Activation Mechanism of Corticotrophin Releasing Factor Receptor Type 1 Elucidated Using Molecular Dynamics Simulations

The corticotropin-releasing factor receptor type 1 (CRF1R), a member of class B G-protein-coupled receptors (GPCRs), is a good drug target for treating depression, anxiety, and other stress-related neurodisorders. However, there is no approved drug targeting the CRF1R to date, partly due to inadequate structural information and its elusive activation mechanism. Here, by use of the crystal structures of its transmembrane domain (TMD) and the N-terminal extracellular domain (ECD) as a template, a full-length homology model of CRF1R was built and its complexes with peptide agonist urocortin 1 or small molecule antagonist CP-376395 were subjected to all-atom molecular dynamics simulations. We observed well preserved helical contents in the TMD through simulations, while the transmembrane (TM) helices showed clear rearrangements. The TM rearrangement is especially pronounced for the TM6 in the agonist-bound CRF1R system. The observed conformational changes are likely due to breakage of interhelical/inter-regional hydrogen bonds in the TMD. Dynamical network analysis identifies communities with high connections to TM6. Simulations reveal three key residues, Y356^6.53, Q384^7.49, and L395^7.60, which corroborate experimental mutagenesis data, implying the important roles in the receptor activation. The observed large-scale conformational changes are related to CRF1R activation by agonist binding, providing guidance for ligand design.

Involvement of 5-HT2 serotonin receptors in cognitive defects induced by aristolochic acid I in mice

Aristolochic acids (AAs) are a natural bioactive substance found in Chinese herbs, which are widely used for treating diseases. Many studies have demonstrated that AAs have various pharmacological function, while increasing reports indicated its toxicity. However, the role AAs in cognition remains poorly understood. This study explored the neurotoxic effect of aristolochic acid I (AAI), the most toxic component of the AAs family, on hippocampal synaptic plasticity and spatial cognition in mice. C57BL/6 mice were exposed to 5 mg/kg AAI for 4 weeks. After chronic treatment, AAI considerably increased the level of anxiety and the degree of behavioral despair in mice. Working and reference error rates were higher in the AAI exposed mice than in the control. This was further validated by the molecular docking studies, which AAI might interact with 5-HT₂ serotonin receptor (5-HT_2AR). Mechanism investigation indicated that AAI triggered inflammation in the hippocampus of mice through increasing the activity of Tnf-α-NF-κB-IL-6 signaling pathway. Conclusively, chronic AAI administration causes inflammation, and it possibly also serves as a potential antagonist of 5-HT_2AR to influence the cognition function in C57BL/6 mice.

Recent Insights from Molecular Dynamics Simulations for G Protein-Coupled Receptor Drug Discovery

G protein-coupled receptors (GPCRs) are critical drug targets. GPCRs convey signals from the extracellular to the intracellular environment through G proteins. Some ligands that bind to GPCRs activate different downstream signaling pathways. G protein activation, or -arrestin biased signaling, involves ligands binding to receptors and stabilizing conformations that trigger a specific pathway. -arrestin biased signaling has become a hot target for structure-based drug discovery. However, challenges include that there are few crystal structures available in the Protein Data Bank and that GPCRs are highly dynamic. Hence, molecular dynamics (MD) simulations are especially valuable for obtaining detailed mechanistic information, including identification of allosteric sites and understanding modulators' interactions with receptors and ligands. Here, we highlight recent MD simulation studies and enhanced sampling methods used to study biased G protein-coupled receptor signaling and their conformational dynamics as well as applications to drug discovery.

Identification of a Different Agonist-Binding Site and Activation Mechanism of the Human P2Y1 Receptor

The human P2Y1 receptor (P2Y1R) is a purinergic G-protein-coupled receptor (GPCR) that functions as a receptor for adenosine 5'-diphosphate (ADP). An antagonist of P2Y1R might potentially have antithrombotic effects, whereas agonists might serve as antidiabetic agents. On the basis of the antagonist-bound MRS2500-P2Y1R crystal structure, we constructed computational models of apo-P2Y1R and the agonist-receptor complex 2MeSADP-P2Y1R. We then performed conventional molecular dynamics (cMD) and accelerated molecular dynamics (aMD) simulations to study the conformational dynamics after binding with agonist/antagonist as well as the P2Y1R activation mechanism. We identified a new agonist-binding site of P2Y1R that is consistent with previous mutagenesis data. This new site is deeper than those of the agonist ADP in the recently simulated ADP-P2Y1R structure and the antagonist MRS2500 in the MRS2500-P2Y1R crystal structure. During P2Y1R activation, the cytoplasmic end of helix VI shifts outward 9.1 Å, the Ser1463.47-Tyr2375.58 hydrogen bond breaks, a Tyr2375.58-Val2626.37 hydrogen bond forms, and the conformation of the χ1 rotamer of Phe2696.44 changes from parallel to perpendicular to helix VI. The apo-P2Y1R system and the MRS2500-P2Y1R system remain inactive. The newly identified agonist binding site and activation mechanism revealed in this study may aid in the design of P2Y1R antagonists/agonists as antithrombotic/antidiabetic agents, respectively.

