges proposed herein, our algorithms exploit combinatorial optimization, computational geometry and topology, and integrate advanced machine learning techniques.
We believe software for PS&D must be i) open-source and ii) free software. This is the goal of OSPREY. Thus, we will (c) continue to develop free, open-source algorithms and software not only for challenging problems in the design of proteins and their interactions, but also to determine difficult protein structures and characterize their dynamics. We will use structural data and computational models to understand molecular mechanism and the basis of therapeutic interventions, and perform detailed experimental measurements in vitro and in vivo to confirm, iterate, and improve both our understanding of protein structure and molecular designs.
The resulting models of protein structures and dynamics, together with our novel design methodology, will illuminate targets of biochemical and pharmacological significance. We will also advance PS&D by making algorithmic and modeling advances. We will test our methods and predictions by creating designed protein and inhibitor constructs, solving empirical structures, and performing in vitro experiments to measure enhanced biophysical properties on purified components, and in-cell experiments to measure biological efficacy.
We will apply our PS&D algorithms to several areas of biomedical importance. We will solve structures of systems under our investigation and further develop the paradigm of protein structure as a continuous probability distribution. A set of synergistic research thrusts is proposed, in which, for example, we will (1) predict future resistance mutations in protein targets of novel drugs, (2) design protein-protein interaction (PPI) inhibitors that target "undruggable" proteins, and (3) use our PS&D methodology to characterize and design antibody:antigen constructs, with the ultimate goal of creating pan-neutralizing antibodies for viral targets.
Our sustained program in developing novel computational methods to accurately predict potential drug target mutations in response to early-stage leads should drive the design of more resilient and durable first-generation drug candidates.
The determination of three-dimensional protein structures is essential for revealing the molecular mechanism of disease processes, and also for structure-based drug design. Concomitantly, technological advances in protein design could revolutionize therapeutic treatment. With these advances, proteins and other molecules can be designed to act on today's undruggable proteins or tomorrow's drug-resistant diseases.
This proposed MIRA research project focuses on computational and experimental studies of protein structure and design (PS&D). The interlocking goals are to (a) determine protein structure and dynamics in systems of biomedical importance; and (b) design proteins, inhibitors, and their molecular interactions, especially to predict and overcome resistance. We develop novel algorithms in structural molecular biology. To surmount the challenges proposed herein, our algorithms exploit combinatorial optimization, computational geometry and topology, and integrate advanced machine learning techniques.
We believe software for PS&D must be i) open-source and ii) free software. This is the goal of OSPREY. Thus, we will (c) continue to develop free, open-source algorithms and software not only for challenging problems in the design of proteins and their interactions, but also to determine difficult protein structures and characterize their dynamics. We will use structural data and computational models to understand molecular mechanism and the basis of therapeutic interventions, and perform detailed experimental measurements in vitro and in vivo to confirm, iterate, and improve both our understanding of protein structure and molecular designs.
The resulting models of protein structures and dynamics, together with our novel design methodology, will illuminate targets of biochemical and pharmacological significance. We will also advance PS&D by making algorithmic and modeling advances. We will test our methods and predictions by creating designed protein and inhibitor constructs, solving empirical structures, and performing in vitro experiments to measure enhanced biophysical properties on purified components, and in-cell experiments to measure biological efficacy.
We will apply our PS&D algorithms to several areas of biomedical importance. We will solve structures of systems under our investigation and further develop the paradigm of protein structure as a continuous probability distribution. A set of synergistic research thrusts is proposed, in which, for example, we will (1) predict future resistance mutations in protein targets of novel drugs, (2) design protein-protein interaction (PPI) inhibitors that target "undruggable" proteins, and (3) use our PS&D methodology to characterize and design antibody:antigen constructs, with the ultimate goal of creating pan-neutralizing antibodies for viral targets.
Our sustained program in developing novel computational methods to accurately predict potential drug target mutations in response to early-stage leads should drive the design of more resilient and durable first-generation drug candidates.
Awardee
Funding Goals
THE NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES (NIGMS) SUPPORTS BASIC RESEARCH THAT INCREASES OUR UNDERSTANDING OF BIOLOGICAL PROCESSES AND LAYS THE FOUNDATION FOR ADVANCES IN DISEASE DIAGNOSIS, TREATMENT, AND PREVENTION. NIGMS ALSO SUPPORTS RESEARCH IN SPECIFIC CLINICAL AREAS THAT AFFECT MULTIPLE ORGAN SYSTEMS: ANESTHESIOLOGY AND PERI-OPERATIVE PAIN, CLINICAL PHARMACOLOGY ?COMMON TO MULTIPLE DRUGS AND TREATMENTS, AND INJURY, CRITICAL ILLNESS, SEPSIS, AND WOUND HEALING.? NIGMS-FUNDED SCIENTISTS INVESTIGATE HOW LIVING SYSTEMS WORK AT A RANGE OF LEVELSFROM MOLECULES AND CELLS TO TISSUES AND ORGANSIN RESEARCH ORGANISMS, HUMANS, AND POPULATIONS. ADDITIONALLY, TO ENSURE THE VITALITY AND CONTINUED PRODUCTIVITY OF THE RESEARCH ENTERPRISE, NIGMS PROVIDES LEADERSHIP IN SUPPORTING THE TRAINING OF THE NEXT GENERATION OF SCIENTISTS, ENHANCING THE DIVERSITY OF THE SCIENTIFIC WORKFORCE, AND DEVELOPING RESEARCH CAPACITY THROUGHOUT THE COUNTRY.
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Durham,
North Carolina
277080001
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 508% from $524,790 to $3,192,742.
Duke University was awarded
Protein Structure & Design Studies: Computational & Experimental
Project Grant R35GM144042
worth $3,192,742
from the National Institute of General Medical Sciences in February 2022 with work to be completed primarily in Durham North Carolina United States.
The grant
has a duration of 5 years and
was awarded through assistance program 93.859 Biomedical Research and Research Training.
The Project Grant was awarded through grant opportunity Maximizing Investigators' Research Award (R35 - Clinical Trial Optional).
Status
(Ongoing)
Last Modified 3/5/26
Period of Performance
2/1/22
Start Date
1/31/27
End Date
Funding Split
$3.2M
Federal Obligation
$0.0
Non-Federal Obligation
$3.2M
Total Obligated
Activity Timeline
Transaction History
Modifications to R35GM144042
Additional Detail
Award ID FAIN
R35GM144042
SAI Number
R35GM144042-3851586698
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Private Institution Of Higher Education
Awarding Office
75NS00 NIH National Institute of General Medical Sciences
Funding Office
75NS00 NIH National Institute of General Medical Sciences
Awardee UEI
TP7EK8DZV6N5
Awardee CAGE
4B478
Performance District
NC-04
Senators
Thom Tillis
Ted Budd
Ted Budd
Budget Funding
| Federal Account | Budget Subfunction | Object Class | Total | Percentage |
|---|---|---|---|---|
| National Institute of General Medical Sciences, National Institutes of Health, Health and Human Services (075-0851) | Health research and training | Grants, subsidies, and contributions (41.0) | $1,407,496 | 100% |
Modified: 3/5/26