Anhydroparthenin as a dual-target inhibitor against Sterol C-24 methyltransferase and Sterol 14-α demethylase of Leishmania donovani: A comprehensive in vitro and in silico study.

Parthenium hysterophorus plant has a diverse chemical profile and immense bioactive potential. It exhibits excellent pharmacological properties such as anti-cancer, anti-inflammatory, anti-malarial, microbicidal, and anti-trypanosomal. The present study aims to evaluate the anti-leishmanial potential and toxicological safety of anhydroparthenin isolated from P. hysterophorus. Anydroparthenin was extracted from the leaves of P. hysterophorus and characterized through detailed analysis of 1H, 13C NMR, and HRMS. Dye-based in vitro and ex vivo assays confirmed that anhydroparthenin significantly inhibited both promastigote and amastigote forms of the Leishmania donovani parasites. Both the cytotoxicity experiment and hemolytic assay revealed its non-toxic nature and safety index in the range of 10 to 15. Further, various mechanistic assays suggested that anhydroparthenin led to the generation of oxidative stress, intracellular ATP depletion, alterations in morphology and mitochondrial membrane potential, formation of intracellular lipid bodies, and acidic vesicles, ultimately leading to parasite death. As a dual targeting approach, computational studies and sterol quantification assays confirmed that anhydroparthenin inhibits the Sterol C-24 methyl transferase and Sterol 14-α demethylase proteins involved in the ergosterol biosynthesis in Leishmania parasites. These results suggest that anhydroparthenin could be a promising anti-leishmanial molecule and can be developed as a novel therapeutic stratagem against leishmaniasis.

Anticancer Drug Discovery Based on Natural Products: From Computational Approaches to Clinical Studies.

Globally, malignancies cause one out of six mortalities, which is a serious health problem. Cancer therapy has always been challenging, apart from major advances in immunotherapies, stem cell transplantation, targeted therapies, hormonal therapies, precision medicine, and palliative care, and traditional therapies such as surgery, radiation therapy, and chemotherapy. Natural products are integral to the development of innovative anticancer drugs in cancer research, offering the scientific community the possibility of exploring novel natural compounds against cancers. The role of natural products like Vincristine and Vinblastine has been thoroughly implicated in the management of leukemia and Hodgkin's disease. The computational method is the initial key approach in drug discovery, among various approaches. This review investigates the synergy between natural products and computational techniques, and highlights their significance in the drug discovery process. The transition from computational to experimental validation has been highlighted through in vitro and in vivo studies, with examples such as betulinic acid and withaferin A. The path toward therapeutic applications have been demonstrated through clinical studies of compounds such as silvestrol and artemisinin, from preclinical investigations to clinical trials. This article also addresses the challenges and limitations in the development of natural products as potential anti-cancer drugs. Moreover, the integration of deep learning and artificial intelligence with traditional computational drug discovery methods may be useful for enhancing the anticancer potential of natural products.

In silico modeling for quick prediction of inhibitory activity against 3CLpro enzyme in SARS CoV diseases.

As of 2 September 2020, the 2019 novel coronavirus or SARS CoV-2 has been responsible for more than 2,56,02,665 infections and 8,52,768 deaths worldwide. There has been an urgent need of newer drug discovery to tackle the situation. Severe acute respiratory syndrome-associated coronavirus 3C-like protease (or 3CLpro) is a potential target as anti-SARS agents as it plays a vital role in the viral life cycle. This study aims at developing a quantitative structure-activity relationship (QSAR) model against a group of 3CLpro inhibitors to study their structural requirements for their inhibitory activity. Further, molecular docking studies were carried out which helped in the justification of the QSAR findings. Moreover, molecular dynamics simulation study was performed for selected compounds to check the stability of interactions as suggested by the docking analysis. The current QSAR model was further used in the prediction and screening of large databases within a short time.Communicated by Ramaswamy H. Sarma.

Target prioritization of novel substituted 5-aryl-2-oxo-/thioxo-2,3-dihydro-1H-benzo[6,7]chromeno[2,3-d]pyrimidine-4,6,11(5H)-triones as anticancer agents using in-silico approach.

Cancer is a multi-origin collection of diseases attributed by abnormal and uncontrolled cell growth spread from origin to other parts of body eventually leading to death. After decades of research, anticancer drug therapy is still very much limited to inhibiting growth and controlling the spread of tumour cells. Finding novel molecular targets and drug candidates using assimilation of experimental and computational approaches is among the recent strategies adopted by researchers to speed up the anticancer drug discovery process. In present study, synthesis of 40 novel substituted 5-aryl-2-oxo-/thioxo-2,3-dihydro-1H-benzo[6,7]chromeno[2,3-d]pyrimidine-4,6,11(5H)-triones has been accomplished followed by molecular target identification using different in silico approaches. The target prioritization methodology involved identification and selection of targets, molecular docking followed by molecular dynamic simulation and determination of binding free energy using MM-GBSA technique. Systematic and stepwise virtual screening of biological targets lead to identification of B-cell lymphoma 6 protein (BCL6), lysine-specific histone demethylase 1 A (LSD1), nuclear factor kappa-light-chain-enhancer of activated B cells (NFkB P65) and poly (ADP-ribose) polymerase 1 (PARP1) as suitable anticancer targets for the set of synthesized compounds.Communicated by Ramaswamy H. Sarma.

Supramolecular Assembly of Amino Acid Based Cationic Polymer for Efficient Gene Transfection Efficiency in Triple Negative Breast Cancer.

