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This study investigates the antidiabetic effect of a ketogenic diet (KD) on sucrose-induced insulin resistance in the fruit fly model. The fruit flies were divided and grouped into four: Group A, B, C, and D, representing the control, high-sucrose diet (HSD), KD, and HSD + KD, respectively. The administration of the various treatments to the groups proceeded for 7 days. The flies were thereafter immobilized, homogenized, and the homogenates used for biochemical parameters determination. This includes glucose concentration, antioxidant status, 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase, total cholesterol (TC), triglycerides (TG), and protein concentration. There was a significant increase (p < .05) in weight gain, glucose concentration, TG, HMG-CoA reductase activity, TC, and lipid peroxidation status of the HSD group compared with the control and KD groups. The antioxidant enzymes measured (superoxide dismutase, catalase, and reduced glutathione) and protein concentrations were repressed significantly (p < .05) in the HD groups but significantly elevated (p < .05) in the KD, HSD + KD, and the control groups. The KD improved biochemical parameters altered during the onset of sucrose-induced insulin resistance. With further research on this, KD may emerge as the much-awaited treatment option for diabetes mellitus type 2 (T2DM) with almost reduced toxicity concerns. PRACTICAL APPLICATIONS: Novel KD are sources of dietary phytocompounds with proven antioxidant activities. The antidiabetic activity of the KD was investigated. The results showed that the KD proves to serve as a better effective antidiabetic option in Drosophila melanogaster. The observed results could provide the potential application of the KD as an alternative therapy for diabetes management.

This study determines the contraceptive activity of Allium sativa (Garlic) and Allium cepa (Onion) juices on reproductive output and development of Drosophila melanogaster. The fruit flies were divided and grouped into 5, group A serves as the control, group B serves as the onion group, group C serves as the garlic group, group D serves as the onion + garlic group, while group E serves as the standard contraceptive group. Biochemical parameters measured were superoxide dismutase (SOD), Catalase (CAT), Glutathione-S-transferase (GST), malondialdehyde (MDA), nitric oxide (NO), total cholesterol (TC), triglyceride, mating test, and negative geotaxis. There was a significant reduction in the levels of MDA in onion, garlic, onion + garlic groups when compared with the control, in contrast, a significant increase was observed in SOD, CAT, and GST activities. Furthermore, there was a significant reduction in nitric oxide levels in garlic, onion + garlic extract with a corresponding increase in the standard contraceptive group. There was a significant reduction in the concentration of TC and HMG-CoA in garlic and standard contraceptive groups when compared with the control while triglyceride revealed a considerable increase in the garlic group when compared with the control. The mating test showed there was a considerable reduction in the onion, garlic, onion + garlic, and standard contraceptive when compared with the control. Taken together, Allium sativum proved to serve as a better contraceptive in D. melanogaster as a possible effective option for contraceptives, which is further, supported by their strong antioxidant activity. PRACTICAL APPLICATIONS: A. cepa and A. sativum are sources of dietary phytocompounds with proven antioxidant activities. The contraceptive activity of A. cepa and A. sativum juice extract was investigated. The results showed that A. cepa and A. sativum and their combination prove to serve as a better effective option for contraceptives in D. melanogaster. The observed results could provide the potential application of A. cepa and A. sativum as an alternative therapy for contraceptives.

Erectile dysfunction (ED) is one of the main challenges occurring among men worldwide, and is characterised by trouble getting or keeping steady erection during sexual intercourse. Various drugs like sildenafil, a phosphodiesterase-5 inhibitor (PDE-5) are freely available in the pharmacies, though normally associated with several adverse. This study was designed to assess the molecular relations obtainable between catechin, garcinal, garcinoic acid and d-tocotrienol compounds isolated from Garcinia kola and targeted receptor linked to ED. These processes include the molecular docking of catechin, garcinal, garcinoic acid, d-tocotrienol, and sildenafil to receptor: PDE-5 via AutoDock Vina. Following the docking of catechin, garcinal, garcinoic acid and d-tocotrienol with the PDE-5-receptor protein, we observed that all are protein inhibitors with garcinoic acid showing better binding affinity -10.0 kcal/mol with PDE-5 receptor relevant to ED. Hence, the results provided insights into the development of garcinoic acid as a replacement for present ED management, with further analysis worth considering.

