Volume 82, Issue 10 pp. 2671-2680
Article

Extracting representative structures from protein conformational ensembles

Alberto Perez

Alberto Perez

Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York

Search for more papers by this author
Arijit Roy

Arijit Roy

Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York

Search for more papers by this author
Koushik Kasavajhala

Koushik Kasavajhala

Department of Chemistry, Stony Brook University, Stony Brook, New York

Search for more papers by this author
Amy Wagaman

Amy Wagaman

Department of Mathematics and Statistics, Amherst College, Massachusetts

Search for more papers by this author
Ken A. Dill

Ken A. Dill

Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York

Department of Chemistry, Stony Brook University, Stony Brook, New York

Department of Physics, Stony Brook University, Stony Brook, New York

Search for more papers by this author
Justin L. MacCallum

Corresponding Author

Justin L. MacCallum

Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York

Department of Chemistry, University of Calgary, Alberta, Canada

Correspondence to: Justin L. MacCallum, Department of Chemistry, University of Calgary, Alberta, Canada. E-mail: [email protected]Search for more papers by this author
First published: 26 June 2014
Citations: 5

ABSTRACT

A large number of methods generate conformational ensembles of biomolecules. Often one structure is selected to be representative of the whole ensemble, usually by clustering and selecting the structure closest to the center of the most populated cluster. We find that this structure is not necessarily the best representation of the cluster and present here two computationally inexpensive averaging protocols that can systematically provide better representations of the system, which can be more directly compared with structures from X-ray crystallography. In practice, systematic errors in the generated conformational ensembles appear to limit the maximum improvement of averaging methods. Proteins 2014; 82:2671–2680. © 2014 Wiley Periodicals, Inc.

The full text of this article hosted at iucr.org is unavailable due to technical difficulties.