The current global epidemic of the novel coronavirus (SARS-CoV-2) has been labeled a global public health emergency since it is causing substantial morbidity and mortality on daily basis. We need to identify an effective medication against SARS-CoV-2 because of its fast dissemination and re-emergence. This research is being carried out as part of a larger strategy to identify the most promising therapeutic targets using protein-protein interactions analysis. Mpro has been identified as one of the most important therapeutic targets. In this study, we did in-silico investigations to identify the target and further molecular docking, ADME, and toxicity prediction were done to assess the potential phyto-active antiviral compounds from Justicia adhatoda as powerful inhibitors of the Mpro of SARS-COV-2. We also investigated the capacity of these molecules to create stable interactions with the Mpro using 100 ns molecular dynamics simulation. The highest scoring compounds (taraxerol, friedelanol, anisotine, and adhatodine) were also found to exhibit excellent solubility and pharmacodynamic characteristics. We employed MMPBSA simulations to assess the stability of docked molecules in the Mpro binding site, revealing that the above compounds form the most stable complex with the Mpro. Network-based Pharmacology suggested that the selected compounds have various modes of action against SARS-CoV-2 that include immunoreaction enrichment, inflammatory reaction suppression, and more. These findings point to a promising class of drugs that should be investigated further in biochemical and cell-based studies to see their effectiveness against nCOVID-19. Communicated by Ramaswamy H. Sarma

Tuberculosis (TB) continues to pose a global health challenge, exacerbated by the rise of drug-resistant strains. The development of new TB therapies is an arduous and time-consuming process. To expedite the discovery of effective treatments, computational structure-based drug repurposing has emerged as a promising strategy. From this perspective, conditionally essential targets present a valuable opportunity, and the mycobactin biosynthesis pathway stands out as a prime example highlighting the intricate response of Mycobacterium tuberculosis (Mtb) to changes in iron availability. This study focuses on the repurposing and revival of FDA-approved drugs (library) as potential inhibitors of MbtA, a crucial enzyme in mycobactin biosynthesis in Mtb conserved among all species of mycobacteria. The literature suggests this pathway to be associated with drug efflux pumps, which potentially contribute to drug resistance. This makes it a potential target for antitubercular drug discovery. Herein, we utilized cheminformatics and structure-based drug repurposing approaches, viz., molecular docking, dynamics, and PCA analysis, to decode the intermolecular interactions and binding affinity of the FDA-reported molecules against MbtA. Virtual screening revealed ten molecules with significant binding affinities and interactions with MbtA. These drugs, originally designed for different therapeutic indications (four antiviral, three anticancer, one CYP450 inhibitor, one ACE inhibitor, and one leukotriene antagonist), were repurposed as potential MbtA inhibitors. Furthermore, our study explores the binding modes and interactions between these drugs and MbtA, shedding light on the structural basis of their inhibitory potential. Principal component analysis highlighted significant motions in MbtA-bound ligands, emphasizing the stability of the top protein–ligand complexes (PLCs). This computational approach provides a swift and cost-effective method for identifying new MbtA inhibitors, which can subsequently undergo validation through experimental assays. This streamlined process is facilitated by the fact that these compounds are already FDA-approved and have established safety and efficacy profiles. This study has the potential to lay the groundwork for addressing the urgent global health challenge at hand, specifically in the context of combating antimicrobial resistance (AMR) and tuberculosis (TB).

