Mohd Athar

Pharmacophore model prediction, 3D-QSAR and molecular docking studies on vinyl sulfones targeting Nrf2-mediated gene transcription intended for anti-Parkinson drug design.

Despite intense research efforts towards clinical and molecular causes of Parkinson disease (PD), the etiology of disease still remains unclear. However, recent studies have provided ample evidences that the oxidative stress is the key player that contributes a lot to dopaminergic (DAergic) neurodegeneration in brain. It is due to the discrepancy of antioxidant defence system of which nuclear factor erythroid 2-related factor 2 (Nrf2) signalling is of central contour. In the current study, potent heme oxygenase-1 agonists (Nrf2 signalling regulator), vinyl sulfones, were selected and an optimal pharmacophore model was brought forth which was examined using a decoy set by atom-based 3D-QSAR. The best four-feature model consists of two hydrogen bond acceptors and two aromatic rings, which has the highest correlation coefficient, R2 = .71 and = .73 in QSAR. These ligands were further studied for molecular docking with Nrf2-keap protein to gain insight into the major binding motifs followed by analysing pharmacokinetic properties to evaluate their bioavailability dominance. From this study, it is concluded that vinyl sulfones could be ideal compounds for targeting Nrf2 pathway which in turn halt the PD progression. Hence, these can be considered as potential leads for drug development against the same. Graphical abstract

A turn-off fluorescence sensor for insensitive munition using anthraquinone-appended oxacalix[4]arene and its computational studies

Herein, a fluorescent oxacalix[4]arene-based receptor, DAQTNOC(5,17-di(N-(9,10-dioxo-9,10-dihydroanthracen-1-yl)acetamide) tetranitrooxacalix[4]arene), was described for the specific recognition of N-methyl-p-nitroaniline (MNA). Among the array of explosives, DAQTNOC shows selective behaviour for MNA in the absorption and as well as emission spectra. The binding constants, stoichiometry, quantum yields, and fluorescence quenching were determined to elucidate the inclusion behaviour. Furthermore, computational insights were rendered for studying the stability and spectroscopic analysis of the inclusion complex using docking, molecular dynamics simulations, and density functional theory (DFT) along with time-dependent density functional theory (TD-DFT). The calculations considerably complement the findings and elucidate the structural geometry and mode of interactions in supramolecular complexation. Herein, we observed that DAQTNOC was selectively stabilized by van der Waals forces and hydrophobic contacts with MNA to generate a low-energy complex. These findings are of wide interest, especially because MNA is a well-known insensitive munition and has been detected for the first time via an oxacalixarenes platform.

Identification of Mycobacterium tuberculosis enoyl-acyl carrier protein reductase inhibitors: A combined in-silico and in-vitro analysis

Mycobacterium tuberculosis (Mtb), had developed evolutionary changes in its genome to adapt for survival and thereby generated multi-drug resistant strains. However, novel drug targets that remained unchanged for their biochemical role has impressed the research community to target such proteins. The comprehensive analysis of multiple protein targets has influenced us to make a consensus structural rule exploited by pharmacophore and other allied techniques from a large repository of protein structures. In this pursuit, we made a retrospective analysis of pharmacophores mapped from the tuberculosis structural proteome and identified unique patterns that can be employed for the novel molecules design. The current work on NADH-dependent enoyl-acyl carrier protein reductase (InhA) has yielded top scored pharmacophore models which were searched over SPECS natural product database to prioritize the molecules that can be targeted against Mtb. With efforts on rigorous validation and expertise, we have identified such pharmacophoric patterns from natural compounds that can be used as initial hits. Subsequently, these hits were subjected to in-vitro antitubercular evaluation to ensure the inhibitory activity against the mycobacterium culture growth (MtbH37Rv). Furthermore, docking simulations were carried out to provide an insight on the possible modes of interaction between the experimentally explored compounds and InhA.

Turn-off fluorescence probe for the selective determination of pendimethalin using a mechanistic docking model of novel oxacalix[4]arene

A novel bidansylated oxacalix[4]arene (BDO) fluoroionophore for the selective determination of pendimethalin (PM) was carried out in the linear range of detection between 0.4 μM and 20 μM. Furthermore, computational studies were performed to assess the binding and stability of the complex. For the predicted model, PM faces laterally and interacts via weak intermolecular forces with BDO with a E value of −176.00 kJ mol−1.

Efficiently functionalized oxacalix[4]arenes: Synthesis, characterization and exploration of their biological profile as novel HDAC inhibitors.

A series of novel substituted oxacalix[4]arene has been synthesized and explored for their biological profile by evaluating anticancer, antifungal and antibacterial properties. The derivatives have been characterized by various spectroscopic techniques such as IR, (1)H NMR, (13)C NMR and Mass spectrometry. Many compounds showed strong inhibition (MIC) in the range of ∼0-50 μM with interesting cytotoxic activities against Hela cells in particular. The compounds were theoretically evaluated by docking studies as potential histone deacetylase inhibitors (HDACi). The study indicates that compounds bound adequately with HDAC, and hence complemented the experimental findings.

