Comparative molecular docking analysis of cytoplasmic dynein light chain DYNLL1 with pilin to explore the molecular mechanism of pathogenesis caused by Pseudomonas aeruginosa PAO

Exploring the Binding Interaction of Raf Kinase Inhibitory Protein With the N-Terminal of C-Raf Through Molecular Docking and Molecular Dynamics Simulation

Protein-protein interactions are indispensable physiological processes regulating several biological functions. Despite the availability of structural information on protein-protein complexes, deciphering their complex topology remains an outstanding challenge. Raf kinase inhibitory protein (RKIP) has gained substantial attention as a favorable molecular target for numerous pathologies including cancer and Alzheimer’s disease. RKIP interferes with the RAF/MEK/ERK signaling cascade by endogenously binding with C-Raf (Raf-1 kinase) and preventing its activation. In the current investigation, the binding of RKIP with C-Raf was explored by knowledge-based protein-protein docking web-servers including HADDOCK and ZDOCK and a consensus binding mode of C-Raf/RKIP structural complex was obtained. Molecular dynamics (MD) simulations were further performed in an explicit solvent to sample the conformations for when RKIP binds to C-Raf. Some of the conserved interface residues were mutated to alanine, phenylalanine and leucine and the impact of mutations was estimated by additional MD simulations and MM/PBSA analysis for the wild-type (WT) and constructed mutant complexes. Substantial decrease in binding free energy was observed for the mutant complexes as compared to the binding free energy of WT C-Raf/RKIP structural complex. Furthermore, a considerable increase in average backbone root mean square deviation and fluctuation was perceived for the mutant complexes. Moreover, per-residue energy contribution analysis of the equilibrated simulation trajectory by HawkDock and ANCHOR web-servers was conducted to characterize the key residues for the complex formation. One residue each from C-Raf (Arg398) and RKIP (Lys80) were identified as the druggable “hot spots” constituting the core of the binding interface and corroborated by additional long-time scale (300 ns) MD simulation of Arg398Ala mutant complex. A notable conformational change in Arg398Ala mutant occurred near the mutation site as compared to the equilibrated C-Raf/RKIP native state conformation and an essential hydrogen bonding interaction was lost. The thirteen binding sites assimilated from the overall analysis were mapped onto the complex as surface and divided into active and allosteric binding sites, depending on their location at the interface. The acquired information on the predicted 3D structural complex and the detected sites aid as promising targets in designing novel inhibitors to block the C-Raf/RKIP interaction.

Consensus Analyses in Molecular Docking Studies Applied to Medicinal Chemistry

The increasing number of computational studies in medicinal chemistry involving molecular docking has put the technique forward as promising in Computer-Aided Drug Design. Considering the main method in the virtual screening based on the structure, consensus analysis of docking has been applied in several studies to overcome limitations of algorithms of different programs and mainly to increase the reliability of the results and reduce the number of false positives. However, some consensus scoring strategies are difficult to apply and, in some cases, are not reliable due to the small number of datasets tested. Thus, for such a methodology to be successful, it is necessary to understand why, when and how to use consensus docking. Therefore, the present study aims to present different approaches to docking consensus, applications, and several scoring strategies that have been successful and can be applied in future studies.

Interaction of human dynein light chain 1 (DYNLL1) with enterochelin esterase (Salmonella typhimurium) and protective antigen (Bacillus anthraci) might be the potential cause of human infection

The cytoplasmic dynein light chain 1 (DYNLL1) is an important constituent of motor proteins complex. In human it is encoded by DYNLL1 gene. It is involved in cargo transport functions and interacts with many viral proteins with the help of short linear consensus motif sequence (K/R) XTQT. Viral proteins bind to DYNLL1 through its consensus short linear motif (SLiM) sequence to reach the target site in the cell and cause different infections in the host. It is still unknown if bacterial proteins also contain the same conserved SLiMs sequence through which they bind to this motor protein and cause infections. So, it is important to investigate the role of DYNLL1 in human bacterial infections. The interaction partner proteins of DYNLL1 against conserved viral motif sequences were predicted through PDBSum. Pairwise sequence alignment, between viral motif sequence and that of predicted proteins, was performed to identify conserved region in predicted interaction partners. Docking between the DYNLL1 and new pathogenic interaction partners was performed, by using PatchDock, to explore the protein-protein binding quality. Interactions of docked complexes were visualized by DimPlot. Three pathogenic bacterial proteins i.e., enterochelin esterase (3MGA), protective antigen (3J9C) and putative lipoprotein (4KT3) were selected as candidate interaction partners of DYNLL1. The putative lipoprotein (4KT3) showed low quality binding with DYNLL1. So, enterochelin esterase (3MGA) and protective antigen (3J9C) were speculated to be involved in human bacterial infections by using DYNLL1 to reach their target sites.

