Design, Synthesis, and In Vitro and In Vivo Evaluation of Cereblon Binding Bruton's Tyrosine Kinase (BTK) Degrader CD79b Targeted Antibody-Drug Conjugates

Antibody-drug conjugates (ADCs) are an established modality that allow for targeted delivery of a potent molecule, or payload, to a desired site of action. ADCs, wherein the payload is a targeted protein degrader, are an emerging area in the field. Herein we describe our efforts of delivering a Bruton's tyrosine kinase (BTK) bifunctional degrader 1 via a CD79b mAb (monoclonal antibody) where the degrader is linked at the ligase binding portion of the payload via a cleavable linker to the mAb. The resulting CD79b ADCs, 3 and 4, exhibit in vitro degradation and cytotoxicity comparable with that of 1, and ADC 3 can achieve more sustained in vivo degradation than intravenously administered 1 with markedly reduced systemic exposure of the payload.

DCAF1-based PROTACs with activity against clinically validated targets overcoming intrinsic- and acquired-degrader resistance

Targeted protein degradation (TPD) mediates protein level through small molecule induced redirection of E3 ligases to ubiquitinate neo-substrates and mark them for proteasomal degradation. TPD has recently emerged as a key modality in drug discovery. So far only a few ligases have been utilized for TPD. Interestingly, the workhorse ligase CRBN has been observed to be downregulated in settings of resistance to immunomodulatory inhibitory drugs (IMiDs). Here we show that the essential E3 ligase receptor DCAF1 can be harnessed for TPD utilizing a selective, non-covalent DCAF1 binder. We confirm that this binder can be functionalized into an efficient DCAF1-BRD9 PROTAC. Chemical and genetic rescue experiments validate specific degradation via the CRL4DCAF1 E3 ligase. Additionally, a dasatinib-based DCAF1 PROTAC successfully degrades cytosolic and membrane-bound tyrosine kinases. A potent and selective DCAF1-BTK-PROTAC (DBt-10) degrades BTK in cells with acquired resistance to CRBN-BTK-PROTACs while the DCAF1-BRD9 PROTAC (DBr-1) provides an alternative strategy to tackle intrinsic resistance to VHL-degrader, highlighting DCAF1-PROTACS as a promising strategy to overcome ligase mediated resistance in clinical settings.

Discovery of Ligands for TRIM58, a Novel Tissue-Selective E3 Ligase

Redirecting E3 ligases to neo-substrates, leading to their proteasomal disassembly, known as targeted protein degradation (TPD), has emerged as a promising alternative to traditional, occupancy-driven pharmacology. Although the field has expanded tremendously over the past years, the choice of E3 ligases remains limited, with an almost exclusive focus on CRBN and VHL. Here, we report the discovery of novel ligands to the PRY-SPRY domain of TRIM58, a RING ligase that is specifically expressed in erythroid precursor cells. A DSF screen, followed by validation using additional biophysical methods, led to the identification of TRIM58 ligand TRIM-473. A basic SAR around the chemotype was established by utilizing a competitive binding assay employing a short FP peptide probe derived from an endogenous TRIM58 substrate. The X-ray co-crystal structure of TRIM58 in complex with TRIM-473 gave insights into the binding mode and potential exit vectors for bifunctional degrader design.

QM assisted ML for 19F NMR chemical shift prediction

BACKGROUND

Ligand-observed 19F NMR detection is an efficient method for screening libraries of fluorinated molecules in fragment-based drug design campaigns. Screening fluorinated molecules in large mixtures makes 19F NMR a high-throughput method. Typically, these mixtures are generated from pools of well-characterized fragments. By predicting 19F NMR chemical shift, mixtures could be generated for arbitrary fluorinated molecules facilitating for example focused screens.

METHODS

In a previous publication, we introduced a method to predict 19F NMR chemical shift using rooted fluorine fingerprints and machine learning (ML) methods. Having observed that the quality of the prediction depends on similarity to the training set, we here propose to assist the prediction with quantum mechanics (QM) based methods in cases where compounds are not well covered by a training set.

