Understanding G Protein-Coupled Receptor Allostery via Molecular Dynamics Simulations: Implications for Drug Discovery

Visualizing agonist-induced M2 receptor activation regulated by aromatic ring dynamics

Despite the growing number of G protein-coupled receptor (GPCR) structures being resolved, the dynamic process of how GPCRs transit from the inactive toward the active state remains unclear. In this study, comprehensive molecular dynamics simulations were performed to explore how ligand binding modulates the conformational dynamics of the M2 muscarinic acetylcholine receptor (M2R). We observed a sequential occurrence of structural changes in the inactive-to-active transition of M2R induced by a superagonist iperoxo, which includes the orthosteric binding site contraction, the TM6 opening into an intermediate conformation, and a further structural change toward full activation upon binding to G protein or a G protein mimetic nanobody. Two activation intermediates were identified, which show structural features different from those reported for apo-GPCRs. Moreover, our results suggest that stabilization of a specific W4006.48 conformation and enhanced F3966.44 dynamics are crucial for activation, whereas distinct side-chain rotamer equilibriums of Y2065.58 in the cytoplasmic cavity are correlated with agonist efficacies. Our work provides atomic-level structural insights into the agonist-induced M2R activation pathway and highlights a mechanism by which ligand efficacy can be encoded and transduced in the form of aromatic ring dynamics.

Investigation of serotonin-receptor interactions, stability and signal transduction pathways via molecular dynamics simulations

Serotonin-receptor binding plays a key role in several neurological and biological processes, including mood, sleep, hunger, cognition, learning, and memory. In this article, we performed molecular dynamics simulation to examine the key residues that play an essential role in the binding of serotonin to the G-protein-coupled 5-HT1B receptor (5HT1BR) via electrostatic interactions. Key residues for electrostatic interactions were identified via bond distance analysis and frustration analysis methods. An end-point free energy calculation method determines the stability of the 5-HT1BR due to serotonin binding. The single-point mutation of the polar/charged amino acid residues (Asp129, Thr134) on the binding sites and the calculation of binding free energy validate the quantitative contribution of these residues to the stability of the serotonin-receptor complex. The principal component analysis reflects that the serotonin-bound 5-HT1BR is more stabilized than the apo-receptor regarding dynamical changes. The difference dynamic cross-correlations map shows the correlation between the transmembranes and mini-Go, which indicates that the signal transduction happens between mini-Go and the receptor. Allosteric pathway analysis reveals the key nodes and key pathways for signal transduction in 5-HT1BR. These results provide useful insights into the study of signal transduction pathways and mutagenesis to regulate the binding and functionality of the complex. The developed protocols can be applied to study local non-covalent interactions and long-range allosteric communications in any protein-ligand system for computer-aided drug design.

A Statistical Journey through the Topological Determinants of the β2 Adrenergic Receptor Dynamics

Activation of G-protein-coupled receptors (GPCRs) is mediated by molecular switches throughout the transmembrane region of the receptor. In this work, we continued along the path of a previous computational study wherein energy transport in the β2 Adrenergic Receptor (β2-AR) was examined and allosteric switches were identified in the molecular structure through the reorganization of energy transport networks during activation. In this work, we further investigated the allosteric properties of β2-AR, using Protein Contact Networks (PCNs). In this paper, we report an extensive statistical analysis of the topological and structural properties of β2-AR along its molecular dynamics trajectory to identify the activation pattern of this molecular system. The results show a distinct character to the activation that both helps to understand the allosteric switching previously identified and confirms the relevance of the network formalism to uncover relevant functional features of protein molecules.

Insights into Phosphorylation-Induced Protein Allostery and Conformational Dynamics of Glycogen Phosphorylase via Integrative Structural Mass Spectrometry and In Silico Modeling

Allosteric regulation plays a fundamental role in innumerable biological processes. Understanding its dynamic mechanism and impact at the molecular level is of great importance in disease diagnosis and drug discovery. Glycogen phosphorylase (GP) is a phosphoprotein responding to allosteric regulation and has significant biological importance to glycogen metabolism. Although the atomic structures of GP have been previously solved, the conformational dynamics of GP related to allostery regulation remain largely elusive due to its macromolecular size (∼196 kDa). Here, we integrated native top-down mass spectrometry (nTD-MS), hydrogen-deuterium exchange MS (HDX-MS), protection factor (PF) analysis, molecular dynamics (MD) simulations, and allostery signaling analysis to examine the structural basis and dynamics for the allosteric regulation of GP by phosphorylation. nTD-MS reveals differences in structural stability as well as oligomeric state between the unphosphorylated (GPb) and phosphorylated (GPa) forms. HDX-MS, PF analysis, and MD simulations further pinpoint the structural differences between GPb and GPa involving the binding interfaces (the N-terminal and tower-tower helices), catalytic site, and PLP-binding region. More importantly, it also allowed us to complete the missing link of the long-range communication process from the N-terminal tail to the catalytic site caused by phosphorylation. This integrative MS and in silico-based platform is highly complementary to biophysical approaches and yields valuable insights into protein structures and dynamic regulation.

