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© Structural Dynamics Of Macromolecules
The structure of a bacterial analog of the nicotinic receptor (one color per subunit) inserted into the cell membrane (grey and orange). A representation of the volume accessible to ions is shown in yellow.
Publication : F1000Research

Combined approaches from physics, statistics, and computer science for protein structure prediction: (unity is strength)?

Scientific Fields
Diseases
Organisms
Applications
Technique

Published in F1000Research - 24 Jul 2018

Delarue M, Koehl P

Link to Pubmed [PMID] – 30079234

F1000Res 2018;7

Connecting the dots among the amino acid sequence of a protein, its structure, and its function remains a central theme in molecular biology, as it would have many applications in the treatment of illnesses related to misfolding or protein instability. As a result of high-throughput sequencing methods, biologists currently live in a protein sequence-rich world. However, our knowledge of protein structure based on experimental data remains comparatively limited. As a consequence, protein structure prediction has established itself as a very active field of research to fill in this gap. This field, once thought to be reserved for theoretical biophysicists, is constantly reinventing itself, borrowing ideas informed by an ever-increasing assembly of scientific domains, from biology, chemistry, (statistical) physics, mathematics, computer science, statistics, bioinformatics, and more recently data sciences. We review the recent progress arising from this integration of knowledge, from the development of specific computer architecture to allow for longer timescales in physics-based simulations of protein folding to the recent advances in predicting contacts in proteins based on detection of coevolution using very large data sets of aligned protein sequences.

https://www.ncbi.nlm.nih.gov/pubmed/30079234