Insilico evaluation on potential Mt-Sp1/matriptase inhibitors data: DFT and molecular modelling approaches.

Nine heterocyclic compounds were investigated using density functional theory, molecular operating environment software, material studio, swissparam (Swiss drug design) software. In this work, the descriptors generated from the optimized compounds proved to be efficient and explain the level of reactivity of the investigated compound. The developed quantitative structure activity relationship (QSAR) model was predictive and reliable. Also, compound 9 proved to be capable of inhibiting Mt-Sp1/Matriptase (pdb id: 1eax) than other examined heterocyclic compounds. Target prediction analysis was carried out on the compound with highest binding affinity (Compound 9) and the results were reported.

Thermally modified nanocrystalline snail shell adsorbent for methylene blue sequestration: equilibrium, kinetic, thermodynamic, artificial intelligence, and DFT studies.

In recent years, the quest for an efficient and sustainable adsorbent material that can effectively remove harmful and hazardous dyes from industrial effluent has become more intense. The goal is to explore the capability of thermally modified nanocrystalline snail shells (TMNSS) as a new biosorbent for removing methylene blue (MB) dye from contaminated wastewater. TMNSS was employed in batch adsorption experiments to remove MB dye from its solutions, taking into account various adsorption parameters such as contact time, temperature, pH, adsorbent dosage, and initial concentration. SEM, EDS, XRD, and FTIR were used to characterize the adsorbent. The study further developed and adopted adaptive neuro-fuzzy inference system (ANFIS) and density functional theory (DFT) studies to holistically examine the adsorption process of MB onto the adsorbent. EDX and FTIR confirm the formation of CaO with a sharp peak at 547 cm-1, and C-O and O-H are present, as well. SEM and XRD show an irregularly shaped highly crystalline nanosized (65 ± 2.81 nm) particle with a lattice parameter value of 8.611617 Å. The adsorption efficiency of 96.48 ± 0.58% was recorded with a pH of 3.0 and an adsorbent dose of 10 mg at 30 °C. The findings from the study fit nicely onto Freundlich isotherms, with Qm = 31.7853 mg g-1 and R2 = 0.9985. Pseudo-second-order kinetics recorded the least error value of 0.8792 and R2 = 0.9868, thus indicating chemisorption and multilayer adsorption processes. The exothermic and spontaneous nature of the adsorption process are demonstrated by ΔH° and ΔG°. The performance of the ANFIS-based prediction of removal rate, which was demonstrated by a root mean square error (RMSE) value of 2.2077, mean absolute deviation (MAD) value of 1.1429, mean absolute error (MAE) value of 1.8786, and mean absolute percentage error (MAPE) value of 2.0178, revealed that the ANFIS model predictions and experimental findings are in good agreement. More so, DFT provides insights into the molecular interactions between MB and the adsorbent surface, with a calculated adsorbate-adsorbent binding affinity value of -1.3 kcal mol-1, thus confirming the ability of TMNSS for MB sequestration. The findings of this study highlight the promising potential of thermally modified nanocrystalline snail shells as sustainable and efficient adsorbents for MB sequestration.

Dataset on substituents effect on biological activities of linear RGD-containing peptides as potential anti-angiotensin converting enzyme.

The angiotensin converting enzyme inhibiting activity of linear rgd-containing peptides was investigated using in silico approach. The synthesized compound (parent compound) using experimental approach as well as its derivatives was subjected to computational examination using appropriate software. The investigated compounds were optimized using Spartan 14 while the docking study was executed via Pymol, AutoDock Tool, AutoDock Vina and discovery studio. The descriptors obtained (2D and 3D) were screened and the descriptor with highest capacity (squared correlation coefficient) was correlated to the calculated binding affinity. More so, the docking analysis was performed on the investigated linear rgd-containing peptides and angiotensin converting enzyme (PDB ID: 3nxq) via docking software and the resulted scoring and the types of the interaction observed were presented. Furthermore, (S)-dimethyl 2-(2-((S)-2-((R)-1-((S)-2-((S)-2-((S)-3-(4-chlorophenyl)-2-(1,3-dioxoisoindolin-2-yl)propanamido)-4-(methylthio)butanamido)-4-methylpentanoyl)pyrrolidine-2-carboxamido)-5-(3-((2,2,4,5,7-pentamethyl-2,3-dihydrobenzofuran-6-yl)sulfonyl)guanidino)pentanamido)acetamido)succinate (AB5) (compound with lowest binding affinity) and metformin were subjected to ADMET analysis and the resulted outcome were reported appropriately.

