Network models for molecular kinetics and their initial applications to human health

Gregory R. Bowman, Xuhui Huang, Vijay S. Pande

Research output: Contribution to journalReview articlepeer-review

39 Scopus citations

Abstract

Molecular kinetics underlies all biological phenomena and, like many other biological processes, may best be understood in terms of networks. These networks, called Markov state models (MSMs), are typically built from physical simulations. Thus, they are capable of quantitative prediction of experiments and can also provide an intuition for complex conformational changes. Their primary application has been to protein folding; however, these technologies and the insights they yield are transferable. For example, MSMs have already proved useful in understanding human diseases, such as protein misfolding and aggregation in Alzheimer's disease.

Original languageEnglish
Pages (from-to)622-630
Number of pages9
JournalCell Research
Volume20
Issue number6
DOIs
StatePublished - Jun 2010

Keywords

  • Alzheimer'sdisease
  • Conformational change
  • Markov state models
  • Molecular dynamics
  • Protein folding
  • Simulations

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