Lead Optimization of the 5-Phenylpyrazolopyrimidinone NPD-2975 toward Compounds with Improved Antitrypanosomal Efficacy.

Human African trypanosomiasis (HAT) still faces few therapeutic options and emerging drug resistance, stressing an urgency for novel antitrypanosomal drug discovery. Here, we describe lead optimization efforts aiming at improving antitrypanosomal efficacy and better physicochemical properties based on our previously reported optimized hit NPD-2975 (pIC50 7.2). Systematic modification of the 5-phenylpyrazolopyrimidinone NPD-2975 led to the discovery of a R4-substituted analogue 31c (NPD-3519), showing higher in vitro potency (pIC50 7.8) against Trypanosoma brucei and significantly better metabolic stability. Further, in vivo pharmacokinetic evaluation of 31c and experiments in an acute T. brucei mouse model confirmed improved oral bioavailability and antitrypanosomal efficacy at 50 mg/kg with no apparent toxicity. With good physicochemical properties, low toxicity, improved pharmacokinetic features, and in vivo efficacy, 31c may serve as a promising candidate for future drug development for HAT.

Pharmacological Characterization and Radiolabeling of VUF15485, a High-Affinity Small-Molecule Agonist for the Atypical Chemokine Receptor ACKR3.

Atypical chemokine receptor 3 (ACKR3), formerly referred to as CXCR7, is considered to be an interesting drug target. In this study, we report on the synthesis, pharmacological characterization and radiolabeling of VUF15485, a new ACKR3 small-molecule agonist, that will serve as an important new tool to study this ß-arrestin-biased chemokine receptor. VUF15485 binds with nanomolar affinity (pIC50 = 8.3) to human ACKR3, as measured in [125I]CXCL12 competition binding experiments. Moreover, in a bioluminescence resonance energy transfer-based ß-arrestin2 recruitment assay VUF15485 acts as a potent ACKR3 agonist (pEC50 = 7.6) and shows a similar extent of receptor activation compared with CXCL12 when using a newly developed, fluorescence resonance energy transfer-based ACKR3 conformational sensor. Moreover, the ACKR3 agonist VUF15485, tested against a (atypical) chemokine receptor panel (agonist and antagonist mode), proves to be selective for ACKR3. VUF15485 labeled with tritium at one of its methoxy groups ([3H]VUF15485), binds ACKR3 saturably and with high affinity (K d = 8.2 nM). Additionally, [3H]VUF15485 shows rapid binding kinetics and consequently a short residence time (<2 minutes) for binding to ACKR3. The selectivity of [3H]VUF15485 for ACKR3, was confirmed by binding studies, whereupon CXCR3, CXCR4, and ACKR3 small-molecule ligands were competed for binding against the radiolabeled agonist. Interestingly, the chemokine ligands CXCL11 and CXCL12 are not able to displace the binding of [3H]VUF15485 to ACKR3. The radiolabeled VUF15485 was subsequently used to evaluate its binding pocket. Site-directed mutagenesis and docking studies using a recently solved cryo-EM structure propose that VUF15485 binds in the major and the minor binding pocket of ACKR3. SIGNIFICANCE STATEMENT: The atypical chemokine receptor atypical chemokine receptor 3 (ACKR3) is considered an interesting drug target in relation to cancer and multiple sclerosis. The study reports on new chemical biology tools for ACKR3, i.e., a new agonist that can also be radiolabeled and a new ACKR3 conformational sensor, that both can be used to directly study the interaction of ACKR3 ligands with the G protein-coupled receptor.

Fragment-to-Lead Medicinal Chemistry Publications in 2022.

This Perspective is the eighth in an annual series that summarizes successful fragment-to-lead (F2L) case studies published each year. A tabulated summary of relevant articles published in 2022 is provided, and features such as target class, screening methods, and ligand efficiency are discussed both for the 2022 examples and for the combined examples over the years 2015-2022. In addition, trends and new developments in the field are summarized. In 2022, 18 publications described successful fragment-to-lead studies, including the development of three clinical compounds (MTRX1719, MK-8189, and BI-823911).