Ethylene and Benzaldehyde Emitted from Postharvest Tomatoes Inhibit Botrytis cinerea via Binding to G-Protein Coupled Receptors and Transmitting with cAMP-Signal Pathway of the Fungus

Tomato storage conditions are difficult largely due to Botrytis cinerea infection which causes gray mold disease. However, the effects of the volatile organic compounds (VOCs) emitted by postharvest tomatoes on this fungus remain unclear. We analyzed the effects of tomato-emitted VOCs on B. cinerea pathogenicity, germination, and hyphal growth with bioassay, predicted the causative active compounds by principle component analysis, identified G-protein-coupled receptors (GPCRs) which captured chemical signals in the B. cinerea genome by stimulating molecular docking, tested the binding affinities of these receptors for the active compounds by fluorescence binding competition assay, and identified an associated signaling pathway by RNA interfere. The VOCs emitted by postharvest tomatoes inhibited B. cinerea; ethylene and benzaldehyde were the active compounds causing this effect. One of the identified GPCRs in B. cinerea, BcGPR3, bound tightly to both active compounds. Two genes associated with the cAMP signaling pathway (BcRcn1 and BcCnA) were downregulated in wild-type B. cinerea exposed to the active compounds, as well as in the ΔBcgpr3 B. cinerea mutant. Exposure to postharvest tomato VOCs reduces B. cinerea pathogenicity due to ethylene and benzaldehyde volatiles. The BcGPR3 protein is inactivated by the active compounds, and thus fails to transmit signals to the cAMP pathway, thereby inhibiting B. cinerea.

A Molecular Dynamics Approach to Explore the Intramolecular Signal Transduction of PPAR-α

Dynamics and functions of the peroxisome proliferator-activated receptor (PPAR)-α are modulated by the types of ligands that bind to the orthosteric sites. While several X-ray crystal structures of PPAR-α have been determined in their agonist-bound forms, detailed structural information in their apo and antagonist-bound states are still lacking. To address these limitations, we apply unbiased molecular dynamics simulations to three different PPAR-α systems to determine their modulatory mechanisms. Herein, we performed hydrogen bond and essential dynamics analyses to identify the important residues involved in polar interactions and conformational structural variations, respectively. Furthermore, betweenness centrality network analysis was carried out to identify key residues for intramolecular signaling. The differences observed in the intramolecular signal flow between apo, agonist- and antagonist-bound forms of PPAR-α will be useful for calculating maps of information flow and identifying key residues crucial for signal transductions. The predictions derived from our analysis will be of great help to medicinal chemists in the design of effective PPAR-α modulators and additionally in understanding their regulation and signal transductions.

Toward an understanding of the structural basis of allostery in muscarinic acetylcholine receptors

Recent breakthroughs and developments in structural biology have led to a spate of crystal structures for G protein-coupled receptors (GPCRs). This is the case for the muscarinic acetylcholine receptors (mAChRs) where inactive-state structures for four of the five subtypes and two active-state structures for one subtype are available. These mAChR crystal structures have provided new insights into receptor mechanisms, dynamics, and allosteric modulation. This is highly relevant to the mAChRs given that these receptors are an exemplar model system for the study of GPCR allostery. Allosteric mechanisms of the mAChRs are predominantly consistent with a two-state model, albeit with some notable recent exceptions. Herein, we discuss the mechanisms for positive and negative allosteric modulation at the mAChRs and compare and contrast these to evidence offered by pharmacological, biochemical, and computational approaches. This analysis provides insight into the fundamental pharmacological properties exhibited by GPCR allosteric modulators, such as enhanced subtype selectivity, probe dependence, and biased modulation while highlighting the current challenges that remain. Though complex, enhanced molecular understanding of allosteric mechanisms will have considerable influence on our understanding of GPCR activation and signaling and development of therapeutic interventions.

Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery

The advent of advanced molecular modeling software, big data analytics, and high-speed processing units has led to the exponential evolution of modern drug discovery and better insights into complex biological processes and disease networks. This has progressively steered current research interests to understanding protein-protein interaction (PPI) systems that are related to a number of relevant diseases, such as cancer, neurological illnesses, metabolic disorders, etc. However, targeting PPIs are challenging due to their "undruggable" binding interfaces. In this review, we focus on the current obstacles that impede PPI drug discovery, and how recent discoveries and advances in in silico approaches can alleviate these barriers to expedite the search for potential leads, as shown in several exemplary studies. We will also discuss about currently available information on PPI compounds and systems, along with their usefulness in molecular modeling. Finally, we conclude by presenting the limits of in silico application in drug discovery and offer a perspective in the field of computer-aided PPI drug discovery.