Recursive dynamics of GspE through machine learning enabled identification of inhibitors.

Type II secretion System has been increasingly recognized as a key driver of virulence in many pathogenic bacteria including Achromobacter xylosoxidans. ATPase GspE is the powerhouse of the T2SS. It powers the entire secretion process by binding with ATP and hydrolyzing it. Therefore, targeting it was thought to have a profound effect on the normal functioning of the whole T2SS. A. xylosoxidans is a Gram-negative bacterium that poses a rising concern to immunocompromised people. It is responsible for many opportunistic infections mostly in people with cystic fibrosis. Due to its intrinsic and acquired resistance mechanisms, it is challenging to treat. In this current study, an extensive machine learning-enabled computational investigation was carried out. Drug libraries were screened using machine learning random forest algorithm trained on non-redundant dataset of 8722 antibacterial compounds with reported IC50 values. Active compounds were then further subjected to molecular docking. To unravel the dynamics and better understand the stability of complexes, the top complexes were subjected to MD Simulations followed by various post-simulation analyses including Trajectory analysis, Atom Contacts, SASA, Hydrogen Bond, RDF, binding free energy calculations, PCA, and AFD analysis. Findings from the study unanimously unveiled Asinex-BAS00263070-28551 as the best inhibitor as it instigated the recursive dynamics of the target by making key hydrogen bond interactions with Walker A motif, suggesting it could serve as the promising drug candidate against GspE. Further experimental in-vivo and in-vitro validation is still required to authenticate the therapeutic effects of these drugs.

Discovery of novel inhibitor via molecular dynamics simulations against D-alanyl-D-alanine carboxypeptidase of Enterobacter cloacae.

Antibiotics resistance by bacterial pathogens is a major concern to public health worldwide resulting in high health care costs and rising mortality. Subtractive proteomics prioritized D-alanyl-D-alanine carboxypeptidas (DacB) enzyme from Enterobacter cloacae ATCC 13047 as a potential candidate for drugs designing to block pathogen cell wall biosynthesis. Virtual screening of an antibacterial library against the target unraveled a hit compound (2-[(1-methylsulfonylpiperidin-3-yl)methyl]-6-(1H-pyrazol-4-yl) pyrazine) showing high affinity and stability with the target. The N-methyl-N-propyl-methanesulfonamide of the compound is seen as a closed affinity towards domain involving strong hydrogen bonds with Ser41, Lys44, Ser285, and Asn287. The 4-methyl-1H-pyrazole is posed towards the open cavity of domain I and II and formed hydrophobic and hydrophilic contacts. The system is highly stable with average carbon-alpha deviations of 1.69 Å over trajectories of 400-ns. Three vital residues projected: Arg437, Arg438 and Leu400 from enzyme pocket via Radial distribution function (RDF) assay, which actively engaged the inhibitor. Further confirmation is done by estimating binding free energies, which confirms the very low delta energy of -7.24 kcal/mol in Generalized Born (GB) method and -7.4363 kcal/mol in Poisson-Boltzmann (PB) method. WaterSwap calculations were performed that revealed the energies highly converged, an agreement on good system stability. Lastly, three DacB mutants were created to investigate the role of functional active residues and a decline in binding affinity of the residues was noticed. These computational results provide a gateway for experimentalists to further confirm their efficacy both in-vitro and in-vivo.Communicated by Ramaswamy H. Sarma.

Three-state dynamics of zinc(II) complexes yielding significant antidiabetic targets.

