Directional ΔG Neural Network (DrΔG-Net): A Modular Neural Network Approach to Binding Free Energy Prediction.

The protein-ligand binding free energy is a central quantity in structure-based computational drug discovery efforts. Although popular alchemical methods provide sound statistical means of computing the binding free energy of a large breadth of systems, they are generally too costly to be applied at the same frequency as end point or ligand-based methods. By contrast, these data-driven approaches are typically fast enough to address thousands of systems but with reduced transferability to unseen systems. We introduce DrΔG-Net (or simply Dragnet), an equivariant graph neural network that can blend ligand-based and protein-ligand data-driven approaches. It is based on a 3D fingerprint representation of the ligand alone and in complex with the protein target. Dragnet is a global scoring function to predict the binding affinity of arbitrary protein-ligand complexes, but can be easily tuned via transfer learning to specific systems or end points, performing similarly to common 2D ligand-based approaches in these tasks. Dragnet is evaluated on a total of 28 validation proteins with a set of congeneric ligands derived from the Binding DB and one custom set extracted from the ChEMBL Database. In general, a handful of experimental binding affinities are sufficient to optimize the scoring function for a particular protein and ligand scaffold. When not available, predictions from physics-based methods such as absolute free energy perturbation can be used for the transfer learning tuning of Dragnet. Furthermore, we use our data to illustrate the present limitations of data-driven modeling of binding free energy predictions.

On Ternary Complex Stability in Protein Degradation: In Silico Molecular Glue Binding Affinity Calculations.

Molecular glues are small molecules that simultaneously bind to two proteins, creating a chemically induced protein-protein interface. CELMoDs (cereblon E3 ligase modulators) are a class of molecular glues that promote recruitment of neosubstrate proteins to the E3 ubiquitin ligase cereblon (CRBN) for poly-Lys48-ubiquitination and proteasomal degradation. Ternary complex structures of clinical CELMoDs CC-885 and CC-90009 bound to CRBN and neosubstrate G1 to S phase transition protein 1 (GSPT1) have been experimentally determined. Although cellular degradation is a downstream event, dependent not only on the affinity of the glue CELMoD in the ternary complex, we test the applicability of established structure-based drug design principles to predict binding affinity of CELMoDs to the protein-protein neointerface and correlation to measured cellular degradation for the neosubstrates GSPT1 and zinc finger Aiolos (IKZF3). For a congeneric series of CELMoDs, which have a similar sequence of binding events and resultant binding modes, we conclude that well-established structure-based methods that measure in silico ternary complex stabilities can predict relative degradation potency by CELMoDs.

Crystal structure of the GLP-1 receptor bound to a peptide agonist.

Glucagon-like peptide 1 (GLP-1) regulates glucose homeostasis through the control of insulin release from the pancreas. GLP-1 peptide agonists are efficacious drugs for the treatment of diabetes. To gain insight into the molecular mechanism of action of GLP-1 peptides, here we report the crystal structure of the full-length GLP-1 receptor bound to a truncated peptide agonist. The peptide agonist retains an α-helical conformation as it sits deep within the receptor-binding pocket. The arrangement of the transmembrane helices reveals hallmarks of an active conformation similar to that observed in class A receptors. Guided by this structural information, we design peptide agonists with potent in vivo activity in a mouse model of diabetes.

Corrigendum: Crystal structure of the GLP-1 receptor bound to a peptide agonist.

This corrects the article DOI: 10.1038/nature22800.

Extra-helical binding site of a glucagon receptor antagonist.

Glucagon is a 29-amino-acid peptide released from the α-cells of the islet of Langerhans, which has a key role in glucose homeostasis. Glucagon action is transduced by the class B G-protein-coupled glucagon receptor (GCGR), which is located on liver, kidney, intestinal smooth muscle, brain, adipose tissue, heart and pancreas cells, and this receptor has been considered an important drug target in the treatment of diabetes. Administration of recently identified small-molecule GCGR antagonists in patients with type 2 diabetes results in a substantial reduction of fasting and postprandial glucose concentrations. Although an X-ray structure of the transmembrane domain of the GCGR has previously been solved, the ligand (NNC0640) was not resolved. Here we report the 2.5 Å structure of human GCGR in complex with the antagonist MK-0893 (ref. 4), which is found to bind to an allosteric site outside the seven transmembrane (7TM) helical bundle in a position between TM6 and TM7 extending into the lipid bilayer. Mutagenesis of key residues identified in the X-ray structure confirms their role in the binding of MK-0893 to the receptor. The unexpected position of the binding site for MK-0893, which is structurally similar to other GCGR antagonists, suggests that glucagon activation of the receptor is prevented by restriction of the outward helical movement of TM6 required for G-protein coupling. Structural knowledge of class B receptors is limited, with only one other ligand-binding site defined--for the corticotropin-releasing hormone receptor 1 (CRF1R)--which was located deep within the 7TM bundle. We describe a completely novel allosteric binding site for class B receptors, providing an opportunity for structure-based drug design for this receptor class and furthering our understanding of the mechanisms of activation of these receptors.