Identification of InhA inhibitors: A combination of virtual screening, molecular dynamics simulations and quantum chemical studies

In the present work, multiple pharmacophore-based virtual screening of the SPECS natural product database was carried out to identify novel inhibitors of the validated biological target, InhA. The pharmacophore models were built from the five different groups of the co-crystallized ligands present within the active site. The generated models with the same features from each group were pooled and subjected to the test set validation, receiver–operator characteristic analysis and Güner–Henry studies. A set of five hypotheses with sensitivity > 0.5, specificity > 0.5, area under curve (AUC) > 0.7, and goodness of hit score > 0.7 were retrieved and exploited for the virtual screening. The common hits (87 molecules) obtained from these hypotheses were processed via drug-likeness filters. The filtered molecules (27 molecules) were compared for the binding modes and the top scored molecules (12 molecules) along with the reference (triclosan (TCL), docking score = −11.65 kcal/mol) were rescored and reprioritized via molecular mechanics-generalized Born surface area approach. Eventually, the stability of reprioritized (10 molecules) docked complexes was scrutinized via molecular dynamics simulations. Moreover, the quantum chemical studies of the dynamically stable compounds (9 molecules) were performed to understand structural features essential for the activity. Overall, the protocol resulted in the recognition of nine lead compounds that can be targeted against InhA.

First protein drug target’s appraisal of lead-likeness descriptors to unfold the intervening chemical space

Despite the advances in combinatorial chemistry, high throughput and virtual screening experiments, plethora of clinical studies disquiet due to lead and drug-likeness attritions. For mitigation, the knowledge of physicochemical properties are really useful for guiding and selection of compounds from libraries dictated by certain rule of thumbs. However, robust bio-technological and instrumental innovations have created exponential increase in novel compounds and databases which compelled rethinking of the evaluation procedures. Known descriptive molecular property filters proposed by Lipinski, Verber and Hann are not efficient enough to encompass long array of compounds. Moreover, these filters do not take into account the specificity of biological target. In this pursuit, we have tried to appraise eight molecular properties for two major classes of biological targets viz membrane proteins and ion channels binding ligands. These molecular properties were utilized to search for the specific attributes that can be identified as an intervening space for dictating the biological activity.

Sensing of Ce(III) using di-naphthoylated oxacalix[4]arene via realistic simulations and experimental studies

Here, we report a fluorescent sensor for the detection of Ce(III) using di-naphthoylated oxacalix[4]arene (DNOC). Formation of the DNOC-Ce(III) complex has been confirmed by 1H NMR and mass spectroscopic observations. A dramatic decrease in the emission intensity of DNOC is observed for Ce(III) with no competitive interference due to other divalent and trivalent ions. The linear range of detection was obtained over a concentration range between 18 nM and 2 μM. Furthermore, density functional theory (DFT)-based quantum mechanical calculations were executed to predict the most probable structure of the host–guest system. As the molecular geometry suggests, the nitro groups of DNOC bent and the naphthoyl groups (oxygen centres of alternate calixarene rings) stabilize the cerium inclusion complex in the 1,3-alternate conformation. Thus, a novel analytical approach has been developed for Ce(III) detection using the oxacalixarene framework in solution. Moreover, the selective behaviour of DNOC also facilitates new opportunities for determining Ce(III) in a wide range of real samples.

Exploration of Mycobacterium tuberculosis structural proteome: An in-silico approach

Pharmacophore approaches are of central contour in drug discovery. However, the dependence of ligand-based pharmacophore model on appropriate training set molecules and typical use of apo-protein or single protein-ligand complex for the construction of structure-based pharmacophore models might skip some vital information. Therefore, multiple-complex based approach was employed for the construction of pharmacophore models of the Mycobacterium structural proteome. Moreover, the strategy of clustering of common pharmacophore hypotheses was made to gain an insight about the pharmacophore-similarity across the protein classes and share of features among the inhibitors. Rationale behind the present work was to present the scenario of virtual screening and guiding principle for designing efficient inhibitor by taking into account the available pharmacophoric space.

Prioritization of natural compounds against mycobacterium tuberculosis 3-dehydroquinate dehydratase: A combined in-silico and in-vitro study

Enormous efforts have been endeavored to develop inhibitors against the potential therapeutic target, mycobacterium tuberculosis 3-dehydroquinate dehydratase (MtbDHQase) to combat resistance. Over a dozen of small molecules have been crystallized to characterize the structural basis of the inhibition. However, the studies accomplished so far, have not incorporated all the essential interactions of these complexes simultaneously, to identify the novel inhibitors. Therefore, an attempt was made to construct the pharmacophore models and identify the essential features that can be employed to prioritize the molecules against this target. Based on validation and expertise, we have identified such complimentary features from the natural compounds that can be used as initial hits. Subsequently, these hits were tested for their inhibitory roles in reducing the mycobacterium tuberculosis (Mtb) culture growth. Moreover, the docking simulations were performed to seek the possible interactions accountable for the activity of these candidates against MtbDHQase.