Dataset on biochemical inhibiting activities of selected phytochemicals in Azadirachta indica L as potential NS2B-NS3 proteases inhibitors.

The anti-NS2B-NS3 proteases activities of Azadirachta indica L. were investigated via the data obtained from selected bioactive compounds from Azadirachta indica L. The work was investigated using insilico approach and the series of computational software were used to execute the task. The software used were Spartan 14, material studio, Padel, Pymol, Autodock tool, Autodock vina and discovery studio. The obtained descriptors from 2D and 3D of the optimized compounds were screened and they were used to develop QSAR model using material studio software. Also, biological interaction between the selected bioactive compounds from Azadirachta indica L. and NS2B-NS3 proteases (PDB ID: 2fom) were accomplished using docking method and the calculated binding affinity as well as the residues involved in the interaction were reported. More so, the ADMET features for [(5S,6R,7S,8R,9S,10R,11S,12R,13S,17R)-17-(2,5-dihydroxy-2,5-dihydrofuran-3-yl)-11,12-dihydroxy-6­methoxy-4,4,8,10,13-pentamethyl-1,16-dioxo-6,7,9,11,12,17-hexahydro-5H-cyclopenta[a]phenanthren-7-yl] 3-methylbut-2-enoate (Compound 6) and (10R,13S,14S,17S)-17-[1-(3,4-dihydroxy-5,5-dimethyloxolan-2-yl)ethyl]-4,4,10,13,14-pentamethyl-1,2,5,6,9,11,12,15,16,17-decahydrocyclopenta[a]phenanthren-3-one (compound 12) with lowest binding affinity were investigated and reported.

Microplastics toxicity, detection, and removal from water/wastewater.

The world has witnessed massive and preeminent microplastics (MPs) pollution in water bodies due to the inevitable continuous production of plastics for various advantageous chemical and mechanical features. Plastic pollution, particularly contamination by MPs (plastic particles having a diameter lesser than 5 mm), has been a rising environmental concern in recent years due to the inappropriate disposal of plastic trash. This study presents the recent advancements in different technologies for MPs removal in order to gain proper insight into their strengths and weaknesses, thereby orchestrating the preparation for innovation in the field. The production, origin, and global complexity of MPs were discussed. This study also reveals MPs' mode of transportation, its feedstock polymers, toxicities, detection techniques, and the conventional removal strategies of MPs from contaminated systems. Modification of conventional methods vis-à-vis new materials/techniques and other emerging technologies, such as magnetic extraction and sol-gel technique with detailed mechanistic information for the removal of MPs are presented in this study. Conclusively, some future research outlooks for advancing the MPs removal technologies/materials for practical realization are highlighted.

Dataset on insightful bio-evaluation of 2-(quinoline-4-yloxy)acetamide analogues as potential anti-Mycobacterium tuberculosis catalase-peroxidase agents via in silico mechanisms.

The continuous havoc wrecked by tuberculosis among humans worldwide remains colossal. In this work, twenty-one (21) 2-(quinoline-4-yloxy)acetamide analogues were observed against Mycobacterium tuberculosis catalase-peroxidase (This enzyme shields bacteria from poisonous drug-like molecules) (PDB ID: 1sj2) using density functional theory method, QSAR study using material studio software and docking method via PyMol, AutoDock Tool, AutoDock Vina and Discovery studio 2017 as well as ADMET study via admetSAR2. Twelve descriptors were obtained from the optimized compounds which were used to develop valid QSAR model. More so, the binding affinity between 2-(quinoline-4-yloxy)acetamide analogues and Mycobacterium tuberculosis catalase-peroxidase (PDB ID: 1sj2) via docking method were reported. ADMET properties of some selected compounds were also examined.