RESULTS

Beyond similarity, the performance of ML methods could be associated with individual features in compounds. A combination of both could be used as a procedure to split input data sets into those that could be predicted by ML and those that required QM processing. We could show on a proprietary fluorinated fragment library, known as LEF (Local Environment of Fluorine), and a public Enamine data set of 19F NMR chemical shifts that ML and QM methods could synergize to outperform either method individually. Models built on Enamine data, as well as model building and QM workflow tools, can be found at https://github.com/PatrickPenner/lefshift and https://github.com/PatrickPenner/lefqm .

Discovery of a selective and biologically active low-molecular weight antagonist of human interleukin-1β

Human interleukin-1β (hIL-1β) is a pro-inflammatory cytokine involved in many diseases. While hIL-1β directed antibodies have shown clinical benefit, an orally available low-molecular weight antagonist is still elusive, limiting the applications of hIL-1β-directed therapies. Here we describe the discovery of a low-molecular weight hIL-1β antagonist that blocks the interaction with the IL-1R1 receptor. Starting from a low affinity fragment-based screening hit 1, structure-based optimization resulted in a compound (S)-2 that binds and antagonizes hIL-1β with single-digit micromolar activity in biophysical, biochemical, and cellular assays. X-ray analysis reveals an allosteric mode of action that involves a hitherto unknown binding site in hIL-1β encompassing two loops involved in hIL-1R1/hIL-1β interactions. We show that residues of this binding site are part of a conformationally excited state of the mature cytokine. The compound antagonizes hIL-1β function in cells, including primary human fibroblasts, demonstrating the relevance of this discovery for future development of hIL-1β directed therapeutics.

Discovery of New Binders for DCAF1, an Emerging Ligase Target in the Targeted Protein Degradation Field

In this study, we describe the rapid identification of potent binders for the WD40 repeat domain (WDR) of DCAF1. This was achieved by two rounds of iterative focused screening of a small set of compounds selected on the basis of internal WDR domain knowledge followed by hit expansion. Subsequent structure-based design led to nanomolar potency binders with a clear exit vector enabling DCAF1-based bifunctional degrader exploration.

The European Federation for Medicinal Chemistry and Chemical Biology (EFMC) Best Practice Initiative: Hit Generation

Hit generation is a crucial step in drug discovery that will determine the speed and chance of success of identifying drug candidates. Many strategies are now available to identify chemical starting points, or hits, and each biological target warrants a tailored approach. In this set of best practices, we detail the essential approaches for target centric hit generation and the opportunities and challenges they come with. We then provide guidance on how to validate hits to ensure medicinal chemistry is only performed on compounds and scaffolds that engage the target of interest and have the desired mode of action. Finally, we discuss the design of integrated hit generation strategies that combine several approaches to maximize the chance of identifying high quality starting points to ensure a successful drug discovery campaign.

Efficient Screening of Target-Specific Selected Compounds in Mixtures by 19F NMR Binding Assay with Predicted 19F NMR Chemical Shifts

Ligand-based 19 F NMR screening is a highly effective and well-established hit-finding approach. The high sensitivity to protein binding makes it particularly suitable for fragment screening. Different criteria can be considered for generating fluorinated fragment libraries. One common strategy is to assemble a large, diverse, well-designed and characterized fragment library which is screened in mixtures, generated based on experimental 19 F NMR chemical shifts. Here, we introduce a complementary knowledge-based 19 F NMR screening approach, named 19 Focused screening, enabling the efficient screening of putative active molecules selected by computational hit finding methodologies, in mixtures assembled and on-the-fly deconvoluted based on predicted 19 F NMR chemical shifts. In this study, we developed a novel approach, named LEFshift , for 19 F NMR chemical shift prediction using rooted topological fluorine torsion fingerprints in combination with a random forest machine learning method. A demonstration of this approach to a real test case is reported.

