Editorial: Computational approaches for interpreting experimental data and understanding protein structure, dynamics and function relationships

Kaifeng Hu; Woonghee Lee; Gaetano T Montelione; Nikolaos G Sgourakis; Beat Vögeli

doi:10.3389/fmolb.2022.1018149

Editorial: Computational approaches for interpreting experimental data and understanding protein structure, dynamics and function relationships

Front Mol Biosci. 2022 Oct 3:9:1018149. doi: 10.3389/fmolb.2022.1018149. eCollection 2022.

Authors

Kaifeng Hu¹, Woonghee Lee², Gaetano T Montelione³, Nikolaos G Sgourakis⁴, Beat Vögeli⁵

Affiliations

¹ Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China.
² Department of Chemistry, University of Colorado Denver, Denver, CO, United States.
³ Department of Chemistry and Chemical Biology, Center for Biotechnology and Interdisciplinary Sciences, Rensselaer Polytechnic Institute, Troy, NY, United States.
⁴ Department of Pathology and Laboratory Medicine, The Children's Hospital of Philadelphia, and Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
⁵ Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical Campus, Aurora, CO, United States.

No abstract available

Keywords: algorithms; biomolecules; data acquisition and analysis; database; experiment-aided computation; multi-scale simulation and application; software and web services; structural biology.

Publication types

Editorial

Publication types

Grants and funding