The new coronavirus SARS-COV-2, which emerged in late 2019 from Wuhan city of China was regarded as causing agent of the COVID-19 pandemic. The primary protease which is also known by various synonymous i.e., main protease, 3-Chymotrypsin-like protease (3CLPRO) has a vital role in the replication of the virus, which can be used as a potential drug target. The current study aimed to identify novel phytochemical therapeutics for 3CLPRO by machine learning-based virtual screening. A total of 4,000 phytochemicals were collected from deep literature surveys and various other sources. The 2D structures of these phytochemicals were retrieved from the PubChem database, and with the use of a molecular operating environment, 2D descriptors were calculated. Machine learning-based virtual screening was performed to predict the active phytochemicals against the SARS-CoV-2 3CLPRO. Random forest achieved 98% accuracy on the train and test set among the different machine learning algorithms. Random forest model was used to screen 4,000 phytochemicals which leads to the identification of 26 inhibitors against the 3CLPRO. These hits were then docked into the active site of 3CLPRO. Based on docking scores and protein-ligand interactions, MD simulations have been performed using 100 ns for the top 5 novel inhibitors, ivermectin, and the APO state of 3CLPRO. The post-dynamic analysis i.e,. Root means square deviation (RMSD), Root mean square fluctuation analysis (RMSF), and MM-GBSA analysis reveal that our newly identified phytochemicals form significant interactions in the binding pocket of 3CLPRO and form stable complexes, indicating that these phytochemicals could be used as potential antagonists for SARS-COV-2.

Pyrazinoic acid-resistant tuberculosis is a severe chronic disorder. First-line drugs specifically target the ribosomal protein subunit-1 (RpsA) and stop trans-translation in the wild-type bacterium, causing bacterial cell death. In mutant bacterial strain, the deletion of ala438 does not let the pyrazinoic acid to bind to the active site of RpsA and ensures that the bacterium survives. Hence, such tuberculosis cases require an immediate and successful regime. The current study was designed to identify inhibitors that could bind to the mutant state of the RpsA protein. Initially, a pharmacophore model was generated based on the recently published most potent inhibitor for the mutant state of RpsA, i.e., zrl 15. The validated pharmacophore model was further used for virtual screening of two chemical libraries, i.e., ZINC and ChemBridge. After applying the Lipinski rule of five (Ro5), a total of 260 and 749 hits from the ChemBridge and ZINC libraries, respectively, were identified using pharmacophore mapping. These hits were then docked into the active site of the mutant state of the RpsA protein, and later, the top 150 compounds from each library were chosen based on the docking score. A total of 21 compounds were shortlisted from each library based on the best protein–ligand interactions. Finally, a total of 05 compounds were subjected to molecular dynamics study to examine the dynamic behavior of each compound in the active site of the mutant state of the RpsA protein. The results revealed that all compounds had good chemical properties such as absorption, distribution, metabolism, excretion, and toxicity (ADMET), and there was no Pan Assay Interference (PAINS) or deviation from Ro5, indicating that these compounds could be useful antagonists for the mutant state of the RpsA protein.

Glycosaminoglycans (GAGs), in particular, heparan sulfate and heparin, are found colocalized with Aβ amyloid. They have been shown to enhance fibril formation, suggesting a possible pathological connection. We have investigated heparin’s assembly of the KLVFFA peptide fragment using molecular dynamics simulation, to gain a molecular-level mechanistic understanding of how GAGs enhance fibril formation. The simulations reveal an exquisite process wherein heparin accelerates peptide assembly by first “gathering” the peptide molecules and then assembling them. Heparin does not act as a mere template but is tightly coupled to the peptides, yielding a composite protofilament structure. The strong intermolecular interactions suggest composite formation to be a general feature of heparin’s interaction with peptides. Heparin’s chain flexibility is found to be essential to its fibril promotion activity, and the need for optimal heparin chain length and concentration has been rationalized. These insights yield design rules (flexibility; chain-length) and protocol guidance (heparin:peptide molar ratio) for developing effective heparin mimetics and other functional GAGs.

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Recent studies show that curcumin, a naturally fluorescent dye, can be used for the noninvasive optical imaging of retinal amyloid-β (Aβ) plaques. We investigated the molecular basis for curcumin’s specificity for hierarchical Aβ structures using molecular dynamics simulations, with a focus on how curcumin is able to detect and discriminate different amyloid morphologies. Curcumin inhibits and breaks up β-sheet formation in Aβ monomers. With disordered Aβ structures, curcumin forms a coarse-grained composite structure. With an ordered fibril, curcumin’s interaction is highly specific, and the curcumin molecules are deposited in the fibril groove. Curcumin tends to self-aggregate, which is finely balanced with its affinity for Aβ. This tendency concentrates curcumin molecules at Aβ deposition sites, potentially increasing the fluorescence signal. This is probably why curcumin is such an effective amyloid imaging agent.