The relationship between the flexibility of proteins and their conformational states on forming protein-protein complexes with an application to protein-protein docking

We investigate the extent to which the conformational fluctuations of proteins in solution reflect the conformational changes that they undergo when they form binary protein-protein complexes. To do this, we study a set of 41 proteins that form such complexes and whose three-dimensional structures are known, both bound in the complex and unbound. We carry out molecular dynamics simulations of each protein, starting from the unbound structure, and analyze the resulting conformational fluctuations in trajectories of 5 ns in length, comparing with the structure in the complex. It is found that fluctuations take some parts of the molecules into regions of conformational space close to the bound state (or give information about it), but at no point in the simulation does each protein as whole sample the complete bound state. Subsequent use of conformations from a clustered MD ensemble in rigid-body docking is nevertheless partially successful when compared to docking the unbound conformations, as long as the unbound conformations are themselves included with the MD conformations and the whole globally rescored. For one key example where sub-domain motion is present, a ribonuclease inhibitor, principal components analysis of the MD was applied and was also able to produce conformations for docking that gave enhanced results compared to the unbound. The most significant finding is that core interface residues show a tendency to be less mobile (by size of fluctuation or entropy) than the rest of the surface even when the other binding partner is absent, and conversely the peripheral interface residues are more mobile. This surprising result, consistent across up to 40 of the 41 proteins, suggests different roles for these regions in protein recognition and binding, and suggests ways that docking algorithms could be improved by treating these regions differently in the docking process.     

Testing a flexible-receptor docking algorithm in a model binding site

Sampling receptor flexibility is challenging for database docking. We consider a method that treats multiple flexible regions of the binding site independently, recombining them to generate different discrete conformations. This algorithm scales linearly rather than exponentially with the receptor's degrees of freedom. The method was first evaluated for its ability to identify known ligands of a hydrophobic cavity mutant of T4 lysozyme (L99A). Some 200000 molecules of the Available Chemical Directory (ACD) were docked against an ensemble of cavity conformations. Surprisingly, the enrichment of known ligands from among a much larger number of decoys in the ACD was worse than simply docking to the apo conformation alone. Large decoys, accommodated in the larger cavity conformations sampled in the ensemble, were ranked better than known small ligands. The calculation was redone with an energy correction term that considered the cost of forming the larger cavity conformations. Enrichment improved, as did the balance between high-ranking large and small ligands. In a second retrospective test, the ACD was docked against a conformational ensemble of thymidylate synthase. Compared to docking against individual enzyme conformations, the flexible receptor docking approach improved enrichment of known ligands. Including a receptor conformational energy weighting term improved enrichment further. To test the method prospectively, the ACD database was docked against another cavity mutant of lysozyme (L99A/M102Q). A total of 18 new compounds predicted to bind this polar cavity and to change its conformation were tested experimentally; 14 were found to bind. The bound structures for seven ligands were determined by X-ray crystallography. The predicted geometries of these ligands all corresponded to the observed geometries to within 0.7A RMSD or better. Significant conformational changes of the cavity were observed in all seven complexes. In five structures, part of the observed accommodations were correctly predicted; in two structures, the receptor conformational changes were unanticipated and thus never sampled. These results suggest that although sampling receptor flexibility can lead to novel ligands that would have been missed when docking a rigid structure, it is also important to consider receptor conformational energy.     

Structural mechanism underlying ligand binding and activation of PPARγ

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Exploration of potential RSK2 inhibitors by pharmacophore modelling,structure-based 3D-QSAR,molecular docking study and molecular dynamics simulation

Abstract

The p90 ribosomal s6 kinase 2 (RSK2) is a promising target because of its over expression and activation in human cancer cells and tissues. Over the last few years, significant efforts have been made in order to develop RSK2 inhibitors to treat myeloma, prostatic cancer, skin cancer and etc., but with limited success so far. In this paper, pharmacophore modelling, molecular docking study and molecular dynamics (MD) simulation have been performed to explore the novel inhibitors of RSK2. Pharmacophore models were developed by 95 molecules having pIC₅₀ ranging from 4.577 to 9.000. The pharmacophore model includes one hydrogen bond acceptor (A), one hydrogen bond donor (D), one hydrophobic feature (H) and one aromatic ring (R). It is the best pharmacophore hypothesis that has the highest correlation coefficient (R² = 0.91) and cross validation coefficient (Q² = 0.71) at 5 component PLS factor. It was evaluated using enrichment analysis and the best model was used for virtual screening. The constraints used in this study were docking score, ADME properties, binding free energy estimates and IFD Score to screen the database. Ultimately, 12 hits were identified as potent and novel RSK2 inhibitors. A 15 ns molecular dynamics (MD) simulation was further employed to validate the reliability of the docking results.     

Probing the “fingers” domain binding pocket of Hepatitis C virus NS5B RdRp and D559G resistance mutation via molecular docking,molecular dynamics simulation and binding free energy calculations

The NS5B RdRp polymerase is a prominent enzyme for the replication of Hepatitis C virus (HCV). During the HCV replication, the template RNA binding takes place in the “fingers” sub-domain of NS5B. The “fingers” domain is a new emerging allosteric site for the HCV drug development. The inhibitors of the “fingers” sub-domain adopt a new antiviral mechanism called RNA intervention. The details of essential amino acid residues, binding mode of the ligand, and the active site intermolecular interactions of RNA intervention reflect that this mechanism is ambiguous in the experimental study. To elucidate these details, we performed molecular docking analysis of the fingers domain inhibitor quercetagetin (QGN) with NS5B polymerase. The detailed analysis of QGN-NS5B intermolecular interactions was carried out and found that QGN interacts with the binding pocket amino acid residues Ala97, Ala140, Ile160, Phe162, Gly283, Gly557, and Asp559; and also forms π?π stacking interaction with Phe162 and hydrogen bonding interaction with Gly283. These are found to be the essential interactions for the RNA intervention mechanism. Among the strong hydrogen bonding interactions, the QGN?Ala140 is a newly identified important hydrogen bonding interaction by the present work and this interaction was not resolved by the previously reported crystal structure. Since D559G mutation at the fingers domain was reported for reducing the inhibition percentage of QGN to sevenfold, we carried out molecular dynamics (MD) simulation for wild and D559G mutated complexes to study the stability of protein conformation and intermolecular interactions. At the end of 50?ns MD simulation, the π?π stacking interaction of Phe162 with QGN found in the wild-type complex is altered into T-shaped π stacking interaction, which reduces the inhibition strength. The origin of the D559G resistance mutation was studied using combined MD simulation, binding free energy calculations and principal component analysis. The results were compared with the wild-type complex. The mutation D559G reduces the binding affinity of the QGN molecule to the fingers domain. The free energy decomposition analysis of each residue of wild-type and mutated complexes revealed that the loss of non-polar energy contribution is the origin of the resistance.

Communicated by Ramaswamy H. Sarma