Ligand Discovery for a Peptide-Binding GPCR by Structure-Based Screening of Fragment- and Lead-Like Chemical Libraries

Identification of a Novel Subtype-Selective α1B-Adrenoceptor Antagonist

α1A-, α1B-, and α1D-adrenoceptors (α1-ARs) are members of the adrenoceptor G protein-coupled receptor family that are activated by adrenaline (epinephrine) and noradrenaline. α1-ARs are clinically targeted using antagonists that have minimal subtype selectivity, such as prazosin and tamsulosin, to treat hypertension and benign prostatic hyperplasia, respectively. Abundant expression of α1-ARs in the heart and central nervous system (CNS) makes these receptors potential targets for the treatment of cardiovascular and CNS disorders, such as heart failure, epilepsy, and Alzheimer's disease. Our understanding of the precise physiological roles of α1-ARs, however, and their involvement in disease has been hindered by the lack of sufficiently subtype-selective tool compounds, especially for α1B-AR. Here, we report the discovery of 4-[(2-hydroxyethyl)amino]-6-methyl-2H-chromen-2-one (Cpd1), as an α1B-AR antagonist that has 10-15-fold selectivity over α1A-AR and α1D-AR. Through computational and site-directed mutagenesis studies, we have identified the binding site of Cpd1 in α1B-AR and propose the molecular basis of α1B-AR selectivity, where the nonconserved V19745.52 residue plays a major role, with contributions from L3146.55 within the α1B-AR pocket. By exploring the structure-activity relationships of Cpd1 at α1B-AR, we have also identified 3-[(cyclohexylamino)methyl]-6-methylquinolin-2(1H)-one (Cpd24), which has a stronger binding affinity than Cpd1, albeit with reduced selectivity for α1B-AR. Cpd1 and Cpd24 represent potential leads for α1B-AR-selective drug discovery and novel tool molecules to further study the physiology of α1-ARs.

Computational drug development for membrane protein targets

The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine learning structure-based design and the evaluation of big data. Recent protein structure predictions based on machine learning tools have delivered surprisingly reliable results for water-soluble and membrane proteins but have limitations for development of drugs that target membrane proteins. Structural transitions of membrane proteins have a central role during transmembrane signaling and are often influenced by therapeutic compounds. Resolving the structural and functional basis of dynamic transmembrane signaling networks, especially within the native membrane or cellular environment, remains a central challenge for drug development. Tackling this challenge will require an interplay between experimental and computational tools, such as super-resolution optical microscopy for quantification of the molecular interactions of cellular signaling networks and their modulation by potential drugs, cryo-electron microscopy for determination of the structural transitions of proteins in native cell membranes and entire cells, and computational tools for data analysis and prediction of the structure and function of cellular signaling networks, as well as generation of promising drug candidates.

The neuropeptide galanin adopts an irregular secondary structure

Human galanin is a 30-residue neuropeptide targeted for development of analgesics, antidepressants, and anticonvulsants. While previous work from our group and others has already produced significant insights into galanin's N-terminal region, no extant structures of galanin in databases include its full-length sequence and the function of its C-terminus remains ambiguous. We report the NMR solution structure of full-length human galanin C-terminal amide, determined from 2D ¹H-¹H COSY, TOCSY, and ROESY NMR data. Galanin adopts an irregular helical structure across its N-terminus, likely the average of several coiling states. We present the NMR structure of a peptide encompassing the C-terminus of galanin as a stand-alone fragment. The C-terminus of full-length galanin appears to indirectly assist the intramolecular association of hydrophobic sidechains within its N-terminus, remotely rigidifying their position when compared to previously studied N-terminal galanin fragments. By contrast, there is flexibility in the C-terminus of galanin, characterized by two i to i + 2 hydrogen-bonded turns within an otherwise dynamic backbone. The C-terminal portion of the peptide renders it soluble, and plays a hitherto undescribed biophysical role in pre-organizing the galanin receptor binding epitope. We speculate that hydrophilic microdomains of signaling peptides, hormones, and perhaps intrinsically disordered proteins may also function similarly.

