Abstract
Computational protein design (CPD) is a powerful technique to engineer existing proteins or to design novel ones that display desired properties. Rosetta is a software suite including algorithms for computational modeling and analysis of protein structures and offers many elaborate protocols created to solve highly specific tasks of protein engineering. Most of Rosetta’s protocols optimize sequences based on a single conformation (i. e. design state). However, challenging CPD objectives like multi-specificity design or the concurrent consideration of positive and negative design goals demand the simultaneous assessment of multiple states. This is why we have developed the multi-state framework MSF that facilitates the implementation of Rosetta’s single-state protocols in a multi-state environment and made available two frequently used protocols. Utilizing MSF, we demonstrated for one of these protocols that multi-state design yields a 15% higher performance than single-state design on a ligand-binding benchmark consisting of structural conformations. With this protocol, we designed de novo nine retro-aldolases on a conformational ensemble deduced from a (βα)8-barrel protein. All variants displayed measurable catalytic activity, testifying to a high success rate for this concept of multi-state enzyme design.
Highlights
Since the 1990s, computational protein design (CPD) has been a powerful tool of protein engineering
Utilizing MSF, we demonstrated for one of these protocols that multi-state design yields a 15% higher performance than single-state design on a ligand-binding benchmark consisting of structural conformations
One generally applicable strategy for protein engineering is rational protein design: based on detailed knowledge of structure and function, computer programs like Rosetta propose the sequence of a protein possessing the desired properties
Summary
Since the 1990s, computational protein design (CPD) has been a powerful tool of protein engineering. Certain design objectives such as negative design [16,17,18], multi-specificity design [19], the design of specific protein interfaces [20, 21] or the mimicking of backbone flexibility [22] require the concurrent assessment of several conformational or chemical states. This is why multi-state design (MSD) methodology is an emerging field in CPD [23] that extends the application spectrum and promises high success rates. Even the design of stable proteins profits from using backbone ensembles [24]
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