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Principal Investigator: Bruce R. Donald
Organization: DUKE UNIVERSITY
Fiscal Year: 2024
Award: $39,452
Funding agency: National Institute of General Medical Sciences
Project Summary. The determination of three-dimensional protein structures is essential for revealing 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.
Terms: <3-D><3-Dimensional><3D><Algorithm Design><Algorithmic Design><Algorithmic Engineering><Algorithms><Antibodies><Antigens><Area><Binding><Biochemical><Biological><Combinatorial Optimization><Computational Geometry><Computer Models><Computer software><Computerized Models><Computing Methodologies><DNA Molecular Biology><Disease><Disease Resistance><Disorder><Drug Design><Drug Targeting><Drug resistance><Future><Generations><Genetic Alteration><Genetic Change><Genetic defect><Goals><Human><In Vitro><Investigation><Machine Learning><Measurement><Measures><Methodology><Methods><Modeling><Modern Man><Molecular><Molecular Biology><Molecular Interaction><Morbidity><Morbidity - disease rate><Mutation><Probability><Process><Program Sustainabilities><Program Sustainability><Protein Dynamics><Protein Engineering><Proteins><R-Series Research Projects><R01 Mechanism><R01 Program><Research><Research Grants><Research Project Grants><Research Projects><Resistance><Software><Structure><System><Techniques><Technology><Testing><Therapeutic><Therapeutic Intervention><Viral Antibodies><algorithm engineering><algorithmic composition><anti-viral antibody><biologic><biophysical characteristics><biophysical characterization><biophysical measurement><biophysical parameters><biophysical properties><computational methodology><computational methods><computational modeling><computational models><computational studies><computer based method><computer based models><computer methods><computer studies><computerized modeling><computing method><data modeling><design><designing><drug candidate><drug resistant><experiment><experimental research><experimental study><experiments><genetic protein engineering><genome mutation><immunogen><improved><in vivo><inhibitor><intervention therapy><machine based learning><model of data><model the data><modeling of the data><mortality><neutralizing antibody><new drug target><new drug treatments><new druggable target><new drugs><new pharmacological therapeutic><new pharmacotherapy target><new therapeutic target><new therapeutics><new therapy><new therapy target><next generation therapeutics><novel><novel drug target><novel drug treatments><novel druggable target><novel drugs><novel pharmaco-therapeutic><novel pharmacological therapeutic><novel pharmacotherapy target><novel therapeutic target><novel therapeutics><novel therapy><novel therapy target><open source><pharmacologic><program sustainment><protein design><protein protein interaction><protein structure><protein structures><proteins structure><resilience><resilient><resistance mutation><resistance to Drug><resistance to disease><resistant><resistant disease><resistant mutation><resistant to Drug><resistant to disease><response><three dimensional>