Minimal Increments of Hydrophobic Collapse within the N-Terminus of the Neuropeptide Galanin

The neuropeptide galanin has a 35-year history as an intriguing target in drug design owing to its implication as a potential anticonvulsant and neuronal trophic factor among many other therapeutically interesting functions including analgesia and mood alteration. In this study, we report the structural characterization of three synthetic fragments of the galanin N-terminus in buffered aqueous solution: hGal(2-12)KK, hGal(1-12)KK, and hGal(1-17)KK. High-field two-dimensional ¹H-¹H nuclear magnetic resonance (NMR) data were acquired for these fragments and used to derive distance restraints. We further utilized modified hydrogen bonding and dihedral restraints to reflect chemical shift patterns in the data, which revealed the signature of a weakly folded helix. Together, these sets of restraints were used to generate NMR structures of all three fragments, which depict a core of hydrophobic residues that cluster together regardless of the presence of a helical structure, and correspond to residues in the N-terminus of galanin that have been previously shown to be critical for binding its receptors. The helical structure only appears following the inclusion of Gly(1) in the sequence, and at longer sequence lengths, unlike many other peptides, the helix does not propagate. Rather, a few turns of poorly ordered helix appear to be a secondary consequence of clusters of hydrophobic sidechains that are conserved across all of the peptides in this study; the helices themselves appear ordered as a consequence of this clustering, and these clusters compare directly to those observed recently to make contacts between galanin and two of its receptor subtypes. Collapsed hydrophobic residues therefore organize and compose the functional core of human galanin and raise interesting questions about the nature of the conformational order in ligands that bind cell surface receptors.

Free Energy-Based Computational Methods for the Study of Protein-Peptide Binding Equilibria

This chapter discusses the theory and application of physics-based free energy methods to estimate protein-peptide binding free energies. It presents a statistical mechanics formulation of molecular binding, which is then specialized in three methodologies: (1) alchemical absolute binding free energy estimation with implicit solvation, (2) alchemical relative binding free energy estimation with explicit solvation, and (3) potential of mean force binding free energy estimation. Case studies of protein-peptide binding application taken from the recent literature are discussed for each method.

Structure-Based Virtual Screening for Ligands of G Protein-Coupled Receptors: What Can Molecular Docking Do for You?

G protein-coupled receptors (GPCRs) constitute the largest family of membrane proteins in the human genome and are important therapeutic targets. During the last decade, the number of atomic-resolution structures of GPCRs has increased rapidly, providing insights into drug binding at the molecular level. These breakthroughs have created excitement regarding the potential of using structural information in ligand design and initiated a new era of rational drug discovery for GPCRs. The molecular docking method is now widely applied to model the three-dimensional structures of GPCR-ligand complexes and screen for chemical probes in large compound libraries. In this review article, we first summarize the current structural coverage of the GPCR superfamily and the understanding of receptor-ligand interactions at atomic resolution. We then present the general workflow of structure-based virtual screening and strategies to discover GPCR ligands in chemical libraries. We assess the state of the art of this research field by summarizing prospective applications of virtual screening based on experimental structures. Strategies to identify compounds with specific efficacy and selectivity profiles are discussed, illustrating the opportunities and limitations of the molecular docking method. Our overview shows that structure-based virtual screening can discover novel leads and will be essential in pursuing the next generation of GPCR drugs. SIGNIFICANCE STATEMENT: Extraordinary advances in the structural biology of G protein-coupled receptors have revealed the molecular details of ligand recognition by this large family of therapeutic targets, providing novel avenues for rational drug design. Structure-based docking is an efficient computational approach to identify novel chemical probes from large compound libraries, which has the potential to accelerate the development of drug candidates.

Directed evolution for high functional production and stability of a challenging G protein-coupled receptor

Membrane proteins such as G protein-coupled receptors (GPCRs) carry out many fundamental biological functions, are involved in a large number of physiological responses, and are thus important drug targets. To allow detailed biophysical and structural studies, most of these important receptors have to be engineered to overcome their poor intrinsic stability and low expression levels. However, those GPCRs with especially poor properties cannot be successfully optimised even with the current technologies. Here, we present an engineering strategy, based on the combination of three previously developed directed evolution methods, to improve the properties of particularly challenging GPCRs. Application of this novel combination approach enabled the successful selection for improved and crystallisable variants of the human oxytocin receptor, a GPCR with particularly low intrinsic production levels. To analyse the selection results and, in particular, compare the mutations enriched in different hosts, we developed a Next-Generation Sequencing (NGS) strategy that combines long reads, covering the whole receptor, with exceptionally low error rates. This study thus gave insight into the evolution pressure on the same membrane protein in prokaryotes and eukaryotes. Our long-read NGS strategy provides a general methodology for the highly accurate analysis of libraries of point mutants during directed evolution.

