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

Investigating RNA-protein recognition mechanisms through supervised molecular dynamics (SuMD) simulations

Ribonucleic acid (RNA) plays a key regulatory role within the cell, cooperating with proteins to control the genome expression and several biological processes. Due to its characteristic structural features, this polymer can mold itself into different three-dimensional structures able to recognize target biomolecules with high affinity and specificity, thereby attracting the interest of drug developers and medicinal chemists. One successful example of the exploitation of RNA's structural and functional peculiarities is represented by aptamers, a class of therapeutic and diagnostic tools that can recognize and tightly bind several pharmaceutically relevant targets, ranging from small molecules to proteins, making use of the available structural and conformational freedom to maximize the complementarity with their interacting counterparts. In this scientific work, we present the first application of Supervised Molecular Dynamics (SuMD), an enhanced sampling Molecular Dynamics-based method for the study of receptor-ligand association processes in the nanoseconds timescale, to the study of recognition pathways between RNA aptamers and proteins, elucidating the main advantages and limitations of the technique while discussing its possible role in the rational design of RNA-based therapeutics.

Selective activation of Gαob by an adenosine A1 receptor agonist elicits analgesia without cardiorespiratory depression

The development of therapeutic agonists for G protein-coupled receptors (GPCRs) is hampered by the propensity of GPCRs to couple to multiple intracellular signalling pathways. This promiscuous coupling leads to numerous downstream cellular effects, some of which are therapeutically undesirable. This is especially the case for adenosine A1 receptors (A1Rs) whose clinical potential is undermined by the sedation and cardiorespiratory depression caused by conventional agonists. We have discovered that the A1R-selective agonist, benzyloxy-cyclopentyladenosine (BnOCPA), is a potent and powerful analgesic but does not cause sedation, bradycardia, hypotension or respiratory depression. This unprecedented discrimination between native A1Rs arises from BnOCPA's unique and exquisitely selective activation of Gob among the six Gαi/o subtypes, and in the absence of β-arrestin recruitment. BnOCPA thus demonstrates a highly-specific Gα-selective activation of the native A1R, sheds new light on GPCR signalling, and reveals new possibilities for the development of novel therapeutics based on the far-reaching concept of selective Gα agonism.

Exploring Ligand Binding to Calcitonin Gene-Related Peptide Receptors

Class B1 G protein-coupled receptors (GPCRs) are important targets for many diseases, including cancer, diabetes, and heart disease. All the approved drugs for this receptor family are peptides that mimic the endogenous activating hormones. An understanding of how agonists bind and activate class B1 GPCRs is fundamental for the development of therapeutic small molecules. We combined supervised molecular dynamics (SuMD) and classic molecular dynamics (cMD) simulations to study the binding of the calcitonin gene-related peptide (CGRP) to the CGRP receptor (CGRPR). We also evaluated the association and dissociation of the antagonist telcagepant from the extracellular domain (ECD) of CGRPR and the water network perturbation upon binding. This study, which represents the first example of dynamic docking of a class B1 GPCR peptide, delivers insights on several aspects of ligand binding to CGRPR, expanding understanding of the role of the ECD and the receptor-activity modifying protein 1 (RAMP1) on agonist selectivity.

Multisite Model of Allosterism for the Adenosine A1 Receptor

Despite being a target for about one-third of approved drugs, G protein-coupled receptors (GPCRs) still represent a tremendous reservoir for therapeutic strategies against diseases. For example, several cardiovascular and central nervous system conditions could benefit from clinical agents that activate the adenosine 1 receptor (A₁R); however, the pursuit of A₁R agonists for clinical use is usually impeded by both on- and off-target side effects. One of the possible strategies to overcome this issue is the development of positive allosteric modulators (PAMs) capable of selectively enhancing the effect of a specific receptor subtype and triggering functional selectivity (a phenomenon also referred to as bias). Intriguingly, besides enforcing the effect of agonists upon binding to an allosteric site, most of the A₁R PAMs display intrinsic partial agonism and orthosteric competition with antagonists. To rationalize this behavior, we simulated the binding of the prototypical PAMs PD81723 and VCP171, the full-agonist NECA, the antagonist 13B, and the bitopic agonist VCP746. We propose that a single PAM can bind several A₁R sites rather than a unique allosteric pocket, reconciling the structure-activity relationship and the mutagenesis results.

