Efficient Prediction of Macromolecular Flexibility and its Applications to Small-Angle Scattering and Structural Bioinformatics
Mercredi 21 février 2018 11:00
- Duree : 1 heure
Lieu : Science Building Room 036 - EPN campus - 71 avenue des Martyrs - Grenoble
Orateur : 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 very important for their structure and function. On the experimental side, molecular flexibility has always been a hurdle for high-resolution structure determination. Computationally, however, molecular flexibility can be very often approximated with collective molecular motions, which can be computed using the Normal Mode Analysis (NMA), for example. NMA is a well-established technique that has recently found many new applications in the field of structural bioinformatics. NMA is able to compute low-frequency motions at a very low cost and these are particularly interesting to the structural biology community because they are commonly assumed to give insight into protein function and dynamics. Another application of NMA is the description and prediction of conformational transitions, for example.
I will first present a new conceptually simple and computationally efficient method for nonlinear normal mode analysis called NOLB [1,2]. I will demonstrate the motions produced with the NOLB method on different molecular systems and show that some of the lowest-frequency normal modes correspond to the biologically relevant motions. Overall, the NOLB method produces better structures compared to the standard approach, especially at large deformation amplitudes. 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. An interactive graphical user interface (GUI) is also made available, where a user can activate a combination o modes with different phases or apply these to opening the binding pockets, for example [3].
I will also present several applications of our NMA method. I will specifically highlight applications to small-angle X-ray scattering (SAXS) that were made possible thanks to our SAXS package called Pepsi-SAXS [4,5]. Pepsi-SAXS is a novel and very efficient method that calculates small angle X-ray scattering profiles from atomistic models. It is based on the multipole expansion scheme and is significantly faster and more precise compared to CRYSOL, FoXS and the 3D-Zernike methods. The method was systematically validated using an excessive set of over fifty models collected from the BioIsis and SASBDB databases, and also in the very recent CASP12 blind structure prediction exercise for SAXS-assisted targets [6]. Recently, we designed a computational scheme that uses the NOLB modes as a low-dimensional representation of the protein motion subspace and optimises protein structures guided by the SAXS profiles. For example, in the CASP12 exercise, this scheme obtained best models for 3 out of 9 SAXS-assisted targets. Overall, this flexible fitting scheme typically allows to significantly improve the goodness of fit to experimental profiles. Finally, I will present some application of NMA for conformational transitions of macromolecules with applications to protein-protein and protein-ligand docking [6,7].
References :
[1] Alexandre Hoffmann & Sergei Grudinin. NOLB : Nonlinear Rigid Block Normal Mode Analysis Method. Journal of Chemical Theory and Computation, 2017, 13 (5), pp.2123-2134.
[2] https://team.inria.fr/nano-d/software/nolb-normal-modes/
[3] https://www.samson-connect.net
[4] Sergei Grudinin, Maria Garkavenko, Andrei Kazennov. Pepsi-SAXS : an adaptive method for rapid and accurate computation of small-angle X-ray scattering profiles. Acta Crystallographica D, 2017, D73, pp.449 – 464.
[5] https://team.inria.fr/nano-d/software/pepsi-saxs/
[6] Tamò GE, Abriata LA, Fonti G, Dal Peraro M, Assessment of data-assisted prediction by inclusion of crosslinking/mass-spectrometry and small angle X-ray scattering data in the 12th Critical Assessment of protein Structure Prediction experiment. Proteins, 2018 in press.
[6] Alexandre Hoffmann, Valérie Perrier, & Sergei Grudinin. A novel fast Fourier transform accelerated off-grid exhaustive search method for cryo-electron microscopy fitting. Journal of Applied Crystallography, 2017, 50 (4), pp.1036-1047.
[7] Maria Kadukova & Sergei Grudinin. Docking of small molecules to farnesoid X receptors using AutoDock Vina with the Convex-PL potential : lessons learned from D3R Grand Challenge 2. J Comput Aided Mol Des (2018) 32 : 151.
Contact : mader@ill.fr
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