Protein Tyrosine Phosphatase 1B (PTP1B), being negative regulator of insulin signaling pathways is considered as potential medicinal target. Selective and targeted inhibitors for PTP1B can impact the therapeutic options available to cure chronic illness such as diabetes. Significant research evidence including computational studies on the role of Zn2+ in binding and inhibiting the catalytic pocket have been reported along with experimental exploration of zinc(II) complexes as potent inhibitors of the enzyme. The current study has employed advanced computational methods to explore the binding and conformational orientation of zinc(II) complexes in the active site of apoenzyme, phosphoenzyme, and TSA 2 of PTP1B. Metal ion modeling was performed for zinc metal center (Zn-OOOO) utilizing a Python based Metal Center Parameter Builder (MCPB.py). The findings of the study suggest that zinc(II) complex binds to structurally and functionally important residues in open and closed conformation as well as in the phosphorylated state of the enzyme. It was observed that when the catalytic cysteine is phosphorylated in a closed conformation, the zinc(II) complex forms significant interactions with PHE182, VAL184, GLY183, and PRO180 while pushing away Q-loop GLN262 which is crucial for the hydrolysis of phosphoenzyme. Subsequently, the reported inhibitor has also demonstrated its potential to function as allosteric modulator of the enzyme occupying catalytic WPD loop residues. The study uncovers putative binding sites of zinc-containing drugs and gives insight into the size and design of such compounds which keeps them accessible and anchored in the vicinity of active site residues. Reported inhibitor offers enhanced selectivity and inhibition in all three states of the enzyme in contrast to zinc ions which can only impede enzyme in the phosphorylated state. In addition to this, investigation of ASP265→GLU265 mutation reveals the role of GLU265 in affecting the flexibility of WPD loop residues highlighting it as loss-of-function mutation. Our results hints towards a metallodrug approach that builds on the research evidence of inhibition effects of Zn2+ in the binding pocket of PTP1B. The findings presented are noteworthy, not just due to their significant relevance for clinical application, but also for the design and synthesis of novel zinc(II) complexes.

Dynamics of water-mediated interaction effects on the stability and transmission of Omicron.

SARS-Cov-2 Omicron variant and its highly transmissible sublineages amidst news of emerging hybrid variants strengthen the evidence of its ability to rapidly spread and evolve giving rise to unprecedented future waves. Owing to the presence of isolated RBD, monomeric and trimeric Cryo-EM structures of spike protein in complex with ACE2 receptor, comparative analysis of Alpha, Beta, Gamma, Delta, and Omicron assist in a rational assessment of their probability to evolve as new or hybrid variants in future. This study proposes the role of hydration forces in mediating Omicron function and dynamics based on a stronger interplay between protein and solvent with each Covid wave. Mutations of multiple hydrophobic residues into hydrophilic residues underwent concerted interactions with water leading to variations in charge distribution in Delta and Omicron during molecular dynamics simulations. Moreover, comparative analysis of interacting moieties characterized a large number of mutations lying at RBD into constrained, homologous and low-affinity groups referred to as mutational drivers inferring that the probability of future mutations relies on their function. Furthermore, the computational findings reveal a significant difference in angular distances among variants of concern due 3 amino acid insertion (EPE) in Omicron variant that not only facilitates tight domain organization but also seems requisite for characterization of mutational processes. The outcome of this work signifies the possible relation between hydration forces, their impact on conformation and binding affinities, and viral fitness that will significantly aid in understanding dynamics of drug targets for Covid-19 countermeasures. The emerging scenario is that hydration forces and hydrophobic interactions are crucial variables to probe in mutational analysis to explore conformational landscape of macromolecules and reveal the molecular origins of protein behaviors.

Non-ß Lactam Inhibitors of the Serine ß-Lactamase blaCTX-M15 in Drug-Resistant Salmonella typhi.

Antibiotic resistance by bacterial pathogens against widely used ß-lactam drugs is a major concern to public health worldwide, resulting in high healthcare cost. The present study aimed to extend previous research by investigating the potential activity of reported compounds against the S. typhi ß-lactamase protein. 74 compounds from computational screening reported in our previous study against ß-lactamase CMY-10 were subjected to docking studies against blaCTX-M15. Site-Identification by Ligand Competitive Saturation (SILCS)-Monte Carlo (SILCS-MC) was applied to the top two ligands selected from molecular docking studies to predict and refine their conformations for binding conformations against blaCTX-M15. The SILCS-MC method predicted affinities of -8.6 and -10.7 kcal/mol for Top1 and Top2, respectively, indicating low micromolar binding to the blaCTX-M15 active site. MD simulations initiated from SILCS-MC docked orientations were carried out to better characterize the dynamics and stability of the complexes. Important interactions anchoring the ligand within the active site include pi-pi stacked, amide-pi, and pi-alkyl interactions. Simulations of the Top2-blaCTX-M15 complex exhibited stability associated with a wide range of hydrogen-bond and aromatic interactions between the protein and the ligand. Experimental ß-lactamase (BL) activity assays showed that Top1 has 0.1 u/mg BL activity, and Top2 has a BL activity of 0.038 u/mg with a minimum inhibitory concentration of 1 mg/mL. The inhibitors proposed in this study are non-ß-lactam-based ß-lactamase inhibitors that exhibit the potential to be used in combination with ß-lactam antibiotics against multidrug-resistant clinical isolates. Thus, Top1 and Top2 represent lead compounds that increase the efficacy of ß-lactam antibiotics with a low dose concentration.