Adaptive simulations, towards interactive protein-ligand modeling

Modeling the dynamic nature of protein-ligand binding with atomistic simulations is one of the main challenges in computational biophysics, with important implications in the drug design process. Although in the past few years hardware and software advances have significantly revamped the use of molecular simulations, we still lack a fast and accurate ab initio description of the binding mechanism in complex systems, available only for up-to-date techniques and requiring several hours or days of heavy computation. Such delay is one of the main limiting factors for a larger penetration of protein dynamics modeling in the pharmaceutical industry. Here we present a game-changing technology, opening up the way for fast reliable simulations of protein dynamics by combining an adaptive reinforcement learning procedure with Monte Carlo sampling in the frame of modern multi-core computational resources. We show remarkable performance in mapping the protein-ligand energy landscape, being able to reproduce the full binding mechanism in less than half an hour, or the active site induced fit in less than 5 minutes. We exemplify our method by studying diverse complex targets, including nuclear hormone receptors and GPCRs, demonstrating the potential of using the new adaptive technique in screening and lead optimization studies.

Don't stress about CRF: assessing the translational failures of CRF1antagonists

BACKGROUND

Dr. Athina Markou sought treatments for a common neural substrate shared by depression and drug dependence. Antagonists of corticotropin-releasing factor (CRF) receptors, a target of interest to her, have not reached the clinic despite strong preclinical rationale and sustained translational efforts.

METHODS

We explore potential causes for the failure of CRF1 antagonists and review recent findings concerning CRF-CRF1 systems in psychopathology.

RESULTS

Potential causes for negative outcomes include (1) poor safety and efficacy of initial drug candidates due to bad pharmacokinetic and physicochemical properties, (2) specificity problems with preclinical screens, (3) the acute nature of screens vs. late-presenting patients, (4) positive preclinical results limited to certain models and conditions with dynamic CRF-CRF1 activation not homologous to tested patients, (5) repeated CRF1 activation-induced plasticity that reduces the importance of ongoing CRF1 agonist stimulation, and (6) therapeutic silencing which may need to address CRF2 receptor or CRF-binding protein molecules, constitutive CRF1 activity, or molecules that influence agonist-independent activity or to target structural regions other than the allosteric site bound by all drug candidates. We describe potential markers of activation towards individualized treatment, human genetic, and functional data that still implicate CRF1 systems in emotional disturbance, sex differences, and suggestive clinical findings for CRF1 antagonists in food craving and CRF-driven HPA-axis overactivation.

CONCLUSION

The therapeutic scope of selective CRF1 antagonists now appears narrower than had been hoped. Yet, much remains to be learned about CRF's role in the neurobiology of dysphoria and addiction and the potential for novel anti-CRF therapies therein.

Activation and conformational dynamics of a class B G-protein-coupled glucagon receptor

The human glucagon receptor (GCGR) is a class B G-protein-coupled receptor (GPCR). The GCGR can be activated by glucagon and regulates the release of glucose. The GCGR has been proposed to be an important drug target for type 2 diabetes. Based on the structural model of a full-length glucagon-bound GCGR (glu-GCGR), we performed accelerated molecular dynamics (aMD) simulations, potential of mean force (PMF) calculations, cross-correlation analysis and community network analysis to study the activation mechanism and the conformational dynamics during the activation process. The PMF map depicts three different conformational states of the GCGR: the inactive, intermediate and active states. The activation of the GCGR is characterized by the outward movement of the intracellular side of helix VI. In the active state of the GCGR, the Arg173(2.46)-Ser350(6.41) and Glu245(3.50)-Thr351(6.42) hydrogen bonds break, and the χ1 rotamer of Phe322(5.54) changes from perpendicular to parallel to helix VI. The binding of the agonist glucagon decreases the correlated motions of the extracellular loops (ELCs) and the helices around the glucagon-binding site. During the activation of the GCGR, the connections between the intracellular sides of helices become weaker, and the connections between glucagon and ECLs and the extracellular sides of helices become stronger. These facilitate G-protein coupling on the intracellular side and glucagon binding on the extracellular side, and stabilize the GCGR in the active state. We expect that this study can provide useful information on the activation mechanism of the GCGR and facilitate the future design of GCGR inhibitors.