BACKGROUND: Pain is a common symptom that is managed in both outpatients and inpatients. There are many side effects associated with opioids such as respiratory depression, constipation, hyperalgesia, and tolerance. Non- steroidal anti-inflammatory drugs cause gastrointestinal tract (GIT) irritation and may be a risk factor for developing peptic ulcer disease. This study aimed to generate active analgesic agents from known analgesics, determine the docking scores of these agents to their receptors, determine the pharmacokinetic properties of these agents, and evaluate their toxicity profiles. METHODS: PubChem was used to download smiles for ibuprofen, aspirin and celecoxib. Avogadro optimized the ligands. The smiles were copied to SwissSimilarity and were used as query compounds to generate zinc compounds. DrugBank and Protein Data Bank were used to download cyclooxygenase 1 and 2. Molecular docking was done using Chimera and Autodock Vina. Smiles for both query compounds and generated zinc compounds were pasted onto the Protox II webserver and SwissADME for toxicity and pharmacokinetics properties determination. The data was presented in tabular forms with textual descriptions of the contents in the tables. RESULTS: Aspirin, ibuprofen and celecoxib’s zinc compounds were generated and the first 20 compounds were docked to COX-1 and COX-2 enzymes. Seven, one, and four of the docked compounds showed better binding energies to COX-2 than COX-1. The zinc compounds were analyzed for toxicity profiles. ZINC01680731 and ZINC33823423 were predicted to have LD50 of 1240 mg/kg as compared to aspirin’s 250mg/kg. Ibuprofen and ZINC39120409 showed LD50 of 299mg/kg and they were hepatoactive. Celecoxib and four of its zinc compounds showed LD50 of 1400mg/kg. All compounds had high GIT absorption and they conformed with Lipinski rule of five. CONCLUSIONS: ZINC01680731 0.994 and ZINC00600558 0.988 were identified as the best compounds as they showed better binding affinities, toxicities and pharmacokinetics properties compared to standard compounds.

Introduction: Use of natural products for management of diseases has increased widely due to the belief that natural products are less toxic than conventional medicines. Natural products have been utilised for management of chronic diseases such as diabetes and cancers. Respiratory infections have also been managed using natural products. Allium sativum is one of the natural products that has been utilised in the management of SARS-CoV infections, diabetes and cancer. Methods: This study was aimed at screening bioactive agents in Allium sativum using computational analysis. The targets of the bioactive agents were predicted using SwissTargetPrediction tools. Molecular docking followed, where the docking energies of the bioactive agents to the targets were generated. The bioactive agents were analysed for pharmacokinetics properties using SwissADME as well as toxicity profiles using the ProTox II webserver. The docking scores, toxicities and pharmacokinetics profiles of the bioactive agents in Allium sativum were compared with those of reference compounds. Results: All the bioactives showed lower docking scores than the reference compounds. The bioactives, however, showed some activity on specific receptors such as carbonic anhydrases, cyclooxygenase and ghrelin. All the bioactives showed high gastrointestinal tract absorption and none violated Lipinski’s rule of five. Diallyl trisulphide was predicted to be most lethal, with an LD50 of 100mg/kg, while was the safest, with 8000mg/kg. Conclusions: In conclusion, bioactives showed lower docking scores than the reference compounds, therefore overall pharmacological activity could be attributed to synergy between the bioactives for a particular receptor.

Both qualitative and quantitative studies were done in this study. Quantitative data was generated in form of binding energies when binding of ligands to the receptors as well as probability scores in toxicity profiles predictions. Qualitative data was generated from pharmacokinetics predictions using SwissADME. This tool assessed the chance of a molecule to have drug–likeness, which is an important parameter when evaluating the chance of high bioavailability with oral drugs. Drug-likeness is the physico-chemical and structural features desired and SWISS ADME analysed these properties based on the Lipinski rule of five. Qualitative data therefore, was generated in form of ‘yes or no ‘in determining the inhibitors of the cytochrome P450 enzymes as well as substrates of p-glycoprotein efflux system.

Introduction: Paracetamol is the most used drug for the management of pain and as an antipyretic through its mechanism of action on Cox 1,2 and 3 receptors. Paracetamol is a lipid-soluble molecule that can pass through the Blood Brain Barrier. Paracetamol has been formulated differently to ensure the optimal onset and duration of action as both analgesic and as antipyretic. Paracetamol overdose is associated with major side effects such as liver damage through its metabolite N-acetyl-p-benzoquinone Imine. Methods: This study generated zinc compounds that are similar in structure to Paracetamol through Ligand-based virtual screening. Molecular docking of these compounds to Cox 1, 2, and 3 receptors followed through Structure-based virtual screening. Compounds with better docking scores to these receptors were analyzed for pharmacokinetics and toxicity profiles. Results: ZINC01714506; 0.986; ZINC01714507; 0.986; and ZINC00394165; 0.987 showed the highest docking scores to cox 3 receptor with probability scores of -6.7kcal/mol, -6.4 and -6.2 kcal/ mol as compared to Paracetamol with -5.3kcal/mol. ZINC01714507; 0.986; ZINC01714506; 0.986; and ZINC00394165; 0.987; showed higher docking scores to Cox 2 with docking scores of -8.3kcal.mol, -8.1kcal/mole and -8.0 kcal/mol compared to paracetamol with -6.6kcal/mol. ZINC00394165; 0.987; ZINC00406627; 0.980; and ZINC01714506; 0.986; showed highest docking scores to Cox-1 than paracetamol  with scores of -7.7kcal/mol, -7.6 and-7.6kcal/mol. ZINC01714506; 0.986 was predicted the safest with oral LD50 of 2000mg/kg as compared to paracetamol’s 338mg/kg. ZINC00294715; 0.980, ZINC01747085; 0.985, ZINC00394165; 0.987, ZINC00406627; 0.980, ZINC01557001; 0.987 and ZINC19281575; 0.992 were predicted hepatoactive. ZINC00294715; 0.980; ZINC01557001; 0.987; and ZINC19281575; 0.992; lack Blood Brain Barrier permeation. All compounds showed high GIT absorption and all conform to Lipinski’s rule of five. Conclusion: ZINC01557001; 0.987; ZINC01714506; 0.986; ZINC34120167; 0.994; ZINC00394165; 0.987, ZINC01714507; 0.986; and ZINC01747085; 0.985; are promising in drug discovery for new analgesic and antipyretic drugs, based on better docking scores and better oral LD50