Structural insight into TNF-α inhibitors through combining pharmacophore-based virtual screening and molecular dynamic simulation

Multilayered screening for multi-targeted anti-Alzheimer's and anti-Parkinson's agents through structure-based pharmacophore modelling, MCDM, docking, molecular dynamics and DFT: a case study of HDAC4 inhibitors

Abstract

Alzheimer's disease (AD) and Parkinson's disease (PD) are neurological conditions that primarily impact the elderly having distinctive traits and some similarities in terms of symptoms and progression. The multifactorial nature of AD and PD encourages exploring potentiality of multi-target therapy for addressing these conditions to conventional, the "one drug one target" strategy. This study highlights the searching of potential HDAC4 inhibitors through multiple screening approaches. In this context, structure-based pharmacophore model, ligand profiler mapping and MCDM approaches were performed for target prioritization. Similarly, ligand profiler, MCDM and Docking studies were performed to prioritize multi-targeted HDAC4 inhibitors. These comprehensive approaches unveiled 5 common targets and 5 multi-targeted prioritized compounds consensually. MD simulations, DFT and binding free energy calculations corroborated the stability and robustness of propitious compound 774 across 5 prioritized targets. In conclusion, the screened compound 774 (ChEMBL 4063938) could be a promising multi-targeted therapy for managing AD and PD further rendering experimental validation.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00302-4.

Two Small Peptides from Buthus martensii Hydrolysates Exhibit Antitumor Activity Through Inhibition of TNF-α-Mediated Signal Transduction Pathways

The scorpion Buthus martensii Karsch is edible and has been an essential resource in traditional Chinese medicine for treating numerous diseases. In this study, two small peptides from B. martensii hydrolysates were examined to elucidate their potential against gastric cancer. The small peptides (AK and GK) were identified using the LC-QTOF-MS-based approach. In silico prediction of therapeutic targets, MGC-803 cells and transgenic zebrafish models, and immunoblotting experiments were used to reveal the molecular mechanism of action of the peptides. The peptides AK and GK competitively bound to the receptor to modulate the TNF/TNFR-signaling cascade and alter the tumor microenvironment. EGFR, TP53, MYC, PTEN, and STAT3 were also identified as major functional targets of the peptides. Mechanistically, AK and GK inactivated the TNF-α/EGFR/STAT3-signaling pathway, decreased c-myc protein expression levels, and upregulated p53 and PTEN expression, thereby preventing TNF-α-induced tumor growth. Our findings indicated that AK and GK played a pivotal role in offsetting the inflammatory stimuli that caused gastric cancer cell invasion and highlighted the use of B. martensii resources as functional products with health benefits.

Potential Utilization of Phenolic Acid Compounds as Anti-Inflammatory Agents through TNF-α Convertase Inhibition Mechanisms: A Network Pharmacology, Docking, and Molecular Dynamics Approach

Inflammation is a dysregulated immune response characterized by an excessive release of proinflammatory mediators, such as cytokines and prostanoids, leading to tissue damage and various pathological conditions. Natural compounds, notably phenolic acid phytocompounds from plants, have recently garnered substantial interest as potential therapeutic agents to bolster well-being and combat inflammation recently. Based on previous research, the precise molecular mechanism underlying the anti-inflammatory activity of phenolic acids remains elusive. Therefore, this study aimed to predict the molecular mechanisms underpinning the anti-inflammatory properties of selected phenolic acid phytocompounds through comprehensive network pharmacology, molecular docking, and dynamic simulations. Network pharmacology analysis successfully identified TNF-α convertase as a potential target for anti-inflammatory purposes. Among tested compounds, chlorogenic acid (-6.90 kcal/mol), rosmarinic acid (-6.82 kcal/mol), and ellagic acid (-5.46 kcal/mol) exhibited the strongest binding affinity toward TNF-α convertase. Furthermore, phenolic acid compounds demonstrated molecular binding poses similar to those of the native ligand, indicating their potential as inhibitors of TNF-α convertase. This study provides valuable insights into the molecular mechanisms that drive the anti-inflammatory effects of phenolic compounds, particularly through the suppression of TNF-α production via TNF-α convertase inhibition, thus reinforcing their anti-inflammatory attributes.

Discovery of novel VEGFR2-TK inhibitors by phthalimide pharmacophore based virtual screening, molecular docking, MD simulation and DFT

Currently, numerous potent chemotherapeutic agents are available in the market but most of them show poor pharmacokinetics, lethal effects and drug resistance during their enduring use. The increased cancer cases, deaths and need of better treatment stimulates us to give newer lifesaving anticancer drugs. The phthalimide derivatives are structurally diverse and exert potential anticancer activity. In this regard, the 3D QSAR Pharmacophore model was developed and validated using fifty-eight phthalimide derivatives. The validation parameters corroborated the reliability and statistical robustness of CEASER Hypo 1. Three databases-NCI Open, Drug Bank, and Asinex were submitted to ADMET and drug-like filtering; 117893 drug-like compounds were mapped on CEASER Hypo 1; and 362 hits with IC50 <1 µM were discovered. These hits were docked on VEGFR2-TK, and in the form of results fifteen hits exhibited greater affinity than sorafenib. The top lead ASN 03206926 was subjected for MD simulation (100 ns) and RMSD, Rg, RMSF, number of hydrogen bonds, and SASA verified that the complex was stable, rigid and highly compact. Results demonstrated GLU885, PHE918, CYS919, LYS920, HIS1026, CYS1045, ASP1046 are the essential residues for favourable interactions. The binding free energy calculations support the affinity and stability revealed by docking and MD simulation. The DFT calculations, negative binding energy and lower HOMO-LUMO band gap revealed that the process is spontaneous and ASN 03206926 is very reactive. Following extensive analysis we suggest that the ASN 03206926 might be employed as a new VEGFR2-TK inhibitor for the treatment of breast and VEGFR2-TK associated cancers.Communicated by Ramaswamy H. Sarma.