In Silico Screening of Synthetic and Natural Compounds to Inhibit the Binding Capacity of Heavy Metal Compounds against EGFR Protein of Lung Cancer.

Inorganic pollutant, specifically heavy metals' contamination, is a significant matter of concern and is one of the key contributors in various health disorders including cancer. However, the interaction of heavy metals (HMs) with lung cancer has rarely been explored yet. Therefore, the present study was intended with the aim to identify the interactions of HMs with the target protein "epidermal growth factor receptor (EGFR)" of lung cancer and explore potential drug candidates, which could inhibit the active site of EGFR against HM exposure. The molecular operating environment (MOE) tool was used to study the interactions of HMs with EGFR protein. The drug-drug interaction (DDI) network approach was used to identify the potential drug candidates, which were further confirmed and compared with the commercial medicines/control group. Various compounds of twenty-three HMs were docked with EGFR protein. Out of which tinidazole, thallium bromodimethyl, and silver acetate (Sn, Ti, and Ag compounds) showed strong interactions with EGFR based on lowest-scoring values (-20.42, -7.86, and -7.74 kcal/mol, respectively). Among 1280 collected drug candidates, three synthetic compounds viz., ZINC00602803, ZINC00602685, and ZINC06718468 and three natural compounds (berberine chloride, transresveratrol, and ellagic acid) depicted strong binding capacity with EGFR. Specifically, the scoring value of ZINC00602803 (-30.99 kcal/mol) was even lowest than standard lung cancer drugs (afatinib, erlotinib, and gefitinib). Our findings revealed that both natural and synthetic compounds having strong associations with EGFR protein could be potential candidates to inhibit the interaction between HMs and lung cancer protein and can also be used as an alternative for the prevention and treatment of lung cancer. However, in vitro and in vivo studies should be conducted to validate the aforementioned natural and synthetic compounds.

Role of Persistent Organic Pollutants in Breast Cancer Progression and Identification of Estrogen Receptor Alpha Inhibitors Using In-Silico Mining and Drug-Drug Interaction Network Approaches.

The strong association between POPs and breast cancer in humans has been suggested in various epidemiological studies. However, the interaction of POPs with the ERα protein of breast cancer, and identification of natural and synthetic compounds to inhibit this interaction, is mysterious yet. Consequently, the present study aimed to explore the interaction between POPs and ERα using the molecular operating environment (MOE) tool and to identify natural and synthetic compounds to inhibit this association through a cluster-based approach. To validate whether our approach could distinguish between active and inactive compounds, a virtual screen (VS) was performed using actives (627 compounds) as positive control and decoys (20,818 compounds) as a negative dataset obtained from DUD-E. Comparatively, short-chain chlorinated paraffins (SCCPs), hexabromocyclododecane (HBCD), and perfluorooctanesulfonyl fluoride (PFOSF) depicted strong interactions with the ERα protein based on the lowest-scoring values of -31.946, -18.916, -17.581 kcal/mol, respectively. Out of 7856 retrieved natural and synthetic compounds, sixty were selected on modularity bases and subsequently docked with ERα. Based on the lowest-scoring values, ZINC08441573, ZINC00664754, ZINC00702695, ZINC00627464, and ZINC08440501 (synthetic compounds), and capsaicin, flavopiridol tectorgenin, and ellagic acid (natural compounds) showed incredible interactions with the active sites of ERα, even more convening and resilient than standard breast cancer drugs Tamoxifen, Arimidex and Letrozole. Our findings confirm the role of POPs in breast cancer progression and suggest that natural and synthetic compounds with high binding affinity could be more efficient and appropriate candidates to treat breast cancer after validation through in vitro and in vivo studies.

Novel vaccine design based on genomics data analysis: A review.

Modification of pathogenic strains with the passage of time is responsible for evolution in the timeline of vaccine development for last 30 years. Recent advancements in computational vaccinology on the one hand and genome sequencing approaches on the other have generated new hopes in vaccine development. The aim of this review was to discuss the evolution of vaccines, their characteristics and limitations. In this review, we highlighted the evolution of vaccines, from first generation to the current status, pointing out how different vaccines have emerged and different approaches that are being followed up in the development of more rational vaccines against a wide range of diseases. Data were collected using Google Scholar, Web of Science, Science Direct, Web of Knowledge, Scopus and Science Hub, whereas computational tools such as NCBI, GeneMANIA and STRING were used to analyse the pathways of vaccine action. Innovative tools, such as computational tools, recombinant technologies and intra-dermal devices, are currently being investigated in order to improve the immunological response. New technologies enlightened the interactions of host proteins with pathogenic proteins for vaccine candidate development, but still there is a need of integrating transcriptomic and proteomic approaches. Although immunization with genomics data is a successful approach, its advantages must be assessed case by case and its applicability depends on the nature of the agent to be immunized, the nature of the antigen and the type of immune response required to achieve effective protection.

In-silico elucidation of Moringa oleifera phytochemicals against diabetes mellitus.

Moringa oleifera is also known as "Miracle tree", due to its multiple uses and adaptability. Because of nutritive and pharmacological values, it is widely cultivated across the world. M. oleifera leaves are rich source of minerals, vitamins and many health beneficial secondary metabolites, and possess significant anti-diabetic potential. Consequently, Insilco study could be noteworthy to expand effective anti-diabetic drugs from this plant. Present study was designed to find out the best bioactive compounds of M. oleifera as a potential therapeutic agent against diabetes mellitus through In-silico method. For this, structures of phytochemicals were extracted from PubChem and docked to mutated protein from PBD. Afterwards, datasets were prepared for ligand based pharmacophore and their pharmacophoric features were generated from LigandScout. Finally five phytochemicals viz. anthraquinone, 2-phenylchromenylium (Anthocyanins), hemlock tannin, sitogluside (glycoside) and A-phenolic steroid were selected, which exhibited effective binding within the active binding pocket of the targeted protein. Ligand based pharmacophore model showed the key features i.e. HBD, HBA, aromatic ring, hydrophobic, positively ionizable surface essential for receptor binding. Our findings suggest that screened phytochemicals present in M. oleifera can be used as potential therapeutic drug candidates to treat diabetes mellitus.

In silico authentication of amygdalin as a potent anticancer compound in the bitter kernels of family Rosaceae.

Amygdalin a naturally occurring compound, predominantly in the bitter kernels of apricot, almond, apple and other members of Rosaceae family. Though, amygdalin is used as an alternative therapy to treat various types of cancer but its role in cancer pathways has rarely been explored yet. Therefore, present study was intended with the aim to investigate the alleged anti-cancerous effects of amygdalin specifically on PI3K-AKT-mTOR and Ras pathways of cancer in human body. Computational modelling and simulation techniques were used to assess the effect of amygdalin on PI3K-AKT-mTOR and Ras pathways using different level of dosage. It was observed that amygdalin had direct and substantial contribution to regulate PI3K-mTOR activities on threshold levels while the other caner pathways were effected indirectly. Consequently, amygdalin is a down-regulator of a cancer within a specified amount and contribute considerably to reduce various types of cancer in human. Furthermore, in-vitro and in-vivo analyses of amygdalin could be of helpful to authenticate its pharmacological effects.