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.

Epilogue to the Gerald Maggiora Festschrift: a tribute to an exemplary mentor, colleague, collaborator, and innovator.

In May 2022, JCAMD published a Special Issue in honor of Gerald (Gerry) Maggiora, whose scientific leadership over many decades advanced the fields of computational chemistry and chemoinformatics for drug discovery. Along the way, he has impacted many researchers in both academia and the pharmaceutical industry. In this Epilogue, we explain the origins of the Festschrift and present a series of first-hand vignettes, in approximate chronological sequence, that together paint a picture of this remarkable man. Whether they highlight Gerry's endless curiosity about molecular life sciences or his willingness to challenge conventional wisdom or his generous support of junior colleagues and peers, these colleagues and collaborators are united in their appreciation of his positive influence. These tributes also reflect key trends and themes during the evolution of modern drug discovery, seen through the lens of people who worked with a visionary leader. Junior scientists will find an inspiring roadmap for creative collegiality and collaboration.

Functional and structural analysis of cytokine-selective IL6ST defects that cause recessive hyper-IgE syndrome.

BACKGROUND: Biallelic variants in IL6ST, encoding GP130, cause a recessive form of hyper-IgE syndrome (HIES) characterized by high IgE level, eosinophilia, defective acute phase response, susceptibility to bacterial infections, and skeletal abnormalities due to cytokine-selective loss of function in GP130, with defective IL-6 and IL-11 and variable oncostatin M (OSM) and IL-27 levels but sparing leukemia inhibitory factor (LIF) signaling. OBJECTIVE: Our aim was to understand the functional and structural impact of recessive HIES-associated IL6ST variants. METHODS: We investigated a patient with HIES by using exome, genome, and RNA sequencing. Functional assays assessed IL-6, IL-11, IL-27, OSM, LIF, CT-1, CLC, and CNTF signaling. Molecular dynamics simulations and structural modeling of GP130 cytokine receptor complexes were performed. RESULTS: We identified a patient with compound heterozygous novel missense variants in IL6ST (p.Ala517Pro and the exon-skipping null variant p.Gly484_Pro518delinsArg). The p.Ala517Pro variant resulted in a more profound IL-6- and IL-11-dominated signaling defect than did the previously identified recessive HIES IL6ST variants p.Asn404Tyr and p.Pro498Leu. Molecular dynamics simulations suggested that the p.Ala517Pro and p.Asn404Tyr variants result in increased flexibility of the extracellular membrane-proximal domains of GP130. We propose a structural model that explains the cytokine selectivity of pathogenic IL6ST variants that result in recessive HIES. The variants destabilized the conformation of the hexameric cytokine receptor complexes, whereas the trimeric LIF-GP130-LIFR complex remained stable through an additional membrane-proximal interaction. Deletion of this membrane-proximal interaction site in GP130 consequently caused additional defective LIF signaling and Stüve-Wiedemann syndrome. CONCLUSION: Our data provide a structural basis to understand clinical phenotypes in patients with IL6ST variants.

Investigation into MAO B-Mediated Formation of CC112273, a Major Circulating Metabolite of Ozanimod, in Humans and Preclinical Species: Stereospecific Oxidative Deamination of (S)-Enantiomer of Indaneamine (RP101075) by MAO B.