Hydrogen Bond Acceptor Propensity of Different Fluorine Atom Types: An Analysis of Experimentally and Computationally Derived Parameters

The propensity of organic fluorine acting as a weak hydrogen bond acceptor (HBA) in intermolecular and intramolecular interactions has been the subject of many experimental and theoretical studies often reaching different conclusions. Over the last few years, new and stronger evidences have emerged for the direct involvement of fluorine in weak hydrogen bond (HB) formation. However, not all the fluorine atom types can act as weak HBA. In this work, the differential HBA propensity of various types of fluorine atoms was analyzed with a particular emphasis for the different types of alkyl fluorides. This was carried out by evaluating ab initio computed parameters, experimental ¹⁹ F NMR chemical shifts and small molecule crystallographic structures (extracted from the CSD database). According to this analysis, shielded (with reference to the ¹⁹ F NMR chemical shift) alkyl mono-fluorinated motifs display the highest HBA propensity in agreement with solution studies. Although much weaker than other well-characterized HB complexes, the fragile HBs formed by these fluorinated motifs have important implications for the chemical-physical and structural properties of the molecules, chemical reactions, and protein-ligand recognition.

Fluorine NMR functional screening: from purified enzymes to human intact living cells

The substrate- or cofactor-based fluorine NMR screening, also known as n-FABS (n fluorine atoms for biochemical screening), represents a powerful method for performing a direct functional assay in the search of inhibitors or enhancers of an enzymatic reaction. Although it suffers from the intrinsic low sensitivity compared to other biophysical techniques usually applied in functional assays, it has some distinctive features that makes it appealing for tackling complex chemical and biological systems. Its strengths are represented by the easy set-up, robustness, flexibility, lack of signal interference and rich information content resulting in the identification of bona fide inhibitors and reliable determination of their inhibitory strength. The versatility of the n-FABS allows its application to either purified enzymes, cell lysates or intact living cells. The principles, along with theoretical, technical and practical aspects, of the methodology are discussed. Furthermore, several applications of the technique to pharmaceutical projects are presented.

Comprehensive and High-Throughput Exploration of Chemical Space Using Broadband 19 F NMR-Based Screening

Fragment-based lead discovery has become a fundamental approach to identify ligands that efficiently interact with disease-relevant targets. Among the numerous screening techniques, fluorine-detected NMR has gained popularity owing to its high sensitivity, robustness, and ease of use. To effectively explore chemical space, a universal NMR experiment, a rationally designed fragment library, and a sample composition optimized for a maximal number of compounds and minimal measurement time are required. Here, we introduce a comprehensive method that enabled the efficient assembly of a high-quality and diverse library containing nearly 4000 fragments and screening for target-specific binders within days. At the core of the approach is a novel broadband relaxation-edited NMR experiment that covers the entire chemical shift range of drug-like ¹⁹ F motifs in a single measurement. Our approach facilitates the identification of diverse binders and the fast ligandability assessment of new targets.

Design of Potent and Selective Covalent Inhibitors of Bruton's Tyrosine Kinase Targeting an Inactive Conformation

Bruton's tyrosine kinase (BTK) is a member of the TEC kinase family and is selectively expressed in a subset of immune cells. It is a key regulator of antigen receptor signaling in B cells and of Fc receptor signaling in mast cells and macrophages. A BTK inhibitor will likely have a positive impact on autoimmune diseases which are caused by autoreactive B cells and immune-complex driven inflammation. We report the design, optimization, and characterization of potent and selective covalent BTK inhibitors. Starting from the selective reversible inhibitor 3 binding to an inactive conformation of BTK, we designed covalent irreversible compounds by attaching an electrophilic warhead to reach Cys481. The first prototype 4 covalently modified BTK and showed an excellent kinase selectivity including several Cys-containing kinases, validating the design concept. In addition, this compound blocked FcγR-mediated hypersensitivity in vivo. Optimization of whole blood potency and metabolic stability resulted in compounds such as 8, which maintained the excellent kinase selectivity and showed improved BTK occupancy in vivo.

Design, Synthesis, and Preclinical Characterization of Selective Factor D Inhibitors Targeting the Alternative Complement Pathway

Complement factor D (FD), a highly specific S1 serine protease, plays a central role in the amplification of the alternative complement pathway (AP) of the innate immune system. Dysregulation of AP activity predisposes individuals to diverse disorders such as age-related macular degeneration, atypical hemolytic uremic syndrome, membranoproliferative glomerulonephritis type II, and paroxysmal nocturnal hemoglobinuria. Previously, we have reported the screening efforts and identification of reversible benzylamine-based FD inhibitors (1 and 2) binding to the open active conformation of FD. In continuation of our drug discovery program, we designed compounds applying structure-based approaches to improve interactions with FD and gain selectivity against S1 serine proteases. We report herein the design, synthesis, and medicinal chemistry optimization of the benzylamine series culminating in the discovery of 12, an orally bioavailable and selective FD inhibitor. 12 demonstrated systemic suppression of AP activation in a lipopolysaccharide-induced AP activation model as well as local ocular suppression in intravitreal injection-induced AP activation model in mice expressing human FD.