Engineering of Challenging G Protein-Coupled Receptors for Structure Determination and Biophysical Studies

Membrane proteins such as G protein-coupled receptors (GPCRs) exert fundamental biological functions and are involved in a multitude of physiological responses, making these receptors ideal drug targets. Drug discovery programs targeting GPCRs have been greatly facilitated by the emergence of high-resolution structures and the resulting opportunities to identify new chemical entities through structure-based drug design. To enable the determination of high-resolution structures of GPCRs, most receptors have to be engineered to overcome intrinsic hurdles such as their poor stability and low expression levels. In recent years, multiple engineering approaches have been developed to specifically address the technical difficulties of working with GPCRs, which are now beginning to make more challenging receptors accessible to detailed studies. Importantly, successfully engineered GPCRs are not only valuable in X-ray crystallography, but further enable biophysical studies with nuclear magnetic resonance spectroscopy, surface plasmon resonance, native mass spectrometry, and fluorescence anisotropy measurements, all of which are important for the detailed mechanistic understanding, which is the prerequisite for successful drug design. Here, we summarize engineering strategies based on directed evolution to reduce workload and enable biophysical experiments of particularly challenging GPCRs.

G protein-coupled receptors: structure- and function-based drug discovery

As one of the most successful therapeutic target families, G protein-coupled receptors (GPCRs) have experienced a transformation from random ligand screening to knowledge-driven drug design. We are eye-witnessing tremendous progresses made recently in the understanding of their structure-function relationships that facilitated drug development at an unprecedented pace. This article intends to provide a comprehensive overview of this important field to a broader readership that shares some common interests in drug discovery.

Complexes of the neurotensin receptor 1 with small-molecule ligands reveal structural determinants of full, partial, and inverse agonism

Neurotensin receptor 1 (NTSR1) and related G protein-coupled receptors of the ghrelin family are clinically unexploited, and several mechanistic aspects of their activation and inactivation have remained unclear. Enabled by a new crystallization design, we present five new structures: apo-state NTSR1 as well as complexes with nonpeptide inverse agonists SR48692 and SR142948A, partial agonist RTI-3a, and the novel full agonist SRI-9829, providing structural rationales on how ligands modulate NTSR1. The inverse agonists favor a large extracellular opening of helices VI and VII, undescribed so far for NTSR1, causing a constriction of the intracellular portion. In contrast, the full and partial agonists induce a binding site contraction, and their efficacy correlates with the ability to mimic the binding mode of the endogenous agonist neurotensin. Providing evidence of helical and side-chain rearrangements modulating receptor activation, our structural and functional data expand the mechanistic understanding of NTSR1 and potentially other peptidergic receptors.

Releasing the technical 'shackles' on GPCR drug discovery: opportunities enabled by detergent-free polymer lipid particle (PoLiPa) purification

G-protein-coupled receptor (GPCR) drug research is presently hindered by the technical challenges associated with generating purified receptors. Consequently, the application of critical modern discovery technologies has been limited, and the vast untapped opportunity for new GPCR-directed medicines is not being realised. A simple but transformative solution is to purify receptors without removing them from their native phospholipid environment by using polymer lipid particle (PoLiPa) technology, with reagents such as styrene-maleic acid co-polymer (SMA). Compared with contemporary detergent-based and stabilising mutagenesis methods, the PoLiPa approach is simple and generic and, therefore, offers huge advantages, with the potential to revolutionise GPCR research by facilitating the availability of the purified receptors that are required for structural biology, biophysical, and panning technologies.

