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.

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.

Dihydrofolate reductase (DHFR) is an essential cellular enzyme and thereby catalyzes the reduction of dihydrofolate to tetrahydrofolate (THF). In cancer medication, inhibition of human DHFR (hDHFR) remains a promising strategy, as it depletes THF and slows DNA synthesis and cell proliferation. In the current study, ligand-based pharmacophore modeling identified and evaluated the critical chemical features of hDHFR inhibitors. A pharmacophore model (Hypo1) was generated from known inhibitors of DHFR with a correlation coefficient (0.94), root mean square (RMS) deviation (0.99), and total cost value (125.28). Hypo1 was comprised of four chemical features, including two hydrogen bond donors (HDB), one hydrogen bond acceptor (HBA), and one hydrophobic (HYP). Hypo1 was validated using Fischer’s randomization, test set, and decoy set validations, employed as a 3D query in a virtual screening at Maybridge, Chembridge, Asinex, National Cancer Institute (NCI), and Zinc databases. Hypo1-retrieved compounds were filtered by an absorption, distribution, metabolism, excretion, and toxicity (ADMET) assessment test and Lipinski’s rule of five, where the drug-like hit compounds were identified. The hit compounds were docked in the active site of hDHFR and compounds with Goldfitness score was greater than 44.67 (docking score for the reference compound), clustering analysis, and hydrogen bond interactions were identified. Furthermore, molecular dynamics (MD) simulation identified three compounds as the best inhibitors of hDHFR with the lowest root mean square deviation (1.2 Å to 1.8 Å), hydrogen bond interactions with hDHFR, and low binding free energy (−127 kJ/mol to −178 kJ/mol). Finally, the toxicity prediction by computer (TOPKAT) affirmed the safety of the novel inhibitors of hDHFR in human body. Overall, we recommend novel hit compounds of hDHFR for cancer and rheumatoid arthritis chemotherapeutics.

Mechanistically, neurotoxic insults provoke Ca²⁺-mediated calpain activation, which cleaves the cytoplasmic region of membrane-embedded p35 and produces its truncated form p25. Upon physical interaction, cyclin-dependent kinase 5 (Cdk5) and p25 forms hyperactivated Cdk5/p25 complex and causes severe neuropathological aberrations including hyperphosphorylated tau-mediated neurofibrillary tangles formation, Alzheimer’s symptoms, and neuronal death. Therefore, the inhibition of Cdk5/p25 complex may relieve p-tau-mediated Alzheimer’s pathology. Herein, computational simulations have identified pyrrolidine-2,3-dione derivatives as novel inhibitors of Cdk5/p25 complex. A ligand-based pharmacophore was designed and employed as 3D query to retrieve drug-like molecules from chemical databases. By molecular docking, drug-like molecules obtaining dock score > 67.67 (Goldcore of the reference compound) were identified. Molecular dynamics simulation and binding free energy calculation retrieved four pyrrolidine-2,3-dione derivatives as novel candidate inhibitors of Cdk5/p25. The root means square deviation of Cdk5/p25 in complex with candidate inhibitors obtained an average value of ~2.15 Å during the 30 ns simulation period. Molecular interactions analysis suggested that each inhibitor occupied the ATP-binding site of Cdk5/p25 and formed stable interactions. Finally, the binding free energy estimation suggested that each inhibitor had lowest binding energy than the reference compound (−113.10 kJ/mol) to recapitulate their strong binding with Cdk5/p25. Overall, these inhibitors could mitigate tau-mediated Alzheimer’s phenotype.

Aromatase inhibitors with an IC50 value ranging from 1.4 to 49.7uM are known to act as antiepileptic drugs besides being potential breast cancer inhibitors. The aim of the present study is to identify novel antiepileptic aromatase inhibitors with higher activity exploiting the ligand-based pharmacophore approach utilizing the experimentally known inhibitors. The resultant Hypo1 consists of four features and was further validated by using three different strategies. Hypo1 was allowed to screen different databases to identify lead molecules and were further subjected to Lipinski' Rule of Five and ADMET to establish their drug-like properties. Consequently, the obtained 68-screened molecules were subjected to molecular docking by GOLD. Furthermore, the compounds with the highest dock scores were assessed for molecular interaction. Later, the MD simulation was applied to evaluate the protein backbone stabilities and binding energies adapting GROMACS 5.0.6 and MM/PBSA which was followed by the density functional theory (DFT), to analyze their orbital energies and further the energy gap between them. Eventually, the number of Hit molecules was culled to three projecting Hit1, Hit2, and Hit3 as the potential lead compounds based on their highest dock scores, hydrogen bond interaction, lowest energy gap and the least binding energies and stable MD results.

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.