Protein Model Discrimination Using Mutational Sensitivity Derived from Deep Sequencing
Data(s) |
02/02/2012
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Resumo |
A major bottleneck in protein structure prediction is the selection of correct models from a pool of decoys. Relative activities of similar to 1,200 individual single-site mutants in a saturation library of the bacterial toxin CcdB were estimated by determining their relative populations using deep sequencing. This phenotypic information was used to define an empirical score for each residue (Rank Score), which correlated with the residue depth, and identify active-site residues. Using these correlations, similar to 98% of correct models of CcdB (RMSD <= 4 angstrom) were identified from a large set of decoys. The model-discrimination methodology was further validated on eleven different monomeric proteins using simulated RankScore values. The methodology is also a rapid, accurate way to obtain relative activities of each mutant in a large pool and derive sequence-structure-function relationships without protein isolation or characterization. It can be applied to any system in which mutational effects can be monitored by a phenotypic readout. |
Formato |
application/pdf |
Identificador |
http://eprints.iisc.ernet.in/43831/1/Protein_Model.pdf Adkar, Bharat V and Tripathi, Arti and Sahoo, Anusmita and Bajaj, Kanika and Goswami, Devrishi and Chakrabarti, Purbani and Swarnkar, Mohit K and Gokhale, Rajesh S and Varadarajan, Raghavan (2012) Protein Model Discrimination Using Mutational Sensitivity Derived from Deep Sequencing. In: Structure, 20 (2). pp. 371-381. |
Publicador |
Elsevier Science |
Relação |
http://dx.doi.org/10.1016/j.str.2011.11.021 http://eprints.iisc.ernet.in/43831/ |
Palavras-Chave | #Molecular Biophysics Unit |
Tipo |
Journal Article PeerReviewed |