Conservation of Allosteric Ligand Binding Sites in G-Protein Coupled Receptors

Decoding allosteric landscapes: computational methodologies for enzyme modulation and drug discovery

Allosteric regulation is a fundamental mechanism in enzyme function, enabling dynamic modulation of activity through ligand binding at sites distal to the active site. Allosteric modulators have gained significant attention due to their unique advantages, including enhanced specificity, reduced off-target effects, and the potential for synergistic interaction with orthosteric agents. However, the inherent complexity of allosteric mechanisms has posed challenges to the systematic discovery and design of allosteric modulators. This review discusses recent advancements in computational methodologies for identifying and characterizing allosteric sites in enzymes, emphasizing techniques such as molecular dynamics (MD) simulations, enhanced sampling methods, normal mode analysis (NMA), evolutionary conservation analysis, and machine learning (ML) approaches. Advanced tools like PASSer, AlloReverse, and AlphaFold have further enhanced the understanding of allosteric mechanisms and facilitated the design of selective allosteric modulators. Case studies on enzymes such as Sirtuin 6 (SIRT6) and MAPK/ERK kinase (MEK) demonstrate the practical applications of these approaches in drug discovery. By integrating computational predictions with experimental validation, this review highlights the transformative potential of computational strategies in advancing allosteric drug discovery, offering innovative opportunities to regulate enzyme activity for therapeutic benefits.

Exploring G Protein-Coupled Receptors in Hematological Cancers

Hematological cancers, such as lymphomas and leukemias, pose significant challenges in oncology, necessitating a deeper understanding of their molecular landscape to enhance therapeutic strategies. This article critically examines and discusses recent research on the roles of G protein-coupled receptors (GPCRs) in myeloma, lymphomas, and leukemias with a particular focus on pediatric acute lymphoblastic (lymphocytic) leukemia (ALL). By utilizing RNA sequencing (RNA-seq), we analyzed GPCR expression patterns in pediatric ALL samples (aged 3-12 years old), with a further focus on Class A orphan GPCRs. Our analysis revealed distinct GPCR expression profiles in pediatric ALL, identifying several candidates with aberrant upregulated expression compared with healthy counterparts. Among these GPCRs, GPR85, GPR65, and GPR183 have varying numbers of studies in the field of hematological cancers and pediatric ALL. Furthermore, we explored missense mutations of pediatric ALL in relation to the RNA gene expression findings, providing insights into the genetic underpinnings of this disease. By integrating both RNA-seq and missense mutation data, this article aims to provide an insightful and broader perspective on the potential correlations between specific GPCR and their roles in pediatric ALL.

Comparative Study of Allosteric GPCR Binding Sites and Their Ligandability Potential

The steadily growing number of experimental G-protein-coupled receptor (GPCR) structures has revealed diverse locations of allosteric modulation, and yet few drugs target them. This gap highlights the need for a deeper understanding of allosteric modulation in GPCR drug discovery. The current work introduces a systematic annotation scheme to structurally classify GPCR binding sites based on receptor class, transmembrane helix contacts, and, for membrane-facing sites, membrane sublocation. This GPCR specific annotation scheme was applied to 107 GPCR structures bound by small molecules contributing to 24 distinct allosteric binding sites for comparative evaluation of three binding site detection methods (BioGPS, SiteMap, and FTMap). BioGPS identified the most in 22 of 24 sites. In addition, our property analysis showed that extrahelical allosteric ligands and binding sites represent a distinct chemical space characterized by shallow pockets with low volume, and the corresponding allosteric ligands showed an enrichment of halogens. Furthermore, we demonstrated that combining receptor and ligand similarity can be a viable method for ligandability assessment. One challenge regarding site prediction is the ligand shaping effect on the observed binding site, especially for extrahelical sites where the ligand-induced effect was most pronounced. To our knowledge, this is the first study presenting a binding site annotation scheme standardized for GPCRs, and it allows a comparison of allosteric binding sites across different receptors in an objective way. The insight from this study provides a framework for future GPCR binding site studies and highlights the potential of targeting allosteric sites for drug development.

