Open Structural Data in Precision Medicine

Ruth Nussinov, Hyunbum Jang, Guy Nir, Chung Jung Tsai, Feixiong Cheng

Research output: Contribution to journalReview articlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)95-117
Number of pages23
JournalAnnual review of biomedical data science
Volume5
DOIs
StatePublished - 10 Aug 2022

Keywords

  • AI
  • KRas
  • cancer
  • chromatin accessibility
  • drug resistance
  • free-energy landscape
  • machine learning
  • network medicine
  • signaling
  • targeted therapy

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