Immunoinformatic and reverse vaccinology-based designing of potent multi-epitope vaccine against Marburgvirus targeting the glycoprotein.

Marburg virus (MARV) has been a major concern since its first outbreak in 1967. Although the deadly BSL-4 pathogen has been reported in few individuals with sporadic outbreaks following 1967, its rarity commensurate the degree of disease severity. The virus has been known to cause extreme hemorrhagic fever presenting flu-like symptoms (as implicated in COVID-19) with a 90% case fatality rate (CFR). After a number of plausible evidences, it has been observed that the virus usually originates from African fruit bat, Rousettus aegyptiacus, who themselves do not indicate any signs of illness. Thus, efforts have been made in the recent years for a universal treatment of the infection, but till date, no such vaccine or therapeutics could circumvent the viral pathogenicity. In an attempt to formulate a vaccine design computationally, we have explored the entire proteome of the virus and found a strong correlation of its glycoprotein (GP) in receptor binding and subsequent role in infection progression. The present study, explores the MARV glycoprotein GP1 and GP2 domains for quality epitopes to elicit an extended immune response design potential vaccine construct using appropriate linkers and adjuvants. Finally, the chimeric vaccine wass evaluated for its binding affinity towards the receptors via molecular docking and molecular dynamics simulation studies. The rare, yet deadly zoonotic infection with mild outbreaks in recent years has flustered an alarming future with various challenges in terms of viral diseases. Thus, our study has aimed to provide novel insights to design potential vaccines by using the predictive framework.

Discrete Dynamics of Warhead Modulation on Covalent Inhibition of Oxyr: A QM/MM Study.

The bacterial transcriptional factor OxyR, a peroxide sensor conserved in bacterial virulence pathways, has the capability to exhibit exceptional reactivity toward hydrogen peroxide (H2O2). H2O2 is essential for oxidizing cysteine thiolates to maintain cellular redox homeostasis and is dispensable for bacterial growth that can potentially mitigate drug resistance, thus underlining OxyR as a valuable target. We employ quantum mechanics/molecular mechanics (QM/MM) umbrella sampling (US) simulations at the DFTB3/MM level of theory and propose a reaction mechanism with four potential covalent inhibitors. The potential of mean force reveals the direct role of intrinsic reactivity of inhibitors, for instance, benzothiophenes and modified experimental inhibitors with methyl oxo-enoate warhead-activated carbonyl samples in the first step of reaction, which shed light on the significance of proton transfer indispensable for full inhibition, whereas the nitrile inhibitor undergoes a stepwise mechanism with a small proton-transfer energy barrier and lower imaginary frequencies that materialize instantly after nucleophilic attack. To unveil the molecular determinants of respective binding affinities, transition states along the reaction path are optimized and characterized with B3LYP 6-31+G(d,p). Furthermore, the post-simulation analysis indicates the catalytic triad (His130/Cys199/Thr129), thermodynamically favored for inhibition, which restricts water molecules from acting as the potential source of protonation/deprotonation. This study thus serves as a preamble to add variation in the proposed structures and unveils the impact of functional groups lying in warheads that modulate the kinetics of proton transfer, which will certainly aid to design more selective and efficient irreversible inhibitors of OxyR.

Deciphering the relational dynamics of AF-2 domain of PAN PPAR through drug repurposing and comparative simulations.