Discovery and Design of First Benzylamine-Based Ligands Binding to an Unlocked Conformation of the Complement Factor D

Complement Factor D, a serine protease of the S1 family and key component of the alternative pathway amplification loop, represents a promising target for the treatment of several prevalent and rare diseases linked to the innate immune system. Previously reported FD inhibitors have been shown to bind to the FD active site in its self-inhibited conformation characterized by the presence of a salt bridge at the bottom of the S1 pocket between Asp189 and Arg218. We report herein a new set of small-molecule FD ligands that harbor a basic S1 binding moiety directly binding to the carboxylate of Asp189, thereby displacing the Asp189-Arg218 ionic interaction and significantly changing the conformation of the self-inhibitory loop.

Discovery of Highly Potent and Selective Small-Molecule Reversible Factor D Inhibitors Demonstrating Alternative Complement Pathway Inhibition in Vivo

The highly specific S1 serine protease factor D (FD) plays a central role in the amplification of the complement alternative pathway (AP) of the innate immune system. Genetic associations in humans have implicated AP activation in age-related macular degeneration (AMD), and AP dysfunction predisposes individuals to disorders such as paroxysmal nocturnal hemoglobinuria (PNH) and atypical hemolytic uremic syndrome (aHUS). The combination of structure-based hit identification and subsequent optimization of the center (S)-proline-based lead 7 has led to the discovery of noncovalent reversible and selective human factor D (FD) inhibitors with drug-like properties. The orally bioavailable compound 2 exerted excellent potency in 50% human whole blood in vitro and blocked AP activity ex vivo after oral administration to monkeys as demonstrated by inhibition of membrane attack complex (MAC) formation. Inhibitor 2 demonstrated sustained oral and ocular efficacy in a model of lipopolysaccharide (LPS)-induced systemic AP activation in mice expressing human FD.

Structure-Based Library Design and Fragment Screening for the Identification of Reversible Complement Factor D Protease Inhibitors

Chronic dysregulation of alternative complement pathway activation has been associated with diverse clinical disorders including age-related macular degeneration and paroxysmal nocturnal hemoglobinurea. Factor D is a trypsin-like serine protease with a narrow specificity for arginine in the P1 position, which catalyzes the first enzymatic reaction of the amplification loop of the alternative pathway. In this article, we describe two hit finding approaches leading to the discovery of new chemical matter for this pivotal protease of the complement system: in silico active site mapping for hot spot identification to guide rational structure-based design and NMR screening of focused and diverse fragment libraries. The wealth of information gathered by these complementary approaches enabled the identification of ligands binding to different subpockets of the latent Factor D conformation and was instrumental for understanding the binding requirements for the generation of the first known potent noncovalent reversible Factor D inhibitors.

Synthesis and Biological Evaluation of New Triazolo- and Imidazolopyridine RORγt Inverse Agonists

Retinoic-acid-related orphan receptor γt (RORγt) is a key transcription factor implicated in the production of pro-inflammatory Th17 cytokines, which drive a number of autoimmune diseases. Despite diverse chemical series having been reported, combining high potency with a good physicochemical profile has been a very challenging task in the RORγt inhibitor field. Based on available chemical structures and incorporating in-house knowledge, a new series of triazolo- and imidazopyridine RORγt inverse agonists was designed. In addition, replacement of the terminal cyclopentylamide metabolic soft spot by five-membered heterocycles was investigated. From our efforts, we identified an optimal 6,7,8-substituted imidazo[1,2-a]pyridine core system and a 5-tert-butyl-1,2,4-oxadiazole as cyclopentylamide replacement leading to compounds 10 ((S)-N-(8-((4-(cyclopentanecarbonyl)-3-methylpiperazin-1-yl)methyl)-7-methylimidazo[1,2-a]pyridin-6-yl)-2-methylpyrimidine-5-carboxamide) and 33 ((S)-N-(8-((4-(5-(tert-butyl)-1,2,4-oxadiazol-3-yl)-3-methylpiperazin-1-yl)methyl)-7-methylimidazo[1,2-a]pyridin-6-yl)-2-methylpyrimidine-5-carboxamide). Both derivatives showed good pharmacological potencies in biochemical and cell-based assays combined with excellent physicochemical properties, including low to medium plasma protein binding across species. Finally, 10 and 33 were shown to be active in a rodent pharmacokinetic/pharmacodynamic (PK/PD) model after oral gavage at 15 mg kg^-1 , lowering IL-17 cytokine production in ex vivo antigen recall assays.

