High-throughput virtual screening of Streptomyces spp. metabolites as antiviral inhibitors against the Nipah virus matrix protein.

Nipah virus (NiV) remains a significant global concern due to its impact on both the agricultural industry and human health, resulting in substantial economic and health consequences. Currently, there is no cure or commercially available vaccine for the virus. Therefore, it is crucial to prioritize the discovery of new and effective treatment options to prevent its continued spread. Streptomyces spp. are rich sources of metabolites known for their bioactivity against certain diseases; however, their potential as antiviral drugs against the Nipah virus remain unexplored. In this study, 6524 Streptomyces spp. metabolites were screened through in silico methods for their inhibitory effects against the Nipah virus matrix (NiV-M) protein, which assists in virion assembly of Nipah virus. Different computer-aided tools were utilized to carry out the virtual screening process: ADMET profiling revealed 913 compounds with excellent safety and efficacy profiles, molecular docking predicted the binding poses and associated docking scores of the ligands in their respective targets, MD simulations confirmed the binding stability of the top ten highest-scoring ligands in a 100 ns all-atom simulation, PCA elucidated simulation convergence, and MMPB(GB)SA calculations estimated the binding energies of the final candidate compounds and determined the key residues crucial for complex formation. Using in silico methods, we identified six metabolites targeting the main substrate-binding site and five targeting the dimerization site that exhibited excellent stability and strong binding affinity. We recommend testing these compounds in the next stages of drug development to confirm their effectiveness as therapeutic agents against Nipah virus.

From antibiotic to antiviral: computational screening reveals a multi-targeting antibiotic from Streptomyces spp. against Nipah virus fusion proteins.

Nipah Virus is a re-emerging zoonotic paramyxovirus that poses a significant threat to both swine industry and human health. The pursuit of potential antiviral agents with both preventive and therapeutic properties holds promise for targeting such viruses. To expedite this search, leveraging computational biology is essential. Streptomyces is renowned for its capacity to produce large and diverse metabolites with promising bioactivities. In the current study, we conducted a comprehensive structure-based virtual screening of 6524 Streptomyces spp. metabolites sourced from the StreptomeDB database to evaluate their potential inhibitory effects on three Nipah virus fusion (NiVF) protein conformations: NiVF pre-fusion 1-mer (NiVF-1mer), pre-fusion 3-mer (NiVF-3mer), and NiVF post-fusion (NiVF-PoF). Prior to virtual screening, the drug-likeness of Streptomyces spp. compounds was profiled using ADMET properties. From the 913 ADMET-filtered compounds, the subsequent targeted and confirmatory blind docking analysis revealed that S896 or virginiamycin M1, a known macrolide antibiotic, showed a maximum binding affinity with the NiVF proteins, suggesting a multi-targeting inhibitory property. In addition, the 200-ns molecular dynamics simulation and MM/PBSA analyses revealed stable and strong binding affinity between the NiVF-S896 complexes, indicating favorable interactions between S896 and the target proteins. These findings suggest the potential of virginiamycin M1, an antibiotic, as a promising multi-targeting antiviral drug. However, in vitro and in vivo experimental validations are necessary to assess their safety and efficacy.

In silico identification of multi-target inhibitors from medicinal fungal metabolites against the base excision repair pathway proteins of African swine fever virus.

African swine fever virus (ASFV) has emerged as a serious threat to the pork industry resulting in significant economic losses and heightened concerns about food security. With no known cure presently available, existing control measures center on animal quarantine and culling. Considering the severity and challenges posed by ASFV, it is imperative to discover new treatment strategies and implement additional measures to prevent its further spread. This study recognized the potential of 1830 fungal metabolites from medicinal fungi as antiviral compounds against base excision repair (BER) proteins of ASFV, specifically ASFVAP, ASFVPolX, and ASFVLig. A wide array of computer-aided drug discovery techniques were employed to carry out the virtual screening process: ADMET profiling revealed 319 molecules with excellent bioavailability and toxicity properties; consensus docking identified the 10 best-scoring ligands against all targets; molecular dynamics simulation elucidated the stability of the protein-ligand complexes; and MM/PB(GB)SA energy calculations predicted the binding energies of the compounds as well as the key residues integral to binding. Through in silico methods, we identified two theoretical lead candidates against ASFVAP, four against ASFVLig, and five against ASFVPolX. Two compounds, methyl ganoderate E and antcamphin M, exhibited potential multi-target inhibitory characteristics against ASFVPolX and ASFVLig, while compound cochlactone A showed promising antagonistic results against all three BER proteins. It is recommended to prioritize these hit compounds in future in vitro and in vivo studies to validate their potential as antiviral drugs against ASFV.

In Silico Screening and Identification of Antidiabetic Inhibitors Sourced from Phytochemicals of Philippine Plants against Four Protein Targets of Diabetes (PTP1B, DPP-4, SGLT-2, and FBPase).

Current oral medications for type 2 diabetes target a single main physiological mechanism. They either activate or inhibit receptors to enhance insulin sensitivity, increase insulin secretion, inhibit glucose absorption, or inhibit glucose production. In advanced stages, combination therapy may be required because of the limited efficacy of single-target drugs; however, medications are becoming more costly, and there is also the risk of developing the combined side effects of each drug. Thus, identifying a multi-target drug may be the best strategy to improve treatment efficacy. This study sees the potential of 2657 Filipino phytochemicals as a source of natural inhibitors against four targets of diabetes: PTP1B, DPP-4, SGLT-2, and FBPase. Different computer-aided drug discovery techniques, including ADMET profiling, DFT optimization, molecular docking, MD simulations, and MM/PBSA energy calculations, were employed to elucidate the stability and determine the binding affinity of the candidate ligands. Through in silico methods, we have identified seven potential natural inhibitors against PTP1B, DPP-4, and FBPase, and ten against SGLT-2. Eight plants containing at least one natural inhibitor of each protein target were also identified. It is recommended to further investigate the plants' potential to be transformed into a safe and scientifically validated multi-target drug for diabetes therapies.

In-silico screening and identification of phytochemicals from Centella asiatica as potential inhibitors of sodium-glucose co-transporter 2 for treating diabetes.

Sodium-glucose co-transporter 2 (SGLT-2) is a major transport protein responsible for reabsorption of glucose from the kidney back to the bloodstream. Inhibiting this protein effectively lowers the glucose level of diabetic patients; however, the use of synthetic SGLT-2 inhibitors has been linked to some serious adverse effects. There is a need to identify safer alternatives that are equally or more effective as the current inhibitor drugs. Phytochemicals are known for their efficacy as herbal remedies, but these molecules remain underexplored as source of therapeutic agents. In this study, we performed in silico screening to identify potential SGLT-2 inhibitors from the 21 phytochemicals from Centella asiatica. Docking results identified eleven compounds with estimated binding energies comparable to that of known inhibitors drugs. The stability of the complexes was then elucidated using 100 ns MD simulations. From our dynamic binding free energy calculations using MM/PBSA, asiaticoside, betulinic acid, centellasapogenol, methyl brahmate, and rutin exceeded at least one of the binding energies of the reference compounds, which highlights their strong affinity towards SGLT-2. Among the five, betulinic acid, centellasapogenol, and methyl brahmate maintained their structural stability to the same extent as the references and exhibited better oral bioavailability and excellent drug-like properties. Because of these results, it is recommended to prioritize betulinic acid, centellasapogenol, and methyl brahmate in future in vitro and in vivo studies to verify their potential as inhibitor drugs for diabetes therapies. Communicated by Ramaswamy H. Sarma.