Structural perspectives on chemokine receptors

Chemokine receptors are integral to the immune system and prime targets in drug discovery that have undergone extensive structural elucidation in recent years. We outline a timeline of these structural achievements, discuss the intracellular negative allosteric modulation of chemokine receptors, analyze the mechanisms of orthosteric receptor activation, and report on the emerging concept of biased signaling. Additionally, we highlight differences of G-protein binding among chemokine receptors. Intracellular allosteric modulators in chemokine receptors interact with a conserved motif within transmembrane helix 7 and helix 8 and exhibit a two-fold inactivation mechanism that can be harnessed for drug-discovery efforts. Chemokine recognition is a multi-step process traditionally explained by a two-site model within chemokine recognition site 1 (CRS1) and CRS2. Recent structural studies have extended our understanding of this complex mechanism with the identification of CRS1.5 and CRS3. CRS3 is implicated in determining ligand specificity and surrounds the chemokine by almost 180°. Within CRS3 we identified the extracellular loop 2 residue 45.51 as a key interaction mediator for chemokine binding. Y2917.43 on the other hand was shown in CCR1 to be a key determinant of signaling bias which, along with specific chemokine-dependent phosphorylation ensembles at the G-protein coupled receptors (GPCR's) C-terminus, seems to play a pivotal role in determining the direction of signal bias in GPCRs.

G protein-coupled receptors (GPCRs): advances in structures, mechanisms, and drug discovery

G protein-coupled receptors (GPCRs), the largest family of human membrane proteins and an important class of drug targets, play a role in maintaining numerous physiological processes. Agonist or antagonist, orthosteric effects or allosteric effects, and biased signaling or balanced signaling, characterize the complexity of GPCR dynamic features. In this study, we first review the structural advancements, activation mechanisms, and functional diversity of GPCRs. We then focus on GPCR drug discovery by revealing the detailed drug-target interactions and the underlying mechanisms of orthosteric drugs approved by the US Food and Drug Administration in the past five years. Particularly, an up-to-date analysis is performed on available GPCR structures complexed with synthetic small-molecule allosteric modulators to elucidate key receptor-ligand interactions and allosteric mechanisms. Finally, we highlight how the widespread GPCR-druggable allosteric sites can guide structure- or mechanism-based drug design and propose prospects of designing bitopic ligands for the future therapeutic potential of targeting this receptor family.

Expanding FTMap for Fragment-Based Identification of Pharmacophore Regions in Ligand Binding Sites

The knowledge of ligand binding hot spots and of the important interactions within such hot spots is crucial for the design of lead compounds in the early stages of structure-based drug discovery. The computational solvent mapping server FTMap can reliably identify binding hot spots as consensus clusters, free energy minima that bind a variety of organic probe molecules. However, in its current implementation, FTMap provides limited information on regions within the hot spots that tend to interact with specific pharmacophoric features of potential ligands. E-FTMap is a new server that expands on the original FTMap protocol. E-FTMap uses 119 organic probes, rather than the 16 in the original FTMap, to exhaustively map binding sites, and identifies pharmacophore features as atomic consensus sites where similar chemical groups bind. We validate E-FTMap against a set of 109 experimentally derived structures of fragment-lead pairs, finding that highly ranked pharmacophore features overlap with the corresponding atoms in both fragments and lead compounds. Additionally, comparisons of mapping results to ensembles of bound ligands reveal that pharmacophores generated with E-FTMap tend to sample highly conserved protein-ligand interactions. E-FTMap is available as a web server at https://eftmap.bu.edu.

Deep Learning Dynamic Allostery of G-Protein-Coupled Receptors

G-protein-coupled receptors (GPCRs) make up the largest superfamily of human membrane proteins and represent primary targets of ∼1/3 of currently marketed drugs. Allosteric modulators have emerged as more selective drug candidates compared with orthosteric agonists and antagonists. However, many X-ray and cryo-EM structures of GPCRs resolved so far exhibit negligible differences upon the binding of positive and negative allosteric modulators (PAMs and NAMs). The mechanism of dynamic allosteric modulation in GPCRs remains unclear. In this work, we have systematically mapped dynamic changes in free energy landscapes of GPCRs upon binding of allosteric modulators using the Gaussian accelerated molecular dynamics (GaMD), deep learning (DL), and free energy prOfiling Workflow (GLOW). GaMD simulations were performed for a total of 66 μs on 44 GPCR systems in the presence and absence of the modulator. DL and free energy calculations revealed significantly reduced dynamic fluctuations and conformational space of GPCRs upon modulator binding. While the modulator-free GPCRs often sampled multiple low-energy conformational states, the NAMs and PAMs confined the inactive and active agonist-G-protein-bound GPCRs, respectively, to mostly only one specific conformation for signaling. Such cooperative effects were significantly reduced for binding of the selective modulators to "non-cognate" receptor subtypes. Therefore, GPCR allostery exhibits a dynamic "conformational selection" mechanism. In the absence of available modulator-bound structures as for most current GPCRs, it is critical to use a structural ensemble of representative GPCR conformations rather than a single structure for compound docking ("ensemble docking"), which will potentially improve structure-based design of novel allosteric drugs of GPCRs.