Dataset on theoretical bio-evaluation of 1,2,4-thiadiazole-1,2,4-triazole analogues against epidermal growth factor receptor kinase down regulating human lung cancer.

Data from eight 1,2,4-thiadiazole-1,2,4-triazole derivatives were used to observe the anti-epidermal growth factor receptor kinase activities of 1,2,4-thiadiazole-1,2,4-triazole analogues thereby reducing human lung cancer. The software used to achieve this work were Spartan 14, Pymol, mgltools_win32_1.5.6, Auto dock vina and biovia2019.ds2019client. Also, the developed QSAR model was developed using the screened descriptors so as to inspect the closeness between the experimental IC50 and the predicted IC50. More so, the binding affinity from 1,2,4-thiadiazole-1,2,4-triazole derivatives - epidermal growth factor receptor kinase complexes using molecular docking approach were reported. Also, the ADMET properties for selected compounds and proposed compounds with better binding affinity were reported.

Dataset on in-silico investigation on triazole derivatives via molecular modelling approach: A potential glioblastoma inhibitors.

In this work, ten molecular compounds were optimised using density functional theory (DFT) method via Spartan 14. The obtained descriptors were used to develop quantitative structural activities relationship (QSAR) model using Gretl and Matlab software and the similarity between predicted IC50 and observed IC50 was investigated. Also, docking study revealed the non-bonding interactions between the studied compounds and the receptor. The molecular interactions between the observed ligands and brain cancer protein (PDB ID: 1q7f) were investigated. Adsorption, distribution, metabolism, excretion and toxicity (ADMET) properties were also investigated.

Dataset on Insilico approaches for 3,4-dihydropyrimidin-2(1H)-one urea derivatives as efficient Staphylococcus aureus inhibitor.

Series of anti- Staphylococcus aureus were studied via quantum chemical method and several molecular descriptors were obtained which were further used to develop QSAR model using back propagation neural network method using MATLAB. More so, the molecular interaction observed between 3,4-dihydropyrimidin-2(1H)-one Urea Derivatives and Staphylococcus aureus Sortase (PDB ID Code: 2kid) via docking was used as a screening tool for the studied compounds. The observed molecular compounds used in this work was also correlated to Lipinski rule of five and the developed QSAR model using selected descriptors from the optimized compounds was also examined for its predictability. Also, the observed molecular docking revealed the interaction between the studied complex.

Dataset on the DFT-QSAR, and docking approaches for anticancer activities of 1, 2, 3-triazole-pyrimidine derivatives against human esophageal carcinoma (EC-109).

The investigation of the novel hybrid, 1, 2, 3-triazole moiety combined with pyrimidine derivatives against human esophageal carcinoma is an unexplored field of theoretical/computational chemistry. Also, the development of new drugs still remains a major challenge, cost-intensive and time-consuming, thus making the computational approach now a hot topic due to its ability to hasten up and aid the process of drug designs. Here, the use of the quantum chemical method via density functional theory (DFT) was employed in calculating molecular descriptors for developing the quantitative structure-activity relation (QSAR) model which predicts bioactivity of the selected 1, 2, 3-triazole-pyrimidine derivatives. Quantum chemical method implemented in Spartan 14, was used in calculating the molecular descriptors. The obtained results were imputed into Gretl and SPSS (software package for social sciences) to generate a novel QSAR model equation for human esophageal carcinoma (EC-109) through multiple linear regression. The relationship between the experimental and predicted inhibition efficiency (IC50) of 1,2,3-triazole-pyrimidine with EC-109 was calculated which gives good correlation results. QSAR was validated using CV.R2 and R a 2 . Fitting value (R2) of 0.999 with an adjusted fitting value ( R a 2 ) of 0.995 was obtained and the result of validating QSAR performance gave CV.R2 and R a 2 value that is greater than 0.6, signifying its appropriateness and dependability. Molecular docking through simulation using Discovery Studio 4.1, Autodock Tool 1.5.6 and AutodockVina 1.1.2 was also carried out to calculate the free energy of ligand-receptor interactions as well as ligand conformation in the receptor-binding site. The results obtained revealed the presence of hydrogen bond interaction of the ligands with the amino acids residue in the binding sites of the receptor. Conformation of the ligands was essential property for binding ligand with the receptor. Critical examination and the correlations between the IC50 and binding energy showed the activeness of ligand conformation in the gouge of the receptor with binding energy greater than the 5-fluorouracil (5- Fu) that was used as the standard compound.