Fluorine as a hydrogen-bond acceptor: experimental evidence and computational calculations

Hydrogen-bonding interactions play an important role in many chemical and biological systems. Fluorine acting as a hydrogen-bond acceptor in intermolecular and intramolecular interactions has been the subject of many controversial discussions and there are different opinions about it. Recently, we have proposed a correlation between the propensity of fluorine to be involved in hydrogen bonds and its (19)F NMR chemical shift. We now provide additional experimental and computational evidence for this correlation. The strength of hydrogen-bond complexes involving the fluorine moieties CH2F, CHF2, and CF3 was measured and characterized in simple systems by using established and novel NMR methods and compared to the known hydrogen-bond complex formed between acetophenone and p-fluorophenol. Implications of these results for (19)F NMR screening are analyzed in detail. Computed values of the molecular electrostatic potential at the different fluorine atoms and the analysis of the electron density topology at bond critical points correlate well with the NMR results.

Design and generation of highly diverse fluorinated fragment libraries and their efficient screening with improved (19) F NMR methodology

Fragment screening performed with (19) F NMR spectroscopy is becoming increasingly popular in drug discovery projects. With this approach, libraries of fluorinated fragments are first screened using the direct-mode format of the assay. The choice of fluorinated motifs present in the library is fundamental in order to ensure a large coverage of chemical space and local environment of fluorine (LEF). Mono- and poly-fluorinated fragments to be included in the libraries for screening are selected from both in-house and commercial collections, and those that are ad hoc designed and synthesized. Additional fluorinated motifs to be included in the libraries derive from the fragmentation of compounds in development and launched on the market, and compounds contained in other databases (such as Integrity, PDB and ChEMBL). Complex mixtures of highly diverse fluorine motifs can be rapidly screened and deconvoluted in the same NMR tube with a novel on the fly combined procedure for the identification of the active molecule(s). Issues and problems encountered in the design, generation and screening of diverse fragment libraries of fluorinated compounds with (19) F NMR spectroscopy are analyzed and technical solutions are provided to overcome them. The versatile screening methodology described here can be efficiently applied in laboratories with limited NMR setup and could potentially lead to the increasing role of (19) F NMR in the hit identification and lead optimization phases of drug discovery projects.

Comparability of mixed IC₅₀ data - a statistical analysis

The biochemical half maximal inhibitory concentration (IC₅₀) is the most commonly used metric for on-target activity in lead optimization. It is used to guide lead optimization, build large-scale chemogenomics analysis, off-target activity and toxicity models based on public data. However, the use of public biochemical IC₅₀ data is problematic, because they are assay specific and comparable only under certain conditions. For large scale analysis it is not feasible to check each data entry manually and it is very tempting to mix all available IC₅₀ values from public database even if assay information is not reported. As previously reported for K_i database analysis, we first analyzed the types of errors, the redundancy and the variability that can be found in ChEMBL IC₅₀ database. For assessing the variability of IC₅₀ data independently measured in two different labs at least ten IC₅₀ data for identical protein-ligand systems against the same target were searched in ChEMBL. As a not sufficient number of cases of this type are available, the variability of IC₅₀ data was assessed by comparing all pairs of independent IC₅₀ measurements on identical protein-ligand systems. The standard deviation of IC₅₀ data is only 25% larger than the standard deviation of K_i data, suggesting that mixing IC₅₀ data from different assays, even not knowing assay conditions details, only adds a moderate amount of noise to the overall data. The standard deviation of public ChEMBL IC₅₀ data, as expected, resulted greater than the standard deviation of in-house intra-laboratory/inter-day IC₅₀ data. Augmenting mixed public IC₅₀ data by public K_i data does not deteriorate the quality of the mixed IC₅₀ data, if the K_i is corrected by an offset. For a broad dataset such as ChEMBL database a K_i- IC₅₀ conversion factor of 2 was found to be the most reasonable.

