Ligand-induced shifts in conformational ensembles that describe transcriptional activation

Enhanced dynamic coupling in a nuclear receptor underlies ligand activity

Bile acids are signaling molecules with critical roles in cholesterol and lipid metabolism, achieved by regulating the transcriptional activity of the farnesoid X receptor (FXR, NR1H4), otherwise known as the bile acid receptor. Modifications to the C6 position of the steroidal core yield bile acid derivatives with 100× improved potency over endogenous bile acids. Prevailing hypotheses suggested increased binding affinity for FXR as the driver for this activity enhancement. Our experimental results contradict this suggestion, motivating us to investigate the underlying mechanisms of enhanced ligand activity. We combined functional assays with over 200 μs of simulations, revealing an unexpected role for helix 5 in the allosteric signaling of obeticholic acid. We uncovered dynamic coupling between adjacent helices 5 and 7, which is uniquely enhanced by the bile acid modification. Ultimately, the enhanced potency of the bile acid analog can be traced to its effect on FXR dynamics. In addition to identifying a previously unknown mechanistic role for helix 5 to helix 7 coupling in FXR, these results emphasize the inextricable linkage between the activity of nuclear receptor ligands and their effects on receptor dynamics.

Illuminating ligand-induced dynamics in nuclear receptors through MD simulations

Nuclear receptors (NRs) regulate gene expression in critical physiological processes, with their functionality finely tuned by ligand-induced conformational changes. While NRs may sometimes undergo significant conformational motions in response to ligand-binding, these effects are more commonly subtle and challenging to study by traditional structural or biophysical methods. Molecular dynamics (MD) simulations are a powerful tool to bridge the gap between static protein-ligand structures and dynamical changes that govern NR function. Here, we summarize a handful of recent studies that apply MD simulations to study NRs. We present diverse methodologies for analyzing simulation data with a detailed examination of the information each method can yield. By delving into the strengths, limitations and unique contributions of these tools, this review provides guidance for extracting meaningful data from MD simulations to advance the goal of understanding the intricate mechanisms by which ligands orchestrate a range of functional outcomes in NRs.

Identification of phytocompounds as potent inhibitors of sodium/glucose cotransporter-2 leading to diabetes treatment

Type-II diabetes, a major metabolic disorder has threatened the very existence of a healthy life since long ago. Commercially available antidiabetic drugs are known for several adverse effects. The present study attempted to identify potential phytocompounds as inhibitors of sodium/glucose cotransporter-2 (SGLT2), a major protein that helps in glucose re-absorption from renal tubules. A total of 28 phytocompounds were collected based on the literature survey. 3D co-ordinates of phytocompounds were collected from PubChem database. Molecular docking was carried out with SGLT2 protein and the best 3 docking complexes were subjected to molecular dynamics simulation for 100 ns. Free energy changes were also analyzed using MM/PBSA analysis. Phytocompounds were also analyzed for their drug-likeness and ADMET properties. Docking study observed a strong binding affinity of phytocompounds (> -7.0 kcal/mol). More than 10 phytocompounds showed better binding affinity compared to reference drugs. Further analysis of three best docking complexes when analyzed by MD simulation showed better stability and compactness of the complexes compared to reference drug, empagliflozin. MM/PBSA analysis also revealed that van der Waals force and electrostatic energy are the major binding energy involved in the complex formation. Like docking energy, free energy analysis also observed stronger binding energies (ΔGGAS) in SGLT2-phytocompound complexes compared to empagliflozin complex. All the phytocompounds showed drug-likeness and considerable ADMET properties. The study, therefore, suggests that Trifolirhizin-6'-monoacetate, Aspalathin, and Quercetin-3-glucoside could be a possible inhibitor of SGLT2 protein. However, further studies need to be carried out to reveal the exact mode of activity.Communicated by Ramaswamy H. Sarma.

Cell phenotypes can be predicted from propensities of protein conformations

Proteins exist as dynamic conformational ensembles. Here we suggest that the propensities of the conformations can be predictors of cell function. The conformational states that the molecules preferentially visit can be viewed as phenotypic determinants, and their mutations work by altering the relative propensities, thus the cell phenotype. Our examples include (i) inactive state variants harboring cancer driver mutations that present active state-like conformational features, as in K-Ras4BG12V compared to other K-Ras4BG12X mutations; (ii) mutants of the same protein presenting vastly different phenotypic and clinical profiles: cancer and neurodevelopmental disorders; (iii) alterations in the occupancies of the conformational (sub)states influencing enzyme reactivity. Thus, protein conformational propensities can determine cell fate. They can also suggest the allosteric drugs efficiency.

Interactions governing transcriptional activity of nuclear receptors

The key players in transcriptional regulation are transcription factors (TFs), proteins that bind specific DNA sequences. Several mechanisms exist to turn TFs ‘on’ and ‘off’, including ligand binding which induces conformational changes within TFs, subsequently influencing multiple inter- and intramolecular interactions to drive transcriptional responses. Nuclear receptors are a specific family of ligand-regulated TFs whose activity relies on interactions with DNA, coregulator proteins and other receptors. These multidomain proteins also undergo interdomain interactions on multiple levels, further modulating transcriptional outputs. Cooperation between these distinct interactions is critical for appropriate transcription and remains an intense area of investigation. In this review, we report and summarize recent findings that continue to advance our mechanistic understanding of how interactions between nuclear receptors and diverse partners influence transcription.