Links
- ORCID
- ORCID
- ORCID
- ORCID
- ORCID
- Crossref | PDF
- [www.ncbi.nlm.nih.gov] | PDF
- [discovery.ucl.ac.uk]
- [www.manchester.ac.uk]
- [www.manchester.ac.uk]
- [digital.csic.es] | PDF
- [europepmc.org] | PDF
- [www.researchgate.net] | PDF
- [www.ncbi.nlm.nih.gov] | PDF
- [www.ncbi.nlm.nih.gov] | PDF
- [su.diva-portal.org] | PDF
Tools
The interface of protein structure, protein biophysics, and molecular evolution
,
Kimmen Sjoelander,
David A. Liberles,
Ivet Bahar,
Ugo Bastolla,
Jesse Bloom,
Erich Bornberg-Bauer,
Lucy J. Colwell,
Apj P. Jason de Koning,
Nikolay V. Dokholyan,
Julian Echave ,
Arne Elofsson ,
Dietlind L. Gerloff,
A. P. Jason de Koning,
Richard A. Goldstein
and other authors.
Abstract
Abstract The interface of protein structural biology, protein biophysics, molecular evolution, and molecular population genetics forms the foundations for a mechanistic understanding of many aspects of protein biochemistry. Current efforts in interdisciplinary protein modeling are in their infancy and the state-of-the art of such models is described. Beyond the relationship between amino acid substitution and static protein structure, protein function, and corresponding organismal fitness, other considerations are also discussed. More complex mutational processes such as insertion and deletion and domain rearrangements and even circular permutations should be evaluated. The role of intrinsically disordered proteins is still controversial, but may be increasingly important to consider. Protein geometry and protein dynamics as a deviation from static considerations of protein structure are also important. Protein expression level is known to be a major determinant of evolutionary rate and several considerations including selection at the mRNA level and the role of interaction specificity are discussed. Lastly, the relationship between modeling and needed high-throughput experimental data as well as experimental examination of protein evolution using ancestral sequence resurrection and in vitro biochemistry are presented, towards an aim of ultimately generating better models for biological inference and prediction.