Abstract
The robust computational design of functional proteins has the potential to deeply impact translational research and broaden our understanding of the determinants of protein function and stability. The low success rates of computational design protocols and the extensive in vitro optimization often required, highlight the challenge of designing proteins that perform essential biochemical functions, such as binding or catalysis. One of the most simplistic approaches for the design of function is to adopt functional motifs in naturally occurring proteins and transplant them to computationally designed proteins. The structural complexity of the functional motif largely determines how readily one can find host protein structures that are “designable”, meaning that are likely to present the functional motif in the desired conformation. One promising route to enhance the “designability” of protein structures is to allow backbone flexibility. Here, we present a computational approach that couples conformational folding with sequence design to embed functional motifs into heterologous proteins—Rosetta Functional Folding and Design (FunFolDes). We performed extensive computational benchmarks, where we observed that the enforcement of functional requirements resulted in designs distant from the global energetic minimum of the protein. An observation consistent with several experimental studies that have revealed function-stability tradeoffs. To test the design capabilities of FunFolDes we transplanted two viral epitopes into distant structural templates including one de novo “functionless” fold, which represent two typical challenges where the designability problem arises. The designed proteins were experimentally characterized showing high binding affinities to monoclonal antibodies, making them valuable candidates for vaccine design endeavors. Overall, we present an accessible strategy to repurpose old protein folds for new functions. This may lead to important improvements on the computational design of proteins, with structurally complex functional sites, that can perform elaborate biochemical functions related to binding and catalysis.
Highlights
Proteins are one of the main functional building blocks of the cell
We developed a computational protocol (Rosetta FunFolDes) to facilitate the insertion of functional motifs into heterologous proteins
We used FunFolDes to design two novel functional proteins, displaying two viral epitopes that can be of interest for vaccine development
Summary
Proteins are one of the main functional building blocks of the cell. The ability to create novel proteins outside of the natural realm has opened the path towards innovative achievements, such as new pathways [1], cellular functions [2], and therapeutic leads [3,4,5]. Computational protein design is the rational and structure-based approach to solve the inverse folding problem, i.e. the search for the best putative sequence capable of fitting and stabilizing a protein’s three-dimensional conformation [6]. A great deal of effort has been placed into understanding the rules of protein folding and stability [7, 8] and its relation to the appropriate sequence space [9]. Computational protein design approaches focus on exploring two interconnected landscapes related to sampling of the conformational and sequence spaces. Fixed backbone approaches use static protein backbone conformations, which greatly constrain the sequence space explored by the computational algorithm [9]. Following the same principles of naturally occurring homologs, which often exhibit confined structural diversity, flexible backbone approaches enhance the sequence diversity, adding the challenge of identifying energetically favorable sequence variants that are correctly coupled to structural perturbations [10]
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