Mechanistic insight into the mode of inhibition of dietary flavonoids; targeting macrophage migration inhibitory factor.

Introduction: The Macrophage Migration Inhibitory Factor (MIF), a key pro-inflammatory mediator, is responsible for modulating immune responses. An array of inflammatory and autoimmune diseases has been linked to the dysregulated activity of MIF. The significance in physiological as well as pathophysiological phenomena underscores the potential of MIF as an attractive target with pharmacological relevance. Extensive research in past has uncovered a number of inhibitors, while the ISO-1, or (S, R)-3-(4-hydroxyphenyl)-4,5-dihydro-5-isoxazole acetic acid methyl ester being recognized as a benchmark standard so far. Recent work by Yang and coworkers identified five promising dietary flavonoids, with superior activity compared to the standard ISO-1. Nevertheless, the exact atomic-level inhibitory mechanism is still elusive. Methods: To improve the dynamic research, and rigorously characterize, and compare molecular signatures of MIF complexes with ISO-1 and flavonoids, principal component analysis (PCA) was linked with molecular dynamics (MD) simulations and binding free energy calculations. Results: The results suggest that by blocking the tautomerase site these small molecule inhibitors could modify the MIF activity by disrupting the intrinsic dynamics in particular functional areas. The stability matrices revealed the average deviation values ranging from 0.27-0.32 nm while the residue level fluctuations indicated that binding of the selected flavonoids confer enhanced stability relative to the ISO-1. Furthermore, the gyration values extracted from the simulated trajectories were found in the range of 1.80-1.83 nm. Discussion: Although all the tested flavonoids demonstrated remarkable results, the one obtained for the potent inhibitors, particularly Morin and Amentoflavone exhibited a good correlation with biological activity. The PCA results featured relatively less variance and constricted conformational landscape than others. The stable ensembles and reduced variation in turns might be the possible reasons for their outstanding performance documented previously. The results from the present exploration provide a comprehensive understanding of the molecular complexes formed by flavonoids and MIF, shedding light on their potential roles and impacts. Future studies on MIF inhibitors may benefit from the knowledge gathered from this investigation.

Uncovering PPAR-γ agonists: An integrated computational approach driven by machine learning.

Peroxisome proliferator-activated receptor gamma (PPAR-γ) serves as a nuclear receptor with a pivotal function in governing diverse facets of metabolic processes. In diabetes, the prime physiological role of PPAR-γ is to enhance insulin sensitivity and regulate glucose metabolism. Although PPAR-γ agonists such as Thiazolidinediones are effective in addressing diabetes complications, it is vital to be mindful that they are associated with substantial side effects that could potentially give rise to health challenges. The recent surge in the discovery of selective modulators of PPAR-γ inspired us to formulate an integrated computational strategy by leveraging the promising capabilities of both machine learning and in silico drug design approaches. In pursuit of our objectives, the initial stage of our work involved constructing an advanced machine learning classification model, which was trained utilizing chemical information and physicochemical descriptors obtained from known PPAR-γ modulators. The subsequent application of machine learning-based virtual screening, using a library of 31,750 compounds, allowed us to identify 68 compounds having suitable characteristics for further investigation. A total of four compounds were identified and the most favorable configurations were complemented with docking scores ranging from -8.0 to -9.1 kcal/mol. Additionally, the compounds engaged in hydrogen bond interactions with essential conserved residues including His323, Leu330, Phe363, His449 and Tyr473 that describe the ligand binding site. The stability indices investigated herein for instance root-mean-square fluctuations in the backbone atoms indicated higher mobility in the region of orthosteric site in the presence of agonist with the deviation peaks in the range of 0.07-0.69 nm, signifying moderate conformational changes. The deviations at global level revealed that the average values lie in the range of 0.25-0.32 nm. In conclusion, our identified hits particularly, CHEMBL-3185642 and CHEMBL-3554847 presented outstanding results and highlighted the stable conformation within the orthosteric site of PPAR-γ to positively modulate the activity.

Interface inhibitory action on Interleukin-1ß using selected anti-inflammatory compounds to mitigate the depression: A computational investigation.

Interleukin-1ß (IL1ß) is a keynote mediator of inflammation with diverse physiological functions, playing a fundamental role in memory and mood regulation. The pleiotropic effects of IL-1ß have been proposed to be implicated in the pathogenesis and etiology of depression. Thus, targeting IL-1ß offers an inimitable opportunity to develop new strategies for an alternative therapy to treat depression. The focus of this study is to find out the potential inhibitors against IL-1ß. Since, there is no oral specific drug reported yet thus, demanding an urgent need to develop new immunomodulatory drugs to combat chronic diseases. In this study, ligand-based pharmacophore modeling integrated with virtual screening and molecular docking strategy was designed to identify novel compounds capable of inhibiting the interactions towards cognitive receptor IL-1RI. In this connection, a set of 30,000 compounds were screened by a developed pharmacophore model that led to the retrieval of 2043 molecules from the in-house library and ZINC Database. Primarily, specific binding regions for IL-1ß inhibitors have been explored by blind docking studies. After the selection of the binding site, the hits identified as actives based on the 3D-pharmacophore model were assessed by molecular docking studies. In a stepwise screening, six potential virtual hits were shortlisted for molecular dynamic simulation to acquire insights into their dynamic behavior. The obtained results highlighted that these compounds are stabilized in the targeted pocket of IL-1ß and possibly block the formation of an active heterocomplex, subsequently locking the associated signaling cascade. Further in vitro experiments confirmed the inhibitory potential of Compound-157 and compound-283 with the IC50 of 1.6 ± 0.1 and 9.1 ± 1.7 µg/mL respectively.