Ozanimod, recently approved for treating relapsing multiple sclerosis, produced a disproportionate, active, MAO B-catalyzed metabolite (CC112273) that showed remarkable interspecies differences and led to challenges in safety testing. This study explored the kinetics of CC112273 formation from its precursor RP101075. Incubations with human liver mitochondrial fractions revealed K Mapp, V max, and intrinsic clearance (Clint) for CC112273 formation to be 4.8 µM, 50.3 pmol/min/mg protein, and 12 µl/min/mg, respectively, whereas Michaelis-Menten constant (K M) with human recombinant MAO B was 1.1 µM. Studies with liver mitochondrial fractions from preclinical species led to K Mapp, V max, and Clint estimates of 3.0, 35, and 33 µM, 80.6, 114, 37.3 pmol/min/mg, and 27.2, 3.25, and 1.14 µl/min/mg in monkey, rat, and mouse, respectively, and revealed marked differences between rodents and primates, primarily attributable to differences in the K M Comparison of Clint estimates revealed monkey to be ∼2-fold more efficient and the mouse and rat to be 11- and 4-fold less efficient than humans in CC112273 formation. The influence of stereochemistry on MAO B-mediated oxidation was also investigated using the R-isomer of RP101075 (RP101074). This showed marked selectivity toward catalysis of the S-isomer (RP101075) only. Docking into MAO B crystal structure suggested that although both the isomers occupied its active site, only the orientation of RP101075 presented the C-H on the α-carbon that was ideal for the C-H bond cleavage, which is a requisite for oxidative deamination. These studies explain the basis for the observed interspecies differences in the metabolism of ozanimod as well as the substrate stereospecificity for formation of CC112273. SIGNIFICANCE STATEMENT: This study evaluates the enzymology and the species differences of the major circulating metabolite of ozanimod, CC112273. Additionally, the study also explores the influence of stereochemistry on MAO B-catalyzed reactions. The study is of significance to the DMD readers given that this oxidation is catalyzed by a non-cytochrome P450 enzyme, and that marked species difference and notable stereospecificity was observed in MAO B-catalyzed biotransformation when the indaneamine enantiomers were used as substrates.

TRPA1 ankyrin repeat six interacts with a small molecule inhibitor chemotype.

TRPA1, a member of the transient receptor potential channel (TRP) family, is genetically linked to pain in humans, and small molecule inhibitors are efficacious in preclinical animal models of inflammatory pain. These findings have driven significant interest in development of selective TRPA1 inhibitors as potential analgesics. The majority of TRPA1 inhibitors characterized to date have been reported to interact with the S5 transmembrane helices forming part of the pore region of the channel. However, the development of many of these inhibitors as clinical drug candidates has been prevented by high lipophilicity, low solubility, and poor pharmacokinetic profiles. Identification of alternate compound interacting sites on TRPA1 provides the opportunity to develop structurally distinct modulators with novel structure-activity relationships and more desirable physiochemical properties. In this paper, we have identified a previously undescribed potent and selective small molecule thiadiazole structural class of TRPA1 inhibitor. Using species ortholog chimeric and mutagenesis strategies, we narrowed down the site of interaction to ankyrinR #6 within the distal N-terminal region of TRPA1. To identify the individual amino acid residues involved, we generated a computational model of the ankyrinR domain. This model was used predictively to identify three critical amino acids in human TRPA1, G238, N249, and K270, which were confirmed by mutagenesis to account for compound activity. These findings establish a small molecule interaction region on TRPA1, expanding potential avenues for developing TRPA1 inhibitor analgesics and for probing the mechanism of channel gating.

Delineating the role of cooperativity in the design of potent PROTACs for BTK.

Proteolysis targeting chimeras (PROTACs) are heterobifunctional small molecules that simultaneously bind to a target protein and an E3 ligase, thereby leading to ubiquitination and subsequent degradation of the target. They present an exciting opportunity to modulate proteins in a manner independent of enzymatic or signaling activity. As such, they have recently emerged as an attractive mechanism to explore previously "undruggable" targets. Despite this interest, fundamental questions remain regarding the parameters most critical for achieving potency and selectivity. Here we employ a series of biochemical and cellular techniques to investigate requirements for efficient knockdown of Bruton's tyrosine kinase (BTK), a nonreceptor tyrosine kinase essential for B cell maturation. Members of an 11-compound PROTAC library were investigated for their ability to form binary and ternary complexes with BTK and cereblon (CRBN, an E3 ligase component). Results were extended to measure effects on BTK-CRBN cooperative interactions as well as in vitro and in vivo BTK degradation. Our data show that alleviation of steric clashes between BTK and CRBN by modulating PROTAC linker length within this chemical series allows potent BTK degradation in the absence of thermodynamic cooperativity.