Peroxisome proliferator-activated receptors (PPARs) are nuclear receptors, and their activation has been proven to treat mild liver fibrosis, reduce steatosis, inflammation, and the extrahepatic effects of chronic liver disease. Considering the significance of the PPARs, it is targeted for the treatment of Non-Alcoholic Steatohepatitis (NASH), for which currently there is no FDA-approved drug. Lanifibranor is a next-generation highly potential indole sulfonamide derivative that is presently in clinical trial phase III as an anti-NASH drug which fully activates PPARα and PPARδ and partially activates PPARγ. In the current study, a comprehensive computational investigation including 3D-QSAR pharmacophore modeling, MD simulations and binding free energy calculations is performed to get insights into the activation mechanism of the Lanifibranor. Furthermore, FDA-approved drugs were explored for repurposing through virtual screening against each PPAR pharmacophore to identify potential drug candidates. Forasartan, Raltitrexed, and Lifitegrast stood out as potential agonists for PPARα (full agonist), PPARγ (partial agonist), and PPARδ (full agonist), respectively. The findings of the study highlighted a lack of hydrogen bond acceptor feature in Raltitrexed and Lanifibranor which is responsible for partial activation of PPARγ that plays a critical role in preventing lipid accumulation. In addition to this, the significant role of AF2 domain in full and partial activation of PPARs through electrostatic interactions was also revealed, that facilitates the anchoring of ligand within the binding cavity. Moreover, common chemical scaffolds (methyl sulfonyl benzene, butyric acid, and chlorobenzene) identified using Fingerprinting technique were presented in this study which hold the potential to aid in the design and development of target specific novel Pan PPAR medications in future.

Quantum Dynamics and Bi Metal Force Field Parameterization Yielding Significant Antileishmanial Targets.

Amid emerging drug resistance to metal inhibitors, high toxicity, and onerous drug delivery procedures, the computational design of alternate formulations encompassing functional metal-containing compounds greatly relies on large-scale atomistic simulations. Simulations particularly with Au(I), Ag, Bi(V), and Sb(V) pose a major challenge to elucidate their molecular mechanism due to the absence of force field parameters. This study thus quantum mechanically derives force field parameters of Bi(V) as an extension of the previous experimental study conducted on heteroleptic triorganobismuth(V) biscarboxylates of type [BiR3(O2CR')2]. We have modeled two organo-bismuth(V) carboxylates, which are optimized and parameterized along with the famous pentavalent antimonial drug: meglumine antimoniate using quantum mechanics original Seminarian methods with the SBKJC effective core potential (ECP) basis set. Furthermore, molecular dynamics (MD) simulations of bismuth- and antimony-containing compounds in complex with two enzymes, trypanothione synthetase-amidase (TSA) and trypanothione reductase, are performed to target the (T(SH)2) pathway at multiple points. MD simulations provide novel insights into the binding mechanism of TSA and highlight the role of a single residue Arg569 in modulating the ligand dynamics. Moreover, the presence of an ortho group in a ligand is emphasized to facilitate interactions between Arg569 and the active site residue Arg313 for higher inhibitory activity of TSA. This preliminary generation of parameters specific to bismuth validated by simulations in replica will become a preamble of future computational and experimental research work to open avenues for newer and suitable drug targets.

Role of hinge motion and ATP dynamics in factors for inversion stimulation FIS protein deduced while targeting drug resistant Orientia tsutsugamushi.

Orientia tsutsugamushi, the causative agent of scrub typhus has been found resistant to various classes of antibiotics such as penicillins, gentamycin and cephalosporins. Review of current literature suggests that the prevalence of scrub typhus has increased globally. Therefore, the current study has aimed at exploring the genome of O. tsutsugamushi to identify potential drug target proteins that can be used for developing novel antibiotics against the pathogen. Subtractive proteomics approach has revealed FIS as a potential drug target protein involved in two component system (TCS), a signaling pathway crucial for bacteria to survive and adjust in changing environmental conditions. Molecular docking studies have revealed compound-356 (CHEMBRIDGE-10040641-3710.356) as a potential inhibitor in both chains A and B of the FIS protein. Simulation results suggest that the docked complex has remained stable and compact throughout the 200 ns run. Significant conformational changes including the hinge motion was observed in the DNA binding domain. Furthermore, the presence of salt bridge between GLU910 and ARG417, rearrangement of interaction residues and displacement of ATP in the central AAA + domain upon binding to the inhibitor were also observed playing a role in stabilizing the protein structure.

