11 research outputs found

    Immunoinformatics and Computer-Aided Drug Design as New Approaches against Emerging and Re-Emerging Infectious Diseases

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    Infectious diseases are initiated by small pathogenic living germs that are transferred from person to person by direct or indirect contact. Recently, different newly emerging and reemerging infectious viral diseases have become greater threats to human health and global stability. Investigators can anticipate epidemics through the advent of numerous mathematical tools that can predict specific pathogens and identify potential targets for vaccine and drug design and will help to fight against these challenges. Currently, computational approaches that include mathematical and essential tools have unfolded the way for a better understanding of newly originated emerging and re-emerging infectious disease, pathogenesis, diagnosis, and treatment option of specific diseases more easily, where immunoinformatics plays a crucial role in the discovery of novel peptides and vaccine candidates against the different viruses within a short time. Computational approaches include immunoinformatics, and computer-aided drug design (CADD)-based model trained biomolecules that offered reasonable and quick implementation approaches for the modern discovery of effective viral therapies. The essence of this review is to give insight into the multiple approaches not only for the detection of infectious diseases but also profound how people can pick appropriate models for the detection of viral therapeutics through computational approaches

    Marine-derived sea urchin compounds as potential anti-cancer drug candidate against colorectal cancer: In silico and in vitro studies

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    Sea urchin-derived compounds are potential candidates for the development of effective drugs for the treatment of cancer diseases. In this study, 19 compounds derived from sea urchin (Diadema savignyi) were used to treat colorectal cancer using the HCT116 cell line. However, molecular docking, ADME (absorption, distribution, metabolism, and excretion), toxicity, molecular dynamic (MD) simulation, and molecular mechanics generalized Born surface area (MM-GBSA) were used to confirm the ligand–protein interaction. Interactions of Importin-11 receptor with sea urchin compounds reveal that four compounds have higher binding affinities (ranging from -8.6 to -7.1 kcal/mol). In vitro testing revealed that the CID 6432458 compound was effective (docking score of −8.6 kcal/mol) against the HCT116 cell line. The cytotoxicity of HCT116 has been documented, with an IC50 value of 6.885 ± 4. MTT assay, apoptosis analysis, and cell cycle assay were utilized to examine cell death in colorectal cancer. In the MTT experiment, 15 µM and 20 µM dosages were associated with 77% cell death; however, flow cytometry analysis using the IC50 value revealed that the selected chemical induced greater apoptosis in the HCT116 cell line (58.5%). The gene expression data revealed that the apoptotic gene BAX is expressed at a higher level than the BCL-2 gene. The IPO11 gene was downregulated during treatment. In the experiment involving the cell cycle, the S phase for the 30  µM dose showed 75.1% apoptosis, which was greater than the other concentrations used alone. These in silico and in vitro analysis will not only provide new information about Importin-11 receptor and insight into colorectal cancer but will also facilitate the development of natural compounds in a significant and worthwhile manner

    Integrated structure model-based virtual screening approaches identified anti-cancer agents against prostate cancer by targeting MAOB protein

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    Abstract Background Flavin monoamine oxidase gene encodes a protein (MAOB) that forms a part of the flavin monoamine oxidase family in the outer membrane of mitochondria. It plays a role in the tissue metabolism of neuroactive and vasoactive amines as well as the oxidative deamination of xenobiotic and biogenic amines. However, overexpression of the receptor reduced apoptosis in cells, resulting in the progress of prostate sarcoma. Therefore, various kinds of MAOB antagonists are often used to fix an apoptosis mechanism that makes it hard to get rid of cancer from live tissues. Moreover, chemical compounds that have been discovered to be MAOB inhibitors to date exhibit side effects that are causing problems in chemotherapy treatment. The study aims to discover new purchasable compound that induces apoptosis by allowing caspases to operate at their maximum efficiency and is low toxic. Methods With the assistance of virtual screening, molecular docking, and molecular dynamics simulation (MD), a structure-based pharmacophore model of the protein active site cavity was made. Twenty hits were found, and then a molecular docking strategy was used to choose four molecules to study in more depth. MD simulations were used to check the stability of the four compounds, and they were all shown to be stable when bound to the target protein. Results Four newly discovered compounds, included with ZINC ID Such as ZINC12143050, ZINC08301324, ZINC16743012, and ZINC64165826 with binding scores of − 11.7, − 11.4, − 11.2 and − 11.1 kcal/mol, respectively, may serve as lead compounds for the treatment of prostate cancer associated with MAOB; however, further evaluation through wet lab is needed to determine the compounds effectiveness. Conclusion A structure-based model was initially developed, followed by molecular docking, ADMET analysis, and MD simulation. The top four natural compounds identified in the A-to-Z virtual screening process could serve as lead molecules in the fight against prostate cancer

