Development of Computational Tools and Experimental Verifications for Protein Design
Costas D Maranas Pennsylvania State University CBET-0639962
Through the processes of natural selection and co-option, nature has crafted an astounding array of protein designs with a remarkable repertoire of functions ranging from catalysis to signaling and regulation. A growing list of biotechnology needs for proteins with altered cofactor/substrate specificities, improved/modified functionalities or activities are creating an ever expanding compilation of protein design challenges. Recent advances in the ability to create protein libraries with customized statistics have brought to the forefront the question of what type of mutations and/or recombination events are likely to yield functionally enriched protein libraries. This project seeks to address this challenge through the development of customized computational frameworks to guide protein design. Research will be tightly integrated with a set of experimental studies that will enable one to not only fine-tune the proposed methods but also to quantitatively assess the benefit of using computations. Two separate tracks of computational methods and associated experimental studies will be pursued depending on the presence or absence of detailed structural information.
Intellectual merit:
The intellectual merit of this project lies in the development of a hierarchy of computational methods and experimental tests for a variety of protein design challenges. Successful completion of this research will lead to new tightly integrated paradigms for protein design where hypotheses generated by the modeling/optimization base are used to guide the experiment and experimental results serve to assess and correct the computational frameworks. The size and complexity of the resulting combinatorial optimization problems will necessitate the development of customized solution procedures and the use of parallel computing architectures. The two Principal Investigators (PIs) have already made significant contributions towards computational and experimental challenges and are uniquely positioned to undertake the proposed challenges.
Broader impacts:
The broader impact of this activity lies primarily in the introduction of undergraduate students to the scientific research process, mentorship and preparation of a research portfolio to aid in their future industrial or academic endeavors. Specifically, this research will be integrated into Penn State's Intercollegiate Genetically Engineered Machines program (IGEM), aimed at providing undergraduate students and high-school students hands-on exposure to synthetic biology. The research results will be broadly disseminated through journal publications and conference presentations, preparation of elective courses on protein design, and by making available, through the web, all developed software programs, databases and experimental protocols to be used by both the academic and industrial communities. The collaborating labs will enable the PIs to amplify the impact of this activity beyond the specifics of the proposed research.