Subpocket analysis method for fragment-based drug discovery

Although two binding sites might be dissimilar overall, they might still bind the same fragments if they share suitable subpockets. Information about shared subpockets can be therefore used in fragment-based drug design to suggest new fragments or to replace existing fragments within an already known compound. A novel computational method called SubCav is described which allows the similarity searching and alignment of subpockets from a PDB-wide database against a user-defined query. The method is based on pharmacophoric fingerprints combined with a subpocket alignment algorithm. SubCav was shown to be effective in producing reasonable alignments for subpockets with low sequence similarity and be able to retrieve relevant subpockets from a large database of structures including those with different folds. It can also be used to analyze subpockets inside a protein family to facilitate drug design and to rationalize compound selectivity.

Technical and practical aspects of (19) F NMR-based screening: toward sensitive high-throughput screening with rapid deconvolution

The technical and practical aspects of (19) F NMR-based screening against a macromolecular target are analyzed in detail. A novel method utilizing the relaxation of (19) F homonuclear double quantum coherence is proposed for performing NMR-based binding assays in a direct- or competition-mode format. A combined strategy based on (19) F NMR chemical shift prediction, 2D (19) F NMR DOSY, and 2D (19) F-(1) H NMR long-range COSY experiments is presented for the deconvolution of complex mixtures of fluorinated molecules generated by either addition of single compounds or by chemical synthesis. The approaches presented here allow the screening of complex mixtures, even in the case where the exact composition is not known, and the rapid identification of the binders contained in the mixtures.

The experimental uncertainty of heterogeneous public K(i) data

The maximum achievable accuracy of in silico models depends on the quality of the experimental data. Consequently, experimental uncertainty defines a natural upper limit to the predictive performance possible. Models that yield errors smaller than the experimental uncertainty are necessarily overtrained. A reliable estimate of the experimental uncertainty is therefore of high importance to all originators and users of in silico models. The data deposited in ChEMBL was analyzed for reproducibility, i.e., the experimental uncertainty of independent measurements. Careful filtering of the data was required because ChEMBL contains unit-transcription errors, undifferentiated stereoisomers, and repeated citations of single measurements (90% of all pairs). The experimental uncertainty is estimated to yield a mean error of 0.44 pK(i) units, a standard deviation of 0.54 pK(i) units, and a median error of 0.34 pK(i) units. The maximum possible squared Pearson correlation coefficient (R(2)) on large data sets is estimated to be 0.81.

Intermolecular and intramolecular hydrogen bonds involving fluorine atoms: implications for recognition, selectivity, and chemical properties

A correlation between 19F NMR isotropic chemical shift and close intermolecular F⋅⋅⋅H-X contacts (with X=N or O) has been identified upon analysis of the X-ray crystal structures of fluorinated molecules listed in the Cambridge Structural Database (CSD). An optimal F⋅⋅⋅X distance involving primary and shielded secondary fluorine atoms in hydrogen-bond formation along with a correlation between F⋅⋅⋅H distance and F⋅⋅⋅H-X angle were also derived from the analysis. The hydrogen bonds involving fluorine are relevant, not only for the recognition mechanism and stabilization of a preferred conformation, but also for improvement in the permeability of the molecules, as shown with examples taken from a proprietary database. Results of an analysis of the small number of fluorine-containing natural products listed in the Protein Data Bank (PDB) appear to strengthen the derived correlation between 19F NMR isotropic chemical shift and interactions involving fluorine (also known as the "rule of shielding") and provides a hypothesis for the recognition mechanism and catalytic activity of specific enzymes. Novel chemical scaffolds, based on the rule of shielding, have been designed for recognizing distinct structural motifs present in proteins. It is envisaged that this approach could find useful applications in drug design for the efficient optimization of chemical fragments or promising compounds by increasing potency and selectivity against the desired biomolecular target.

