APS March Meeting 2016
Volume 61, Number 2
Monday–Friday, March 14–18, 2016;
Baltimore, Maryland
Session F41: Maximum Entropy Models: A Promising Link Between Statistical Physics, Inference, and Biology
11:15 AM–2:15 PM,
Tuesday, March 15, 2016
Room: 344
Sponsoring
Units:
DBIO GSNP GSOFT
Chair: Gasper Tkacik, IST Austria
Abstract ID: BAPS.2016.MAR.F41.10
Abstract: F41.00010 : Coevolutionary modeling of protein sequences: Predicting structure, function, and mutational landscapes
1:03 PM–1:39 PM
Preview Abstract
Abstract
Author:
Martin Weigt
(Universite Pierre et Marie Curie, Paris)
Over the last years, biological research has been revolutionized by
experimental high-throughput techniques, in particular by next-generation
sequencing technology. Unprecedented amounts of data are accumulating, and
there is a growing request for computational methods unveiling the
information hidden in raw data, thereby increasing our understanding of
complex biological systems. Statistical-physics models based on the
maximum-entropy principle have, in the last few years, played an important
role in this context.
To give a specific example, proteins and many non-coding RNA show a
remarkable degree of structural and functional conservation in the course of
evolution, despite a large variability in amino acid sequences. We have
developed a statistical-mechanics inspired inference approach - called
Direct-Coupling Analysis - to link this sequence variability (easy to
observe in sequence alignments, which are available in public sequence
databases) to bio-molecular structure and function.
In my presentation I will show, how this methodology can be used (i) to
infer contacts between residues and thus to guide tertiary and quaternary
protein structure prediction and RNA structure prediction, (ii) to
discriminate interacting from non-interacting protein families, and thus to
infer conserved protein-protein interaction networks, and (iii) to
reconstruct mutational landscapes and thus to predict the phenotypic effect
of mutations.
References
[1] M. Figliuzzi, H. Jacquier, A. Schug, O. Tenaillon and M. Weigt
"Coevolutionary landscape inference and the context-dependence of mutations
in beta-lactamase TEM-1", Mol. Biol. Evol. (2015), doi:
10.1093/molbev/msv211
[2] E. De Leonardis, B. Lutz, S. Ratz, S. Cocco, R. Monasson, A. Schug, M.
Weigt "Direct-Coupling Analysis of nucleotide coevolution facilitates RNA
secondary and tertiary structure prediction", Nucleic Acids Research (2015),
doi: 10.1093/nar/gkv932
[3] F. Morcos, A. Pagnani, B. Lunt, A. Bertolino, D. Marks, C. Sander, R.
Zecchina, J.N. Onuchic, T. Hwa, M. Weigt, "Direct-coupling analysis of
residue co-evolution captures native contacts across many protein families",
Proc. Natl. Acad. Sci. 108, E1293-E1301 (2011).
To cite this abstract, use the following reference: http://meetings.aps.org/link/BAPS.2016.MAR.F41.10