@inproceedings{
 title = {Simulated tempering distributed replica sampling: A practical guide to enhanced conformational sampling},
 type = {inproceedings},
 year = {2010},
 volume = {256},
 issue = {1},
 id = {b67c7aa3-302e-3146-8bba-89e8c2353840},
 created = {2018-06-08T17:39:27.542Z},
 file_attached = {false},
 profile_id = {0633c91d-b6d5-3fcd-9fa3-6021f99f2c58},
 last_modified = {2018-06-08T17:39:27.542Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {Simulated tempering distributed replica sampling (STDR) is a generalized-ensemble method designed specifically for simulations of large molecular systems on shared and heterogeneous computing platforms [Rauscher, Neale and Pomès (2009) J. Chem. Theor. Comput. 5, 2640]. The STDR algorithm consists of an alternation of two steps: (1) a short molecular dynamics (MD) simulation; and (2) a stochastic temperature jump. Repeating these steps thousands of times results in a random walk in temperature, which allows the system to overcome energetic barriers, thereby enhancing conformational sampling. The aim of the present paper is to provide a practical guide to applying STDR to complex biomolecular systems. We discuss the details of our STDR implementation, which is a highly-parallel algorithm designed to maximize computational efficiency while simultaneously minimizing network communication and data storage requirements. Using a 35-residue disordered peptide in explicit water as a test system, we characterize the efficiency of the STDR algorithm with respect to both diffusion in temperature space and statistical convergence of structural properties. Importantly, we show that STDR provides a dramatic enhancement of conformational sampling compared to a canonical MD simulation. © 2010 IOP Publishing Ltd.},
 bibtype = {inproceedings},
 author = {Rauscher, S. and Pomès, R.},
 doi = {10.1088/1742-6596/256/1/012011},
 booktitle = {Journal of Physics: Conference Series}
}

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