Machine Learning for Prioritization of Thermostabilizing Mutations for G-Protein Coupled Receptors.

Although the three-dimensional structures of G-protein coupled receptors (GPCRs), the largest superfamily of drug targets, have enabled structure-based drug design, there are no structures available for 87% of GPCRs. This is due to the stiff challenge in purifying the inherently flexible GPCRs. Identifying thermostabilized mutant GPCRs via systematic alanine scanning mutations has been a successful strategy in stabilizing GPCRs, but it remains a daunting task for each GPCR. We developed a computational method that combines sequence-, structure-, and dynamics-based molecular properties of GPCRs that recapitulate GPCR stability, with four different machine learning methods to predict thermostable mutations ahead of experiments. This method has been trained on thermostability data for 1231 mutants, the largest publicly available data set. A blind prediction for thermostable mutations of the complement factor C5a receptor 1 retrieved 36% of the thermostable mutants in the top 50 prioritized mutants compared to 3% in the first 50 attempts using systematic alanine scanning.

Cyclic Peptide Design Guided by Residual Dipolar Couplings, J-Couplings, and Intramolecular Hydrogen Bond Analysis.

Cyclic peptides have long tantalized drug designers with their potential ability to combine the best attributes of antibodies and small molecules. An ideal cyclic peptide drug candidate would be able to recognize a protein surface like an antibody while achieving the oral bioavailability of a small molecule. It has been hypothesized that such cyclic peptides balance permeability and solubility using their solvent-dependent conformational flexibility. Herein we report a conformational deconvolution NMR methodology that combines residual dipolar couplings, J-couplings, and intramolecular hydrogen bond analysis along with conformational analysis using molecular dynamics simulations and density functional theory calculations for studying cyclic peptide conformations in both low-dielectric solvent (chloroform) and high-dielectric solvent (DMSO) to experimentally study the solvent-dependent conformational change hypothesis. Taken together, the combined experimental and computational approaches can illuminate conformational ensembles of cyclic peptides in solution and help identify design opportunities for better permeability.

Inducing protein-protein interactions with molecular glues.

The drugable proteome is limited by the number of functional binding sites that can bind small molecules and respond with a therapeutic effect. Orthosteric and allosteric modulators of enzyme function or receptor signaling are well-established mechanisms of drug action. Drugs that perturb protein-protein interactions have only recently been launched. This approach is more difficult due to the extensive contact surfaces that must be perturbed antagonistically. Compounds that promote novel protein-protein interactions promise to dramatically expand opportunities for therapeutic intervention. This approach is precedented with natural products (rapamycin, FK506, sanglifehrin A), synthetic small molecules (thalidomide and IMiD derivatives) and indisulam analogues.

Novel Methods for Prioritizing "Close-In" Analogs from Structure-Activity Relationship Matrices.

Here we describe the development of novel methods for compound evaluation and prioritization based on the structure-activity relationship matrix (SARM) framework. The SARM data structure allows automatic and exhaustive extraction of SAR patterns from data sets and their organization into a chemically intuitive scaffold/functional-group format. While SARMs have been used in the retrospective analysis of SAR discontinuity and identifying underexplored regions of chemistry space, there have been only a few attempts to apply SARMs prospectively in the prioritization of "close-in" analogs. In this work, three new ways of prioritizing virtual compounds based on SARMs are described: (1) matrix pattern-based prioritization, (2) similarity weighted, matrix pattern-based prioritization, and (3) analysis of variance based prioritization (ANV). All of these methods yielded high predictive power for six benchmark data sets (prediction accuracy R2 range from 0.63 to 0.82), yielding confidence in their application to new design ideas. In particular, the ANV method outperformed the previously reported SARM based method for five out of the six data sets tested. The impact of various SARM parameters were investigated and the reasons why SARM-based compound prioritization methods provide higher predictive power are discussed.