Performance of virtual screening against GPCR homology models: Impact of template selection and treatment of binding site plasticity

Rational drug design for G protein-coupled receptors (GPCRs) is limited by the small number of available atomic resolution structures. We assessed the use of homology modeling to predict the structures of two therapeutically relevant GPCRs and strategies to improve the performance of virtual screening against modeled binding sites. Homology models of the D2 dopamine (D2R) and serotonin 5-HT2A receptors (5-HT2AR) were generated based on crystal structures of 16 different GPCRs. Comparison of the homology models to D2R and 5-HT2AR crystal structures showed that accurate predictions could be obtained, but not necessarily using the most closely related template. Assessment of virtual screening performance was based on molecular docking of ligands and decoys. The results demonstrated that several templates and multiple models based on each of these must be evaluated to identify the optimal binding site structure. Models based on aminergic GPCRs showed substantial ligand enrichment and there was a trend toward improved virtual screening performance with increasing binding site accuracy. The best models even yielded ligand enrichment comparable to or better than that of the D2R and 5-HT2AR crystal structures. Methods to consider binding site plasticity were explored to further improve predictions. Molecular docking to ensembles of structures did not outperform the best individual binding site models, but could increase the diversity of hits from virtual screens and be advantageous for GPCR targets with few known ligands. Molecular dynamics refinement resulted in moderate improvements of structural accuracy and the virtual screening performance of snapshots was either comparable to or worse than that of the raw homology models. These results provide guidelines for successful application of structure-based ligand discovery using GPCR homology models.

High-Throughput Fluorescence Polarization Assay to Identify Ligands Using Purified G Protein-Coupled Receptor

The development of cell-free high-throughput (HT) methods to screen and select novel lead compounds remains one of the key challenges in G protein-coupled receptor (GPCR) drug discovery. Mutational approaches have allowed the stabilization of GPCRs in a purified and ligand-free state. The increased intramolecular stability overcomes two major drawbacks for usage in in vitro screening, the low receptor density on cells and the low stability in micelles. Here, an HT fluorescence polarization (FP) assay for the neurotensin receptor type 1 (NTS1) was developed. The assay operates in a 384-well format and is tolerant to DMSO. From a library screen of 1272 compounds, 12 (~1%) were identified as primary hits. These compounds were validated in orthogonal assay formats using surface plasmon resonance (SPR), which confirmed binding of seven compounds (0.6%). One of these compounds showed a clear preference for the orthosteric binding pocket with submicromolar affinity. A second compound revealed binding at a nonorthosteric binding region and showed specific biological activity on NTS1-expressing cells. A search of analogs led to further enhancement of affinity, but at the expense of activity. The identification of GPCR ligands in a cell-free assay should allow the expansion of GPCR pharmaceuticals with antagonistic or agonistic activity.

Expression and Purification of a Functional E. coli 13CH3-Methionine-Labeled Thermostable Neurotensin Receptor 1 Variant for Solution NMR Studies

Escherichia coli (E. coli) is the most widely used expression host for recombinant proteins due to high expression yields and straightforward molecular cloning. Directed evolution of G protein-coupled receptors (GPCRs) has made several of these difficult to express membrane proteins amenable to prokaryotic expression. Here, we describe a protocol for near complete ¹³CH₃-methionine labeling of a thermostable neurotensin receptor 1 (enNTS₁) variant in E. coli for solution NMR-based dynamics studies. Our expression strategy utilizes methionine biosynthesis pathway inhibition forcing E. coli to incorporate exogenous methionine with 96% efficiency at expression levels of 2.6 mg enNTS₁ per liter of expression culture containing 50 mg of ¹³CH₃-methionine. We also provide a 3-step purification protocol that produces final yields of 0.6 mg of functional Apo-state enNTS₁.

The role of small-angle scattering in structure-based screening applications

In many biomolecular interactions, changes in the assembly states and structural conformations of participants can act as a complementary reporter of binding to functional and thermodynamic assays. This structural information is captured by a number of structural biology and biophysical techniques that are viable either as primary screens in small-scale applications or as secondary screens to complement higher throughput methods. In particular, small-angle X-ray scattering (SAXS) reports the average distance distribution between all atoms after orientational averaging. Such information is important when for example investigating conformational changes involved in inhibitory and regulatory mechanisms where binding events do not necessarily cause functional changes. Thus, we summarise here the current and prospective capabilities of SAXS-based screening in the context of other methods that yield structural information. Broad guidelines are also provided to assist readers in preparing screening protocols that are tailored to available X-ray sources.

