Introduction
In vivo, macro- and small molecules are surrounded by an aqueous milieu. Water participates in virtually all biomolecular processes and plays a crucial role in the formation of complexes, such as enzymesubstrate or protein-inhibitor complexes. During these events, solvent water molecules need to be rearranged, impacting on the thermodynamics of the binding process.1
Water molecules have a key role in trypsin-like Serine Proteases protein family, in which a water molecule located in the proximity of the catalytic triad takes part in the last step of the catalytic machinery, promoting the release of the acylated product and the regeneration of the active site. In addition to this, individual water molecules are located in the S1 pocket and can be displaced upon ligand binding: depending on ligand classes, different water molecules can be displaced determining different inhibition and selectivity profiles (Figure 1A).2 Also in ATP pocket of protein kinases there are differences in water networks depending on the kinase system. Displacement of or interaction with a specific water molecule are strategies that have been successfully applied to improve activity and selectivity of ligand series towards a specific kinase (Figure 1B).3 Higgs C. et al have also investigated the role of water molecules in GPCR, revealing that proper understating of the hydration state of these receptors can be important to understand the ligand SAR trends.4
In the development of novel compounds, carefully addressing the impact of the new ligand on the preexisting water network is important for improving affinity and also selectivity against similar proteins. 3D-RISM is useful to understand the hydration state of a complex, but does not allow to characterize the water reorganization upon side chain movements induced by ligand binding. Therefore we developed a workflow combining MOE tools5 with NAMD MD package6, AmberTools7 and python scripts to analyze the reorganization of the water network around the ligand and protein-ligand interaction energy.
References
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3. a) Chrencik JE et al, J Mol Biol 2010, 400, 413;
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4. Higgs C. et al, ACS Med Chem Lett 2010, 1, 160
5. Molecular Operating Environment (MOE), 2018.01;Chemical Computing Group ULC, Montreal, QC, Canada
6. Phillips J.C. Et al, Journal of Computational Chemistry
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7. Case D.A. et al, AMBER 2018, University of California, San Francisco
