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Prediction of biomolecular complexes

From Protein Structure to Function with Bioinformatics: Second Edition, Page: 265-292
2017
  • 10
    Citations
  • 0
    Usage
  • 7
    Captures
  • 0
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    10
    • Citation Indexes
      10
  • Captures
    7

Book Chapter Description

Almost all processes in living organisms occur through specific interactions between biomolecules. Any dysfunction of those interactions can lead to pathological events. Understanding such interactions is therefore a crucial step in the investigation of biological systems and a starting point for drug design. In recent years, experimental studies have been devoted to unravel the principles of biomolecular interactions; however, due to experimental difficulties in solving the three-dimensional (3D) structure of biomolecular complexes, the number of available, high-resolution experimental 3D structures does not fulfill the current needs. Therefore, complementary computational approaches to model such interactions are necessary to assist experimentalists since a full understanding of how biomolecules interact (and consequently how they perform their function) only comes from 3D structures which provide crucial atomic details about binding and recognition processes. In this chapter we review approaches to predict biomolecular complexes, introducing the concept of molecular docking, a technique which uses a combination of geometric, steric and energetics considerations to predict the 3D structure of a biological complex starting from the individual structures of its constituent parts. We provide a mini-guide about docking concepts, its potential and challenges, along with post-docking analysis and a list of related software.

Bibliographic Details

Anna Vangone; Romina Oliva; Luigi Cavallo; Alexandre M. J. J. Bonvin

Springer Science and Business Media LLC

Engineering; Agricultural and Biological Sciences; Environmental Science; Economics, Econometrics and Finance; Business, Management and Accounting; Social Sciences

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