Roxadustat and its failure: A comparative dynamic study.

Roxadustat, a small-molecule inhibitor of hypoxia-inducible factor prolyl hydroxylase domain 2 (HIF-PHD2) has been recently overruled by the American Food and Drug Administration (FDA) in Phase 3 clinical trials. This study provides insights into the dynamics of Roxadustat with PHD2 and proposes two FDA-approved drugs; Pemetrexed and Valrubicin to treat chronic kidney disease (CKD). Role of chemical scaffolds such as synthetic pyrimidine-based antifolate is found critical for PHD2 inhibitory activity, which is concurrent with the experimental findings for stimulating Endogenous erythropoietin (EPO) gene expression. Furthermore, Fe+2 and Mn+2 in solution are essential for imparting structural stability to the screened carboxylic and non-carboxylic acid drugs. Comparative analysis of FDA-approved drugs namely, Roxadustat, two-hit carboxylic, and non-carboxylic-acid type compounds (Pemetrexed and Valrubicin), as well as the control ligands (KU1 and 4JR), unveil structural dynamics of Roxadustat and its failure. However, the proposed FDA compounds, Pemetrexed and Valrubicin, used to treat mesothelioma, non-small cell lung cancer, and bladder cancer should be subjected to in vitro analysis for renal anemia.

In Silico and In Vitro Study of Janus Kinases Inhibitors from Naphthoquinones.

Janus kinases (JAKs) are involved in numerous cellular signaling processes related to immune cell functions. JAK2 and JAK3 are associated with the pathogenesis of leukemia and common lymphoid-derived illnesses. JAK2/3 inhibitors could reduce the risk of various diseases by targeting this pathway. Herein, the naphthoquinones were experimentally and theoretically investigated to identify novel JAK2/3 inhibitors. Napabucasin and 2'-methyl napabucasin exhibited potent cell growth inhibition in TF1 (IC50 = 9.57 and 18.10 µM) and HEL (IC50 = 3.31 and 6.65 µM) erythroleukemia cell lines, and they significantly inhibited JAK2/3 kinase activity (in a nanomolar range) better than the known JAK inhibitor, tofacitinib. Flow cytometric analysis revealed that these two compounds induced apoptosis in TF1 cells in a time and dose-dependent manner. From the molecular dynamics study, both compounds formed hydrogen bonds with Y931 and L932 residues and hydrophobically contacted with the conserved hinge region, G loop, and catalytic loop of the JAK2. Our obtained results suggested that napabucasin and its methylated analog were potential candidates for further development of novel anticancer drug targeting JAKs.

New lead compounds identification against KRas mediated cancers through pharmacophore-based virtual screening and in vitro assays.

Cancer remains the leading cause of mortality and morbidity in the world, with 19.3 million new diagnoses and 10.1 million deaths in 2020. Cancer is caused due to mutations in proto-oncogenes and tumor-suppressor genes. Genetic analyses found that Ras (Rat sarcoma) is one of the most deregulated oncogenes in human cancers. The Ras oncogene family members including NRas (Neuroblastoma ras viral oncogene homolog), HRas (Harvey rat sarcoma) and KRas are involved in different types of human cancers. The mutant KRas is considered as the most frequent oncogene implicated in the development of lung, pancreatic and colon cancers. However, there is no efficient clinical drug even though it has been identified as an oncogene for 30 years. Therefore there is an emerging need to develop potent, new anticancer drugs. In this study, computer-aided drug designing approaches as well as experimental methods were employed to find new and potential anti-cancer drugs. The pharmacophore model was developed from an already known FDA approved anti-cancer drug Bortezomib using the software MOE. The validated pharmacophore model was then used to screen the in-house and commercially available databases. The pharmacophore-based virtual screening resulted in 26 and 86 hits from in-house and commercial databases respectively. Finally, 6/13 (in-house database) and 24/64 hits (commercial databases) were selected with different scaffolds having good interactions with the significant active residues of KRasG12D protein that were predicted as potent lead compounds. Finally, the results of pharmacophore-based virtual screening were further validated by molecular dynamics simulation analysis. The 6 hits of the in-house database were further evaluated experimentally. The experimental results showed that these compounds have good anti-cancer activity which validate the protocol of our in silico studies. KRasG12D protein is a very important anti-cancer target and potent inhibitors for this target are still not available, so small lead compound inhibitors were identified to inhibit the activity of this protein by blocking the GTP-binding pocket.Communicated by Ramaswamy H. Sarma.

