Giuseppe Deganutti

Understanding allosteric interactions in G protein-coupled receptors using Supervised Molecular Dynamics: A prototype study analysing the human A3 adenosine receptor positive allosteric modulator LUF6000.

The search for G protein-coupled receptors (GPCRs) allosteric modulators represents an active research field in medicinal chemistry. Allosteric modulators usually exert their activity only in the presence of the orthosteric ligand by binding to protein sites topographically different from the orthosteric cleft. They therefore offer potentially therapeutic advantages by selectively influencing tissue responses only when the endogenous agonist is present. The prediction of putative allosteric site location, however, is a challenging task. In facts, they are usually located in regions showing more structural variation among the family members. In the present work, we applied the recently developed Supervised Molecular Dynamics (SuMD) methodology to interpret at the molecular level the positive allosteric modulation mediated by LUF6000 toward the human adenosine A3 receptor (hA3 AR). Our data suggest at least two possible mechanisms to explain the experimental data available. This study represent, to the best of our knowledge, the first case reported of an allosteric recognition mechanism depicted by means of molecular dynamics simulations.

Deciphering the Complexity of Ligand-Protein Recognition Pathways Using Supervised Molecular Dynamics (SuMD) Simulations.

Molecular recognition is a crucial issue when aiming to interpret the mechanism of known active substances as well as to develop novel active candidates. Unfortunately, simulating the binding process is still a challenging task because it requires classical MD experiments in a long microsecond time scale that are affordable only with a high-level computational capacity. In order to overcome this limiting factor, we have recently implemented an alternative MD approach, named supervised molecular dynamics (SuMD), and successfully applied it to G protein-coupled receptors (GPCRs). SuMD enables the investigation of ligand-receptor binding events independently from the starting position, chemical structure of the ligand, and also from its receptor binding affinity. In this article, we present an extension of the SuMD application domain including different types of proteins in comparison with GPCRs. In particular, we have deeply analyzed the ligand-protein recognition pathways of six different case studies that we grouped into two different classes: globular and membrane proteins. Moreover, we introduce the SuMD-Analyzer tool that we have specifically implemented to help the user in the analysis of the SuMD trajectories. Finally, we emphasize the limit of the SuMD applicability domain as well as its strengths in analyzing the complexity of ligand-protein recognition pathways.

Exploring the recognition pathway at the human A2A adenosine receptor of the endogenous agonist adenosine using supervised molecular dynamics simulations

Adenosine is a naturally occurring purine nucleoside that exerts a variety of important biological functions through the activation of four G protein-coupled receptor (GPCR) isoforms, namely the A1, A2A, A2B and A3 adenosine receptors (ARs). Recently, the X-ray structure of adenosine-bound hA2A AR has been solved, thus providing precious structural details on receptor recognition and activation mechanisms. To date, however, little is still known about the possible recognition pathway the endogenous agonist might go through while approaching the hA2A AR from the extracellular environment. In the present work, we report the adenosine-hA2A AR recognition pathway through the analysis of a series of Supervised Molecular Dynamics (SuMD) trajectories. Interestingly, a possible energetically stable meta-binding site has been detected and characterized.

Estimation of kinetic and thermodynamic ligand-binding parameters using computational strategies

Kinetic and thermodynamic ligand-protein binding parameters are gaining growing importance as key information to consider in drug discovery. The determination of the molecular structures, using particularly x-ray and NMR techniques, is crucial for understanding how a ligand recognizes its target in the final binding complex. However, for a better understanding of the recognition processes, experimental studies of ligand-protein interactions are needed. Even though several techniques can be used to investigate both thermodynamic and kinetic profiles for a ligand-protein complex, these procedures are very often laborious, time consuming and expensive. In the last 10 years, computational approaches have enormous potential in providing insights into each of the above effects and in parsing their contributions to the changes in both kinetic and thermodynamic binding parameters. The main purpose of this review is to summarize the state of the art of computational strategies for estimating the kinetic and thermodynamic parameters of a ligand-protein binding.

Extracellular loops 2 and 3 of the calcitonin receptor selectively modify agonist binding and efficacy

Graphical abstract Figure. No Caption available. Abstract Class B peptide hormone GPCRs are targets for the treatment of major chronic disease. Peptide ligands of these receptors display biased agonism and this may provide future therapeutic advantage. Recent active structures of the calcitonin (CT) and glucagon‐like peptide‐1 (GLP‐1) receptors reveal distinct engagement of peptides with extracellular loops (ECLs) 2 and 3, and mutagenesis of the GLP‐1R has implicated these loops in dynamics of receptor activation. In the current study, we have mutated ECLs 2 and 3 of the human CT receptor (CTR), to interrogate receptor expression, peptide affinity and efficacy. Integration of these data with insights from the CTR and GLP‐1R active structures, revealed marked diversity in mechanisms of peptide engagement and receptor activation between the CTR and GLP‐1R. While the CTR ECL2 played a key role in conformational propagation linked to Gs/cAMP signalling this was mechanistically distinct from that of GLP‐1R ECL2. Moreover, ECL3 was a hotspot for distinct ligand‐ and pathway‐specific effects, and this has implications for the future design of biased agonists of class B GPCRs.