Evaluation and Characterization of Trk Kinase Inhibitors for the Treatment of Pain: Reliable Binding Affinity Predictions from Theory and Computation.

Optimization of ligand binding affinity to the target protein of interest is a primary objective in small-molecule drug discovery. Until now, the prediction of binding affinities by computational methods has not been widely applied in the drug discovery process, mainly because of its lack of accuracy and reproducibility as well as the long turnaround times required to obtain results. Herein we report on a collaborative study that compares tropomyosin receptor kinase A (TrkA) binding affinity predictions using two recently formulated fast computational approaches, namely, Enhanced Sampling of Molecular dynamics with Approximation of Continuum Solvent (ESMACS) and Thermodynamic Integration with Enhanced Sampling (TIES), to experimentally derived TrkA binding affinities for a set of Pfizer pan-Trk compounds. ESMACS gives precise and reproducible results and is applicable to highly diverse sets of compounds. It also provides detailed chemical insight into the nature of ligand-protein binding. TIES can predict and thus optimize more subtle changes in binding affinities between compounds of similar structure. Individual binding affinities were calculated in a few hours, exhibiting good correlations with the experimental data of 0.79 and 0.88 from the ESMACS and TIES approaches, respectively. The speed, level of accuracy, and precision of the calculations are such that the affinity predictions can be used to rapidly explain the effects of compound modifications on TrkA binding affinity. The methods could therefore be used as tools to guide lead optimization efforts across multiple prospective structurally enabled programs in the drug discovery setting for a wide range of compounds and targets.

Molecular Basis for Inhibition of the Na+/Citrate Transporter NaCT (SLC13A5) by Dicarboxylate Inhibitors.

The Na+/citrate transporter, NaCT (SLC13A5), is a therapeutic target for metabolic diseases. Citrate is an important signaling molecule that regulates the activity of lipid- and glucose-metabolizing enzymes in cells. Previous studies identified two compounds, PF-06649298 (compound 2: ) and PF-06678419 (compound 4: ), that inhibit human NaCT with high affinity, and one of the compounds demonstrated specificity relative to other SLC13 family members. Here we use molecular modeling and site-directed mutagenesis of hNaCT followed by transport characterization and cell-surface biotinylation to examine the residues involved in inhibitor binding and transport. The results indicate that residues located near the putative citrate binding site, G228, V231, V232, and G409, affect both citrate transport and inhibition of citrate uptake by compounds 2: and 4: V231 appears to distinguish between compounds 2: and 4: as inhibitors. Furthermore, residues located outside of the putative citrate binding site, Q77 and T86, may also play a role in NaCT inhibition by compounds 2: and 4: Our results provide new insight into the mechanism of transport and inhibition in NaCT and the SLC13 family. These findings should provide a basis for future drug design of SLC13 inhibitors.

Collaborating to improve the use of free-energy and other quantitative methods in drug discovery.

In May and August, 2016, several pharmaceutical companies convened to discuss and compare experiences with Free Energy Perturbation (FEP). This unusual synchronization of interest was prompted by Schrödinger's FEP+ implementation and offered the opportunity to share fresh studies with FEP and enable broader discussions on the topic. This article summarizes key conclusions of the meetings, including a path forward of actions for this group to aid the accelerated evaluation, application and development of free energy and related quantitative, structure-based design methods.

Discovery of a Highly Selective Glycogen Synthase Kinase-3 Inhibitor (PF-04802367) That Modulates Tau Phosphorylation in the Brain: Translation for PET Neuroimaging.

Glycogen synthase kinase-3 (GSK-3) regulates multiple cellular processes in diabetes, oncology, and neurology. N-(3-(1H-1,2,4-triazol-1-yl)propyl)-5-(3-chloro-4-methoxyphenyl)oxazole-4-carboxamide (PF-04802367 or PF-367) has been identified as a highly potent inhibitor, which is among the most selective antagonists of GSK-3 to date. Its efficacy was demonstrated in modulation of tau phosphorylation in vitro and in vivo. Whereas the kinetics of PF-367 binding in brain tissues are too fast for an effective therapeutic agent, the pharmacokinetic profile of PF-367 is ideal for discovery of radiopharmaceuticals for GSK-3 in the central nervous system. A (11) C-isotopologue of PF-367 was synthesized and preliminary PET imaging studies in non-human primates confirmed that we have overcome the two major obstacles for imaging GSK-3, namely, reasonable brain permeability and displaceable binding.