Multiplexed experimental strategies for fragment library screening against challenging drug targets using SPR biosensors.

Surface plasmon resonance (SPR) biosensor methods are ideally suited for fragment-based lead discovery.  However, generally applicable experimental procedures and detailed protocols are lacking, especially for structurally or physico-chemically challenging targets or when tool compounds are not available. Success depends on accounting for the features of both the target and the chemical library, purposely designing screening experiments for identification and validation of hits with desired specificity and mode-of-action, and availability of orthogonal methods capable of confirming fragment hits. The range of targets and libraries amenable to an SPR biosensor-based approach for identifying hits is considerably expanded by adopting multiplexed strategies, using multiple complementary surfaces or experimental conditions. Here we illustrate principles and multiplexed approaches for using flow-based SPR biosensor systems for screening fragment libraries of different sizes (90 and 1056 compounds) against a selection of challenging targets. It shows strategies for the identification of fragments interacting with 1) large and structurally dynamic targets, represented by acetyl choline binding protein (AChBP), a Cys-loop receptor ligand gated ion channel homologue, 2) targets in multi protein complexes, represented by lysine demethylase 1 and a corepressor (LSD1/CoREST), 3) structurally variable or unstable targets, represented by farnesyl pyrophosphate synthase (FPPS), 4) targets containing intrinsically disordered regions, represented by protein tyrosine phosphatase 1B  (PTP1B), and 5) aggregation-prone proteins, represented by an engineered form of human tau  (tau K18M). Practical considerations and procedures accounting for the characteristics of the proteins and libraries, and that increase robustness, sensitivity, throughput and versatility are highlighted. The study shows that the challenges for addressing these types of targets is not identification of potentially useful fragments per se, but establishing methods for their validation and evolution into leads.

PSW-Designer: An Open-Source Computational Platform for the Design and Virtual Screening of Photopharmacological Ligands.

Photoswitchable (PSW) molecules offer an attractive opportunity for the optical control of biological processes. However, the successful design of such compounds remains a challenging multioptimization endeavor, resulting in several biological target classes still relatively poorly explored by photoswitchable ligands, as is the case for G protein-coupled receptors (GPCRs). Here, we present the PSW-Designer, a fully open-source computational platform, implemented in the KNIME Analytics Platform, to design and virtually screen novel photoswitchable ligands for photopharmacological applications based on privileged scaffolds. We demonstrate the applicability of the PSW-Designer to GPCRs and assess its predictive capabilities via two retrospective case studies. Furthermore, by leveraging bioactivity information on known ligands, typical and atypical strategies for photoswitchable group incorporation, and the increasingly structural information available for biological targets, the PSW-Design will facilitate the design of novel photoswitchable molecules with improved photopharmacological properties and increased binding affinity shifts upon illumination for GPCRs and many other protein targets.

Predicting the target landscape of kinase inhibitors using 3D convolutional neural networks.

Many therapies in clinical trials are based on single drug-single target relationships. To further extend this concept to multi-target approaches using multi-targeted drugs, we developed a machine learning pipeline to unravel the target landscape of kinase inhibitors. This pipeline, which we call 3D-KINEssence, uses a new type of protein fingerprints (3D FP) based on the structure of kinases generated through a 3D convolutional neural network (3D-CNN). These 3D-CNN kinase fingerprints were matched to molecular Morgan fingerprints to predict the targets of each respective kinase inhibitor based on available bioactivity data. The performance of the pipeline was evaluated on two test sets: a sparse drug-target set where each drug is matched in most cases to a single target and also on a densely-covered drug-target set where each drug is matched to most if not all targets. This latter set is more challenging to train, given its non-exclusive character. Our model's root-mean-square error (RMSE) based on the two datasets was 0.68 and 0.8, respectively. These results indicate that 3D FP can predict the target landscape of kinase inhibitors at around 0.8 log units of bioactivity. Our strategy can be utilized in proteochemometric or chemogenomic workflows by consolidating the target landscape of kinase inhibitors.

