Contribution to a conference proceedings/Contribution to a book

FZJ-2018-02966

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Biomolecular Structure Prediction via Coevolutionary Analysis: A Guide to the Statistical Framework

Zerihun, M. B. ; Schug, A. (Corresponding author)FZJ*

2018
Forschungszentrum Jülich GmbH, Zentralbibliothek Jülich

Please use a persistent id in citations: http://hdl.handle.net/2128/18571

Abstract: On the molecular level, life is orchestrated through an interplay of many biomolecules. To gain any detailed understanding of biomolecular function, one needs to know their structure. Yet despite incredible progress in experimental structure determination techniques, many important biomolecules are still not structurally resolved. An orthogonal theoretical approach are structure prediction techniques which take advantage of constantly growing computational resources. Mostly untapped information of evolutionarily closely related sequences in the exponentially growing genomic databases can be statistically analysed to: (i) accurately infer pairs of residues in spatial contact within biomolecules and (ii) guide the prediction of biomolecular structures when used in combination with molecular modelling techniques. By now, this approach has revolutionised the field of protein structure prediction by providing highly accurate models. The same mathematical framework can also go beyond structure prediction by analysing evolutionary fitness landscapes and inferring biomolecular interactions or epistasis.

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Contributing Institute(s):

1. John von Neumann - Institut für Computing (NIC)
2. Jülich Supercomputing Center (JSC)

Research Program(s):

1. 511 - Computational Science and Mathematical Methods (POF3-511) (POF3-511)

Appears in the scientific report 2018

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Database coverage:

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