Neighborhood-based prediction of novel active compounds from SAR matrices.

The SAR matrix data structure organizes compound data sets according to structurally analogous matching molecular series in a format reminiscent of conventional R-group tables. An intrinsic feature of SAR matrices is that they contain many virtual compounds that represent unexplored combinations of core structures and substituents extracted from compound data sets on the basis of the matched molecular pair formalism. These virtual compounds are candidates for further exploration but are difficult, if not impossible to prioritize on the basis of visual inspection of multiple SAR matrices. Therefore, we introduce herein a compound neighborhood concept as an extension of the SAR matrix data structure that makes it possible to identify preferred virtual compounds for further analysis. On the basis of well-defined compound neighborhoods, the potency of virtual compounds can be predicted by considering individual contributions of core structures and substituents from neighbors. In extensive benchmark studies, virtual compounds have been prioritized in different data sets on the basis of multiple neighborhoods yielding accurate potency predictions.

Novel 3-O-carbamoyl erythromycin A derivatives (carbamolides) with activity against resistant staphylococcal and streptococcal isolates.

A novel series of 3-O-carbamoyl erythromycin A derived analogs, labeled carbamolides, with activity versus resistant bacterial isolates of staphylococci (including macrolide and oxazolidinone resistant strains) and streptococci are reported. An (R)-2-aryl substituent on a pyrrolidine carbamate appeared to be critical for achieving potency against resistant strains. Crystal structures showed a distinct aromatic interaction between the (R)-2-aryl (3-pyridyl for 4d) substituent on the pyrrolidine and G2484 (G2505, Escherichia coli) of the Deinococcus radiodurans 50S ribosome (3.2Å resolution).

Structural basis for effectiveness of siderophore-conjugated monocarbams against clinically relevant strains of Pseudomonas aeruginosa.

Pseudomonas aeruginosa is an opportunistic Gram-negative pathogen that causes nosocomial infections for which there are limited treatment options. Penicillin-binding protein PBP3, a key therapeutic target, is an essential enzyme responsible for the final steps of peptidoglycan synthesis and is covalently inactivated by ß-lactam antibiotics. Here we disclose the first high resolution cocrystal structures of the P. aeruginosa PBP3 with both novel and marketed ß-lactams. These structures reveal a conformational rearrangement of Tyr532 and Phe533 and a ligand-induced conformational change of Tyr409 and Arg489. The well-known affinity of the monobactam aztreonam for P. aeruginosa PBP3 is due to a distinct hydrophobic aromatic wall composed of Tyr503, Tyr532, and Phe533 interacting with the gem-dimethyl group. The structure of MC-1, a new siderophore-conjugated monocarbam complexed with PBP3 provides molecular insights for lead optimization. Importantly, we have identified a novel conformation that is distinct to the high-molecular-weight class B PBP subfamily, which is identifiable by common features such as a hydrophobic aromatic wall formed by Tyr503, Tyr532, and Phe533 and the structural flexibility of Tyr409 flanked by two glycine residues. This is also the first example of a siderophore-conjugated triazolone-linked monocarbam complexed with any PBP. Energetic analysis of tightly and loosely held computed hydration sites indicates protein desolvation effects contribute significantly to PBP3 binding, and analysis of hydration site energies allows rank ordering of the second-order acylation rate constants. Taken together, these structural, biochemical, and computational studies provide a molecular basis for recognition of P. aeruginosa PBP3 and open avenues for future design of inhibitors of this class of PBPs.

