A Generic Program for Multistate Protein Design
By Andrew Leaver-Fay, Ron Jacak, P. Benjamin Stranges, Brian Kuhlman. 2011
95 citations recorded by the source corpus.
Some protein design tasks cannot be modeled by the traditional single state design strategy of finding a sequence that is optimal for a single fixed backbone. Such cases require multistate design, where a single sequence is threaded onto multiple backbones (states) and evaluated for its strengths and weaknesses on each backbone. For example, to design a protein that can switch between two specific conformations, it is necessary to to find a sequence that is compatible with both backbone conformations. We present in this paper a generic implementation of multistate design that is suited for a wide range of protein design tasks and demonstrate in silico its capabilities at two design tasks: one of redesigning an obligate homodimer into an obligate heterodimer such that the new monomers would not homodimerize, and one of redesigning a promiscuous interface to bind to only a single partner and to no longer bind the rest of its partners. Both tasks contained negative design in that multistate design was asked to find sequences that would produce high energies for several of the states being modeled. Success at negative design was assessed by computationally redocking the undesired protein-pair interactions; we found that multistate design's accuracy improved as the diversity of conformations for the undesired protein-pair interactions increased. The paper concludes with a discussion of the pitfalls of negative design, which has proven considerably more challenging than positive design.
Subfields: Molecular Biology
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In Molecular Biology
- Andrew Leaver-Fay
- Brian Kuhlman
- Pablo Gainza
- Hunter M. Nisonoff
- Bruce Randall Donald
- David Baker
- Tanja Kortemme
- Jeffrey J. Gray
Citations in the corpus
- Computationally Designed Bispecific Antibodies Using Negative State Repertoires (2016, methodology): “The improved agreement in these energies shows the value of NSRs and confirms our previous in silico observations in a different system (Leaver-Fay et al., 2011).”
- Algorithms for Protein Design (2016, background): “[77] developed a genetic algorithm for multistate design within a multistate program that allows the user to define custom multistate optimization objectives.”
- Reconfigurable asymmetric protein assemblies through implicit negative design (2021, unknown): “Explicit negative-design methods favor one state by considering the effect of amino acid substitutions on the free energies of both states ( 15 – 17 ).”