Docking Screens for Dual Inhibitors of Disparate Drug Targets for Parkinson's Disease

Modulation of multiple biological targets with a single drug can lead to synergistic therapeutic effects and has been demonstrated to be essential for efficient treatment of CNS disorders. However, rational design of compounds that interact with several targets is very challenging. Here, we demonstrate that structure-based virtual screening can guide the discovery of multi-target ligands of unrelated proteins relevant for Parkinson's disease. A library with 5.4 million molecules was docked to crystal structures of the A_2A adenosine receptor (A_2AAR) and monoamine oxidase B (MAO-B). Twenty-four compounds that were among the highest ranked for both binding sites were evaluated experimentally, resulting in the discovery of four dual-target ligands. The most potent compound was an A_2AAR antagonist with nanomolar affinity ( K_i = 19 nM) and inhibited MAO-B with an IC₅₀ of 100 nM. Optimization guided by the predicted binding modes led to the identification of a second potent dual-target scaffold. The two discovered scaffolds were shown to counteract 6-hydroxydopamine-induced neurotoxicity in dopaminergic neuronal-like SH-SY5Y cells. Structure-based screening can hence be used to identify ligands with specific polypharmacological profiles, providing new avenues for drug development against complex diseases.

Optimization and 13CH3 methionine labeling of a signaling competent neurotensin receptor 1 variant for NMR studies

Neurotensin is a 13-residue peptide that acts as a neuromodulator of classical neurotransmitters such as dopamine and glutamate in the mammalian central nervous system, mainly by activating the G protein-coupled receptor (GPCR), neurotensin receptor 1 (NTS₁). Agonist binding to GPCRs shifts the conformational equilibrium of the transmembrane helices towards distinct, thermodynamically favorable conformations that favor effector protein interactions and promotes cell signaling. The introduction of site specific labels for NMR spectroscopy has proven useful for investigating this dynamic process, but the low expression levels and poor stability of GPCRs is a hindrance to solution NMR experiments. Several thermostabilized mutants of NTS₁ have been engineered to circumvent this, with the crystal structures of four of these published. The conformational dynamics of NTS₁ however, has not been thoroughly investigated with NMR. It is generally accepted that stabilized GPCRs exhibit attenuated signaling, thus we thoroughly characterized the signaling characteristics of several thermostabilized NTS₁ variants to identify an optimal variant for protein NMR studies. A variant termed enNTS₁ exhibited the best combination of signaling capability and stability upon solubilization with detergents. enNTS₁ was subsequently labeled with ¹³CH₃-methionine in E. coli and purified to homogeneity in the absence of bound ligands. Using solution NMR spectroscopy we observed several well dispersed ¹³CH₃-methionine resonances, many of which exhibited chemical shift changes upon the addition of the high affinity agonist peptide, NT8-13. Thus, enNTS₁ represents a novel tool for investigating ligand induced conformational changes in NTS₁ to gain insights into the molecular mechanisms underlying neurotensin signaling.

Functional characterisation of G protein-coupled receptors

Characterisation of receptors can involve either assessment of their ability to bind ligands or measure receptor activation as a result of agonist or inverse agonist interactions. This review focuses on G protein-coupled receptors (GPCRs), examining techniques that can be applied to both receptors in membranes and after solubilisation. Radioligand binding remains a widely used technique, although there is increasing use of fluorescent ligands. These can be used in a variety of experimental designs, either directly monitoring ligand itself with techniques such as fluorescence polarisation or indirectly via resonance energy transfer (fluorescence/Forster resonance energy transfer, FRET and bioluminescence resonance energy transfer, BRET). Label free techniques such as isothermal titration calorimetry (ITC) and surface plasmon resonance (SPR) are also increasingly being used. For GPCRs, the main measure of receptor activation is to investigate the association of the G protein with the receptor. The chief assay measures the receptor-stimulated binding of GTP or a suitable analogue to the receptor. The direct association of the G protein with the receptor has been investigated via resonance energy techniques. These have also been used to measure ligand-induced conformational changes within the receptor; a variety of experimental techniques are available to incorporate suitable donors and acceptors within the receptor.