Structure-based identification of dual ligands at the A2AR and PDE10A with anti-proliferative effects in lung cancer cell-lines

Enhanced/prolonged cAMP signalling has been suggested as a suppressor of cancer proliferation. Interestingly, two key modulators that elevate cAMP, the A2A receptor (A2AR) and phosphodiesterase 10A (PDE10A), are differentially co-expressed in various types of non-small lung cancer (NSCLC) cell-lines. Thus, finding dual-target compounds, which are simultaneously agonists at the A2AR whilst also inhibiting PDE10A, could be a novel anti-proliferative approach. Using ligand- and structure-based modelling combined with MD simulations (which identified Val84 displacement as a novel conformational descriptor of A2AR activation), a series of known PDE10A inhibitors were shown to dock to the orthosteric site of the A2AR. Subsequent in-vitro analysis confirmed that these compounds bind to the A2AR and exhibit dual-activity at both the A2AR and PDE10A. Furthermore, many of the compounds exhibited promising anti-proliferative effects upon NSCLC cell-lines, which directly correlated with the expression of both PDE10A and the A2AR. Thus, we propose a structure-based methodology, which has been validated in in-vitro binding and functional assays, and demonstrated a promising therapeutic value.

The latest automated docking technologies for novel drug discovery

INTRODUCTION

Molecular docking has been consolidated as one of the most important methods in the molecular modeling field. It has been recognized as a prominent tool in the study of protein-ligand complexes, to describe intermolecular interactions, to accurately predict poses of multiple ligands, to discover novel promising bioactive compounds. Molecular docking methods have evolved in terms of their accuracy and reliability; but there are pending issues to solve for improving the connection between the docking results and the experimental evidence.

AREAS COVERED

In this article, the author reviews very recent innovative molecular docking applications with special emphasis on reverse docking, treatment of protein flexibility, the use of experimental data to guide the selection of docking poses, the application of Quantum mechanics(QM) in docking, and covalent docking.

EXPERT OPINION

There are several issues being worked on in recent years that will lead to important breakthroughs in molecular docking methods in the near future These developments are related to more efficient exploration of large datasets and receptor conformations, advances in electronic description, and the use of structural information for guiding the selection of results.

The rise of molecular simulations in fragment-based drug design (FBDD): an overview

Fragment-based drug discovery (FBDD) is an innovative approach, progressively more applied in the academic and industrial context, to enhance hit identification for previously considered undruggable biological targets. In particular, FBDD discovers low-molecular-weight (LMW) ligands (<300Da) able to bind to therapeutically relevant macromolecules in an affinity range from the micromolar (μM) to millimolar (mM). X-ray crystallography (XRC) and nuclear magnetic resonance (NMR) spectroscopy are commonly the methods of choice to obtain 3D information about the bound ligand-protein complex, but this can occasionally be problematic, mainly for early, low-affinity fragments. The recent development of computational fragment-based approaches provides a further strategy for improving the identification of fragment hits. In this review, we summarize the state of the art of molecular dynamics simulations approaches used in FBDD, and discuss limitations and future perspectives for these approaches.

Insights into adenosine A2A receptor activation through cooperative modulation of agonist and allosteric lipid interactions

The activation process of G protein-coupled receptors (GPCRs) has been extensively studied, both experimentally and computationally. In particular, Molecular Dynamics (MD) simulations have proven useful in exploring GPCR conformational space. The typical behaviour of class A GPCRs, when subjected to unbiased MD simulations from their crystallized inactive state, is to fluctuate between inactive and intermediate(s) conformations, even with bound agonist. Fully active conformation(s) are rarely stabilized unless a G protein is also bound. Despite several crystal structures of the adenosine A2a receptor (A2aR) having been resolved in complex with co-crystallized agonists and Gs protein, its agonist-mediated activation process is still not completely understood. In order to thoroughly examine the conformational landscape of A2aR activation, we performed unbiased microsecond-length MD simulations in quadruplicate, starting from the inactive conformation either in apo or with bound agonists: endogenous adenosine or synthetic NECA, embedded in two homogeneous phospholipid membranes: 1,2-dioleoyl-sn-glycerol-3-phosphoglycerol (DOPG) or 1,2-dioleoyl-sn-glycerol-3-phosphocholine (DOPC). In DOPC with bound adenosine or NECA, we observe transition to an intermediate receptor conformation consistent with the known adenosine-bound crystal state. In apo state in DOPG, two different intermediate conformations are obtained. One is similar to that observed with bound adenosine in DOPC, while the other is closer to the active state but not yet fully active. Exclusively, in DOPG with bound adenosine or NECA, we reproducibly identify receptor conformations with fully active features, which are able to dock Gs protein. These different receptor conformations can be attributed to the action/absence of agonist and phospholipid-mediated allosteric effects on the intracellular side of the receptor.

