Information-Driven Modeling of Biomolecular Complexes

This figure illustrates the information-driven modeling of biomolecular complexes, within the central panel, an illustration of various information sources, on the left, a docking protocol that would only make use of the information in the filtering stage after sampling the interaction space, and on the right, an information-guided docking protocol that uses the data to bias the sampling and score the resulting models.

Proteins play crucial roles in every cellular process by interacting with each other, nucleic acids, metabolites, and other molecules. The resulting assemblies can be very large and intricate and pose challenges to experimental methods.

In the current era of integrative modeling, it is often only by a combination of various experimental techniques and computations that three-dimensional models of those molecular machines can be obtained.

Among the various computational approaches available, molecular docking is often the method of choice when it comes to predicting three-dimensional structures of complexes. Docking can generate particularly accurate models when taking into account the available information on the complex of interest.

We review here the use of experimental and bioinformatics data in protein-protein docking, describing recent software developments and highlighting applications for the modeling of antibody–antigen complexes and membrane protein complexes, and the use of evolutionary and shape information.

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Charlotte W. van Noort, Rodrigo V. Honorato, Alexandre M.J.J. Bonvin (2022):
Information-Driven Modeling of Biomolecular Complexes.
Current Opinion in Structural Biology 70