The success of gene therapy is enormously dependent on an efficient gene carrier, and in this context, cationic polymers still continue to play a major role particularly with respect to the safety issue compared to viral vectors. Developing an efficient gene carrier system having promising gene transfection efficiency with low toxicity is the foremost impediment associated with a nonviral carrier. Here, we explored amino acid based biocompatible polymers synthesized via reversible addition-fragmentation chain transfer (RAFT) polymerization where glycine (Gly), leucine (Leu), and phenyl alanine (Phe) amino acids were used as the pendent groups of the polymeric brushes. The presence of both a hydrophobic group (long chain aliphatic group associated with the RAFT agent) and hydrophilic amino groups was associated with the supramolecular assembly of the polymeric chain having hydrodynamic sizes within the range of 150-300 nm with a positive zeta potential of 30 ± 5 mV. All polymers showed very low toxicity and possessed >80% cell viability even at a very high concentration of 1000 µg/mL against both normal and cancerous cells. In addition to this, the polymers also showed excellent blood compatibility, and negligible hemolysis was observed at the concentration of 500 µg/mL. All polymers showed efficient DNA complexation capability as well as excellent protection of DNA against highly negatively charged surfactant and enzymatic digestion, although the efficiency was dependent on the N/P ratio of polymer/DNA complexes. Interestingly, the phenyl alanine moiety containing polymer brush P(HEMA-Phe-NH2) showed a hexagonal shaped nanoparticle after complexation with pDNA and consequently showed higher cellular uptake, resulting in a higher transfection efficiency in a triple negative breast cancer cell, the MDA-MB-231 cell. Therefore, the synthesized polymer containing an amino acid pendent group, especially the phenyl alanine moiety, may be a promising nonviral gene carrier system in gene therapy application in the future.

Andrographolide inhibits human serum albumin fibril formations through site-specific molecular interactions.

Protein misfolding and fibrillation are the fundamental traits in degenerative diseases like Alzheimer's, Parkinsonism, and diabetes mellitus. Bioactives such as flavonoids and terpenoids from plant sources are known to express protective effects against an array of diseases including diabetes, Alzheimer's and obesity. Andrographolide (AG), a labdane diterpenoid is prescribed widely in the Indian and Chinese health care systems for classical efficacy against a number of degenerative diseases. This work presents an in depth study on the effects of AG on protein fibrillating pathophysiology. Thioflavin T fluorescence spectroscopy and DLS results indicated concentration dependent inhibition of human serum albumin (HSA) fibrillation. The results were confirmed by electron microscopy studies. HSA fibril formations were markedly reduced in the presence of AG. Fluorescence studies and UV-Vis experiments confirmed further that AG molecularly interacts with HSA at site. In silico molecular docking studies revealed hydrogen bonding and hydrophobic interactions with HSA in the native state. Thus AG interacts with HSA, stabilizes the native protein structure and inhibits fibrillation. The results demonstrated that the compound possesses anti-amyloidogenic properties and can be promising against some human degenerative diseases.

Diabetes mellitus caused by mutations in human insulin: analysis of impaired receptor binding of insulins Wakayama, Los Angeles and Chicago using pharmacoinformatics.

Several naturally occuring mutations in the human insulin gene are associated with diabetes mellitus. The three known mutant molecules, Wakayama, Los Angeles and Chicago were evaluated using molecular docking and molecular dynamics (MD) to analyse mechanisms of deprived binding affinity for insulin receptor (IR). Insulin Wakayama, is a variant in which valine at position A3 is substituted by leucine, while in insulin Los Angeles and Chicago, phenylalanine at positions B24 and B25 is replaced by serine and leucine, respectively. These mutations show radical changes in binding affinity for IR. The ZDOCK server was used for molecular docking, while AMBER 14 was used for the MD study. The published crystal structure of IR bound to natural insulin was also used for MD. The binding interactions and MD trajectories clearly explained the critical factors for deprived binding to the IR. The surface area around position A3 was increased when valine was substituted by leucine, while at positions B24 and B25 aromatic amino acid phenylalanine replaced by non-aromatic serine and leucine might be responsible for fewer binding interactions at the binding site of IR that leads to instability of the complex. In the MD simulation, the normal mode analysis, rmsd trajectories and prediction of fluctuation indicated instability of complexes with mutant insulin in order of insulin native insulin < insulin Chicago < insulin Los Angeles < insulin Wakayama molecules which corresponds to the biological evidence of the differing affinities of the mutant insulins for the IR.

Synthesis of Bis-pyrrolizidine-Fused Dispiro-oxindole Analogues of Curcumin via One-Pot Azomethine Ylide Cycloaddition: Experimental and Computational Approach toward Regio- and Diastereoselection.

Curcumin has been transformed to racemic curcuminoids via an azomethine ylide cycloaddition reaction using isatin/acenaphthoquinone and proline as the reagents. The products were characterized by extensive 1D/2D NMR analysis and single-crystal X-ray crystallographic studies. The enantiomers of one racemic product were separated by HPLC on a Chiralcel OD-H column and were indeed confirmed by the CD spectra of the separated enantiomers.

Molecular dynamics directed CoMFA studies on carbocyclic neuraminidase inhibitors.

Zanamivir is the known potent anti-influenza agent targeting the key enzyme neuraminidase that cleaves sialic acid from cell receptors allowing release of newly formed virions. Molecular dynamics simulation was carried out to determine the dynamic behavior of Zanamivir upon its binding to flexible loops of neuraminidase and to analyse its interactions in the bioactive state. Neuraminidase exhibits wide range of affinity with structurally similar compounds. CoMFA study was used to determine quantitative structure-activity relationship for 36 carbocyclic Neuraminidase inhibitors (NIs). The CoMFA model was also successfully built using cross-validated r²cv = 0.580 and r²pred = 0.638.