Open Structural Data in Precision Medicine.
AI
KRas
cancer
chromatin accessibility
drug resistance
free-energy landscape
machine learning
network medicine
signaling
targeted therapy
Journal
Annual review of biomedical data science
ISSN: 2574-3414
Titre abrégé: Annu Rev Biomed Data Sci
Pays: United States
ID NLM: 101714020
Informations de publication
Date de publication:
10 08 2022
10 08 2022
Historique:
pubmed:
29
4
2022
medline:
13
8
2022
entrez:
28
4
2022
Statut:
ppublish
Résumé
Three-dimensional protein structural data at the molecular level are pivotal for successful precision medicine. Such data are crucial not only for discovering drugs that act to block the active site of the target mutant protein but also for clarifying to the patient and the clinician how the mutations harbored by the patient work. The relative paucity of structural data reflects their cost, challenges in their interpretation, and lack of clinical guidelines for their utilization. Rapid technological advancements in experimental high-resolution structural determination increasingly generate structures. Computationally, modeling algorithms, including molecular dynamics simulations, are becoming more powerful, as are compute-intensive hardware, particularly graphics processing units, overlapping with the inception of the exascale era. Accessible, freely available, and detailed structural and dynamical data can be merged with big data to powerfully transform personalizedpharmacology. Here we review protein and emerging genome high-resolution data, along with means, applications, and examples underscoring their usefulness in precision medicine.
Identifiants
pubmed: 35483346
doi: 10.1146/annurev-biodatasci-122220-012951
doi:
Substances chimiques
Proteins
0
Types de publication
Journal Article
Review
Research Support, N.I.H., Intramural
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
95-117Subventions
Organisme : NCI NIH HHS
ID : HHSN261201500003I
Pays : United States
Organisme : NIA NIH HHS
ID : U01 AG073323
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG066707
Pays : United States
Organisme : NIA NIH HHS
ID : R56 AG074001
Pays : United States