Discovery of 5-Phenylpyrazolopyrimidinone Analogs as Potent Antitrypanosomal Agents with In Vivo Efficacy.

Human African Trypanosomiasis (HAT), caused by Trypanosoma brucei, is one of the neglected tropical diseases with a continuing need for new medication. We here describe the discovery of 5-phenylpyrazolopyrimidinone analogs as a novel series of phenotypic antitrypanosomal agents. The most potent compound, 30 (NPD-2975), has an in vitro IC50 of 70 nM against T. b. brucei with no apparent toxicity against human MRC-5 lung fibroblasts. Showing good physicochemical properties, low toxicity potential, acceptable metabolic stability, and other pharmacokinetic features, 30 was further evaluated in an acute mouse model of T. b. brucei infection. After oral dosing at 50 mg/kg twice per day for five consecutive days, all infected mice were cured. Given its good drug-like properties and high in vivo antitrypanosomal potential, the 5-phenylpyrazolopyrimidinone analog 30 represents a promising lead for future drug development to treat HAT.

An Automated, Open-Source Workflow for the Generation of (3D) Fragment Libraries.

The recent success of fragment-based drug discovery (FBDD) is inextricably linked to adequate library design. To guide the design of our fragment libraries, we have constructed an automated workflow in the open-source KNIME software. The workflow considers chemical diversity and novelty of the fragments, and can also take into account the three-dimensional (3D) character. This design tool can be used to create large and diverse libraries but also to select a small number of representative compounds as a focused set of unique screening compounds to enrich existing fragment libraries. To illustrate the procedures, the design and synthesis of a 10-membered focused library is reported based on the cyclopropane scaffold, which is underrepresented in our existing fragment screening library. Analysis of the focused compound set indicates significant shape diversity and a favorable overall physicochemical profile. By virtue of its modular setup, the workflow can be readily adjusted to design libraries that focus on properties other than 3D shape.

To Target or Not to Target Schistosoma mansoni Cyclic Nucleotide Phosphodiesterase 4A?

Schistosomiasis is a neglected tropical disease with high morbidity. Recently, the Schistosoma mansoni phosphodiesterase SmPDE4A was suggested as a putative new drug target. To support SmPDE4A targeted drug discovery, we cloned, isolated, and biochemically characterized the full-length and catalytic domains of SmPDE4A. The enzymatically active catalytic domain was crystallized in the apo-form (PDB code: 6FG5) and in the cAMP- and AMP-bound states (PDB code: 6EZU). The SmPDE4A catalytic domain resembles human PDE4 more than parasite PDEs because it lacks the parasite PDE-specific P-pocket. Purified SmPDE4A proteins (full-length and catalytic domain) were used to profile an in-house library of PDE inhibitors (PDE4NPD toolbox). This screening identified tetrahydrophthalazinones and benzamides as potential hits. The PDE inhibitor NPD-0001 was the most active tetrahydrophthalazinone, whereas the approved human PDE4 inhibitors roflumilast and piclamilast were the most potent benzamides. As a follow-up, 83 benzamide analogs were prepared, but the inhibitory potency of the initial hits was not improved. Finally, NPD-0001 and roflumilast were evaluated in an in vitro anti-S. mansoni assay. Unfortunately, both SmPDE4A inhibitors were not effective in worm killing and only weakly affected the egg-laying at high micromolar concentrations. Consequently, the results with these SmPDE4A inhibitors strongly suggest that SmPDE4A is not a suitable target for anti-schistosomiasis therapy.

Green Drug Discovery: Novel Fragment Space from the Biomass-Derived Molecule Dihydrolevoglucosenone (CyreneTM).

Biomass-derived molecules can provide a basis for sustainable drug discovery. However, their full exploration is hampered by the dominance of millions of old-fashioned screening compounds in classical high-throughput screening (HTS) libraries frequently utilized. We propose a fragment-based drug discovery (FBDD) approach as an efficient method to navigate biomass-derived drug space. Here, we perform a proof-of-concept study with dihydrolevoglucosenone (CyreneTM), a pyrolysis product of cellulose. Diverse synthetic routes afforded a 100-membered fragment library with a diversity in functional groups appended. The library overall performs well in terms of novelty, physicochemical properties, aqueous solubility, stability, and three-dimensionality. Our study suggests that Cyrene-based fragments are a valuable green addition to the drug discovery toolbox. Our findings can help in paving the way for new hit drug candidates that are based on renewable resources.