Neurodegenerative diseases, for example Alzheimer’s, are perceived as driven by hereditary, cellular, and multifaceted biochemical actions. Numerous plant products, for example flavonoids, are documented in studies for having the ability to pass the blood-brain barrier and moderate the development of such illnesses. Computer-aided drug design (CADD) has achieved importance in the drug discovery world, innovative developments in the aspects of structure identification and characterization, bio-computational science, and molecular biology have added to the preparation of new medications towards these ailments. In this study we evaluated nine flavonoid compounds identified from three medicinal plants, namely T. diversifolia, B. sapida, and I. gabonensis for their inhibitory role on acetylcholinesterase (AChE), butyrylcholinesterase (BChE) and monoamine oxidase (MAO) activity, using pharmacophore modeling, auto-QSAR prediction, and molecular studies, in comparison with standard drugs. The results indicated that the pharmacophore models produced from structures of AChE, BChE and MAO could identify the active compounds, with a recuperation rate of the actives found near 100% in the complete ranked decoy database. Moreso, the robustness of the virtual screening method was accessed by well-established methods including enrichment factor (EF), receiver operating characteristic curve (ROC), Boltzmann-enhanced discrimination of receiver operating characteristic (BEDROC), and area under accumulation curve (AUAC). Most notably, the compounds’ pIC50 values were predicted by a machine learning-based model generated by the AutoQSAR algorithm. The generated model was validated to affirm its predictive model. The best models achieved for AChE, BChE and MAO were models kpls_radial_17 (R2 = 0.86 and Q2 = 0.73), pls_38 (R2 = 0.77 and Q2 = 0.72), kpls_desc_44 (R2 = 0.81 and Q2 = 0.81) and these externally validated models were utilized to predict the bioactivities of the lead compounds. The binding affinity results of the ligands against the three selected targets revealed that luteolin displayed the highest affinity score of −9.60 kcal/mol, closely followed by apigenin and ellagic acid with docking scores of −9.60 and −9.53 kcal/mol, respectively. The least binding affinity was attained by gallic acid (−6.30 kcal/mol). The docking scores of our standards were −10.40 and −7.93 kcal/mol for donepezil and galanthamine, respectively. The toxicity prediction revealed that none of the flavonoids presented toxicity and they all had good absorption parameters for the analyzed targets. Hence, these compounds can be considered as likely leads for drug improvement against the same.

Type-2 diabetes mellitus (T2DM), is considered being a multifaceted disorder that presents a major therapeutic problem. Despite the widespread efforts in managing T2DM, drug discovery therapies remain insufficient. There are several new and vital antidiabetic drug agents under examination of many research clusters. Computational tools have influenced drug discovery at several levels. Hence, this study aimed to explain the molecular interactions via an in silico simulation approach between Aframomum melegueta seed-derived compounds as antidiabetic agents against carbohydrate metabolism regulatory target proteins (DPP-4, GSK-3, and GLP-1) involved in T2DM. Pharmacophore modeling, Auto-QSAR, induced-fit docking (IFD) simulation, free energy of binding affinity through the MM-GBSA method, and molecular docking were used to sort out the compounds as well as determining their drug ability. The results revealed the pharmacophore models created from the structures of DPP-4, GSK-3, and GLP-1 could determine the lead candidates with a restorative ability rate found near 100% of the actives in the comprehensive decoy database ranking. We predicted the pIC50 values of the compounds via a learning-based machine that was created by auto-QSAR. We authenticated the created model to confirm its analytical procedure. The greatest models attained for DPP-4, GSK-3, and GLP-1 were kpls_desc_35 (R2 = 0.73 and Q2 = 0.73), kpls_desc_4 (R2 = 0.72 and Q2 = 0.66), and kpls_radical_14 (R2 = 0.88 and Q2 = 0.64) and these confirmed models were used to predict the bioactivities of the hit candidates. While several isolated bioactive compounds from Aframomum melegueta revealed a better binding affinity score, binding free energy along with observance of RO5, only three compounds (ethinyl estradiol, 8-gingerol, and zingerone) revealed a more satisfactory pIC50. Thus, these compounds can be novel candidates for drug discovery in diabetes treatment.