Identification of Small Molecule Inhibitors and Ligand Directed Degraders of Calcium/Calmodulin Dependent Protein Kinase Kinase 1 and 2 (CaMKK1/2).

CaMKK2 signals through AMPK-dependent and AMPK-independent pathways to trigger cellular outputs including proliferation, differentiation, and migration, resulting in changes to metabolism, bone mass accrual, neuronal function, hematopoiesis, and immunity. CAMKK2 is upregulated in tumors including hepatocellular carcinoma, prostate, breast, and gastric cancer, and genetic deletion in myeloid cells results in increased antitumor immunity in several syngeneic models. Validation of the biological roles of CaMKK2 has relied on genetic deletion or small molecule inhibitors with activity against several biological targets. We sought to generate selective inhibitors and degraders to understand the biological impact of inhibiting catalytic activity and scaffolding and the potential therapeutic benefits of targeting CaMKK2. We report herein selective, ligand-efficient inhibitors and ligand-directed degraders of CaMKK2 that were used to probe immune and tumor intrinsic biology. These molecules provide two distinct strategies for ablating CaMKK2 signaling in vitro and in vivo.

Thermodynamic analysis of water molecules at the surface of proteins and applications to binding site prediction and characterization.

Water plays an essential role in determining the structure and function of all biological systems. Recent methodological advances allow for an accurate and efficient estimation of the thermodynamic properties of water molecules at the surface of proteins. In this work, we characterize these thermodynamic properties and relate them to various structural and functional characteristics of the protein. We find that high-energy hydration sites often exist near protein motifs typically characterized as hydrophilic, such as backbone amide groups. We also find that waters around alpha helices and beta sheets tend to be less stable than waters around loops. Furthermore, we find no significant correlation between the hydration site-free energy and the solvent accessible surface area of the site. In addition, we find that the distribution of high-energy hydration sites on the protein surface can be used to identify the location of binding sites and that binding sites of druggable targets tend to have a greater density of thermodynamically unstable hydration sites. Using this information, we characterize the FKBP12 protein and show good agreement between fragment screening hit rates from NMR spectroscopy and hydration site energetics. Finally, we show that water molecules observed in crystal structures are less stable on average than bulk water as a consequence of the high degree of spatial localization, thereby resulting in a significant loss in entropy. These findings should help to better understand the characteristics of waters at the surface of proteins and are expected to lead to insights that can guide structure-based drug design efforts.

Early insights into the interactions of different ß-lactam antibiotics and ß-lactamase inhibitors against soluble forms of Acinetobacter baumannii PBP1a and Acinetobacter sp. PBP3.

Acinetobacter baumannii is an increasingly problematic pathogen in United States hospitals. Antibiotics that can treat A. baumannii are becoming more limited. Little is known about the contributions of penicillin binding proteins (PBPs), the target of ß-lactam antibiotics, to ß-lactam-sulbactam susceptibility and ß-lactam resistance in A. baumannii. Decreased expression of PBPs as well as loss of binding of ß-lactams to PBPs was previously shown to promote ß-lactam resistance in A. baumannii. Using an in vitro assay with a reporter ß-lactam, Bocillin, we determined that the 50% inhibitory concentrations (IC(50)s) for PBP1a from A. baumannii and PBP3 from Acinetobacter sp. ranged from 1 to 5 µM for a series of ß-lactams. In contrast, PBP3 demonstrated a narrower range of IC(50)s against ß-lactamase inhibitors than PBP1a (ranges, 4 to 5 versus 8 to 144 µM, respectively). A molecular model with ampicillin and sulbactam positioned in the active site of PBP3 reveals that both compounds interact similarly with residues Thr526, Thr528, and Ser390. Accepting that many interactions with cell wall targets are possible with the ampicillin-sulbactam combination, the low IC(50)s of ampicillin and sulbactam for PBP3 may contribute to understanding why this combination is effective against A. baumannii. Unraveling the contribution of PBPs to ß-lactam susceptibility and resistance brings us one step closer to identifying which PBPs are the best targets for novel ß-lactams.