Computational Evaluation of Bioactive Compounds from Vaccinium vitis-idaea L (Ligonberry) for Treating KRAS-associated Lung Cancer

Lung cancer is the cancer of the lung\u27s epithelial cells typically characterized by difficult breathing, chest pain, blood-stained coughs, headache, and weight loss. If left unmanaged, lung cancer can spread to other body parts. While several treatment methods exist for managing lung cancer, exploring natural plant sources for developing therapeutics offers great potential in complementing different treatment approaches. In this study, we concentrated on inhibiting the mutated Kirsten rat sarcoma viral oncogene homolog (KRAS) by targeting an associated protein (Phosphodiesterase 6δ) to which KRAS form complexes. We evaluated bioactive compounds from Lingonberry (Vaccinium vitis-idaea L), adopting computational approaches such as molecular docking, molecular dynamics simulation, molecular mechanics/generalized Born surface area (MM/GBSA) calculations, and pharmacokinetics analysis. A total of 26 out of 39 bioactive compounds of Vaccinium vitis-idaea L had a higher binding affinity to the target receptor than the approved drug, Sotorasib. Further, the pharmacokinetics properties of the lead compounds were examined, and the best four compounds, namely, (+) – Catechin (Cianidanol), Arbutin, Resveratrol, and Sinapic acid, were further subjected to molecular dynamic simulation. In conclusion, Arbutin (+) – Catechin and Sinapic acid are predicted to be the best compound of Vaccinium vitis-idaea L. because of their pharmacokinetic properties and drug-likeness attributes. Also, their stability to the target receptor makes them a potential drug candidate that could be explored for treating KRAS-mutation-associated lung cancer

Compounds from Morchella esculenta as Potential Inhibitors of RNA-Binding Protein La in Ovarian Cancer: A Molecular Modeling and Quantum Mechanics Approach

Ovarian cancer (OC) is implicated in most gynecological cancer-related deaths. Currently, the primary treatments for OC are surgery and chemotherapy using platinum-based drugs to induce remission. However, OC recurs in 70-80% of patients within two years, which usually results in the death of most OC patients. La protein is significantly expressed in various malignant tumors, including OC. Previous studies reported that OC patients have significantly higher levels of La protein expression in their serum than healthy individuals, which is related to the poor response to platinum-based chemotherapy. Inhibiting La protein could control the expression of the potential downstream genes involved in promoting proliferation and chemotherapy resistance to OC, which could serve as a therapeutic intervention in treating OC. Extract from Morchella esculenta (morel mushroom) has been reported to contain anti-cancer properties, but no study has reported the interaction of its bioactive compounds with La protein in OC. This study examines the interaction of La protein with some bioactive compounds of Morchella esculenta, as well as their pharmacokinetics and thermochemical properties using structural bioinformatics and advanced theoretical chemistry techniques. Molecular modeling techniques incorporating molecular docking, free energy calculation, MD simulation, drug-likeness, and quantum chemical calculations, including the global hybrid and long-range corrected density functional theory approximations, were employed in this study. Thus, the results identify hits compounds from morchella esculanta, which could serve as a starting for the development of novel LA protein inhibitors for OC therapeutics

Targeting PDE6D for inhibiting KRAS: A computational approach

Lung cancer is the cancer of the lung\u27s epithelial cells typically characterized by difficult breathing, chest pain, blood-stained coughs, headache, and weight loss. If left unmanaged, lung cancer can spread to other body parts. While several treatment methods exist for managing lung cancer, exploring natural plant sources for developing therapeutics offers great potential in complementing different treatment approaches. Several efforts have focused on inhibiting specific mutated genes, including Epidermal Growth Factor Receptors and Anaplastic Lymphoma Kinase implicated in lung cancer. In this study, we concentrated on inhibiting the mutated Kirsten rat sarcoma viral oncogene homolog (KRAS) by targeting an associated protein (Phosphodiesterase 6δ) to which KRAS form complexes. We evaluated bioactive compounds from Lingonberry (Vaccinium vitis-idaea L), adopting computational approaches such as molecular docking, molecular dynamics simulation, molecular mechanics/generalized Born surface area (MM/GBSA) calculations, and pharmacokinetics analysis. A total of 26 out of 39 bioactive compounds of Vaccinium vitis-idaea L had a higher binding affinity to the target receptor than the approved drug, Sotorasib. Further, the pharmacokinetics properties of the lead compounds were examined, and the best four compounds, namely, (+) – Catechin (Cianidanol), Arbutin, Resveratrol, and Sinapic acid, were further subjected to molecular dynamic simulation. In conclusion, Arbutin (+) – Catechin and Sinapic acid are predicted to be the best compound of Vaccinium vitis-idaea L. because of their pharmacokinetic properties and drug-likeness attributes. Also, their stability to the target receptor makes them a potential drug candidate that could be explored for treating KRAS-mutation-associated lung cancer