Deconstructing the Pharmacological Contribution of Sphingosine-1 Phosphate Receptors to Mouse Models of Multiple Sclerosis Using the Species Selectivity of Ozanimod, a Dual Modulator of Human Sphingosine 1-Phosphate Receptor Subtypes 1 and 5.

Ozanimod, a sphingosine 1-phosphate (S1P) receptor modulator that binds with high affinity selectively to S1P receptor subtypes 1 (S1P1) and 5 (S1P5), is approved for the treatment of relapsing multiple sclerosis (MS) in multiple countries. Ozanimod profiling revealed a species difference in its potency for S1P5 in mouse, rat, and canine compared with that for human and monkey. Site-directed mutagenesis identified amino acid alanine at position 120 to be responsible for loss of activity for mouse, rat, and canine S1P5, and mutation back to threonine as in human/monkey S1P5 restored activity. Radioligand binding analysis performed with mouse S1P5 confirmed the potency loss is a consequence of a loss of affinity of ozanimod for mouse S1P5 and was restored with mutation of alanine 120 to threonine. Study of ozanimod in preclinical mouse models of MS can now determine the S1P receptor(s) responsible for observed efficacies with receptor engagement as measured using pharmacokinetic exposures of free drug. Hence, in the experimental autoimmune encephalomyelitis model, ozanimod exposures sufficient to engage S1P1, but not S1P5, resulted in reduced circulating lymphocytes, disease scores, and body weight loss; reduced inflammation, demyelination, and apoptotic cell counts in the spinal cord; and reduced circulating levels of the neuronal degeneration marker, neurofilament light. In the demyelinating cuprizone model, ozanimod prevented axonal degradation and myelin loss during toxin challenge but did not facilitate enhanced remyelination after intoxication. Since free drug levels in this model only engaged S1P1, we concluded that S1P1 activation is neuroprotective but does not appear to affect remyelination. SIGNIFICANCE STATEMENT: Ozanimod, a selective modulator of human sphingisone 1-phosphate receptor subtypes 1 and 5 (S1P1/5), displays reduced potency for rodent and dog S1P5 compared with human, which results from mutation of threonine to alanine at position 120. Ozanimod can thus be used as a selective S1P1 agonist in mouse models of multiple sclerosis to define efficacies driven by S1P1 but not S1P5. Based on readouts for experimental autoimmune encephalomyelitis and cuprizone intoxication, S1P1 modulation is neuroprotective, but S1P5 activity may be required for remyelination.

Mechanical thrombectomy in a pediatric patient with sedation aided by contralateral intra-arterial propofol injection: feasibility in an extreme condition.

Pediatric patients undergoing mechanical thrombectomy may be challenging for the anesthesiologists as regards the best anesthetic choice, especially if concomitant to severe comorbidities such as heart failure. A 16-year-old patient affected by arrhythmogenic right ventricle dysplasia/cardiomyopathy underwent mechanical thrombectomy. He was not eligible for deep sedation or general anesthesia since he has been suffering from severe heart failure. The patient stillness was obtained by intra-arterial injection of propofol from the contralateral internal carotid artery. The procedure has been well tolerated, without cardiorespiratory impairment. The case stresses the growing importance to tailor a proper anesthesiologic plan during mechanical thrombectomy, especially in extreme conditions.

Continuous stellate ganglion block in delayed cerebral ischemia: A possible supplementary approach to traditional therapy?

