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-  2019 

Dynamic “Molecular Portraits” of Proteins and Cell Membranes: A Computational View

DOI: https://doi.org/10.1016/j.bpj.2018.11.1134

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Abstract:

Molecular surfaces are the key players in processes of bimolecular recognition, interaction, and signaling. Nowadays, state of the art methods exist for visualizing molecule surface and surface distributed properties in three-dimensional space. However, such a visual information could only be analyzed by human eye and therefore prompt to be biased and onerous in case of biomacromolecules with a complex structural organization or for large sets of objects. This is especially true for such mesoscopic systems like cell membranes. Therefore, alternative (mostly computational) techniques operating with such “molecular portraits” are indispensable. Here, we present a number of original in silico methods to map and process multivariate and dynamic surface properties of biomolecules and their assemblies - proteins, membranes, carbohydrates and their complexes. These techniques were shown to improve protein-ligand [1] and protein-protein [2] docking results. A new protein surface topography (PST) method [3] is described. It permits pictorial visualization of the whole protein surface in terms of 2D “earth maps”. PST can be used to delineate conformational changes, perform group analysis of molecules. It is a useful tool to add to docking experiments. The proposed original tools have been shown to be very efficient in analysis of atomistic details of the recognition processes in cell membranes - they allow easy monitoring of dynamic amphiphilic properties of lipid membranes, proteins, peptides, polysaccharides, etc. Implementation of the “molecular portrait” technologies is capable of rational design of new physiologically important compounds with predefined activities [4]. References. 1. Pyrkov T.V. et al. (2009) Bioinformatics. 25:1201. 2. Polyansky A.A. et al. (2014) Bioinformatics 30:889. 3. Koromyslova A.D. et al. (2014) J. Chem. Inf. Mod. 54:1189. 4. Kasheverov I.E. et al. (2016) Scientific Reports, 6:36848. Acknowledgements Russian Foundation for Basic Research (18-54-15007), Russian Science Foundation (18-14-00375)

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