Algorithms for computational design of protein biosensors
Creators: name: University Of California Office Of The President
Publisher: name: University of California Office of the President
publisherIdentifier: https://ror.org/00dmfq477
publisherIdentifierScheme: ROR
Year: 2024

description: Research Question. Predictive design of biological molecular “parts” with highly specific functions is a grand challenge in biological engineering. Computational methods based on modeling the atomic-level three-dimensional structures of proteins and their interactions have recently made significant strides towards this goal. The Rosetta program for protein-modeling (co-developed by “RosettaCommons” labs including the groups of the two investigators on this proposal) has been successfully applied to protein structure prediction, refinement, reengineering protein interactions and to create biocatalysts with new functions. We propose to integrate new algorithms borrowed from robotics into the state-of-the-art Rosetta protein design methodology to engineer entirely new and selective interactions between proteins. Successful construction of such novel interactions would be a first in the field. Development and proof-of-concept application of new algorithms for protein loop modeling enabling these designs would be a stepping-stone towards the engineering of protein biosensors with artificial recognition sites for many diverse targets. Specific Aims: 1.Improve and assess the accuracy of protein loop modeling in Rosetta, employing algorithms from robotics, constrained optimization, and sampling techniques. Applications will be (a) reconstruction of protein loop conformations; (b) constraint solving such as fitting of electron density and (c) iterative protocols of loop modeling and protein interaction design. 2.Use new loop modeling and design algorithms to construct and experimentally characterize novel protein interactions. Applications will be design of novel antibodies &amp; fluorescent affinity reagents (supporting letter from A. Bradbury, LANL) and engineered GTPases as synthetic biological control parts and biosensors. 3.Integrate advances into major software packages for widespread distribution and use. (supporting letter from T. Terwilliger, LANL) Approach. Computational protein design methods seek to identify low energy amino acid sequences that adopt a desired protein conformation or functional interaction. This proposal aims to address the challenge of accurate sampling of protein conformations, which is crucial to engineer defined surface structures of protein affinity reagents and biosensors that need to precisely match their targets. The project combines demonstrated expertise in structure modeling, computational optimization and algorithm development (Strauss) with advances in protein interaction design (Kortemme). Using concepts from robotics, we have developed new algorithms to model the polypeptide backbone structures of protein loops with very high accuracy. We aim to extend, improve, assess and apply this methodology to design protein loops that will create new tightly binding interfaces with other molecules. Impact. The outcomes of this research are two-fold: First, new algorithms for engineering novel protein-based interactions and constraint-based protein structure solution, and second, the physical construction and proof-of-principle characterization of such designer proteins. Broader applications are highly selective protein biosensors, small-molecule aptamers and ultimately new molecules able to mediate interactions between existing cellular pathways and human designed molecular machines. Our specific initial application to design biosensors for GTPase activation in living cells would facilitate real-time investigation of many crucial biological processes. New and improved algorithms for loop modeling have further major uses for constraint-based modeling in protein structure determination, which will be disseminated via major software packages, i.e. SOLVE/RESOLVE (supporting letter from T. Terwilliger, LANL) and the RosettaCommons commercial and academic releases. UCSF/LANL collaboration. A pre-existing conduit between our labs facilitates an uncommonly advanced level of shared effort. The Co-PIs have collectively contributed to Rosetta for over 18 combined years and are founding members of the RosettaCommons, a multi-institutional collaborative research and software environment. We share a common software repository, have an annual Rosetta developer’s conference, and jointly transfer technology to industry through a centrally-administrated licensing structure. This proposal aims to tighten this further by targeting shared LANL/UC application domain interests in algorithms for biosensor development.