Comparison of the Human A2A Adenosine Receptor Recognition by Adenosine and Inosine: New Insights from Supervised Molecular Dynamics Simulations.

Adenosine deaminase converts adenosine into inosine. In contrast to adenosine, relatively little attention has been paid to the physiological roles of inosine. Nevertheless, recent studies have demonstrated that inosine has neuroprotective, cardioprotective, immunomodulatory, and antidepressive effects. Inosine was recently shown to be a less potent agonist than adenosine at the A2A adenosine receptor. To better depict the differences in the mechanisms of receptor recognition between adenosine and inosine, we carried out supervised molecular dynamics (SuMD) simulations, and the results are analyzed herein.

Supporting the Identification of Novel Fragment-Based Positive Allosteric Modulators Using a Supervised Molecular Dynamics Approach: A Retrospective Analysis Considering the Human A2A Adenosine Receptor as a Key Example

Structure-driven fragment-based (SDFB) approaches have provided efficient methods for the identification of novel drug candidates. This strategy has been largely applied in discovering several pharmacological ligand classes, including enzyme inhibitors, receptor antagonists and, more recently, also allosteric (positive and negative) modulators. Recently, Siegal and collaborators reported an interesting study, performed on a detergent-solubilized StaR adenosine A2A receptor, describing the existence of both fragment-like negative allosteric modulators (NAMs), and fragment-like positive allosteric modulators (PAMs). From this retrospective study, our results suggest that Supervised Molecular Dynamics (SuMD) simulations can support, on a reasonable time scale, the identification of fragment-like PAMs following their receptor recognition pathways and characterizing the possible allosteric binding sites.

AquaMMapS: An Alternative Tool to Monitor the Role of Water Molecules During Protein-Ligand Association

Unquestionably, water appears to be an active player in the noncovalent protein–ligand binding process, as it can either bridge interactions between protein and ligand or can be replaced by the bound ligand. Accordingly, in the last decade, alternative computational methodologies have been sought with the aim of predicting the position and thermodynamic profile of water molecules (i.e., hydration sites) in the binding site using either the ligand‐bound or ligand‐free protein conformation. Herein, we present an alternative approach, named AquaMMapS, that provides a three‐dimensional sampling of putative hydration sites. Interestingly, AquaMMapS can post‐inspect molecular dynamics (MD) trajectories obtained from different MD engines using indifferently crystallographic or docking‐driven structures as a starting point. Moreover, AquaMMapS is naturally integrated into supervised molecular dynamics (SuMD) simulations, presenting the possibility to inspect hydration sites during the ligand–protein association process. Finally, a penalty scoring method, named AquaMMapScoring(AMS), was developed to evaluate the number and nature of the water molecules displaced by a ligand approaching its binding site during the binding event, guiding a medicinal chemist to explore the most suitable regions of a ligand that can be decorated either with or without interfering with the interaction networks mediated by water molecules with specific recognition regions of the protein.

New Trends in Inspecting GPCR-ligand Recognition Process: the Contribution of the Molecular Modeling Section (MMS) at the University of Padova.

In this review, we present a survey of the recent advances carried out by our research groups in the field of ligand‐GPCRs recognition process simulations recently implemented at the Molecular Modeling Section (MMS) of the University of Padova. We briefly describe a platform of tools we have tuned to aid the identification of novel GPCRs binders and the better understanding of their binding mechanisms, based on two extensively used computational techniques such as molecular docking and MD simulations. The developed methodologies encompass: (i) the selection of suitable protocols for docking studies, (ii) the exploration of the dynamical evolution of ligand‐protein interaction networks, (iii) the detailed investigation of the role of water molecules upon ligand binding, and (iv) a glance at the way the ligand might go through prior reaching the binding site.

Cryo-EM structure of the active, Gs-protein complexed, human CGRP receptor

Calcitonin gene-related peptide (CGRP) is a widely expressed neuropeptide that has a major role in sensory neurotransmission. The CGRP receptor is a heterodimer of the calcitonin receptor-like receptor (CLR) class B G-protein-coupled receptor and a type 1 transmembrane domain protein, receptor activity-modifying protein 1 (RAMP1). Here we report the structure of the human CGRP receptor in complex with CGRP and the Gs-protein heterotrimer at 3.3 Å global resolution, determined by Volta phase-plate cryo-electron microscopy. The receptor activity-modifying protein transmembrane domain sits at the interface between transmembrane domains 3, 4 and 5 of CLR, and stabilizes CLR extracellular loop 2. RAMP1 makes only limited direct contact with CGRP, consistent with its function in allosteric modulation of CLR. Molecular dynamics simulations indicate that RAMP1 provides stability to the receptor complex, particularly in the positioning of the extracellular domain of CLR. This work provides insights into the control of G-protein-coupled receptor function.The structure of a complex containing calcitonin gene-related peptide, the human calcitonin gene-related peptide receptor and the Gs heterotrimer, determined using Volta phase-plate cryo-electron microscopy, provides structural insight into the regulation of G-protein-coupled receptors by receptor activity modifying protein 1.