Exploring the Potential Role of Theaflavin-3,3′-Digallate in Inhibiting Various Stages of SARS-CoV-2 Life Cycle: An In-Silico Approach

Structure-guided identification of mitogen-activated protein kinase-1 inhibitors towards anticancer therapeutics

Mitogen-activated protein kinase 1 (MAPK1) is a serine/threonine kinase that plays a crucial role in the MAP kinase signaling transduction pathway. This pathway plays a crucial role in various cellular processes, including cell proliferation, differentiation, adhesion, migration, and survival. Besides, many chemotherapeutic drugs targeting the MAPK pathway are used in clinical practice, and novel inhibitors of MAPK1 with improved specificity and efficacy are required. Hence, targeting MAPK1 can be crucial to control metastasis in cancer therapeutics. In this study, we utilized a structure-guided virtual screening approach to screen a library of thousands of natural compounds from the ZINC database. The Lipinski rule of five (RO5) was used as a criterion for the primary selection of natural compounds. The screened compounds were prioritized based on their binding affinity, docking scores, and specificity towards the kinase domain of MAPK1 during the molecular docking process. Subsequently, the selected hits underwent rigorous screening that included the identification of potential pan-assay interference compounds (PAINS), ADMET evaluation, and prediction of pharmacological activities using PASS analysis. Afterwards, we performed a comprehensive interaction analysis to explore the binding prototypes of the screened molecules with the key residues within the MAPK1 kinase domain. Finally, selected molecules underwent extensive all-atom molecular dynamics (MD) simulations for a time duration of 200 nanoseconds. The study pinpointed three natural compounds with ZINC database IDs ZINC0209285, ZINC02130647, and ZINC02133691 as potential inhibitors of MAPK1. The study highlights that these compounds could be explored further in preclinical and clinical investigations to develop anticancer therapeutics.

Elucidating the monoamine oxidase B inhibitory effect of kaurene diterpenoids from Xylopia aethiopica: An in silico approach

Parkinson disease is a neurogenerative disease common in adults and results in different kinds of memory dysfuntions. This study evaluated the monoamine oxidase B (MAO-B) inhibitory potential of kaurane diterpenoids previously isolated from Xylopia aethiopica through comprehensive computational approaches. Molecular docking study and molecular dynamics simulation were used to access the binding mode and interaction of xylopic acid and MAO-B enzyme. The ADMET properties of the phytochemical were evaluated to provide information on its druggability. The molecular docking and molecular dynamics simulation revealed xylopic acid as potential MAO-B inhibitor due to the good binding energy elicited and stability throughout the 100 ns simulation period. The ADMET properties of the ligand showed it as a promising drug candidate. The study recommend further comprehensive in vitro investigation towards the development of xylopic acid as potent MAO-B inhibitor.

Exploring the conformational dynamics and key amino acids in the CD26-caveolin-1 interaction and potential therapeutic interventions

This study aimed to decipher the interaction between CD26 and caveolin-1, key proteins involved in cell signaling and linked to various diseases. Using computational methods, we predicted their binding conformations and assessed stability through 100 ns molecular dynamics (MD) simulations. We identified two distinct binding conformations (con1 and con4), with con1 exhibiting superior stability. In con1, specific amino acids in CD26, namely GLU237, TYR241, TYR248, and ARG147, were observed to engage in interactions with the F-J chain of Caveolin-1, establishing hydrogen bonds and cation or π-π interactions. Meanwhile, in con4, CD26 amino acids ARG253, LYS250, and TYR248 interacted with the J chain of Caveolin-1 via hydrogen bonds, cation-π interactions, and π-π interactions. Virtual screening also revealed potential small-molecule modulators, including Crocin, Poliumoside, and Canagliflozin, that could impact this interaction. Additionally, predictive analyses were conducted on the potential bioactivity, drug-likeness, and ADMET properties of these three compounds. These findings offer valuable insights into the binding mechanism, paving the way for new therapeutic strategies. However, further validation is required before clinical application. In summary, we provide a detailed understanding of the CD26 and caveolin-1 interaction, identifying key amino acids and potential modulators, essential for developing targeted therapies.