Delayed Cerebral Ischemia (DCI) is a major contributor to morbidity and mortality after SAH. Currently the prevention of vasospasm and DCI relies on nimodipine administration and on maintaining an adequate cerebral perfusion pressure. We report a patient with initial DCI after SAH in which stellate ganglion block (SGB) was performed after nimodipine administration. Firstly the procedure was characterized by a iv and intra-arterial nimodipine administration which did not result into a normal perfusion pattern. Therefore a single-shot stellate ganglion block was performed, as suggested in literature. Because of the not sufficient but promising perfusion improvement, we decided to deliver a continuous ganglion block (cSGB) for 5 days. Consequently a further improvement of the cerebral perfusion on CTPerfusion and Real Time Angiographic Perfusion Assessment was registered. In order to treat cerebral vasospasm, SGB is known to be a further valuable treatment, despite its temporary effect. However the continuous use of SGB during initial DCI has never been described before.

Identification of a novel allosteric GLP-1R antagonist HTL26119 using structure- based drug design.

A series of novel allosteric antagonists of the GLP-1 receptor (GLP-1R), exemplified by HTL26119, are described. SBDD approaches were employed to identify HTL26119, exploiting structural understanding of the allosteric binding site of the closely related Glucagon receptor (GCGR) (Jazayeri et al., 2016) and the homology relationships between GCGR and GLP-1R. The region around residue C3476.36b of the GLP-1R receptor represents a key difference from GCGR and was targeted for selectivity for GLP-1R.

Reaction-Based Enumeration, Active Learning, and Free Energy Calculations To Rapidly Explore Synthetically Tractable Chemical Space and Optimize Potency of Cyclin-Dependent Kinase 2 Inhibitors.

The hit-to-lead and lead optimization processes usually involve the design, synthesis, and profiling of thousands of analogs prior to clinical candidate nomination. A hit finding campaign may begin with a virtual screen that explores millions of compounds, if not more. However, this scale of computational profiling is not frequently performed in the hit-to-lead or lead optimization phases of drug discovery. This is likely due to the lack of appropriate computational tools to generate synthetically tractable lead-like compounds in silico, and a lack of computational methods to accurately profile compounds prospectively on a large scale. Recent advances in computational power and methods provide the ability to profile much larger libraries of ligands than previously possible. Herein, we report a new computational technique, referred to as "PathFinder", that uses retrosynthetic analysis followed by combinatorial synthesis to generate novel compounds in synthetically accessible chemical space. In this work, the integration of PathFinder-driven compound generation, cloud-based FEP simulations, and active learning are used to rapidly optimize R-groups, and generate new cores for inhibitors of cyclin-dependent kinase 2 (CDK2). Using this approach, we explored >300 000 ideas, performed >5000 FEP simulations, and identified >100 ligands with a predicted IC50 < 100 nM, including four unique cores. To our knowledge, this is the largest set of FEP calculations disclosed in the literature to date. The rapid turnaround time, and scale of chemical exploration, suggests that this is a useful approach to accelerate the discovery of novel chemical matter in drug discovery campaigns.

Structure of class B GPCR corticotropin-releasing factor receptor 1.

Structural analysis of class B G-protein-coupled receptors (GPCRs), cell-surface proteins that respond to peptide hormones, has been restricted to the amino-terminal extracellular domain, thus providing little understanding of the membrane-spanning signal transduction domain. The corticotropin-releasing factor receptor type 1 is a class B receptor which mediates the response to stress and has been considered a drug target for depression and anxiety. Here we report the crystal structure of the transmembrane domain of the human corticotropin-releasing factor receptor type 1 in complex with the small-molecule antagonist CP-376395. The structure provides detailed insight into the architecture of class B receptors. Atomic details of the interactions of the receptor with the non-peptide ligand that binds deep within the receptor are described. This structure provides a model for all class B GPCRs and may aid in the design of new small-molecule drugs for diseases of brain and metabolism.

GPCR-Bench: A Benchmarking Set and Practitioners' Guide for G Protein-Coupled Receptor Docking.

Virtual screening is routinely used to discover new ligands and in particular new ligand chemotypes for G protein-coupled receptors (GPCRs). To prepare for a virtual screen, we often tailor a docking protocol that will enable us to select the best candidates for further screening. To aid this, we created GPCR-Bench, a publically available docking benchmarking set in the spirit of the DUD and DUD-E reference data sets for validation studies, containing 25 nonredundant high-resolution GPCR costructures with an accompanying set of diverse ligands and computational decoy molecules for each target. Benchmarking sets are often used to compare docking protocols; however, it is important to evaluate docking methods not by "retrospective" hit rates but by the actual likelihood that they will produce novel prospective hits. Therefore, docking protocols must not only rank active molecules highly but also produce good poses that a chemist will select for purchase and screening. Currently, no simple objective machine-scriptable function exists that can do this; instead, docking hit lists must be subjectively examined in a consistent way to compare between docking methods. We present here a case study highlighting considerations we feel are of importance when evaluating a method, intended to be useful as a practitioners' guide.

