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Background: Plasmodium falciparum dihydroorotate dehydrogenase (PfDODH) is one of the enzymes currently explored in the treatment of malaria. Although there is currently no clinically approved drug targeting PfDODH, many of the compounds in clinical trials have [1, 2, 4,] triazolo [1, 5-a] pyrimidin- 7-amine backbone structure. Objective: This study sought to design new compounds from the fragments of known experimental inhibitors of PfDODH. Methods: Nine experimental compounds retrieved from Drug Bank online were downloaded and broken into fragments using the Schrodinger power shell; the fragments were recombined to generate new ligand structures using the BREED algorithm. The new compounds were docked with PfDODH crystal structure, after which the compounds were filtered with extensive drug-likeness and toxicity parameters. A 2D-QSAR model was built using the multiple linear regression method and externally validated. The electronic properties of the compounds were calculated using the density functional theory method. Results: Structural investigation of the six designed compounds, which had superior binding energies than the standard inhibitors, showed that five of them had [1, 2, 4,] triazolo [1, 5-a] pyrimidin-7-amine moieties and interacted with essential residues at the PfDODH binding site. In addition to their drug-like and pharmacokinetic properties, they also showed minimal toxicities. The externally validated 2D-QSAR model with R2 and Q2 values of 0.6852 and 0.6691 confirmed the inhibitory prowess of these compounds against PfDODH. The DFT calculations showed regions of the molecules prone to electrophilic and nucleophilic attacks. Conclusion: The current study thus provides insight into the development of a new set of potent PfDODH inhibitors.

Background: Oxidative stress is a significant player in the pathogenesis of diabetes mellitus and the Kelch-like ECH-associated protein1/nuclear factor erythroid 2-related factor 2/antioxidant response element (Keap1/Nrf2/ARE) signaling pathway serves as the essential defense system to mitigate oxidative stress. Nrf2 is responsible for the mitigation of oxidative stress while Keap1 represses Nrf2’s activation upon binding. Identification of Nrf2 activators has started to pick up enthusiasm as they can be used as therapeutic agents against diabetes mellitus. One of the ongoing mechanisms in the activation of Nrf2 is to disrupt Keap1/Nrf2 protein-protein interaction. This study aimed at using computational analysis to screen natural compounds capable of inhibiting Keap1/Nrf2 protein-protein interaction. Methods: A manual curated library of natural compounds was screened against crystal structure of Keap1 using glide docking algorithm. Binding free energy of the docked complexes, and adsorption, digestion, metabolism and excretion (ADME) properties were further employed to identify the hit compounds. The bioactivity of the identified hit against Keap1 was predicted using quantitative structure-activity relationship (QSAR) model. Results: A total of 7 natural compounds (Compound 222, 230, 310, 208, 210, 229 and 205) identified from different medicinal plants were found to be potent against Keap1 based on their binding affinity and binding free energy. The internal validated model kpls_radial_30 with R2 of 0.9109, Q2 of 0.7287 was used to predict the compounds’ bioactivities. Compound 205 was considered as the ideal drug candidate because it showed moderation for ADME properties, had predicted pIC50 of 6.614 and obeyed Lipinski’s rule of five. Conclusion: This study revealed that Compound 205, a compound isolated from Amphipterygium adstringens is worth considering for further experimental analysis.

Background: P-21 activating kinase 4 (PAK4) is implicated in the poor prognosis of many cancers, especially in the progression of Triple Negative Breast Cancer (TNBC). The present study was aimed at designing some potential drug candidates as PAK4 inhibitors for breast cancer therapy. Objective: This study aimed to finding novel inhibitors of PAK4 from natural compounds using computational approach. Methods: An e-pharmacophore model was developed from docked PAK4-co-ligand complex and used to screen over a thousand natural compounds downloaded from BIOFACQUIM and NPASS databases to match a minimum of 5 sites for selected (ADDDHRR) hypothesis. The robustness of the virtual screening method was accessed by well-established methods including EF, ROC, BEDROC, AUAC, and the RIE. Compounds with fitness score greater than one were filtered by applying molecular docking (HTVS, SP, XP and Induced fit docking) and ADME prediction. Using Machine learning-based approach QSAR model was generated using Automated QSAR. The computed top model kpls_des_17 (R2= 0.8028, RMSE = 0.4884 and Q2 = 0.7661) was used to predict the pIC50 of the lead compounds. Internal and external validations were accessed to determine the predictive quality of the model. Finally, the binding free energy calculation was computed. Results: The robustness/predictive quality of the models was affirmed. The hits had better binding affinity than the reference drug and interacted with key amino acids for PAK4 inhibition. Overall, the present analysis yielded three potential inhibitors that are predicted to bind with PAK4 better than the reference drug tamoxifen. The three potent novel inhibitors, vitexin, emodin and ziganein recorded IFD score of -621.97 kcal/mol, -616.31 kcal/mol and -614.95 kcal/mol, respectively while showing moderation for ADME properties and inhibition constant. Conclusion: It is expected that the findings reported in this study may provide insight for designing effective and less toxic PAK4 inhibitors for triple negative breast cancer.

Background: The recent outbreak of Coronavirus SARS-CoV-2 (Covid-19), which has rapidly spread around the world in about three months with tens of thousands of deaths recorded so far is a global concern. An urgent need for potential therapeutic intervention is of necessity. Mpro is an attractive druggable target for the development of anti-COVID-19 drug development. Methods: Compounds previously characterized by Melissa officinalis were queried against the main protease of coronavirus SARS-CoV-2 using a computational approach. Results: Melitric acid A and salvanolic acid A had higher affinity than lopinavir and ivermectin using both AutodockVina and XP docking algorithms. The computational approach was employed in the generation of the QSAR model using automated QSAR, and in the docking of ligands from Melissa officinalis with SARS-CoV-2 Mpro inhibitors. The best model obtained was KPLS_Radial_ 28 (R2 = 0.8548 and Q2=0.6474, which was used in predicting the bioactivity of the lead compounds. Molecular mechanics based MM-GBSA confirmed salvanolic acid A as the compound with the highest free energy and predicted bioactivity of 4.777; it interacted with His-41 of the catalytic dyad (Cys145-His41) of SARS-CoV-2 main protease (Mpro), as this may hinder the cutting of inactive viral protein into active ones capable of replication. Conclusion: Salvanolic acid A can be further evaluated as a potential Mpro inhibitor.

Background: In a bid to come up with effective compounds as inhibitors for antimalarial treatment, we built a library of 2,000 traditional Chinese medicine(TCM)-derived compounds retrieved from TCM Database@Taiwan. Methods: The active sites of both the wild type and mutant Plasmodium falciparum dihydrofolatereductase (pfDHFR) were explored using computational tools. pfDHFR, one of the prime drug targets in the prevention of malaria infection induced by the female anopheles mosquito has continued to offer resistance to drugs (antifolates) due to mutation in some of the key amino acid residues crucial for its inhibition. Results: We utilized virtual throughput screening and glide XP docking to screen the compounds, and 8 compounds were found to have promising docking scores with both the wild type and mutant pfDHFR. They were further subjected to Induce Fit Docking (IFD) to affirm their inhibitory potency. The ADME properties and biological activity spectrum of the compounds were also considered. The inhibition profile of the compounds revealed that a number of compounds formed intermolecular interactions with ASP54, ILE14, LEU164, SER108/ASN108, ARG122 and ASP58. Most of the compounds can be considered as drug candidates due to their antiprotozoal activities and accordance with the Lipinski’s Rule of Five (ROF). Conclusion: The outcome of the present study should further be investigated to attest the efficacy of these compounds as better drug candidates than the antifolates.