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Volkmann R.A.,Mnemosyne Pharmaceuticals Inc. | Fanger C.M.,Mnemosyne Pharmaceuticals Inc. | Anderson D.R.,Mnemosyne Pharmaceuticals Inc. | Sirivolu V.R.,Jubilant Biosys Ltd and 96 | And 9 more authors.
PLoS ONE | Year: 2016

GluN2A is the most abundant of the GluN2 NMDA receptor subunits in the mammalian CNS. Physiological and genetic evidence implicate GluN2A-containing receptors in susceptibility to autism, schizophrenia, childhood epilepsy and neurodevelopmental disorders such as Rett Syndrome. However, GluN2A-selective pharmacological probes to explore the therapeutic potential of targeting these receptors have been lacking. Here we disclose a novel series of pyrazine-containing GluN2A antagonists exemplified byMPX-004 (5-(((3-chloro-4-fluorophenyl) sulfonamido)methyl)-N-((2-methylthiazol-5-yl)methyl)pyrazine-2-carboxamide) and MPX- 007 (5-(((3-fluoro-4-fluorophenyl)sulfonamido)methyl)-N-((2-methylthiazol-5-yl)methyl) methylpyrazine-2-carboxamide). MPX-004 and MPX-007 inhibit GluN2A-containing NMDA receptors expressed in HEK cells with IC50s of 79 nM and 27 nM, respectively. In contrast, at concentrations that completely inhibited GluN2A activity these compounds have no inhibitory effect on GluN2B or GluN2D receptor-mediated responses in similar HEK cell-based assays. Potency and selectivity were confirmed in electrophysiology assays in Xenopus oocytes expressing GluN2A-D receptor subtypes. Maximal concentrations of MPX-004 and MPX-007 inhibited ~30%of the whole-cell current in rat pyramidal neurons in primary culture and MPX- 004 inhibited ~60% of the total NMDA receptor-mediated EPSP in rat hippocampal slices. GluN2A-selectivity at native receptors was confirmed by the finding thatMPX-004 had no inhibitory effect on NMDA receptor mediated synaptic currents in cortical slices from GRIN2A knock out mice. Thus, MPX-004 and MPX-007 offer highly selective pharmacological tools to probe GluN2A physiology and involvement in neuropsychiatric and developmental disorders. © 2016 Volkmann et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Scior T.,Laboratorio Of Simulaciones Moleculares Computacionales | Lozano-Aponte J.,Laboratorio Of Simulaciones Moleculares Computacionales | Ajmani S.,Jubilant Biosys Ltd and 96 | Hernandez-Montero E.,Posgrado en Matematicas | And 4 more authors.
Current Computer-Aided Drug Design | Year: 2015

In view of the serious health problems concerning infectious diseases in heavily populated areas, we followed the strategy of lead compound diversification to evaluate the near-by chemical space for new organic compounds. To this end, twenty derivatives of nitazoxanide (NTZ) were synthesized and tested for activity against Entamoeba histolytica parasites. To ensure drug-likeliness and activity relatedness of the new compounds, the synthetic work was assisted by a quantitative structure-activity relationships study (QSAR). Many of the inherent downsides – well-known to QSAR practitioners – we circumvented thanks to workarounds which we proposed in prior QSAR publication. To gain further mechanistic insight on a molecular level, ligand-enzyme docking simulations were carried out since NTZ is known to inhibit the protozoal pyruvate ferredoxin oxidoreductase (PFOR) enzyme as its biomolecular target. © 2015 Bentham Science Publishers.

Kristam R.,Jubilant Biosys Ltd and 96 | Kristam R.,SASTRA University | Parmar V.,Jubilant Biosys Ltd and 96 | Viswanadhan V.N.,Jubilant Biosys Ltd and 96
Journal of Molecular Graphics and Modelling | Year: 2013

TRPV1 (Transient Receptor Potential Vanilloid Type 1) receptor, a member of Transient Receptor Potential Vanilloid subfamily of ion channels, occurs in the peripheral and central nervous system, and plays a key role in transmission of pain. Consequently, this has been the target for discovery of several pain relieving agents which have undergone clinical trials. Though several TRPV1 antagonists have progressed to become clinical candidates, many are known to cause temperature elevation in humans, halting their further advancement, and signifying the need for new chemotypes. Different chemical classes of TRPV1 antagonists share three important features: an amide or an isostere flanked by an aromatic (or fused aromatic) ring with polar substitutions on one side, and a hydrophobic group on the other. Recent work identified new series of compounds with these and additional features, leading to improvement of properties, and development of clinical candidates. Herein, we describe a 3D-QSAR model (n = 62; R2 = 0.9 and Q2 = 0.75) developed from the piperazinyl-aryl series of compounds and a novel 5-point pharmacophore model is shown to fit several diverse scaffolds, six clinical candidates, five pre-clinical candidates and three lead compounds. The pharmacophore model can aid in finding new chemotypes as starting points that can be developed further. © 2013 Elsevier Inc. All rights reserved.

Ajmani S.,Jubilant Biosys Ltd and 96 | Viswanadhan V.N.,Jubilant Biosys Ltd and 96
Current Computer-Aided Drug Design | Year: 2013

Receptor and non-receptor tyrosine kinases have emerged as clinically useful drug target for treating certain types of cancer. It is well known that tyrosine kinase inhibitors with multi-kinases inhibitory potency are useful in anticancer therapy. In recent study, we have demonstrated application of a novel Group based QSAR (GQSAR) method to assist in lead optimization of multi-tyrosine kinase (PDGFR-beta, FGFR-1 and SRC) inhibitors. Although GQSAR method provides an alternative way to design new compounds, it could not be applied for virtual screening of large databases, because of its limitation to fragment each of the compound in the diverse database. So to circumvent this limitation of GQSAR method, herein we present the development of multi-kinase QSAR model using artificial neural networks. Various simple, easy and fast to calculate 2D/3D descriptors were used in the present analysis. The resulting neural network based QSAR (NN-QSAR) model was found to be statistically significant and provided insight into common structural requirements to inhibit different tyrosine kinases. The NN-QSAR model suggests five descriptors viz. number of rotatable bonds, number of hydrogen bond donors, number of building blocks, polar surface area and sum of nitrogen and oxygen atoms to be of major importance in explaining the activity variation in all the three kinases. In addition, this multi-target QSAR model could be useful to predict the activities of new compounds designed as tyrosine kinase inhibitors. © 2013 Bentham Science Publishers.

Mulakala C.,Jubilant Biosys Ltd and 96 | Viswanadhan V.N.,Jubilant Biosys Ltd and 96
Journal of Molecular Graphics and Modelling | Year: 2013

Implicit solvation methods such as MM-GBSA, when applied to evaluating protein/ligand binding free energies, are widely believed to be accurate only for the estimation of relative binding free energies for a congeneric series of ligands. In this work, we show that the MM-GBSA flavor of Prime 3.0, VSGB-2.0, with a variable dielectric model and a novel energy function, could be approaching the accuracy required for evaluating absolute binding free energies, albeit, through a linear regression fit. The data-set used for validation includes 106 protein-ligand complexes that were carefully selected to control for variability in the affinity data as well as error in the modeled complexes. Through systematic analysis, we also quantify the degradation in the R 2 of fit between experimental and calculated values with either greater variability in the affinity data or an increase in error in the modeled protein/ligand complexes. Limitations for its application in drug discovery are discussed along with the identification of areas for future development. © 2013 Elsevier Inc. All rights reserved.

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