Decoding the Role of Water Dynamics in Ligand-Protein Unbinding: CRF1R as a Test Case.

The residence time of a ligand-protein complex is a crucial aspect in determining biological effect in vivo. Despite its importance, the prediction of ligand koff still remains challenging for modern computational chemistry. We have developed aMetaD, a fast and generally applicable computational protocol to predict ligand-protein unbinding events using a molecular dynamics (MD) method based on adiabatic-bias MD and metadynamics. This physics-based, fully flexible, and pose-dependent ligand scoring function evaluates the maximum energy (RTscore) required to move the ligand from the bound-state energy basin to the next. Unbinding trajectories are automatically analyzed and translated into atomic solvation factor (SF) values representing the water dynamics during the unbinding event. This novel computational protocol was initially tested on two M3 muscarinic receptor and two adenosine A2A receptor antagonists and then evaluated on a test set of 12 CRF1R ligands. The resulting RTscores were used successfully to classify ligands with different residence times. Additionally, the SF analysis was used to detect key differences in the degree of accessibility to water molecules during the predicted ligand unbinding events. The protocol provides actionable working hypotheses that are applicable in a drug discovery program for the rational optimization of ligand binding kinetics.

Machine Learning Guided AQFEP: A Fast and Efficient Absolute Free Energy Perturbation Solution for Virtual Screening.

Structure-based methods in drug discovery have become an integral part of the modern drug discovery process. The power of virtual screening lies in its ability to rapidly and cost-effectively explore enormous chemical spaces to select promising ligands for further experimental investigation. Relative free energy perturbation (RFEP) and similar methods are the gold standard for binding affinity prediction in drug discovery hit-to-lead and lead optimization phases, but have high computational cost and the requirement of a structural analog with a known activity. Without a reference molecule requirement, absolute FEP (AFEP) has, in theory, better accuracy for hit ID, but in practice, the slow throughput is not compatible with VS, where fast docking and unreliable scoring functions are still the standard. Here, we present an integrated workflow to virtually screen large and diverse chemical libraries efficiently, combining active learning with a physics-based scoring function based on a fast absolute free energy perturbation method. We validated the performance of the approach in the ranking of structurally related ligands, virtual screening hit rate enrichment, and active learning chemical space exploration; disclosing the largest reported collection of free energy simulations to date.

The Discovery of MORF-627, a Highly Selective Conformationally-Biased Zwitterionic Integrin αvß6 Inhibitor for Fibrosis.

Inhibition of integrin αvß6 is a promising approach to the treatment of fibrotic disease such as idiopathic pulmonary fibrosis. Screening a small library combining head groups that stabilize the bent-closed conformation of integrin αIIbß3 with αv integrin binding motifs resulted in the identification of hit compounds that bind the bent-closed conformation of αvß6. Crystal structures of these compounds bound to αvß6 and related integrins revealed opportunities to increase potency and selectivity, and these efforts were accelerated using accurate free energy perturbation (FEP+) calculations. Optimization of PK parameters including permeability, bioavailability, clearance, and half-life resulted in the discovery of development candidate MORF-627, a highly selective inhibitor of αvß6 that stabilizes the bent-closed conformation and has good oral PK. Unfortunately, the compound showed toxicity in a 28-day NHP safety study, precluding further development. Nevertheless, MORF-627 is a useful tool compound for studying the biology of integrin αvß6.

Water network perturbation in ligand binding: adenosine A(2A) antagonists as a case study.

Recent efforts in the computational evaluation of the thermodynamic properties of water molecules have resulted in the development of promising new in silico methods to evaluate the role of water in ligand binding. These methods include WaterMap, SZMAP, GRID/CRY probe, and Grand Canonical Monte Carlo simulations. They allow the prediction of the position and relative free energy of the water molecule in the protein active site and the analysis of the perturbation of an explicit water network (WNP) as a consequence of ligand binding. We have for the first time extended these approaches toward the prediction of kinetics for small molecules and of relative free energy of binding with a focus on the perturbation of the water network and application to large diverse data sets. Our results support a qualitative correlation between the residence time of 12 related triazine adenosine A(2A) receptor antagonists and the number and position of high energy trapped solvent molecules. From a quantitative viewpoint, we successfully applied these computational techniques as an implicit solvent alternative, in linear combination with a molecular mechanics force field, to predict the relative ligand free energy of binding (WNP-MMSA). The applicability of this linear method, based on the thermodynamics additivity principle, did not extend to 375 diverse A(2A) receptor antagonists. However, a fast but effective method could be enabled by replacing the linear approach with a machine learning technique using probabilistic classification trees, which classified the binding affinity correctly for 90% of the ligands in the training set and 67% in the test set.

