TY - JOUR
T1 - Open Structural Data in Precision Medicine
AU - Nussinov, Ruth
AU - Jang, Hyunbum
AU - Nir, Guy
AU - Tsai, Chung Jung
AU - Cheng, Feixiong
N1 - Publisher Copyright:
© 2022 by Annual Reviews. All rights reserved.
PY - 2022/8/10
Y1 - 2022/8/10
N2 - 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.
AB - 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.
KW - AI
KW - KRas
KW - cancer
KW - chromatin accessibility
KW - drug resistance
KW - free-energy landscape
KW - machine learning
KW - network medicine
KW - signaling
KW - targeted therapy
UR - http://www.scopus.com/inward/record.url?scp=85130313912&partnerID=8YFLogxK
U2 - 10.1146/annurev-biodatasci-122220-012951
DO - 10.1146/annurev-biodatasci-122220-012951
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C2 - 35483346
AN - SCOPUS:85130313912
SN - 2574-3414
VL - 5
SP - 95
EP - 117
JO - Annual review of biomedical data science
JF - Annual review of biomedical data science
ER -