Allosteric crosstalk in modular proteins: Function fine-tuning and drug design

Modular proteins are regulatory proteins that carry out more than one function. These proteins upregulate or downregulate a biochemical cascade to establish homeostasis in cells. To switch the function or alter the efficiency (based on cellular needs), these proteins require different facilitators that bind to a site different from the catalytic (active/orthosteric) site, aka 'allosteric site', and fine-tune their function. These facilitators (or effectors) are allosteric modulators. In this Review, we have discussed the allostery, characterized them based on their mechanisms, and discussed how allostery plays an important role in the activity modulation and function fine-tuning of proteins. Recently there is an emergence in the discovery of allosteric drugs. We have also emphasized the role, significance, and future of allostery in therapeutic applications.

An inverse agonist of orphan receptor GPR61 acts by a G protein-competitive allosteric mechanism

GPR61 is an orphan GPCR related to biogenic amine receptors. Its association with phenotypes relating to appetite makes it of interest as a druggable target to treat disorders of metabolism and body weight, such as obesity and cachexia. To date, the lack of structural information or a known biological ligand or tool compound has hindered comprehensive efforts to study GPR61 structure and function. Here, we report a structural characterization of GPR61, in both its active-like complex with heterotrimeric G protein and in its inactive state. Moreover, we report the discovery of a potent and selective small-molecule inverse agonist against GPR61 and structural elucidation of its allosteric binding site and mode of action. These findings offer mechanistic insights into an orphan GPCR while providing both a structural framework and tool compound to support further studies of GPR61 function and modulation.

Advances in the allostery of angiotensin II type 1 receptor

Angiotensin II type 1 receptor (AT1R) is a promising therapeutic target for cardiovascular diseases. Compared with orthosteric ligands, allosteric modulators attract considerable attention for drug development due to their unique advantages of high selectivity and safety. However, no allosteric modulators of AT1R have been applied in clinical trials up to now. Except for the classical allosteric modulators of AT1R such as antibody, peptides and amino acids, cholesterol and biased allosteric modulators, there are non-classical allosteric modes including the ligand-independent allosteric mode, and allosteric mode of biased agonists and dimers. In addition, finding the allosteric pockets based on AT1R conformational change and interaction interface of dimers are the future of drug design. In this review, we summarize the different allosteric mode of AT1R, with a view to contribute to the development and utilization of drugs targeting AT1R allostery.

Selective Deuteration Improves the Affinity of Adenosine A2A Receptor Ligands: A Computational Case Study with Istradefylline and Caffeine

We used a range of computational techniques to assess the effect of selective C-H deuteration on the antagonist istradefylline affinity for the adenosine A_2A receptor, which was discussed relative to its structural analogue caffeine, a well-known and likely the most widely used stimulant. The obtained results revealed that smaller caffeine shows high receptor flexibility and exchanges between two distinct poses, which agrees with crystallographic data. In contrast, the additional C8-trans-styryl fragment in istradefylline locks the ligand within a uniform binding pose, while contributing to the affinity through the C-H···π and π···π contacts with surface residues, which, together with its much lower hydration prior to binding, enhances the affinity over caffeine. In addition, the aromatic C8-unit shows a higher deuteration sensitivity over the xanthine part, so when both of its methoxy groups are d₆-deuterated, the affinity improvement is -0.4 kcal mol^-1, which surpasses the overall affinity gain of -0.3 kcal mol^-1 in the perdeuterated d₉-caffeine. Yet, the latter predicts around 1.7-fold potency increase, being relevant for its pharmaceutical implementations, and also those within the coffee and energy drink production industries. Still, the full potential of our strategy is achieved in polydeuterated d₁₉-istradefylline, whose A_2A affinity improves by -0.6 kcal mol^-1, signifying a 2.8-fold potency increase that strongly promotes it as a potential synthetic target. This knowledge supports deuterium application in drug design, and while the literature already reports about over 20 deuterated drugs currently in the clinical development, it is easily foreseen that more examples will hit the market in the years to come. With this in mind, we propose that the devised computational methodology, involving the ONIOM division of the QM region for the ligand and the MM region for its environment, with an implicit quantization of nuclear motions relevant for the H/D exchange, allows fast and efficient estimates of the binding isotope effects in any biological system.