Machine Learning-based Virtual Screening for STAT3 Anticancer Drug Target.

BACKGROUND: Signal transducers and activators of the transcription (STAT) family is composed of seven structurally similar and highly conserved members, including STAT1, STAT2, STAT3, STAT4, STAT5a, STAT5b, and STAT6. The STAT3 signaling cascade is activated by upstream kinase signals and undergoes phosphorylation, homo-dimerization, nuclear translocation, and DNA binding, resulting in the expression of target genes involved in tumor cell proliferation, metastasis, angiogenesis, and immune editing. STAT3 hyperactivation has been documented in a number of tumors, including head and neck, breast, lung, liver, kidney, prostate, pancreas cancer, multiple myeloma, and acute myeloid leukemia. Drug discovery is a timeconsuming and costly process; it may take ten to fifteen years to bring a single drug to the market. Machine learning algorithms are very fast and effective and commonly used in the field, such as drug discovery. These algorithms are ideal for the virtual screening of large compound libraries to classify molecules as active or inactive. OBJECTIVE: The present work aims to perform machine learning-based virtual screening for the STAT3 drug target. METHODS: Machine learning models, such as k-nearest neighbor, support vector machine, Gaussian naïve Bayes, and random forest for classifying the active and inactive inhibitors against a STAT3 drug target, were developed. Ten-fold cross-validation was used for model validation. Then the test dataset prepared from the zinc database was screened using the random forest model. A total of 20 compounds with 88% accuracy was predicted as active against STAT3. Furthermore, these twenty compounds were docked into the active site of STAT3. The two complexes with good docking scores as well as the reference compound were subjected to MD simulation. A total of 100ns MD simulation was performed. RESULTS: Compared to all other models, the random forest model revealed better results. Compared to the standard reference compound, the top two hits revealed greater stability and compactness. CONCLUSION: In conclusion, our predicted hits have the ability to inhibit STAT3 overexpression to combat STAT3-associated diseases.

Discovery of novel Glutaminase allosteric inhibitors through drug repurposing and comparative MMGB/PBSA and molecular dynamics simulation.

GLS1 enzymes (Glutaminase C (GAC) and kidney-type Glutaminase (KGA)) are gaining prominence as a target for tumor treatment including lung, breast, kidney, prostate, and colorectal. To date, several medicinal chemistry studies are being conducted to develop new and effective inhibitors against GLS1 enzymes. Telaglenastat, a drug that targets the allosteric site of GLS1, has undergone clinical trials for the first time for the therapy of solid tumors and hematological malignancies. A comprehensive computational investigation is performed to get insights into the inhibition mechanism of the Telaglenastat. Some novel inhibitors are also proposed against GLS1 enzymes using the drug repurposing approach using 2D-fingerprinting virtual screening method against 2.4 million compounds, application of pharmacokinetics, Molecular Docking, and Molecular Dynamic (MD) Simulations. A TIP3P water box of 10 Å was defined to solvate both enzymes to improve MD simulation reliability. The dynamics results were validated further by the MMGB/PBSA binding free energy method, RDF, and AFD analysis. Results of these computational analysis revealed a stable binding affinity of Telaglenastat, as well as an FDA approved drug Astemizole (IC50 ∼ 0.9 nM) and a novel para position oriented methoxy group containing Chembridge compound (Chem-64284604) that provides an effective inhibitory action against GAC and KGA.

Senna makki and other active phytochemicals: Myths and realities behind covid19 therapeutic interventions.

