College of Liberal Arts & Sciences

On efficient modelling of flexible proteins and their complexes.

Tuesday, October 29, 2019

Title: On efficient modelling of flexible proteins and their complexes.
Time: 11:00 a.m.
Location: MRB 202 Conference Room
Presenter: Sergei Grudinin, Inria / CNRS, Grenoble, France.

Large macromolecular machines, such as proteins and their complexes, are typically very flexible at physiological conditions, and this flexibility is important for their structure and function. Computationally, this flexibility can be often approximated with just a few collective coordinates, which can be computed e.g. using the Normal Mode Analysis (NMA). NMA determines low-frequency motions at a very low computational cost and these are particularly interesting to the structural biology community because they are commonly assumed to give insight into protein function and dynamics.

We have recently introduced a new conceptually simple and computationally efficient method for nonlinear normal mode analysis called NOLB [1]. It is an extension of a very popular rotation translation blocks (RTB) approach [2]. Overall, the NOLB method produces structures with a better local geometry compared to the standard techniques, especially at large deformation amplitudes, and it also predicts better structural transitions between conformational states of macromolecules. Also, the NOLB method is scalable and robust, it typically runs at interactive time rates, and can be applied to very large molecular systems, such as ribosomes. NMA can be combined with other computational techniques for various applications, such as fitting [3] and docking [4]. I will specifically present our approaches fro protein-protein docking and explain how the fast Fourier transform (FFT)-based docking methods can be extended to flexible docking cases.

[1] Hoffmann, A. & Grudinin, S. (2017). J. Chem. Theory Comput. 13, 2123 – 2134. For more information https://team.inria.fr/nano-d/software/nolb-normal-modes/
[2] Tama et al. (2000). Proteins: Structure, Function and Genetics 41, p1-7.
[3] Hoffmann et al (2017). J. Appl. Cryst. 50, 1036-1047.
[4] Neveu et al. (2018). Bioinformatics, 34, 2757–2765.



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