Integrative Modelling of Biomolecular Complexes
2020
Koukos, P.I. | Bonvin, A.M.J.J.
In recent years, the use of integrative, information-driven computational approaches for modeling the structure of biomolecules has been increasing in popularity. These are now recognized as a crucial complement to experimental structural biology techniques such as X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy and cryo-electron microscopy (cryo-EM). This trend can be credited to a few reasons such as the increased prominence of structures solved by cryo-EM, the improvements in proteomics approaches such as cross-linking mass spectrometry (XL-MS), the drive to study systems of higher complexity in their native state, and the maturation of many computational techniques combined with the widespread availability of information-driven integrative modeling platforms.In this review, we highlight recent works that exemplify how the use of integrative and/or information-driven approaches and platforms can produce highly accurate structural models. These examples include systems which present many challenges when studied with traditional structural biology techniques such as flexible and dynamic macromolecular assemblies and membrane-associated complexes.We also identify some key areas of interest for information-driven, integrative modeling and discuss how they relate to ongoing challenges in the fields of computational structural biology. These include the use of coarse-grained force fields for biomolecular simulations—allowing for simulations across longer (time-) and bigger (size-dimension) scales—the use of bioinformatics predictions to drive sampling and/or scoring in docking such as those derived from coevolution analysis and finally the study of membrane and membrane-associated protein complexes.
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