This project is focused on modeling and validating the macromolecular assembly of viral capsids. Rigorous, mechanistic explanations and predictions are lacking for many milestone processes that occur during self-assembly of symmetric macromolecular structures. This is despite the fact that numerous representative structures of self-assembled viral capsids are available. In this project, we are specifically interested in: a) nucleations, b) autostery, conformational switches and c) scaffolding removal, all of which are processes driven by configurational and combinatorial entropy, a stumbling block for commonly used computational molecular simulation paradigms including molecular dynamics and Monte Carlo methods. Multiscale Geometry and Symmetry Constraints (MGSC) is a versatile and computationally highly efficient new modeling paradigm developed by this PI team during a prior NSF project: it complements and integrates with former paradigms while addressing key shortcomings. The project will use the MGSC paradigm to translate key questions about biological processes driven by configurational and combinatorial entropy into diverse mathematical and algorithmic questions that elucidate the influence of geometry and symmetry upon these processes. These questions are independently interesting and are related to longstanding open problems in combinatorial rigidity, algebraic geometry of configuration spaces, algebraic combinatorics, and complexity. Moreover, using MGSC, we will obtain a systematic modeling procedure not only for extracting the minimal, relevant data (model input) for answering focused questions about these processes (Occam?s razor), but also for interpreting the answers (model output) biologically. Finally, the project will use existing experimental results (in vitro and in vivo, performed at a co-PI?s lab) on representative families of viruses (such as the Murine Parvovirus (MVM), Maize Streak Virus (MSV), Adeno associated viruses (AAV4) to validate its predictions, for instance, on crucial inter-molecular interactions whose removal disrupts assembly.
Viral capsid self-assembly from its constituent protein molecules is a phase of the viral lifecycle that is relatively independent of the structure and processes of the host cell. Yet, the self-assembly phase has not been targeted in the design of drugs or vaccines for treating viral infections, nor has it been leveraged in the design and use of viral vectors in gene therapy. This is because the rapidity, efficacy, robustness, spontaneity and mathematically complex orchestration of viral capsid self-assembly, occurring at the nano-scale, is extremely difficult to understand. This project aims at bringing new insights into the viral capsid self-assembly process by combining the expertise of two mathematicians, a computer scientist and an experimental structural biologist. The project will build upon these results to continue the development of an open source software suite EASAL (Efficient Atlasing and Search of Assembly Landscapes). This has the potential to be used by a wide variety of disciplines that are interested in isolating the crucial inter-atomic interactions that drive macromolecular self-assembly. Hence the project will provide outstanding interdisciplinary research experience not only to the graduate students and postdocs involved, but to the PIs as well. The project will provide research experience for STEM teachers at local schools and will additionally involve Tertl Studos - a game-based learning software company that is interested in working in the public domain - to creatively incorporate geometric constraint solving algorithms into a wide variety of math and science benchmarks in grades 4-12.
This proposal was submitted to the DMS programs in Mathematical Biology and Computational Mathematics, to CCF/CISE and to MCB/BIO in response to the Dear Colleague Letter: Unsolicited Proposals at the Interface of the Biological, Mathematical and Physical Sciences. It is co-funded by sevral NSF programs: Mathematical Biology/DMS/MPS, Molecular and Cellular Biology/BIO, Algorithmic Foundations CCF/CISE as well as by the DMS Cyberinfrastructure for the 21st Century (CIF21) fund.