The evaluation of in vitro biological activity of several previously reported quinolinequinones (AQQ1–5) against 60 human cancer cell lines (NCI-60) used by the National Cancer Institute’s Developmental Therapeutics Program (DTP) contributed to our earlier research on possible anticancer and/or antibacterial agents. Of interest, NCI-60 screening revealed that two quinolinequinones (AQQ1 and AQQ2) significantly reduced the proliferation of several cancer genotypes. Following the administration of a single dose and five additional doses, all quinolinequinones demonstrated a significant inhibitory effect on the growth of leukemia and other cancer cell lines. Hence, a series of subsequent in vitro biological assessments were performed to further understand the mechanistic impact of the compounds. In MTT assays, it was found that AQQ1 and AQQ2 exhibited higher efficacy against DU-145 cells (IC₅₀ 4.18 µM and 4.17 µM, respectively) compared to MDA-MB-231 (IC₅₀ 8.27 and 13.33 µM, respectively) and HCT-116 cells (IC₅₀ 5.83 and 9.18 µM, respectively). Additionally, AQQ1 demonstrated greater activity in this context. Further investigations revealed that AQQ1 inhibited DU-145 cell growth and migration dose-dependently. Remarkably, arrest of the DU-145 cell cycle at G0/G1 phase and ROS elevation were observed. Pharmacokinetic (PK) studies revealed that AQQ1 has better PK parameters than AQQ2 with %F of 9.83 in rat. Considering the data obtained with human liver microsomal stability studies, AQQ1 should have a better PK profile in human subjects. In silico studies (molecular dynamics) with three kinases (CDK2, CDK4, and MAPK) leading to cell cycle arrest at G₀/G₁ identified MAPK as a probable target for AQQ1. Taken together, our results showed that AQQ1 could be a potential chemotherapeutic lead molecule for prostate cancer.

Tuberculosis (TB) continues to pose a global health challenge, exacerbated by the rise of drug-resistant strains. The development of new TB therapies is an arduous and time-consuming process. To expedite the discovery of effective treatments, computational structure-based drug re-purposing has emerged as a promising strategy. From this perspective, conditionally essential targets present a valuable opportunity, and the mycobactin biosynthesis pathway stands out as a prime example highlighting the intricate response of Mycobacterium tuberculosis (Mtb) to changes in iron availability. This study focuses on the re-purposing and revival of FDA-approved drugs (library) as potential inhibitors of MbtA, a crucial enzyme in mycobactin biosynthesis in Mtb conserved among all species of mycobacteria. Literature suggests this pathway to be associated with drug efflux pumps, which potentially contribute to drug resistance. This makes it a potential target for antitubercular drug discovery. Herein we utilized cheminformatics and structure-based drug repurposing approaches, viz., molecular docking, dynamics, and PCA analysis, to decode the intermolecular interactions and binding affinity of the FDA-reported molecules against MbtA. The virtual screening revealed ten molecules with significant binding affinities and interactions with MbtA. These drugs, originally designed for different therapeutic indications (4: antiviral, 3: anticancer, 1: CYP450 inhibitor, 1: ACE inhibitor, and 1: leukotriene antagonist), are repurposed as potential MbtA inhibitors. Furthermore, our study explores the binding modes and interactions between these drugs and MbtA, shedding light on the structural basis of their inhibitory potential. Principal component analysis highlighted significant motions in MbtA-bound ligands, emphasizing the stability of the top Protein-Ligand Complexes (PLCs). This computational approach provides a swift and cost-effective method for identifying new MbtA inhibitors, which can subsequently undergo validation through experimental assays. This streamlined process is facilitated by the fact that these compounds are already FDA-approved and have established safety and efficacy profiles. This study has the potential to lay the groundwork for addressing the urgent global health challenge at hand, specifically in the context of combating Antimicrobial Resistance (AMR) and Tuberculosis (TB).

Cytochrome P450 1B1 (CYP1B1) is an important anticancer target due to its overexpression in tumors and role in carcinogen metabolism. In this work, we attempted to build a first-generation QSAR model for 63 synthesized inhibitors using Quantum Chemical Descriptors (QCDs) and Thermodynamic Descriptors (TCDs) derived from xTB calculations. After descriptor reduction was carried out by multicollinearity analysis, recursive feature elimination (RFE), different regression and classification models were built with eight selected descriptors. Validation included k-fold cross-validation, leave-one-out CV, bootstrapping, Y-randomization, and applicability domain analysis. Among the different classifiers, Support Vector Classifier (rbf kernel) model showed promising internal validation (accuracy ~0.72, ROC-AUC ~0.79); however, stringent validations revealed bias toward predicting actives (recall ~1.0, ROC-AUC collapse). Y-randomization confirmed the non-random nature of the structure–activity relationship, while the Williams plot indicated most compounds were within the applicability domain. Although preliminary, this work demonstrates the feasibility of quantum descriptor-based QSAR modeling of CYP1B1 inhibitors and outlines pathways for improving model balance and predictive power