This study aims to investigate the binding potential of chemical compounds of Senna in comparison with the experimentally tested active phytochemicals against SARS-CoV-2 protein targets to assist in prevention of infection by exploring multiple treatment options. The entire set of phytochemicals from both the groups were subjected to advanced computational analysis that explored functional molecular descriptors from a set of known medicinal-based active therapeutics followed by MD simulations on multiple SARS-CoV-2 target proteins. Our findings manifest the importance of hydrophobic substituents in chemical structures of potential inhibitors through cross-validation with the FDA-approved anti-3CLpro drugs. Noteworthy improvement in end-point binding free energies and pharmacokinetic profiles of the proposed compounds was perceived in comparison to the control drug, vizimpro. Moreover, the identification of common drug targets namely; AKT1, PTGS1, TNF, and DPP4 between proposed active phytochemicals and Covid19 using network pharmacological analysis further substantiate the importance of medicinal scaffolds. The structural dynamics and binding affinities of phytochemical compounds xanthoangelol_E, hesperetin, and beta-sitosterol reported as highly potential against 3CLpro in cell-based and cell-free assays are consistent with the computational analysis. Whereas, the secondary metabolites such as sennosides A, B, C, D present in higher amount in Senna exhibited weak binding affinity and instability against the spike protein, helicase nsp13, RdRp nsp12, and 3CLpro. In conclusion, the results contravene fallacious efficacy claims of Senna tea interventions circulating on electronic/social media as Covid19 cure; thus emphasizing the importance of well-examined standardized data of the natural products in hand; thereby preventing unnecessary deaths under pandemic hit situations worldwide.

Structural characterization and antileishmanial activity of newly synthesized organo-bismuth(V) carboxylates: experimental and molecular docking studies.

In a quest to discover new formulations for the treatment of various parasitic diseases, a series of heteroleptic triorganobismuth(V) biscarboxylates of type [BiR3(O2CR')2], where R=C6H5 for 1-4 and p-CH3C6H4 for 5-8, were synthesized, characterized and evaluated for their biological potential against L. tropica. All the synthesized complexes were fully characterized by elemental analysis, FT-IR, multinuclear (1H and 13C) NMR spectroscopy and X-ray crystallography. The crystal structures for [BiPh3(O2CC6H4(o-Br))2] (1), [BiPh3(O2CC2H2C6H4)2] (2), [BiPh3(O2CC6H4(m-NO2))2] (3) and [BiPh3(O2CC6H4(2-OH,3-CH3))2] (4) were determined and found to have a distorted pentagonal bipyramidal molecular geometry with seven coordinated bismuth center for 1-3 and for 4 distorted octahedral geometry, respectively. All the synthesized complexes demonstrated a moderate to significant activity against leishmania parasites. A broad analytical approach was followed to testify the stability for (1-8) in solid state as well as in solution and in leishmanial culture M199, ensuring them to be stable enough to exert a significant antileishmanial effect with promising results. Cytotoxicity profile suggests that tris(tolyl) derivatives show lower toxicity against isolated lymphocytes with higher antileishmanial potential. Molecular docking studies were carried out to reveal the binding modes for (1-8) targeting the active site of trypanothione reductase (TR) (PDB ID: 4APN) and Trypanothione Synthetase-Amidase structure (PDB ID 2vob).

Structure Based in Silico Screening Revealed a Potent Acinetobacter Baumannii Ftsz Inhibitor From Asinex Antibacterial Library.

The superbug Acinetobacter baumannii is an increasingly prevalent pathogen of the intensive care units where its treatment is challenging. The identification of newer drug targets and the development of propitious therapeutics against this pathogen is of utmost importance. A drug target, cell division enzyme (FtsZ), involved in A. baumannii cytokinesis is a promising avenue for antibacterial therapy. Structure based virtual screening illustrated a lead-like molecule from Asinex antibacterial library to have the best binding affinity for the FtsZ active pocket. Computational pharmacokinetics predicted the compound to have the safest pharmacokinetics profile, thus maximizing the chances of the molecule reaching the market with enhanced efficacy and lesser toxicity. Molecular dynamics simulations in an aqueous environment revealed the flexibility of protein loop regions, and upward extension followed by the backward movement of the inhibitor N, N-dimethylpyridazin-3-amine ring on its axis. The active pocket residue Thr310 demonstrated to play significant role in inhibitor binding. The binding free energy predicted by MM/GBSA and MM/PBSA reflected system stability with a total value of -62.15 kcal/mol and -10.60 kcal/mol, respectively. The absolute binding free energy estimated by WaterSwap was -16 kcal/mol that validates and affirms complex stability. The inhibitor represents a promising scaffold as a lead optimization for the FtsZ enzyme.

