American Chemical Society
ct6b01238_si_001.pdf (292.63 kB)

Ward Clustering Improves Cross-Validated Markov State Models of Protein Folding

Download (292.63 kB)
journal contribution
posted on 2017-02-14, 00:00 authored by Brooke E. Husic, Vijay S. Pande
Markov state models (MSMs) are a powerful framework for analyzing protein dynamics. MSMs require the decomposition of conformation space into states via clustering, which can be cross-validated when a prediction method is available for the clustering method. We present an algorithm for predicting cluster assignments of new data points with Ward’s minimum variance method. We then show that clustering with Ward’s method produces better or equivalent cross-validated MSMs for protein folding than other clustering algorithms.