Fragment-to-Lead Medicinal Chemistry Publications in 2021.

This Perspective is the seventh in an annual series that summarizes successful Fragment-to-Lead (F2L) case studies published in a given year. A tabulated summary of relevant articles published in 2021 is provided, and features such as target class, screening methods, and ligand efficiency are discussed, both for the 2021 examples and for the combined examples over the years 2015-2021. In addition, trends and new developments in the field are summarized. In particular, the use of structural information in fragment-based drug discovery is discussed.

SAR exploration of the non-imidazole histamine H3 receptor ligand ZEL-H16 reveals potent inverse agonism.

Histamine H3 receptor (H3 R) agonists without an imidazole moiety remain very scarce. Of these, ZEL-H16 (1) has been reported previously as a high-affinity non-imidazole H3 R (partial) agonist. Our structure-activity relationship analysis using derivatives of 1 identified both basic moieties as key interaction motifs and the distance of these from the central core as a determinant for H3 R affinity. However, in spite of the reported H3 R (partial) agonism, in our hands, 1 acts as an inverse agonist for Gαi signaling in a CRE-luciferase reporter gene assay and using an H3 R conformational sensor. Inverse agonism was also observed for all of the synthesized derivatives of 1. Docking studies and molecular dynamics simulations suggest ionic interactions/hydrogen bonds to H3 R residues D1143.32 and E2065.46 as essential interaction points.

Exploring the Activity Profile of TbrPDEB1 and hPDE4 Inhibitors Using Free Energy Perturbation.

Human African trypanosomiasis (HAT) is a neglected tropical disease caused by the parasite Trypanosoma brucei (T.b.). A validated target for the treatment of HAT is the parasitic T.b. cyclic nucleotide phosphodiesterase B1 (TbrPDEB1). Although nanomolar TbrPDEB1 inhibitors have been obtained, their activity against the off-target human PDE4 (hPDE4) is likely to lead to undesirable clinical side effects, such as nausea, emesis, and immune suppression. Thus, new and more selective TbrPDEB1 inhibitors are still needed. This retrospective study evaluated the free energy perturbation (FEP+) method to predict the affinity profiles of TbrPDEB1 inhibitors against hPDE4. We demonstrate that FEP+ can be used to accurately predict the activity profiles of these homologous proteins. Moreover, we show how FEP+ can overcome challenges like protein flexibility and high sequence conservation. This also implies that the method can be applied prospectively for the lead optimization campaigns to design new and more selective TbrPDEB1 inhibitors.

Collaborative university-industry R&D practices supporting the pharmaceutical innovation process: Insights from a bibliometric review.

University-industry collaborative research and development (UIC R&D) is generally seen as a driver of the pharmaceutical innovation process. Here, we perform a bibliometric review of UIC R&D practices over the past 30 years (1991-2020) by analyzing 800+ publications. At the strategic level of organizational cooperation patterns, the analysis shows that pharmaceutical UIC R&D mainly aims at strategic alliance formation, which gears toward universities and companies collaboratively exploring and commercializing technological breakthroughs. At the structural level of universities and companies investing in cooperation and aligning their activities, analytical results indicate that universities and companies organize themselves as interdependent entities in an open innovation ecosystem. At the cultural level of generally accepted collaboration norms and habits, analytical results show that university-company partnerships are becoming a rule rather than an exception. This study delves into a 30-year history of UIC R&D practices that support the pharmaceutical innovation process. It provides academics and practitioners with an insight into possible strategies for UIC R&D in the future and presents avenues for science, business and innovation research.

Escape from planarity in fragment-based drug discovery: A synthetic strategy analysis of synthetic 3D fragment libraries.