Discovery of beta-lactamase CMY-10 inhibitors for combination therapy against multi-drug resistant Enterobacteriaceae.

ß-lactam antibiotics are the most widely used antimicrobial agents since the discovery of benzylpenicillin in the 1920s. Unfortunately, these life-saving antibiotics are vulnerable to inactivation by continuously evolving ß-lactamase enzymes that are primary resistance determinants in multi-drug resistant pathogens. The current study exploits the strategy of combination therapeutics and aims at identifying novel ß-lactamase inhibitors that can inactivate the ß-lactamase enzyme of the pathogen while allowing the ß-lactam antibiotic to act against its penicillin-binding protein target. Inhibitor discovery applied the Site-Identification by Ligand Competitive Saturation (SILCS) technology to map the functional group requirements of the ß-lactamase CMY-10 and generate pharmacophore models of active site. SILCS-MC, Ligand-grid Free Energy (LGFE) analysis and Machine-learning based random-forest (RF) scoring methods were then used to screen and filter a library of 700,000 compounds. From the computational screens 74 compounds were subjected to experimental validation in which ß-lactamase activity assay, in vitro susceptibility testing, and Scanning Electron Microscope (SEM) analysis were conducted to explore their antibacterial potential. Eleven compounds were identified as enhancers while 7 compounds were recognized as inhibitors of CMY-10. Of these, compound 11 showed promising activity in ß-lactamase activity assay, in vitro susceptibility testing against ATCC strains (E. coli, E. cloacae, E. agglomerans, E. alvei) and MDR clinical isolates (E. cloacae, E. alvei and E. agglomerans), with synergistic assay indicating its potential as a ß-lactam enhancer and ß-lactamase inhibitor. Structural similarity search against the active compound 11 yielded 28 more compounds. The majority of these compounds also exhibited ß-lactamase inhibition potential and antibacterial activity. The non-ß-lactam-based ß-lactamase inhibitors identified in the current study have the potential to be used in combination therapy with lactam-based antibiotics against MDR clinical isolates that have been found resistant against last-line antibiotics.

From normal to competo-allosteric regulation: insights into the binding pattern dynamics of DSPI protein of Pseudomonas aeruginosa.

DSPI, a putative enoyl-coenzyme A (CoA) hydratase/isomerase, is anticipated to be involved in the synthesis of cis-2-decenoic acid (CDA), a quorum sensing (QS) signal molecule present in the superbug Pseudomonas aeruginosa. The current study not only adapts a broad-spectrum strategy for the lucid design of small molecule modulators but also provides novel allosteric inhibitors for DSPI, to investigate its function and potential as a therapeutic target. Docking analysis revealed that the compound 10252273, bound to the specific allosteric site, interacted with Glu118, unique amino acid residue of the active binding pocket, hence indicates the presence of a competitive allosteric site. The current study thus identifies and characterizes inhibitors by targeting the normal binding site and also reports the presence of the competo-allosteric site in the same binding tunnel as the normal site. Molecular docking studies proposed two chemical compounds that share a benzamide-benzimidazole (BB) backbone as potent inhibitors that can obstruct the mechanism of DSPI by targeting both the normal and proposed allosteric binding sites. MD simulations further revealed the disruption of the normal binding site due to the displacement of critical residues Cys146 and Glu118. The rearrangement of H-bond pattern, pi-pi interactions, and strong hydrophobic interactions were observed at both the binding sites. The allosteric pocket inhibitor exhibited improved binding energy than the normal site inhibitor based on MMGBSA and MMPBSA analysis. With subsequent characterization, the current study reveals the allosteric binding site and provides insights into the drug binding mechanism of DSPI.Communicated by Ramaswamy H. Sarma.