Olfaction: Allosteric modulation

New research indicates that the odor-evoked responses of human olfactory receptors can be enhanced via the non-competitive binding of an allosteric modulator. This modulatory mechanism adds an additional layer of complexity to the peripheral encoding of odors.

Deep Learning Dynamic Allostery of G-Protein-Coupled Receptors

G-protein-coupled receptors (GPCRs) are the largest superfamily of human membrane proteins and represent primary targets of ~ 1/3 of currently marketed drugs. Allosteric modulators have emerged as more selective drug candidates compared with orthosteric agonists and antagonists. However, many X-ray and cryo-EM structures of GPCRs resolved so far exhibit negligible differences upon binding of positive and negative allosteric modulators (PAMs and NAMs). Mechanism of dynamic allosteric modulation in GPCRs remains unclear. In this work, we have systematically mapped dynamic changes in free energy landscapes of GPCRs upon binding of allosteric modulators using the Gaussian accelerated molecular dynamics (GaMD), Deep Learning (DL) and free energy prOfiling Workflow (GLOW). A total of 18 available high-resolution experimental structures of allosteric modulator-bound class A and B GPCRs were collected for simulations. A number of 8 computational models were generated to examine selectivity of the modulators by changing their target receptors to different subtypes. All-atom GaMD simulations were performed for a total of 66 μs on 44 GPCR systems in the presence/absence of the modulator. DL and free energy calculations revealed significantly reduced conformational space of GPCRs upon modulator binding. While the modulator-free GPCRs often sampled multiple low-energy conformational states, the NAMs and PAMs confined the inactive and active agonist-G protein-bound GPCRs, respectively, to mostly only one specific conformation for signaling. Such cooperative effects were significantly reduced for binding of the selective modulators to "non-cognate" receptor subtypes in the computational models. Therefore, comprehensive DL of extensive GaMD simulations has revealed a general dynamic mechanism of GPCR allostery, which will greatly facilitate rational design of selective allosteric drugs of GPCRs.

Deep Learning Dynamic Allostery of G-Protein-Coupled Receptors

G-protein-coupled receptors (GPCRs) are the largest superfamily of human membrane proteins and represent primary targets of ~1/3 of currently marketed drugs. Allosteric modulators have emerged as more selective drug candidates compared with orthosteric agonists and antagonists. However, many X-ray and cryo-EM structures of GPCRs resolved so far exhibit negligible differences upon binding of positive and negative allosteric modulators (PAMs and NAMs). Mechanism of dynamic allosteric modulation in GPCRs remains unclear. In this work, we have systematically mapped dynamic changes in free energy landscapes of GPCRs upon binding of allosteric modulators using the Gaussian accelerated molecular dynamics (GaMD), Deep Learning (DL) and free energy prOfiling Workflow (GLOW). A total of 18 available high-resolution experimental structures of allosteric modulator-bound class A and B GPCRs were collected for simulations. A number of 8 computational models were generated to examine selectivity of the modulators by changing their target receptors to different subtypes. All-atom GaMD simulations were performed for a total of 66 μs on 44 GPCR systems in the presence/absence of the modulator. DL and free energy calculations revealed significantly reduced conformational space of GPCRs upon modulator binding. While the modulator-free GPCRs often sampled multiple low-energy conformational states, the NAMs and PAMs confined the inactive and active agonist-G protein-bound GPCRs, respectively, to mostly only one specific conformation for signaling. Such cooperative effects were significantly reduced for binding of the selective modulators to "non-cognate" receptor subtypes in the computational models. Therefore, comprehensive DL of extensive GaMD simulations has revealed a general dynamic mechanism of GPCR allostery, which will greatly facilitate rational design of selective allosteric drugs of GPCRs.