49 research outputs found
Discovery of Novel Acetylcholinesterase Inhibitors as Potential Candidates for the Treatment of Alzheimer’s Disease
Acetylcholinesterase (AChE) catalyzes the hydrolysis of neurotransmitter acetylcholine to acetate and choline in a synaptic cleft. Deficits in cholinergic neurotransmitters are linked closely with the progression of Alzheimer’s disease (AD), which is a neurodegenerative disorder characterized by memory impairment, and a disordered cognitive function. Since the previously approved AChE inhibitors, donepezil (Aricept), galantamine (Reminyl), and rivastigmine (Exelon), have side effects and several studies are being carried out out to develop novel AD drugs, we have applied a three-dimensional quantitative structure−activity relationship (3D QSAR) and structure-based pharmacophore modeling methodologies to identify potential candidate inhibitors against AChE. Herein, 3D QSAR and structure-based pharmacophore models were built from known inhibitors and crystal structures of human AChE in complex with donepezil, galantamine, huperzine A, and huprine W, respectively. The generated models were used as 3D queries to screen new scaffolds from various chemical databases. The hit compounds obtained from the virtual screening were subjected to an assessment of drug-like properties, followed by molecular docking. The final hit compounds were selected based on binding modes and molecular interactions in the active site of the enzyme. Furthermore, molecular dynamics simulations for AChE in complex with the final hits were performed to evaluate that they maintained stable interactions with the active site residues. The binding free energies of the final hits were also calculated using molecular mechanics/Poisson-Boltzmann surface area method. Taken together, we proposed that these hits can be promising candidates for anti-AD drugs
Discovery of Novel Acetylcholinesterase Inhibitors as Potential Candidates for the Treatment of Alzheimer’s Disease
Discovery of Potential Plant-Derived Peptide Deformylase (PDF) Inhibitors for Multidrug-Resistant Bacteria Using Computational Studies
Bacterial peptide deformylase (PDF) is an attractive target for developing novel inhibitors against several types of multidrug-resistant bacteria. The objective of the current study is to retrieve potential phytochemicals as prospective drugs against Staphylococcus aureus peptide deformylase (SaPDF). The current study focuses on applying ligand-based pharmacophore model (PharmL) and receptor-based pharmacophore (PharmR) approaches. Utilizing 20 known active compounds, pharmL was built and validated using Fischer’s randomization, test set method and the decoy set method. PharmR was generated from the knowledge imparted by the Interaction Generation protocol implemented on the Discovery Studio (DS) v4.5 and was validated using the decoy set that was employed for pharmL. The selection of pharmR was performed based upon the selectivity score and further utilizing the Pharmacophore Comparison module available on the DS. Subsequently, the validated pharmacophore models were escalated for Taiwan Indigenous Plants (TIP) database screening and furthermore, a drug-like evaluation was performed. Molecular docking was initiated for the resultant compounds, employing CDOCKER (available on the DS) and GOLD. Eventually, the stability of the final PDF⁻hit complexes was affirmed using molecular dynamics (MD) simulation conducted by GROMACS v5.0.6. The redeemed hits demonstrated a similar binding mode and stable intermolecular interactions with the key residues, as determined by no aberrant behaviour for 30 ns. Taken together, it can be stated that the hits can act as putative scaffolds against SaPDF, with a higher therapeutic value. Furthermore, they can act as fundamental structures for designing new drug candidates
Development of predictive quantitative structure–activity relationship model and its application in the discovery of human leukotriene A4 hydrolase inhibitors
Sulfonanilide Derivatives in Identifying Novel Aromatase Inhibitors by Applying Docking, Virtual Screening, and MD Simulations Studies
Breast cancer is one of the leading causes of death noticed in women across the world. Of late the most successful treatments rendered are the use of aromatase inhibitors (AIs). In the current study, a two-way approach for the identification of novel leads has been adapted. 81 chemical compounds were assessed to understand their potentiality against aromatase along with the four known drugs. Docking was performed employing the CDOCKER protocol available on the Discovery Studio (DS v4.5). Exemestane has displayed a higher dock score among the known drug candidates and is labeled as reference. Out of 81 ligands 14 have exhibited higher dock scores than the reference. In the second approach, these 14 compounds were utilized for the generation of the pharmacophore. The validated four-featured pharmacophore was then allowed to screen Chembridge database and the potential Hits were obtained after subjecting them to Lipinski’s rule of five and the ADMET properties. Subsequently, the acquired 3,050 Hits were escalated to molecular docking utilizing GOLD v5.0. Finally, the obtained Hits were consequently represented to be ideal lead candidates that were escalated to the MD simulations and binding free energy calculations. Additionally, the gene-disease association was performed to delineate the associated disease caused by CYP19A1
Exploration of Virtual Candidates for Human HMG-CoA Reductase Inhibitors Using Pharmacophore Modeling and Molecular Dynamics Simulations
<div><p>3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) is a rate-controlling enzyme in the mevalonate pathway which involved in biosynthesis of cholesterol and other isoprenoids. This enzyme catalyzes the conversion of HMG-CoA to mevalonate and is regarded as a drug target to treat hypercholesterolemia. In this study, ten qualitative pharmacophore models were generated based on chemical features in active inhibitors of HMGR. The generated models were validated using a test set. In a validation process, the best hypothesis was selected based on the statistical parameters and used for virtual screening of chemical databases to find novel lead candidates. The screened compounds were sorted by applying drug-like properties. The compounds that satisfied all drug-like properties were used for molecular docking study to identify their binding conformations at active site of HMGR. The final hit compounds were selected based on docking score and binding orientation. The HMGR structures in complex with the hit compounds were subjected to 10 ns molecular dynamics simulations to refine the binding orientation as well as to check the stability of the hits. After simulation, binding modes including hydrogen bonding patterns and molecular interactions with the active site residues were analyzed. In conclusion, four hit compounds with new structural scaffold were suggested as novel and potent HMGR inhibitors.</p></div
Functional mechanism of C-terminal tail in the enzymatic role of porcine testicular carbonyl reductase: a combined experiment and molecular dynamics simulation study of the C-terminal tail in the enzymatic role of PTCR.