    Whole Genome Sequence of the Newly Prescribed Subspecies Oreochromis spilurus saudii: A Valuable Genetic Resource for Aquaculture in Saudi Arabia

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    Tilapia (Oreochromis spp.) have significant potential for aquaculture production around the world. There is an increasing demand among tilapia producers for strains with higher yields and for fish that can survive in highly saline water. Novel strains and consistent seedstock are critically important objectives for sustainable aquaculture, but for these required targets there is still not enough progress. Therefore, this study describes the genome sequence of Oreochromis spilurus to support the seawater culture of tilapia. The draft genome is 0.768 Gb (gigabases), with a scaffold N50 (the genome (50%) is in fragments of this length) of 0.22 Mb (megabases). The GC content is 40.4%, the heterozygosity rate is 0.35%, and the repeat content is 47.97%. The predicted protein-coding peptide encoded 51,642 and predicted 10,641 protein-coding genes in the O. spilurus genome. The predicted antimicrobial peptides were 262, bringing new hope for further research. This whole genome sequence provides new insights for biomedical and molecular research and will also improve the breeding of tilapia for high yields, resistance to disease, and adaptation to salt water

    Pharmacophore-Model-Based Virtual-Screening Approaches Identified Novel Natural Molecular Candidates for Treating Human Neuroblastoma

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    The mortality of cancer patients with neuroblastoma is increasing due to the limited availability of specific treatment options. Few drug candidates for combating neuroblastoma have been developed, and identifying novel therapeutic candidates against the disease is an urgent issue. It has been found that muc-N protein is amplified in one-third of human neuroblastomas and expressed as an attractive drug target against the disease. The myc-N protein interferes with the bromodomain and extraterminal (BET) family proteins. Pharmacologically inhibition of the protein potently depletes MYCN in neuroblastoma cells. BET inhibitors target MYCN transcription and show therapeutic efficacy against neuroblastoma. Therefore, the study aimed to identify potential inhibitors against the BET family protein, specifically Brd4 (brodamine-containing protein 4), to hinder the activity of neuroblastoma cells. To identify effective molecular candidates against the disease, a structure-based pharmacophore model was created for the binding site of the Brd4 protein. The pharmacophore model generated from the protein Brd4 was validated to screen potential natural active compounds. The compounds identified through the pharmacophore-model-based virtual-screening process were further screened through molecular docking, ADME (absorption, distribution, metabolism, and excretion), toxicity, and molecular dynamics (MD) simulation approach. The pharmacophore-model-based screening process initially identified 136 compounds, further evaluated based on molecular docking, ADME analysis, and toxicity approaches, identifying four compounds with good binding affinity and lower side effects. The stability of the selected compounds was also confirmed by dynamic simulation and molecular mechanics with generalized Born and surface area solvation (MM-GBSA) methods. Finally, the study identified four natural lead compounds, ZINC2509501, ZINC2566088, ZINC1615112, and ZINC4104882, that will potentially inhibit the activity of the desired protein and help to fight against neuroblastoma and related diseases. However, further evaluations through in vitro and in vivo assays are suggested to identify their efficacy against the desired protein and disease

    Suitability of drinking water quality in Chittagong Metropolitan City, Bangladesh: research on urban water bodies (UWBs) using multivariate analytic techniques

