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WIREs Comput Mol Sci
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Computational close up on protein–protein interactions: how to unravel the invisible using molecular dynamics simulations?

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As an essential part of many biological processes, protein–protein interactions (PPIs) offer exciting and promising opportunities for drug discovery by extension of the druggable target space. Over the last decade, studies on protein networks have significantly increased the number of identified PPIs. However, despite steadily growing data on PPIs, detailed understanding of the interaction surfaces and their dynamics remains limited. Furthermore, the development of small‐molecule inhibitors of PPIs faces technological challenges, leaving the question about the ‘druggability’ of PPIs open. Molecular dynamics (MD) simulations may facilitate the prediction of druggable binding sites on protein–protein interfaces by detecting binding hot spots and transient pockets. MD allows for a detailed analysis of structural and functional aspects of PPIs and thus provides valuable insights into PPI mechanisms and supports the design of PPI modulators. We provide an overview on the main areas of MD applications to PPIs including structural investigations and the design of PPI disruptors. Emphasizing the beneficial synergies between computational and experimental techniques, MD techniques are also frequently applied to low‐resolution structural data and have been used to elucidate structure and movements of complex macromolecular structures relevant for biological processes. WIREs Comput Mol Sci 2015, 5:345–359. doi: 10.1002/wcms.1222

This article is categorized under:

  • Structure and Mechanism > Molecular Structures
  • Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods
  • Molecular and Statistical Mechanics > Molecular Interactions
Fields of application for molecular dynamics in protein–protein interaction (PPI) investigations.
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Overview on the macromolecular mechanisms discussed in Section Macromolecular Mechanisms. The illustrated cellular multiprotein processes include the nuclear pore complex, actin filaments, and microtubules. Red circles indicate the area of molecular dynamics (MD) application of the reviewed studies in Section Macromolecular Mechanisms (red letters). (FG‐nups = phenylalanine‐ and glycine‐enriched nucleoporins).
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De novo designed coiled‐coil models investigated by molecular dynamics (MD). (a) Two‐dimensional (2D) representation of a βγ chimera mimicking the typical α‐helical features and incorporated in a peptide sequence made of canonical amino acids. (b) Tetrameric complex involving two αβγ chimeras B3β2γ (in blue) and the natural sequence acid‐pp (in red) in anti‐parallel orientation. (c) Alignment of the two sequences with randomized positions highlighted in gray. (d) Schematic top view of the coiled‐coil with the randomized positions X in the hydrophobic core highlighted in red.
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Illustration of the concept of dimer interface characterization to elucidate the inhibition paradigm of HIV‐1 protease by application of the computational alanine scanning mutagenesis (ASM) method to molecular dynamics (MD) simulations. In the study of Sousa et al., HIV‐1 protease [here protein data bank (PDB) entry 1T3R] was analyzed to determine warm and hot spots, i.e., amino acid residues that contribute most to the binding of the two monomers (indicated by yellow and red areas). This analysis might facilitate the design of antiviral drugs that allow disruption of interactions at the dimer interface.
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Molecular and Statistical Mechanics > Molecular Interactions
Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods
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