Structure-based discovery of selective positive allosteric modulators of antagonists for the M2 muscarinic acetylcholine receptor

The orthosteric binding sites of the five muscarinic acetylcholine receptor (mAChR) subtypes are highly conserved, making the development of selective antagonists challenging. The allosteric sites of these receptors are more variable, allowing one to imagine allosteric modulators that confer subtype selectivity, which would reduce the major off-target effects of muscarinic antagonists. Accordingly, a large library docking campaign was prosecuted seeking unique positive allosteric modulators (PAMs) for antagonists, ultimately revealing a PAM that substantially potentiates antagonist binding leading to subtype selectivity at the M₂ mAChR. This study supports the feasibility of discovering PAMs that can convert an armamentarium of potent but nonselective G-protein–coupled receptor (GPCR) antagonist drugs into subtype-selective reagents.

Subtype-selective antagonists for muscarinic acetylcholine receptors (mAChRs) have long been elusive, owing to the highly conserved orthosteric binding site. However, allosteric sites of these receptors are less conserved, motivating the search for allosteric ligands that modulate agonists or antagonists to confer subtype selectivity. Accordingly, a 4.6 million-molecule library was docked against the structure of the prototypical M₂ mAChR, seeking molecules that specifically stabilized antagonist binding. This led us to identify a positive allosteric modulator (PAM) that potentiated the antagonist N-methyl scopolamine (NMS). Structure-based optimization led to compound ’628, which enhanced binding of NMS, and the drug scopolamine itself, with a cooperativity factor (α) of 5.5 and a K_B of 1.1 μM, while sparing the endogenous agonist acetylcholine. NMR spectral changes determined for methionine residues reflected changes in the allosteric network. Moreover, ’628 slowed the dissociation rate of NMS from the M₂ mAChR by 50-fold, an effect not observed at the other four mAChR subtypes. The specific PAM effect of ’628 on NMS antagonism was conserved in functional assays, including agonist stimulation of [³⁵S]GTPγS binding and ERK 1/2 phosphorylation. Importantly, the selective allostery between ’628 and NMS was retained in membranes from adult rat hypothalamus and in neonatal rat cardiomyocytes, supporting the physiological relevance of this PAM/antagonist approach. This study supports the feasibility of discovering PAMs that confer subtype selectivity to antagonists; molecules like ’628 can convert an armamentarium of potent but nonselective GPCR antagonist drugs into subtype-selective reagents, thus reducing their off-target effects.

Structural Features and Ligand Selectivity for 10 Intermediates in the Activation Process of β2-Adrenergic Receptor

It has already been suggested by researchers that there should be multiple intermediate states in the activation process for G-protein-coupled receptors (GPCRs). However, the intermediate states are very short-lived and hardly captured by the experiments, leading to very limited understanding of their structural features and drug efficacies. In this work, a novel joint strategy of targeted molecular dynamics simulation, conventional molecular dynamics simulation, and virtual screening is developed to address the problems. The results from 10 intermediate conformations obtained from the work reveal that the ligand pocket is very unstable and fluctuates between the inactive state and the active one in the case of ligand-free, in particular for ECL2 as a gate-keeper of the ligand-binding. The ligand-binding site could be stable in the active state with a small volume and a completely closed ECL2, only when the G-protein-binding region is fully activated. In addition, the activations of the ligand-binding pocket and G-protein-binding site are relatively independent and exhibit a loose allosteric coupling, which contributes to the existence of multiple intermediate conformations. Interestingly, the screening performance of the agonists does not increase on increasing the overall activity of the intermediate state, but is dependent on the activated extent of the ligand pocket. The receptor is prone to bind the agonist when closing ECL2 and reducing the ligand-binding pocket volume, whereas it is more favorable for binding the antagonist when opening ECL2 and increasing the pocket volume. These observations added to previous studies could help us better understand the activation mechanism of GPCRs and provide valuable information for drug design.