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    This is empirical research that focuses on the urban water ecosystems in the humid tropics of South Asia. The purpose of the study was to evaluate the quality of drinking water in the urban water bodies (UWBs) of Chittagong Metropolitan City (CMC), Bangladesh. The field data was centered on the analysis and depiction of twenty-three (23) water quality parameters, collected from twenty-one (21) spatial observation units. Analytic tools include suitability analysis, correlation matrix, principal component analysis (PCA), and cluster analysis (CA) as a means to an end. The data were analyzed using SPSS. The analysis reveals that drinking water quality in studied UWBs was inappropriate during the monsoon season. Parameters that crossed the extreme permissible concentration incorporate EC, BOD, COD, Turbidity, Nitrate, Total coliform, and Fecal coliform. The PCA extracted four factors (PC1–4) with an eigenvalue of 10.23, explaining 73.1% of the total variation in the dataset in cumulative terms. The CA recognized three (3) broad groups of the sampling stations. Group A represents nine cases, suffering the most from pollution concentration in CMC. Awareness building at all levels is advocated to improve clean water sources, increase service provision, and ensure public health safeguards. HIGHLIGHTS Urban water bodies are alternative sources of drinking water.; A significant gap exists between the demand for and supply of municipal piped water supply.; Anthropogenic activities have an impact on the quality of drinking water.; Multivariate analytic techniques (MATs) have been used to determine the suitability of drinking water quality.; Promoting awareness-raising on all levels is encouraged.

    Application of Mathematical Modeling and Computational Tools in the Modern Drug Design and Development Process

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    The conventional drug discovery approach is an expensive and time-consuming process, but its limitations have been overcome with the help of mathematical modeling and computational drug design approaches. Previously, finding a small molecular candidate as a drug against a disease was very costly and required a long time to screen a compound against a specific target. The development of novel targets and small molecular candidates against different diseases including emerging and reemerging diseases remains a major concern and necessitates the development of novel therapeutic targets as well as drug candidates as early as possible. In this regard, computational and mathematical modeling approaches for drug development are advantageous due to their fastest predictive ability and cost-effectiveness features. Computer-aided drug design (CADD) techniques utilize different computer programs as well as mathematics formulas to comprehend the interaction of a target and drugs. Traditional methods to determine small-molecule candidates as a drug have several limitations, but CADD utilizes novel methods that require little time and accurately predict a compound against a specific disease with minimal cost. Therefore, this review aims to provide a brief insight into the mathematical modeling and computational approaches for identifying a novel target and small molecular candidates for curing a specific disease. The comprehensive review mainly focuses on biological target prediction, structure-based and ligand-based drug design methods, molecular docking, virtual screening, pharmacophore modeling, quantitative structure–activity relationship (QSAR) models, molecular dynamics simulation, and MM-GBSA/MM-PBSA approaches along with valuable database resources and tools for identifying novel targets and therapeutics against a disease. This review will help researchers in a way that may open the road for the development of effective drugs and preventative measures against a disease in the future as early as possible

    Integrative Ligand-Based Pharmacophore Modeling, Virtual Screening, and Molecular Docking Simulation Approaches Identified Potential Lead Compounds against Pancreatic Cancer by Targeting FAK1

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    Pancreatic cancer is a very deadly disease with a 5-year survival rate, making it one of the leading causes of cancer-related deaths globally. Focal adhesion kinase 1 (FAK1) is a ubiquitously expressed protein in pancreatic cancer. FAK, a tyrosine kinase that is overexpressed in cancer cells, is crucial for the development of tumors into malignant phenotypes. FAK functions in response to extracellular signals by triggering transmembrane receptor signaling, which enhances focal adhesion turnover, cell adhesion, cell migration, and gene expression. The ligand-based drug design approach was used to identify potential compounds against the target protein, which included molecular docking: ADME (absorption, distribution, metabolism, and excretion), toxicity, molecular dynamics (MD) simulation, and molecular mechanics generalized born surface area (MM-GBSA). Following the retrieval of twenty hits, four compounds were selected for further evaluation based on a molecular docking approach. Three newly discovered compounds, including PubChem CID24601203, CID1893370, and CID16355541, with binding scores of −10.4, −10.1, and −9.7 kcal/mol, respectively, may serve as lead compounds for the treatment of pancreatic cancer associated with FAK1. The ADME (absorption, distribution, metabolism, and excretion) and toxicity analyses demonstrated that the compounds were effective and nontoxic. However, further wet laboratory investigations are required to evaluate the activity of the drugs against the cancer

    Identification of natural antiviral drug candidates against Tilapia Lake Virus: Computational drug design approaches.

