Are Protein Conformational Ensembles in Agreement with Experimental Data? A Geometrical Interpretation of the Problem.


Journal

Journal of chemical information and modeling
ISSN: 1549-960X
Titre abrégé: J Chem Inf Model
Pays: United States
ID NLM: 101230060

Informations de publication

Date de publication:
03 Jul 2024
Historique:
medline: 3 7 2024
pubmed: 3 7 2024
entrez: 3 7 2024
Statut: aheadofprint

Résumé

The conformational variability of biological macromolecules can play an important role in their biological function. Therefore, understanding conformational variability is expected to be key for predicting the behavior of a particular molecule in the context of organism-wide studies. Several experimental methods have been developed and deployed for accessing this information, and computational methods are continuously updated for the profitable integration of different experimental sources. The outcome of this endeavor is conformational ensembles, which may vary significantly in properties and composition when different ensemble reconstruction methods are used, and this raises the issue of comparing the predicted ensembles against experimental data. In this article, we discuss a geometrical formulation to provide a framework for understanding the agreement of an ensemble prediction to the experimental observations.

Identifiants

pubmed: 38959217
doi: 10.1021/acs.jcim.4c00582
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Letizia Fiorucci (L)

Department of Chemistry "Ugo Schiff" and Magnetic Resonance Center (CERM), University of Florence, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy.
Consorzio Interuniversitario Risonanze Magnetiche di Metalloproteine (CIRMMP), Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy.

Marco Schiavina (M)

Department of Chemistry "Ugo Schiff" and Magnetic Resonance Center (CERM), University of Florence, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy.
Consorzio Interuniversitario Risonanze Magnetiche di Metalloproteine (CIRMMP), Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy.

Isabella C Felli (IC)

Department of Chemistry "Ugo Schiff" and Magnetic Resonance Center (CERM), University of Florence, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy.
Consorzio Interuniversitario Risonanze Magnetiche di Metalloproteine (CIRMMP), Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy.

Roberta Pierattelli (R)

Department of Chemistry "Ugo Schiff" and Magnetic Resonance Center (CERM), University of Florence, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy.
Consorzio Interuniversitario Risonanze Magnetiche di Metalloproteine (CIRMMP), Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy.

Enrico Ravera (E)

Department of Chemistry "Ugo Schiff" and Magnetic Resonance Center (CERM), University of Florence, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy.
Consorzio Interuniversitario Risonanze Magnetiche di Metalloproteine (CIRMMP), Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Florence, Italy.
Florence Data Science, University of Florence, Viale G.B. Morgagni 59, 50134 Florence, Italy.

Classifications MeSH