Identification of allosteric inhibitor against AKT1 through structure-based virtual screening.

AKT (serine/threonine protein kinase) is a potential therapeutic target for many types of cancer as it plays a vital role in cancer progression. Many AKT inhibitors are already in practice under single and combinatorial therapy. However, most of these inhibitors are orthosteric / pan-AKT that are non-selective and non-specific to AKT kinase and their isoforms. Hence, researchers are searching for novel allosteric inhibitors that bind in the interface between pH and kinase domain. In this study, we performed structure-based virtual screening from the afroDB (a diverse natural compounds library) to find the potential inhibitor targeting the AKT1. These compounds were filtered through Lipinski, ADMET properties, combined with a molecular docking approach to obtain the 8 best compounds. Then we performed molecular dynamics simulation for apoprotein, AKT1 with 8 complexes, and AKT1 with the positive control (Miransertib). Molecular docking and simulation analysis revealed that Bianthracene III (hit 1), 10-acetonyl Knipholonecyclooxanthrone (hit 2), Abyssinoflavanone VII (hit 5) and 8-c-p-hydroxybenzyldiosmetin (hit 6) had a better binding affinity, stability, and compactness than the reference compound. Notably, hit 1, hit 2 and hit 5 had molecular features required for allosteric inhibition.

Cheminformatics-Based Identification of Potential Novel Anti-SARS-CoV-2 Natural Compounds of African Origin.

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome virus 2 (SARS-CoV-2) has impacted negatively on public health and socioeconomic status, globally. Although, there are currently no specific drugs approved, several existing drugs are being repurposed, but their successful outcomes are not guaranteed. Therefore, the search for novel therapeutics remains a priority. We screened for inhibitors of the SARS-CoV-2 main protease and the receptor-binding domain of the spike protein from an integrated library of African natural products, compounds generated from machine learning studies and antiviral drugs using AutoDock Vina. The binding mechanisms between the compounds and the proteins were characterized using LigPlot+ and molecular dynamics simulations techniques. The biological activities of the hit compounds were also predicted using a Bayesian-based approach. Six potential bioactive molecules NANPDB2245, NANPDB2403, fusidic acid, ZINC000095486008, ZINC0000556656943 and ZINC001645993538 were identified, all of which had plausible binding mechanisms with both viral receptors. Molecular dynamics simulations, including molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) computations revealed stable protein-ligand complexes with all the compounds having acceptable free binding energies <-15 kJ/mol with each receptor. NANPDB2245, NANPDB2403 and ZINC000095486008 were predicted as antivirals; ZINC000095486008 as a membrane permeability inhibitor; NANPDB2403 as a cell adhesion inhibitor and RNA-directed RNA polymerase inhibitor; and NANPDB2245 as a membrane integrity antagonist. Therefore, they have the potential to inhibit viral entry and replication. These drug-like molecules were predicted to possess attractive pharmacological profiles with negligible toxicity. Novel critical residues identified for both targets could aid in a better understanding of the binding mechanisms and design of fragment-based de novo inhibitors. The compounds are proposed as worthy of further in vitro assaying and as scaffolds for the development of novel SARS-CoV-2 therapeutic molecules.

Virtual screening, MMGBSA, and molecular dynamics approaches for identification of natural products from South African biodiversity as potential Onchocerca volvulus pi-class glutathione S-transferase inhibitors.

We investigated 1012 molecules from natural products previously isolated from the South African biodiversity (SANCDB, https://sancdb.rubi.ru.ac.za/), for putative inhibition of Onchocerca volvulus pi-class glutathione S-transferase (Ov-GST2) by virtual screening, MMGBSA, and molecular dynamics approaches. ADMET, docking, and MMGBSA shortlisted 12 selected homoisoflavanones-type hit molecules, among which two namely SANC00569, and SANC00689 displayed high binding affinities of -46.09 and -46.26 kcal mol-1, respectively towards π-class Ov-GST2, respectively. The molecular dynamics results of SANC00569 showed the presence of intermolecular H-bonding, hydrophobic interactions between the ligand and key amino acids of Ov-GST2, throughout the simulation period. This hit molecule had a stable binding pose and occupied the binding pockets throughout the 200 ns simulation. To the best of our knowledge, there is no report of any alleged anti-onchocerciasis activity referring to homoisoflavanones or flavonoids. Nevertheless, homoisoflavanones, which are a subclass of flavonoids, exhibit a plethora of biological activities. All these results led to the conclusion that SANC00569 is the most hypothetical Ov-GST2, which could lead the development of new drugs against Onchocerca volvulus pi-class glutathione S-transferase. Further validation of these findings through in vitro and in vivo studies is required.

Identification of promising high-affinity inhibitors of SARS-CoV-2 main protease from African Natural Products Databases by Virtual Screening.