Green synthesis of copper oxide nanoparticles for biomedical application and environmental remediation.

Recent development in nanoscience and nanotechnology has contributed to the wide applications of metal and metal oxides nanoparticles in several field of sciences, research institutes and industries. Among all metal oxides, copper oxide nanoparticles (CuONPs) has gained more attention due to its distinctive properties and applications. The high cost of reagents, equipment and environmental hazards associated with the physical and chemical methods of synthesizing CuONPs has been a major setback. In order to puffer solution to the aforementioned challenges by reducing environmental pollution and production of cheaper nanoparticles with good properties and efficiency, this review focus on collection of comprehensive information from recent developments in the synthesis, characterization and applications from previous scientific findings on biological method of synthesizing CuONPs due to the acclaimed advantages of been cheap, environmentally friendly, convenient and possibility of been scale up in into large scale production reported by numerous researchers. Our finding also support the synthesis of CuONPs from plant sources due to relative abundance of plants for the production of reducing and stabilizing agents required for CuONPs synthesis, potential efficiency of plant biomolecules in enhancing the toxicity effect of CuONPs against microbes, prevention of environmental pollution due of nontoxic chemicals and degradation effectiveness of CuONPs synthesized from plant sources. Furthermore, this study provide useful information on the rapid synthesis of CuONPs with desired properties from plant extracts.

Stellaria media (L.) Vill.- A plant with immense therapeutic potentials: phytochemistry and pharmacology.

Stellaria media Vill. is a representative of Caryophyllaceae family. The plant is widely dispersed all over the world and has been used as therapeutic substance since time immemorial. This review is aimed at exploring the chemical constituents and pharmacological activities of S. media. The findings revealed important secondary metabolites such as flavonoid, oligosaccharide stellariose, anthraquinone derivatives, fatty acid, steroid saponins and phenolic compounds. These bioactive metabolites displayed diverse pharmacological activities such as anti-obesity, antifungal, antibacterial, antioxidant, anti-proliferative, anti-inflammatory, analgesic, antidiabetic and anxiolytic activities. All findings revealed that S. media is a major species of Caryophyllaceae family. However, bioactive constituents and pharmacological potential of are not well appraised. Hence, extracts with established pharmacological activities should be subjected to bioassay guided isolation so as to obtain compounds with novel structural moieties prior to toxicogenetic appraisals.

Theoretical calculations of molecular descriptors for anticancer activities of 1, 2, 3-triazole-pyrimidine derivatives against gastric cancer cell line (MGC-803): DFT, QSAR and docking approaches.

This work used quantum chemical method via DFT to calculate molecular descriptors for the development of QSAR model to predict bioactivity (IC50- 50% inhibition concentration) of the selected 1, 2, 3-triazole-pyrimidine derivatives against receptor (human gastric cancer cell line, MGC-803). The selected molecular parameters were obtained by B3LYP/6-31G∗∗. QSAR model linked the molecular parameters of the studied compounds to their cytotoxicity and reproduced their observed bioactivities against MGC-803. The calculated IC50 tailored the observed IC50 and greater than standard compound, 5-fluorouracil, suggesting that the developed QSAR model reproduced the observed bioactivity. Statistical analyses (including R2, CV. R2 and R a 2 gave 0.950, 0.970 and 0.844 respectively) revealed a very good fitness. Molecular docking studies revealed the hydrogen bonding with the amino acid residues in the binding site, as well as ligand conformations which are essential feature for ligand-receptor interactions. Therefore, the methods used in this study are veritable tools that can be employed in pharmacological and medicinal chemistry researches in designing better drugs with improve potency.