Identifying protein conformational states in the Protein Data Bank: Toward unlocking the potential of integrative dynamics studies.
Struct Dyn
; 11(3): 034701, 2024 May.
Article
en En
| MEDLINE
| ID: mdl-38774441
ABSTRACT
Studying protein dynamics and conformational heterogeneity is crucial for understanding biomolecular systems and treating disease. Despite the deposition of over 215 000 macromolecular structures in the Protein Data Bank and the advent of AI-based structure prediction tools such as AlphaFold2, RoseTTAFold, and ESMFold, static representations are typically produced, which fail to fully capture macromolecular motion. Here, we discuss the importance of integrating experimental structures with computational clustering to explore the conformational landscapes that manifest protein function. We describe the method developed by the Protein Data Bank in Europe - Knowledge Base to identify distinct conformational states, demonstrate the resource's primary use cases, through examples, and discuss the need for further efforts to annotate protein conformations with functional information. Such initiatives will be crucial in unlocking the potential of protein dynamics data, expediting drug discovery research, and deepening our understanding of macromolecular mechanisms.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
Struct Dyn
Año:
2024
Tipo del documento:
Article
País de afiliación:
Reino Unido
Pais de publicación:
Estados Unidos