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    Tilapia Lake Virus (TiLV) is a disease that affects tilapia fish, causing a high rate of sudden death at any stage in their life cycle. Unfortunately, there are currently no effective antiviral drugs or vaccines to prevent or control the progression of this disease. Researchers have discovered that the CRM1 protein plays a critical function in the development and spreading of animal viruses. By inhibiting CRM1, the virus's spread in commercial fish farms can be suppressed. With this in mind, this study intended to identify potential antiviral drugs from two different tropical mangrove plants from tropical regions: Heritiera fomes and Ceriops candolleana. To identify promising compounds that target the CRM1 protein, a computer-aided drug discovery approach is employed containing molecular docking, ADME (absorption, distribution, metabolism and excretion) analysis, toxicity assessment as well as molecular dynamics (MD) simulation. To estimate binding affinities of all phytochemicals, molecular docking is used and the top three candidate compounds with the highest docking scores were selected, which are CID107876 (-8.3 Kcal/mol), CID12795736 (-8.2 Kcal/mol), and CID12303662 (-7.9 Kcal/mol). We also evaluated the ADME and toxicity properties of these compounds. Finally, MD simulation was conducted to analyze the stability of the protein-ligand complex structures and confirm the suitability of these compounds. The computational study demonstrated that the phytochemicals found in H. fomes and C. candolleana could potentially serve as important inhibitors of TiLV, offering practical utility. However, further in vivo investigations are necessary to investigate and potentially confirm the effectiveness of these compounds as antiviral drugs against the virus TiLV

    Computational Identification of Druggable Bioactive Compounds from Catharanthus roseus and Avicennia marina against Colorectal Cancer by Targeting Thymidylate Synthase

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    Colorectal cancer (CRC) is the second most common cause of death worldwide, affecting approximately 1.9 million individuals in 2020. Therapeutics of the disease are not yet available and discovering a novel anticancer drug candidate against the disease is an urgent need. Thymidylate synthase (TS) is an important enzyme and prime precursor for DNA biosynthesis that catalyzes the methylation of deoxyuridine monophosphate (dUMP) to deoxythymidine monophosphate (dTMP) that has emerged as a novel drug target against the disease. Elevated expression of TS in proliferating cells promotes oncogenesis as well as CRC. Therefore, this study aimed to identify potential natural anticancer agents that can inhibit the activity of the TS protein, subsequently blocking the progression of colorectal cancer. Initially, molecular docking was implied on 63 natural compounds identified from Catharanthus roseus and Avicennia marina to evaluate their binding affinity to the desired protein. Subsequently, molecular dynamics (MD) simulation, ADME (Absorption, Distribution, Metabolism, and Excretion), toxicity, and quantum chemical-based DFT (density-functional theory) approaches were applied to evaluate the efficacy of the selected compounds. Molecular docking analysis initially identified four compounds (PubChem CID: 5281349, CID: 102004710, CID: 11969465, CID: 198912) that have better binding affinity to the target protein. The ADME and toxicity properties indicated good pharmacokinetics (PK) and toxicity ability of the selected compounds. Additionally, the quantum chemical calculation of the selected molecules found low chemical reactivity indicating the bioactivity of the drug candidate. The global descriptor and HOMO-LUMO energy gap values indicated a satisfactory and remarkable profile of the selected molecules. Furthermore, MD simulations of the compounds identified better binding stability of the compounds to the desired protein. To sum up, the phytoconstituents from two plants showed better anticancer activity against TS protein that can be further developed as an anti-CRC drug
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