Molecular Dynamics Simulations of Adenosine Receptors: Advances, Applications and Trends

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Adenosine receptors (ARs) are transmembrane proteins that belong to the G protein-coupled receptors (GPCRs) superfamily and mediate the biological functions of adenosine. To date, four AR subtypes are known, namely A1, A2A, A2B and A3 that exhibit different signaling pathways, tissue localization, and mechanisms of activation. Moreover, the widespread ARs and their implication in numerous physiological and pathophysiological conditions had made them pivotal therapeutic targets for developing clinically effective agents.

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The crystallographic success in identifying the 3D crystal structures of A2A and A1 ARs has dramatically enriched our understanding of their structural and functional properties such as ligand binding and signal transduction. This, in turn, has provided a structural basis for a larger contribution of computational methods, particularly molecular dynamics (MD) simulations, toward further investigation of their molecular properties and designing bioactive ligands with therapeutic potential. MD simulation has been proved to be an invaluable tool in investigating ARs and providing answers to some critical questions. For example, MD has been applied in studying ARs in terms of ligand-receptor interactions, molecular recognition, allosteric modulations, dimerization, and mechanisms of activation, collectively aiding in the design of subtype selective ligands.

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In this review, we focused on the advances and different applications of MD simulations utilized to study the structural and functional aspects of ARs that can foster the structure-based design of drug candidates. In addition, relevant literature was briefly discussed which establishes a starting point for future advances in the field of drug discovery to this pivotal group of drug targets.

Bridging Molecular Docking to Molecular Dynamics in Exploring Ligand-Protein Recognition Process: An Overview

Computational techniques have been applied in the drug discovery pipeline since the 1980s. Given the low computational resources of the time, the first molecular modeling strategies relied on a rigid view of the ligand-target binding process. During the years, the evolution of hardware technologies has gradually allowed simulating the dynamic nature of the binding event. In this work, we present an overview of the evolution of structure-based drug discovery techniques in the study of ligand-target recognition phenomenon, going from the static molecular docking toward enhanced molecular dynamics strategies.

An overview of recent molecular dynamics applications as medicinal chemistry tools for the undruggable site challenge

Molecular dynamics (MD) has become increasingly popular due to the development of hardware and software solutions and the improvement in algorithms, which allowed researchers to scale up calculations in order to speed them up. MD simulations are usually used to address protein folding issues or protein-ligand complex stability through energy profile analysis over time. In recent years, the development of new tools able to deeply explore a potential energy surface (PES) has allowed researchers to focus on the dynamic nature of the binding recognition process and binding-induced protein conformational changes. Moreover, modern approaches have been demonstrated to be effective and reliable in calculating some kinetic and thermodynamic parameters behind the host-guest recognition process. Starting from all of these considerations, several efforts have been made in order to integrate MD within the virtual screening process in drug discovery. Knowledge retrieved from MD can, in fact, be exploited as a starting point to build pharmacophores or docking constraints in the early stage of the screening campaign as well as to define key features, in order to unravel hidden binding modes and help the optimisation of the molecular structure of a lead compound. Based on these outcomes, researchers are nowadays using MD as an invaluable tool to discover and target previously considered undruggable binding sites, including protein-protein interactions and allosteric sites on a protein surface. As a matter of fact, the use of MD has been recognised as vital to the discovery of selective protein-protein interaction modulators. The use of a dynamic overview on how the host-guest recognition occurs and of the relative conformational modifications induced allows researchers to optimise small molecules and small peptides capable of tightly interacting within the cleft between two proteins. In this review, we aim to present the most recent applications of MD as an integrated tool to be used in the rational design of small molecules or small peptides able to modulate undruggable targets, such as allosteric sites and protein-protein interactions.

Special Issue: Adenosine Receptors

Nearly 90 years ago, Drury and Szent-Györgyi revealed that adenosine produced profound hypotension and bradycardia, and it affected kidney function in mammals [1]. [...].