Computational Evaluation of Bioactive Compounds from Viscum album (Mistletoe) as Inhibitors of p63 for Pancreatic Cancer Treatment

Pancreatic ductal adenocarcinoma is an aggressive malignancy usually detectable at the advanced stage, with a 5-year survival rate of less than 8%. It has been reported that a gene called tumor-protein 63 (TP63) is expressed in an aggressive form of pancreatic cancer with a squamous signature. Thus, inhibiting the activity of p63 can be a means of treating and managing PDA. Different studies have shown that plant constituents are rich and can be a promising source for discovering drug candidates. The extract from mistletoe (Viscum album) is known to contain anticancer compounds; however, the specific molecular mechanism of the bioactive compounds is unknown. This study examines the pancreatic cancer therapeutic potential of the bioactive compounds in the flavonoid and phenolic acid constituents of mistletoe by adopting structural bioinformatics and advanced theoretical chemistry techniques via molecular docking, molecular dynamics simulation, molecular mechanics/ generalized Born surface area (MM/GBSA) calculations, pharmacokinetic analysis, and density functional theory analysis. The six best compounds from the flavonoid constituent with the highest binding affinity ranging from -6.8 kcal/mol to -6.7 kcal/mol were selected with the control gemcitabine (-5.5 kcal/mol) for further computational analysis after molecular docking. Furthermore, MM/GBSA calculation showed the highest binding energy for the selected docked compounds, which validates their inhibitory potential. Hence, the molecular dynamics simulation, post-simulation analysis, pharmacokinetics model, and DFT results showed that mistletoe compounds are reliable due to their stable interaction with the target protein and drug-likeness properties

Discovery of putative inhibitors against main drivers of SARS-CoV-2 infection: Insight from quantum mechanical evaluation and molecular modeling

International audienceSARS-CoV-2 triggered a worldwide medical crisis, affecting the world’s social, emotional, physical, and economic equilibrium. However, treatment choices and targets for finding a solution to COVID-19’s threat are becoming limited. A viable approach to combating the threat of COVID-19 is by unraveling newer pharmacological and therapeutic targets pertinent in the viral survival and adaptive mechanisms within the host biological milieu which in turn provides the opportunity to discover promising inhibitors against COVID-19. Therefore, using high-throughput virtual screening, manually curated compounds library from some medicinal plants were screened against four main drivers of SARS-CoV-2 (spike glycoprotein, PLpro, 3CLpro, and RdRp). In addition, molecular docking, Prime MM/GBSA (molecular mechanics/generalized Born surface area) analysis, molecular dynamics (MD) simulation, and drug-likeness screening were performed to identify potential phytodrugs candidates for COVID-19 treatment. In support of these approaches, we used a series of computational modeling approaches to develop therapeutic agents against COVID-19. Out of the screened compounds against the selected SARS-CoV-2 therapeutic targets, only compounds with no violations of Lipinski’s rule of five and high binding affinity were considered as potential anti-COVID-19 drugs. However, lonchocarpol A, diplacol, and broussonol E (lead compounds) were recorded as the best compounds that satisfied this requirement, and they demonstrated their highest binding affinity against 3CLpro. Therefore, the 3CLpro target and the three lead compounds were selected for further analysis. Through protein–ligand mapping and interaction profiling, the three lead compounds formed essential interactions such as hydrogen bonds and hydrophobic interactions with amino acid residues at the binding pocket of 3CLpro. The key amino acid residues at the 3CLpro active site participating in the hydrophobic and polar inter/intra molecular interaction were TYR54, PRO52, CYS44, MET49, MET165, CYS145, HIS41, THR26, THR25, GLN189, and THR190. The compounds demonstrated stable protein–ligand complexes in the active site of the target (3CLpro) over a 100 ns simulation period with stable protein–ligand trajectories. Drug-likeness screening shows that the compounds are druggable molecules, and the toxicity descriptors established that the compounds demonstrated a good biosafety profile. Furthermore, the compounds were chemically reactive with promising molecular electron potential properties. Collectively, we propose that the discovered lead compounds may open the way for establishing phytodrugs to manage COVID-19 pandemics and new chemical libraries to prevent COVID-19 entry into the host based on the findings of this computational investigation