Computational design of new protein kinase D 1 (PKD1) inhibitors: homology-based active site prediction, energy-optimized pharmacophore, docking and database screening.

Protein kinase D 1 (PKD1) overexpression has a well-validated role in cancer progression and its inhibitors have defined a protective role-play of PKD1 for various cancers such as prostate, pancreatic and noninvasive breast cancers, and more. Therefore, the current research was aimed at designing new PKD1 inhibitors combining different ligand- and structure-based computational drug designing methodologies. Initially, the three-dimensional structure of PKD1's active site was computationally modeled, corrected using molecular dynamic simulations and validated for docking experiments. The highest active PKD1 inhibitor was used to develop a structure-based energetic pharmacophore (e-pharmacophore) model, and a final model was selected with five structural features (Pmodel_AADHR). Pmodel_AADHR was validated and used for database screening to obtain new hits against PKD1. These newly retrieved hits were docked against our PKD1 protein model, and those displaying essential interactions are reported herein as new hits, which could serve as new leads for cancer research, especially pancreatic cancer.

Discovery of non-peptidic small molecule inhibitors of cyclophilin D as neuroprotective agents in Aß-induced mitochondrial dysfunction.

Cyclophilin D (CypD) is a mitochondria-specific cyclophilin that is known to play a pivotal role in the formation of the mitochondrial permeability transition pore (mPTP).The formation and opening of the mPTP disrupt mitochondrial homeostasis, cause mitochondrial dysfunction and eventually lead to cell death. Several recent studies have found that CypD promotes the formation of the mPTP upon binding to ß amyloid (Aß) peptides inside brain mitochondria, suggesting that neuronal CypD has a potential to be a promising therapeutic target for Alzheimer's disease (AD). In this study, we generated an energy-based pharmacophore model by using the crystal structure of CypD-cyclosporine A (CsA) complex and performed virtual screening of ChemDiv database, which yielded forty-five potential hit compounds with novel scaffolds. We further tested those compounds using mitochondrial functional assays in neuronal cells and identified fifteen compounds with excellent protective effects against Aß-induced mitochondrial dysfunction. To validate whether these effects derived from binding to CypD, we performed surface plasmon resonance (SPR)-based direct binding assays with selected compounds and discovered compound 29 was found to have the equilibrium dissociation constants (KD) value of 88.2 nM. This binding affinity value and biological activity correspond well with our predicted binding mode. We believe that this study offers new insights into the rational design of small molecule CypD inhibitors, and provides a promising lead for future therapeutic development.

Multiple e-Pharmacophore modeling to identify a single molecule that could target both streptomycin and paromomycin binding sites for 30S ribosomal subunit inhibition.

The bacterial ribosome is an established target for anti-bacterial therapy since decades. Several inhibitors have already been developed targeting both defined subunits (50S and 30S) of the ribosome. Aminoglycosides and tetracyclines are two classes of antibiotics that bind to the 30S ribosomal subunit. These inhibitors can target multiple active sites on ribosome that have a complex structure. To screen putative inhibitors against 30S subunit of the ribosome, the crystal structures in complex with various known inhibitors were analyzed using pharmacophore modeling approach. Multiple active sites were considered for building energy-based three-dimensional (3D) pharmacophore models. The generated models were validated using enrichment factor on decoy data-set. Virtual screening was performed using the developed 3D pharmacophore models and molecular interaction towards the 30S ribosomal unit was analyzed using the hits obtained for each pharmacophore model. The hits that were common to both streptomycin and paromomycin binding sites were identified. Further, to predict the activity of these hits a robust 2D-QSAR model with good predictive ability was developed using 16 streptomycin analogs. Hence, the developed models were able to identify novel inhibitors that are capable of binding to multiple active sites present on 30S ribosomal subunit.

Hybrid Receptor-Bound/MM-GBSA-Per-residue Energy-Based Pharmacophore Modelling: Enhanced Approach for Identification of Selective LTA4H Inhibitors as Potential Anti-inflammatory Drugs.

Leukotriene A4 hydrolase has been identified as an enzyme with dual anti- and pro-inflammatory role, thus, the conversion of leukotriene to leukotriene B4 in the initiation stage of inflammation and the removal of the chemotactic Pro-Gly-Pro tripeptide. These findings make leukotriene A4 hydrolase an attractive drug target: suggesting an innovative approach towards the identification and design of novel class of compounds that can selectively inhibit leukotriene B4 synthesis while sparing the aminopeptidase activity. Previous inhibitors block the dual activity of the enzyme. Recently, a small lead molecule inhibitor denoted as ARM1 has been identified to block the hydrolase activity of leukotriene A4 hydrolase whilst sparing the aminopeptidase activity. In this study, a hybrid receptor-bound/MM-GBSA-per-residue energy based pharmacophore modeling approach was implemented to identify potential selective hydrolase inhibitors of leukotriene A4 hydrolase. In this approach, active site residues that favorably contributed to the binding of the bound conformation of ARM1 were derived from MD ensembles and MM/GBSA thermodynamic calculations. These residues were then mapped to key pharmacophore features of ARM1. The generated pharmacophore model was used to search the ZINC database for 3D structures that match the pharmacophore. Five new compounds have been identified and proposed as potential epoxide hydrolase selective inhibitors of leukotriene A4 hydrolase. Molecular docking and MM/GBSA analyses revealed that, these top five lead-like compounds ZINC00142747, ZINC94260794, ZINC01382396, ZINC02508448, and ZINC53994447 showed better binding affinities to the hydrolase active site pocket compared to ARM1. Per-residue energy decomposition analysis revealed that amino acid residues Phe314, Tyr378, Pro382, Trp311, Val367, and Ala377 are key residues critical in the selective inhibition of these hits. Information highlighted in this study may guide the the design the next generation of novel and potent epoxide hydrolase selective inhibitors of leukotriene A4 hydrolase.