Identification of potential isoform-selective histone deacetylase inhibitors for cancer therapy: a combined approach of structure-based virtual screening, ADMET prediction and molecular dynamics simulation assay

Histone deacetylases (HDACs) have gained increased attention as targets for anticancer drug design and development. HDAC inhibitors have proven to be effective for reversing the malignant phenotype in HDAC-dependent cancer cases. However, lack of selectivity of the many HDAC inhibitors in clinical use and trials contributes to toxicities to healthy cells. It is believed that, the continued identification of isoform-selective inhibitors will eliminate these undesirable adverse effects - a task that remains a major challenge to HDAC inhibitor designs. Here, in an attempt to identify isoform-selective inhibitors, a large compound library containing 2,703,000 compounds retrieved from Otava database was screened against class I HDACs by exhaustive approach of structure-based virtual screening using rDOCK and Autodock Vina. A total of 41 compounds were found to show high-isoform selectivity and were further redocked into their respective targets using Autodock4. Thirty-six compounds showed remarkable isoform selectivity and passed drug-likeness and absorption, distribution, metabolism, elimination and toxicity prediction tests using ADMET Predictor™ and admetSAR. Furthermore, to study the stability of ligand binding modes, 10 ns-molecular dynamics (MD) simulations of the free HDAC isoforms and their complexes with respective best-ranked ligands were performed using nanoscale MD software. The inhibitors remained bound to their respective targets over time of the simulation and the overall potential energy, root-mean-square deviation, root-mean-square fluctuation profiles suggested that the detected compounds may be potential isoform-selective HDAC inhibitors or serve as promising scaffolds for further optimization towards the design of selective inhibitors for cancer therapy.

Exploration of Novel Inhibitors for Class I Histone Deacetylase Isoforms by QSAR Modeling and Molecular Dynamics Simulation Assays

Histone deacetylases (HDAC) are metal-dependent enzymes and considered as important targets for cell functioning. Particularly, higher expression of class I HDACs is common in the onset of multiple malignancies which results in deregulation of many target genes involved in cell growth, differentiation and survival. Although substantial attempts have been made to control the irregular functioning of HDACs by employing various inhibitors with high sensitivity towards transformed cells, limited success has been achieved in epigenetic cancer therapy. Here in this study, we used ligand-based pharmacophore and 2-dimensional quantitative structure activity relationship (QSAR) modeling approaches for targeting class I HDAC isoforms. Pharmacophore models were generated by taking into account the known IC50 values and experimental energy scores with extensive validations. The QSAR model having an external R2 value of 0.93 was employed for virtual screening of compound libraries. 10 potential lead compounds (C1-C10) were short-listed having strong binding affinities for HDACs, out of which 2 compounds (C8 and C9) were able to interact with all members of class I HDACs. The potential binding modes of HDAC2 and HDAC8 to C8 were explored through molecular dynamics simulations. Overall, bioactivity and ligand efficiency (binding energy/non-hydrogen atoms) profiles suggested that proposed hits may be more effective inhibitors for cancer therapy.

Molecular handoffs in nitrergic neurotransmission

Postsynaptic density (PSD) proteins in excitatory synapses are relatively immobile components, while there is a structured organization of mobile scaffolding proteins lying beneath the PSDs. For example, shank proteins are located further away from the membrane in the cytosolic faces of the PSDs, facing the actin cytoskeleton. The rationale of this organization may be related to important roles of these proteins as “exchange hubs” for the signaling proteins for their migration from the subcortical cytosol to the membrane. Notably, PSD95 have also been demonstrated in prejunctional nerve terminals of nitrergic neuronal varicosities traversing the gastrointestinal smooth muscles. It has been recently reported that motor proteins like myosin Va play important role in transcytosis of nNOS. In this review, the hypothesis is forwarded that nNOS delivered to subcortical cytoskeleton requires interactions with scaffolding proteins prior to docking at the membrane. This may involve significant role of “shank,” named for SRC-homology (SH3) and multiple ankyrin repeat domains, in nitric oxide synthesis. Dynein light chain LC8–nNOS from acto-myosin Va is possibly exchanged with shank, which thereafter facilitates transposition of nNOS for binding with palmitoyl-PSD95 at the nerve terminal membrane. Shank knockout mice, which present with features of autism spectrum disorders, may help delineate the role of shank in enteric nitrergic neuromuscular transmission. Deletion of shank3 in humans is a monogenic cause of autism called Phelan–McDermid syndrome. One fourth of these patients present with cyclical vomiting, which may be explained by junctionopathy resulting from shank deficit in enteric nitrergic nerve terminals.

NMR Characterization of Self-Association Domains Promoted by Interactions with LC8 Hub Protein

Most proteins in interaction networks have a small number of partners, while a few, called hubs, participate in a large number of interactions and play a central role in cell homeostasis. One highly conserved hub is a protein called LC8 that was originally identified as an essential component of the multi-subunit complex dynein but later shown to be also critical in multiple protein complexes in diverse systems. What is intriguing about this hub protein is that it does not passively bind its various partners but emerging evidence suggests that LC8 acts as a dimerization engine that promotes self-association and/or higher order organization of its primarily disordered monomeric partners. This structural organization process does not require ATP but is triggered by long-range allosteric regulation initiated by LC8 binding a pair of disordered chains forming a bivalent or polybivalent scaffold. This review focuses on the role of LC8 in promoting self-association of two of its binding partners, a dynein intermediate chain and a non dynein protein called Swallow.