Computational structural biology: Successes, future directions, and challenges

Ruth Nussinov*, Chung Jung Tsai, Amarda Shehu, Hyunbum Jang

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review


Computational biology has made powerful advances. Among these, trends in human health have been uncovered through heterogeneous ‘big data’ integration, and disease-associated genes were identified and classified. Along a different front, the dynamic organization of chromatin is being elucidated to gain insight into the fundamental question of genome regulation. Powerful conformational sampling methods have also been developed to yield a detailed molecular view of cellular processes. when combining these methods with the advancements in the modeling of supramolecular assemblies, including those at the membrane, we are finally able to get a glimpse into how cells’ actions are regulated. Perhaps most intriguingly, a major thrust is on to decipher the mystery of how the brain is coded. Here, we aim to provide a broad, yet concise, sketch of modern aspects of computational biology, with a special focus on computational structural biology. We attempt to forecast the areas that computational structural biology will embrace in the future and the challenges that it may face. We skirt details, highlight successes, note failures, and map directions.

Original languageEnglish
Article number637
Issue number3
StatePublished - 12 Feb 2019


  • Big data
  • Bioinformatics
  • Biological modeling
  • Free-energy landscape
  • Machine intelligence
  • Mutations


Dive into the research topics of 'Computational structural biology: Successes, future directions, and challenges'. Together they form a unique fingerprint.

Cite this