With the rapid spread of the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen agent of COVID-19 pandemic created a serious threat to global public health, requiring the most urgent research for potential therapeutic agents. The availability of genomic data of SARS-CoV-2 and efforts to determine the protein structure of the virus facilitated the identification of potent inhibitors by using structure-based approach and bioinformatics tools. Many pharmaceuticals have been proposed for the treatment of COVID-19, although their effectiveness has not been assessed yet. However, it is important to find out new-targeted drugs to overcome the resistance concern. Several viral proteins such as proteases, polymerases or structural proteins have been considered as potential therapeutic targets. But the virus target must be essential for host invasion match some drugability criterion. In this Work, we selected the highly validated pharmacological target main protease Mpro and we performed high throughput virtual screening of African Natural Products Databases such as NANPDB, EANPDB, AfroDb, and SANCDB to identify the most potent inhibitors with the best pharmacological properties. In total, 8753 natural compounds were virtually screened by AutoDock vina against the main protease of SARS-CoV-2. Two hundred and five (205) compounds showed high-affinity scores (less than - 10.0 Kcal/mol), while fifty-eight (58) filtered through Lipinski's rules showed better affinity than known Mpro inhibitors (i.e., ABBV-744, Onalespib, Daunorubicin, Alpha-ketoamide, Perampanel, Carprefen, Celecoxib, Alprazolam, Trovafloxacin, Sarafloxacin, Ethyl biscoumacetate…). Those promising compounds could be considered for further investigations toward the developpement of SARS-CoV-2 drug development.

Ensemble-based virtual screening of African natural products to target human thymidylate synthase.

Human thymidylate synthase (hTS) is a validated drug target for chemotherapy. A virtual screening experiment was used to prioritize a list of compounds from African Natural Products Databases docked against the orthosteric binding pocket of hTS. Consensus scores of binding affinities from ensemble-based virtual screening, hydrated docking and MM-PBSA calculations ranked compounds NEA4433 and NEA4434 as the best candidates owing to binding affinity scores in the picomolar order, their excellent ADMET profiles and the good stability of the protein-ligand complexes formed. The current study demonstrates the role of water in small molecule binding to hTS in mediating protein-ligand interactions. Similarly, the robust ensemble docking (relaxed scheme complex) ranked NEA4433 and NEA4434 as the best candidates. Furthermore, the best candidates prioritized were shown to strongly interact with the same residues that interacted with hTS substrate and cofactor.

The Discovery of Potential SARS-CoV-2 Natural Inhibitors among 4924 African Metabolites Targeting the Papain-like Protease: A Multi-Phase In Silico Approach.

Four compounds, hippacine, 4,2'-dihydroxy-4'-methoxychalcone, 2',5'-dihydroxy-4-methoxychalcone, and wighteone, were selected from 4924 African natural metabolites as potential inhibitors against SARS-CoV-2 papain-like protease (PLpro, PDB ID: 3E9S). A multi-phased in silico approach was employed to select the most similar metabolites to the co-crystallized ligand (TTT) of the PLpro through molecular fingerprints and structural similarity studies. Followingly, to examine the binding of the selected metabolites with the PLpro (molecular docking. Further, to confirm this binding through molecular dynamics simulations. Finally, in silico ADMET and toxicity studies were carried out to prefer the most convenient compounds and their drug-likeness. The obtained results could be a weapon in the battle against COVID-19 via more in vitro and in vivo studies.

Pharmacoinformatics-based identification of potential bioactive compounds against Ebola virus protein VP24.

BACKGROUND: The impact of Ebola virus disease (EVD) is devastating with concomitant high fatalities. Currently, various drugs and vaccines are at different stages of development, corroborating the need to identify new therapeutic molecules. The VP24 protein of the Ebola virus (EBOV) plays a key role in the pathology and replication of the EVD. The VP24 protein interferes with the host immune response to viral infections and promotes nucleocapsid formation, thus making it a viable drug target. This study sought to identify putative lead compounds from the African flora with potential to inhibit the activity of the EBOV VP24 protein using pharmacoinformatics and molecular docking. METHODS: An integrated library of 7675 natural products originating from Africa obtained from the AfroDB and NANPDB databases, as well as known inhibitors were screened against VP24 (PDB ID: 4M0Q) utilising AutoDock Vina after energy minimization using GROMACS. The top 19 compounds were physicochemically and pharmacologically profiled using ADMET Predictor™, SwissADME and DataWarrior. The mechanisms of binding between the molecules and EBOV VP24 were characterised using LigPlot+. The performance of the molecular docking was evaluated by generating a receiver operating characteristic (ROC) by screening known inhibitors and decoys against EBOV VP24. The prediction of activity spectra for substances (PASS) and machine learning-based Open Bayesian models were used to predict the anti-viral and anti-Ebola activity of the molecules, respectively. RESULTS: Four natural products, namely, ZINC000095486070, ZINC000003594643, ZINC000095486008 and sarcophine were found to be potential EBOV VP24-inhibitiory molecules. The molecular docking results showed that ZINC000095486070 had high binding affinity of -9.7 kcal/mol with EBOV VP24, which was greater than those of the known VP24-inhibitors used as standards in the study including Ouabain, Nilotinib, Clomiphene, Torimefene, Miglustat and BCX4430. The area under the curve of the generated ROC for evaluating the performance of the molecular docking was 0.77, which was considered acceptable. The predicted promising molecules were also validated using induced-fit docking with the receptor using Schrödinger and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations. The molecules had better binding mechanisms and were pharmacologically profiled to have plausible efficacies, negligible toxicity as well as suitable for designing anti-Ebola scaffolds. ZINC000095486008 and sarcophine (NANPDB135) were predicted to possess anti-viral activity, while ZINC000095486070 and ZINC000003594643 to be anti-Ebola compounds. CONCLUSION: The identified compounds are potential inhibitors worthy of further development as EBOV biotherapeutic agents. The scaffolds of the compounds could also serve as building blocks for designing novel Ebola inhibitors.