Protein Model Discrimination Using Mutational Sensitivity Derived from Deep Sequencing
| Autor: | Devrishi Goswami, Mohit K. Swarnkar, Kanika Bajaj, Purbani Chakrabarti, Arti Tripathi, Rajesh S. Gokhale, Raghavan Varadarajan, Anusmita Sahoo, Bharat V. Adkar |
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| Rok vydání: | 2012 |
| Předmět: |
Models
Molecular Protein Conformation Mutant Biology Deep sequencing Bacterial Proteins Structural Biology Catalytic Domain Protein purification Escherichia coli Cluster Analysis Computer Simulation Angstrom Amino Acid Sequence Molecular Biology Genetics Microbial toxins Escherichia coli Proteins High-Throughput Nucleotide Sequencing Protein structure prediction Rank score Phenotype Amino Acid Substitution Mutation Protein model Mutagenesis Site-Directed |
| Zdroj: | Structure. 20(2):371-381 |
| ISSN: | 0969-2126 |
| DOI: | 10.1016/j.str.2011.11.021 |
| Popis: | 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 |
| Databáze: | OpenAIRE |
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