Porcine testicular carbonyl reductase, PTCR which is one of the short chain dehydrogenases/reductases (SDR) superfamily catalyzes the NADPH-dependent reduction of carbonyl compounds including steroids and prostaglandins. Previously we reported C-terminal tail of PTCR was deleted due to a nonsynonymous single nucleotide variation (nsSNV). Here we identified from kinetic studies that the enzymatic properties for 5α-dihydrotestosterone (5α-DHT) were different between wild-type and C-terminal-deleted PTCRs. Compared to wild-type PTCR, C-terminal-deleted PTCR has much higher reduction rate. To investigate structural difference between wild-type and C-terminal-deleted PTCRs upon 5α-DHT binding, we performed molecular dynamics simulations for two complexes. Using trajectories, molecular interactions including hydrogen bonding patterns, distance between 5α-DHT and catalytic Tyr193, and interaction energies are analyzed and compared. During the MD simulation time, the dynamic behavior of C-terminal tail in wild-type PTCR is also examined using essential dynamics analysis. The results of our simulations reveal that the binding conformation of 5α-DHT in C-terminal-deleted PTCR is more favorable for reduction reaction in PTCR, which shows strong agreement with kinetic data. These structural findings provide valuable information to understand substrate specificity of PTCR and further kinetic properties of enzymes belonging to the SDR superfamily
The binding modes of reference and four hit compounds.
<p>All compounds in their representative structures were superimposed (left) and enlarged (right). The dimeric structure of HMGR is shown by cartoon model and each monomer is displayed in cyan and salmon color. All compounds are represented as stick model and in the same colors described in Fig. 6. Only polar hydrogen atoms were shown for clarify.</p
Discovery of Non-Peptidic Compounds against Chagas Disease Applying Pharmacophore Guided Molecular Modelling Approaches
Chagas disease is one of the primary causes of heart diseases accounting to 50,000 lives annually and is listed as the neglected tropical disease. Because the currently available therapies have greater toxic effects with higher resistance, there is a dire need to develop new drugs to combat the disease. In this pursuit, the 3D QSAR ligand-pharmacophore (pharm 1) and receptor-based pharmacophore (pharm 2) search was initiated to retrieve the candidate compounds from universal natural compounds database. The validated models were allowed to map the universal natural compounds database. The obtained lead candidates were subjected to molecular docking against cysteine protease (PDB code: 1ME3) employing -Cdocker available on the discovery studio. Subsequently, two Hits have satisfied the selection criteria and were escalated to molecular dynamics simulation and binding free energy calculations. These Hits have demonstrated higher dock scores, displayed interactions with the key residues portraying an ideal binding mode complemented by mapping to all the features of pharm 1 and pharm 2. Additionally, they have rendered stable root mean square deviation (RMSD) and potential energy profiles illuminating their potentiality as the prospective antichagastic agents. The study further demonstrates the mechanism of inhibition by tetrad residues compromising of Gly23 and Asn70 holding the ligand at each ends and the residues Gly65 and Gly160 clamping the Hits at the center. The notable feature is that the Hits lie in close proximity with the residues Glu66 and Leu67, accommodating within the S1, S2 and S3 subsites. Considering these findings, the study suggests that the Hits may be regarded as effective therapeutics against Chagas disease
The results of the common feature pharmacophore model generation and validation.
<p>The calculation of hit rates using test set compounds was used for validation.</p><p>All the Hypos have Direct hit  = 1111111, Partial hit  = 0000000, and Max. Fit  = 4. Direct or Partial hit means direct or partial match of compound to the pharmocophoric features in each hypothesis. 1, match and 0, no match.</p><p><sup>a</sup> Pharmacophore features: H, hydrophobic; D, hydrogen bond donor; A, hydrogen bond acceptor.</p><p><sup>b</sup> The number of compounds which charges ten-percent of the total number of screened compounds.</p><p><sup>c</sup> Activity scale: Active (IC<sub>50</sub> <10 nM); Moderately active (10< IC<sub>50</sub> <100 nM); Inactive (100 nM < IC<sub>50</sub>).</p