title: Augmenting the anisotropic network model with torsional potentials improves PATH performance, enabling detailed comparison with experimental rate data.
abstract: PATH algorithms for identifying conformational transition states provide computational parameters-time to the transition state, conformational free energy differences, and transition state activation energies-for comparison to experimental data and can be carried out sufficiently rapidly to use in the "high throughput" mode. These advantages are especially useful for interpreting results from combinatorial mutagenesis experiments. This report updates the previously published algorithm with enhancements that improve correlations between PATH convergence parameters derived from virtual variant structures generated by RosettaBackrub and previously published kinetic data for a complete, four-way combinatorial mutagenesis of a conformational switch in Tryptophanyl-tRNA synthetase.
authors.affiliation: Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School , Worcester, Massachusetts 01655, USA.
authors.forename: Srinivas Niranj
authors.initials: SN
authors.lastname: Chandrasekaran
authors.affiliation: Department of Biochemistry and Biophysics, The University of North Carolina at Chapel Hill , Chapel Hill, North Carolina 27599-7260, USA.
authors.forename: Charles W
authors.initials: CW
authors.lastname: Carter