The perils of dental vacation: possible anaesthetic and medicolegal consequences.

INTRODUCTION: The aim of this paper is to emphasize anaesthesiologists' difficulty in detecting poor dentition in cases of poorly applied prostheses and/or advanced periodontal disease, and to establish whether it is possible, and in which conditions, to calculate compensation in cases of dental damage postlaryngoscopy and/or intubation. The main complex problem here lies in trying to reconstruct exactly what the dental situation was before the teeth were damaged. For this reason the important preoperative factors (dental prostheses, crown fractures, parodontal disease, etc.) must be clearly shown before surgery on a dental chart. CLINICAL CASES: Two cases of interest, both to anaesthesiologists practising intubation and medicolegal physicians who have to deal with potential claims, are briefly reported. The first patient was a 55-year-old diabetic patient, who underwent emergency surgery for acute abdominal pathology. He had gone outside Italy for dental treatment three years previously and now presented with very poor pre-existing dentition, carefully noted on an anaesthetic chart. He now demanded compensation for dental damage due to intubation in Italy; the resulting dental treatment was very expensive because substantial remedial work was required. The second patient had received treatment outside Italy, work which involved cosmetic coating of the teeth. After surgery in Italy, she demanded compensation because one tooth, which had been coated and appeared to be healthy, was broken after emergency intubation. In both cases, the patients demanded very high compensation. COMMENT: Dental tourism alone accounts for more than 250,000 patients each year who combine a holiday with dental treatment in Eastern Europe. However, if prosthetic devices or conservative treatments are not applied correctly, it should be noted that durability may be poorer than expected, but iatrogenic damage may also be caused.

Competitive Binding of Ozanimod and Other Sphingosine 1-Phosphate Receptor Modulators at Receptor Subtypes 1 and 5.

Ozanimod, a sphingosine 1-phosphate (S1P) receptor modulator, binds with high affinity selectively to S1P receptor subtypes 1 (S1P1) and 5 (S1P5), and is approved in multiple countries for treating adults with relapsing forms of multiple sclerosis (MS) or moderately to severely active ulcerative colitis (UC). Other S1P receptor modulators have been approved for the treatment of MS or are in clinical development for MS or UC, but it is unknown whether these compounds bind competitively with each other to S1P1 or S1P5. We developed a competitive radioligand binding assay using tritiated ozanimod and demonstrate full displacement of ozanimod by S1P (endogenous ligand), suggesting that ozanimod binds to the S1P1 and S1P5 orthosteric binding sites. S1P receptor modulators FTY720-p, siponimod, etrasimod, ponesimod, KRP-203-p, and amiselimod-p also completely displacing radiolabeled ozanimod; thus, on a macroscopic level, all bind to the same site. Molecular docking studies support these results and predict the binding of each molecule to the orthosteric site of the receptors, creating similar interactions within S1P1 and S1P5. The absolute free energy perturbation method further validated key proposed binding modes. Functional potency tightly aligned with binding affinities across S1P1 and S1P5 and all compounds elicited S1P1-mediated ß-arrestin recruitment. Since all the S1P modulators included in this study display similar receptor pharmacology and compete for binding at the same site, they can be considered interchangeable with one another. The choice of any one particular agent should therefore be made on the basis of overall therapeutic profile, and patients can be offered the opportunity to switch S1P medications without the potential concern of additive S1P pharmacology.

Novel Macrocyclic Antagonists of the Calcitonin Gene-Related Peptide Receptor: Design, Realization, and Structural Characterization of Protein-Ligand Complexes.

A series of macrocyclic calcitonin gene-related peptide (CGRP) receptor antagonists identified using structure-based design principles, exemplified by HTL0028016 (1) and HTL0028125 (2), is described. Structural characterization by X-ray crystallography of the interaction of two of the macrocycle antagonists with the CGRP receptor ectodomain is described, along with structure-activity relationships associated with point changes to the macrocyclic antagonists. The identification of non-peptidic/natural product-derived, macrocyclic ligands for a G protein coupled receptor (GPCR) is noteworthy.