Performance prediction of polypeptide derivatives as efficient potential microbial inhibitors: a computational approach.

Objective: Lately, various scientists have been paying a lot of consideration to the design of operational antimicrobial agents due to the rise of multiple drug-resistant strains. Therefore, this work is aimed at discovering the biochemical behavior of the analyzed polypeptides in relation to glutamine amidotransferase GatD (pdb id: 5n9m) for gram positive bacteria and beta-lactamase class A (pdb id: 5fqq) for gram negative bacteria. Additionally, this study aims to identify the specific atoms involved in the observed biochemical interactions between the studied complexes using computational methods.

Computational screening of phytochemicals present in some Nigerian medicinal plants against sickle cell disease.

Four hundred Phytochemical (bio-active) compounds having predictive activity for treating Sickle Cell Anemia were screened, using PASS online computational resource. Twenty-six compounds out of the four hundred compounds which showed high probability for treating sickle were further screened for pharmacokinetics profiles (ADMET properties) using SwissAdmet, AdmetSAR 2 and Pro-tox II online resources. Only thirteen compounds that displayed good ADMET properties from the twenty-six were further used for DFT calculations and molecular docking against carbonmonoxy sickle hemoglobin (PDB ID: 5E6E).

Hybrid Molecules Containing Methotrexate, Vitamin D, and Platinum Derivatives: Synthesis, Characterization, In Vitro Cytotoxicity, In Silico ADME Docking, Molecular Docking and Dynamics.

Designing hybrid-based drugs is one promising strategy for developing effective anticancer drugs that explore combination therapy to enhance treatment efficacy, overcome the development of drug resistance, and lower treatment duration. Bisphosphonates and Vitamin D are commonly administered drugs for the treatment of bone diseases and the prevention of bone metastases. Platinum-based and methotrexate are widely used anticancer drugs in clinics.

evaluation on potential 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.

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.

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 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.

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

The anti-NS2B-NS3 proteases activities of L. were investigated via the data obtained from selected bioactive compounds from L. The work was investigated using approach and the series of computational software were used to execute the task.

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.

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

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.

Dataset on 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 IC and observed IC was investigated. Also, docking study revealed the non-bonding interactions between the studied compounds and the receptor.

Dataset on 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 Sortase (PDB ID Code: ) 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.

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.

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.

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

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.

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 (IC- 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.