In Silico Approach Triterpene Glycoside of H. atra Targeting Orotidine 5-Monophosphate Decarboxylase Protein (PfOMPDC) in P. falciparum Infection Mechanism

This study accessed the potential antimalarial activity of triterpene glycoside of H. atra through targeting orotidine 5-monophosphate decarboxylase protein (PfOMPDC) in P. falciparum by molecular docking. Nine triterpene glycosides from H. atra extract modeled the structure by the Corina web server and interacted with PfOMPDC protein by using Hex 8.0.0. The docking results were visualized and analyzed by Discovery Studio version 21.1.1. 17-Hydroxyfuscocineroside B showed the lowest binding energy in PfOMPDC interaction, which was -1,098.13 kJ/mol. Holothurin A3, echinoside A, and fuscocineroside C showed low binding energy. Nine triterpene glycosides of H. atra performed interaction with PfOMPDC protein at the same region. Holothurin A1 posed interaction with PfOMPDC protein by 8 hydrogen bonds, 3 hydrophobic interactions, and 8 unfavorable bonds. Several residues were detected in the same active sites of other triterpene glycosides. Residue TYR111 was identified in all triterpene glycoside complexes, except holothurin A3 and calcigeroside B. In summary, the triterpene glycoside of H. atra is potentially a drug candidate for malaria therapeutic agents. In vitro and in vivo studies were required for further investigation.

In Silico Investigation of Novel Compounds as Inhibitors of Acetylcholinesterase Enzyme for the Treatment of Alzheimer's Diseases

Alzheimer's disease (AD) is a "progressive, neurodegenerative disease that occurs when nerve cells in the brain die." There are only 4 drugs approved by the United States Food and Drug Administration (FDA). Three (donepezil, rivastigmine, and galantamine) out of these four drugs are anticholinesterase inhibitors, while the fourth one memantine is an N-methyl-D-aspartate (NMDA) receptor inhibitor. Currently, two immunotherapy drugs that target amyloid protein (donanemab and lecanemab) are being considered for the treatment of Alzheimer's disease at an early stage. All these drug molecules are still not the complete answer to the treatment of Alzheimer's disease. A recent report from the Office of National Statistics showed that AD is the leading cause of death in 2022. Therefore, there is an urgency to develop more drugs that can treat AD. Based on this urgency, we aim to investigate how bioactive and already approved drugs could be repurposed for inhibiting the anticholinesterase enzyme using computational studies. To achieve this, the data science tool-Python coding was compiled on Jupyter Notebook to mine bioactive compounds from the ChEMBL database. The most bioactive compounds obtained were further investigated using Molecular Operating Environment (MOE) software to carry out molecular docking and ligand analysis, and this was followed by molecular dynamics simulation production at 35 ns using GROMACS 2022.4 on Archer 2 machine. The molecular dynamic analysis was carried out using HeroMDanalysis software. Data mining of the ChEMBL database was carried out for lipase inhibitors, and this gave CHEMBL-ID 1240685, a peptide molecule, the most active compound at the time of data mining. Further literature studies gave Zoladex an FDA-approved drug for the treatment of breast cancer as another compound of interest. The in silico studies were carried out against the anticholinesterase enzyme using two FDA-approved drugs donepezil and galantamine as a template for comparing the in silico activities of the repurposed drugs. A very useful receptor for this study was PDB-1DX6, a cocrystallized galantamine inhibitor of acetylcholinesterase enzyme. The molecular docking analysis (using ligand interactions) and molecular dynamic analysis (root mean square deviation (RMSD) and root mean square fluctuation (RMSF)) showed that the two peptide molecules CHEMBL-1240685 and Zoladex gave the best binding energy and stability when compared to the FDA-approved drugs (donepezil and galantamine). Finally, further literature studies revealed that Zoladex affects memory reduction; therefore, it was dropped as a possible repurposed drug. Our research showed that CHEMBL-1240685 is a potential compound that could be investigated for the inhibition of anticholinesterase enzyme and might be another drug molecule that could be used to treat Alzheimer's disease.