In fragment-based drug discovery (FBDD), there is a developing appreciation that 3D fragments could offer opportunities that are not provided by 2D fragments. This review provides an overview of the synthetic strategies that have been used to prepare 3D fragments, as discussed in 25 papers published from 2011 to mid-May 2020. Three distinct strategies are highlighted: (i) diversity-oriented synthesis; (ii) the synthesis and diversification of scaffolds; and (iii) computational design and synthesis (where 3D fragments were computationally enumerated and filtered on the basis of computationally generated 3D shape descriptors and other properties). We conclude that a workflow that combines computational design and one other strategy, together with a consideration of fragment properties, 3D shape and 'fragment sociability', could allow 3D fragments to feature more widely in fragment libraries and could facilitate fragment-to-lead optimisation.

Puckering the Planar Landscape of Fragments: Design and Synthesis of a 3D Cyclobutane Fragment Library.

Fragment-based drug discovery (FBDD) has a growing need for unique screening libraries. The cyclobutane moiety was identified as an underrepresented yet attractive three-dimensional (3D) scaffold. Synthetic strategies were developed via a key 3-azido-cyclobutanone intermediate, giving potential access to a range of functional groups with accessible growth vectors. A focused set of 33 novel 3D cyclobutane fragments was synthesised, comprising three functionalities: secondary amines, amides, and sulfonamides. This library was designed using Principal Component Analysis (PCA) and an expanded version of the rule of three (RO3), followed by Principal Moment of Inertia (PMI) analysis to achieve both chemical diversity and high 3D character. Cis and trans ring isomers of library members were generated to maximise the shape diversity obtained, while limiting molecular complexity through avoiding enantiomers. Property analyses of the cyclobutane library indicated that it fares favourably against existing synthetic 3D fragment libraries in terms of shape and physicochemical properties.

Fragment-to-Lead Medicinal Chemistry Publications in 2020.

Fragment-based drug discovery (FBDD) continues to evolve and make an impact in the pharmaceutical sciences. We summarize successful fragment-to-lead studies that were published in 2020. Having systematically analyzed annual scientific outputs since 2015, we discuss trends and best practices in terms of fragment libraries, target proteins, screening technologies, hit-optimization strategies, and the properties of hit fragments and the leads resulting from them. As well as the tabulated Fragment-to-Lead (F2L) programs, our 2020 literature review identifies several trends and innovations that promise to further increase the success of FBDD. These include developing structurally novel screening fragments, improving fragment-screening technologies, using new computer-aided design and virtual screening approaches, and combining FBDD with other innovative drug-discovery technologies.

Progress in Free Energy Perturbation: Options for Evolving Fragments.

One of the remaining bottlenecks in fragment-based drug design (FBDD) is the initial exploration and optimization of the identified hit fragments. There is a growing interest in computational approaches that can guide these efforts by predicting the binding affinity of newly designed analogues. Among others, alchemical free energy (AFE) calculations promise high accuracy at a computational cost that allows their application during lead optimization campaigns. In this review, we discuss how AFE could have a strong impact in fragment evolution, and we raise awareness on the challenges that could be encountered applying this methodology in FBDD studies.

Exploring the Effect of Cyclization of Histamine H1 Receptor Antagonists on Ligand Binding Kinetics.

There is an increasing interest in guiding hit optimization by considering the target binding kinetics of ligands. However, compared to conventional structure-activity relationships, structure-kinetics relationships have not been as thoroughly explored, even for well-studied archetypical drug targets such as the histamine H1 receptor (H1R), a member of the family A G-protein coupled receptor. In this study, we show that the binding kinetics of H1R antagonists at the H1R is dependent on the cyclicity of both the aromatic head group and the amine moiety of H1R ligands, the chemotypes that are characteristic for the first-generation H1R antagonists. Fusing the two aromatic rings of H1R ligands into one tricyclic aromatic head group prolongs the H1R residence time for benchmark H1R ligands as well as for tailored synthetic analogues. The effect of constraining the aromatic rings and the basic amines is systematically explored, leading to a coherent series and detailed discussions of structure-kinetics relationships. This study shows that cyclicity has a pronounced effect on the binding kinetics.