Improving virtual screening of G protein-coupled receptors via ligand-directed modeling

G protein-coupled receptors (GPCRs) play crucial roles in cell physiology and pathophysiology. There is increasing interest in using structural information for virtual screening (VS) of libraries and for structure-based drug design to identify novel agonist or antagonist leads. However, the sparse availability of experimentally determined GPCR/ligand complex structures with diverse ligands impedes the application of structure-based drug design (SBDD) programs directed to identifying new molecules with a select pharmacology. In this study, we apply ligand-directed modeling (LDM) to available GPCR X-ray structures to improve VS performance and selectivity towards molecules of specific pharmacological profile. The described method refines a GPCR binding pocket conformation using a single known ligand for that GPCR. The LDM method is a computationally efficient, iterative workflow consisting of protein sampling and ligand docking. We developed an extensive benchmark comparing LDM-refined binding pockets to GPCR X-ray crystal structures across seven different GPCRs bound to a range of ligands of different chemotypes and pharmacological profiles. LDM-refined models showed improvement in VS performance over origin X-ray crystal structures in 21 out of 24 cases. In all cases, the LDM-refined models had superior performance in enriching for the chemotype of the refinement ligand. This likely contributes to the LDM success in all cases of inhibitor-bound to agonist-bound binding pocket refinement, a key task for GPCR SBDD programs. Indeed, agonist ligands are required for a plethora of GPCRs for therapeutic intervention, however GPCR X-ray structures are mostly restricted to their inactive inhibitor-bound state.

G protein-coupled receptors (GPCRs) are a major target for drug discovery. These receptors are highly dynamic membrane proteins, and have had limited tractability using with biophysical screens that are widely adopted for globular protein targets. Thus, structure-based virtual screening (SBVS) holds great promise as a complement to physical screening for rational design of novel drugs. Indeed, the increasing number of atomic-detail GPCR X-ray crystal structures has coincided with an increase in prospective SBVS studies that have identified novel compounds. However, experimentally solved GPCR structures do not meet the full demand for SBVS, as the GPCR structural landscape is incomplete, lacking both in coverage of available GPCRs, and diversity in both receptor conformations and the chemistry of co-crystalised ligands. Here we present a novel computational GPCR binding pocket refinement method that can generate predictive GPCR/ligand complexes with improved SBVS performance. This ligand-directed modeling workflow uses parallel processing and efficient algorithms to search the GPCR/ligand conformational space faster and more efficiently than the widely used protein refinement method molecular dynamics. In this study, the resulting models are evaluated both structurally, and in retrospective SBVS. We demonstrate improved performance of refined models over their starting structures in the majority of our test cases.

Fragment-Based Discovery and Optimization of Enzyme Inhibitors by Docking of Commercial Chemical Space

Fragment-based lead discovery has emerged as a leading drug development strategy for novel therapeutic targets. Although fragment-based drug discovery benefits immensely from access to atomic-resolution information, structure-based virtual screening has rarely been used to drive fragment discovery and optimization. Here, molecular docking of 0.3 million fragments to a crystal structure of cancer target MTH1 was performed. Twenty-two predicted fragment ligands, for which analogs could be acquired commercially, were experimentally evaluated. Five fragments inhibited MTH1 with IC₅₀ values ranging from 6 to 79 μM. Structure-based optimization guided by predicted binding modes and analogs from commercial chemical libraries yielded nanomolar inhibitors. Subsequently solved crystal structures confirmed binding modes predicted by docking for three scaffolds. Structure-guided exploration of commercial chemical space using molecular docking gives access to fragment libraries that are several orders of magnitude larger than those screened experimentally and can enable efficient optimization of hits to potent leads.

SPR-based fragment screening with neurotensin receptor 1 generates novel small molecule ligands

The neurotensin receptor 1 represents an important drug target involved in various diseases of the central nervous system. So far, the full exploitation of potential therapeutic activities has been compromised by the lack of compounds with favorable physicochemical and pharmacokinetic properties which efficiently penetrate the blood-brain barrier. Recent progress in the generation of stabilized variants of solubilized neurotensin receptor 1 and its subsequent purification and successful structure determination presents a solid starting point to apply the approach of fragment-based screening to extend the chemical space of known neurotensin receptor 1 ligands. In this report, surface plasmon resonance was used as primary method to screen 6369 compounds. Thereby 44 hits were identified and confirmed in competition as well as dose-response experiments. Furthermore, 4 out of 8 selected hits were validated using nuclear magnetic resonance spectroscopy as orthogonal biophysical method. Computational analysis of the compound structures, taking the known crystal structure of the endogenous peptide agonist into consideration, gave insight into the potential fragment-binding location and interactions and inspires chemistry efforts for further exploration of the fragments.