Fluorine-protein interactions and ¹⁹F NMR isotropic chemical shifts: An empirical correlation with implications for drug design

An empirical correlation between the fluorine isotropic chemical shifts, measured by ¹⁹F NMR spectroscopy, and the type of fluorine-protein interactions observed in crystal structures is presented. The CF, CF₂, and CF₃ groups present in fluorinated ligands found in the Protein Data Bank were classified according to their ¹⁹F NMR chemical shifts and their close intermolecular contacts with the protein atoms. Shielded fluorine atoms, i.e., those with increased electron density, are observed primarily in close contact to hydrogen bond donors within the protein structure, suggesting the possibility of intermolecular hydrogen bond formation. Deshielded fluorines are predominantly found in close contact with hydrophobic side chains and with the carbon of carbonyl groups of the protein backbone. Correlation between the ¹⁹F NMR chemical shift and hydrogen bond distance, both derived experimentally and computed through quantum chemical methods, is also presented. The proposed "rule of shielding" provides some insight into and guidelines for the judicious selection of appropriate fluorinated moieties to be inserted into a molecule for making the most favorable interactions with the receptor.

Combined use of computational chemistry, NMR screening, and X-ray crystallography for identification and characterization of fluorophilic protein environments

(19)F NMR screening of fluorinated fragments with different Local Environment of Fluorine, a.k.a. LEF library, is an experimental methodology which, beyond providing useful starting fragments for fragment-based drug discovery projects, offers, in combination with crystal and computational analysis, an approach for the identification of fluorophilic hot-spots in the proteins of interest. The application of this approach in the identification of fluorinated fragments binding to the serine protease trypsin, and the X-ray structures of the complexes are presented. The specific nature of the observed fluorine-protein interactions is discussed and compared with the interactions detected for other fluorinated ligands reported in the protein data bank. The presence of similar 3D arrangements of protein atoms at the fluorine sub-sites is identified with a newly developed tool. In this approach, protein sub-sites are extracted around each fluorine contained in the protein data bank and compared with the query of interest by using a pharmacophoric description.

Tautomer preference in PDB complexes and its impact on structure-based drug discovery

Tautomer enrichment is a key step of ligand preparation prior to virtual screening. In this paper, we have investigated how tautomer preference in various media (water, gas phase, and crystal) compares to tautomer preference at the active site of the protein by analyzing the different possible H-bonding contacts for a set of 13 tautomeric structures. In addition, we have explored the impact of four different protocols for the enumeration of tautomers in virtual screening by using Flap, Glide, and Gold as docking tools on seven targets of the DUD data set. Excluding targets in which the binding does not involve tautomeric atoms (HSP90, p38, and VEGFR2), we found that the average receiver operating characteristic curve enrichment at 10% was 0.25 (Gold), 0.24 (Glide), and 0.50 (Flap) by considering only tautomers predicted to be unstable in water versus 0.41 (Gold), 0.56 (Glide), 0.51 (Flap) by limiting the enumeration process only to the predicted most stable tautomer. The inclusion of all tautomers (stable and unstable) yielded slightly poorer results than considering only the most stable form in water.

Identification of N,1,4,4-tetramethyl-8-{[4-(4-methylpiperazin-1-yl)phenyl]amino}-4,5-dihydro-1H-pyrazolo[4,3-h]quinazoline-3-carboxamide (PHA-848125), a potent, orally available cyclin dependent kinase inhibitor

The discovery of a novel class of inhibitors of cyclin dependent kinases (CDKs) is described. Starting from compound 1, showing good potency as inhibitor of CDKs but being poorly selective against a panel of serine-threonine and tyrosine kinases, new analogues were synthesized. Enhancement in selectivity, antiproliferative activity against A2780 human ovarian carcinoma cells, and optimization of the physical properties and pharmacokinetic profile led to the identification of highly potent and orally available compounds. Compound 28 (PHA-848125), which in the preclinical xenograft A2780 human ovarian carcinoma model showed good efficacy and was well tolerated upon repeated daily treatments, was identified as a drug candidate for further development. Compound 28 is currently undergoing phase I and phase II clinical trials.

Identification of potent pyrazolo[4,3-h]quinazoline-3-carboxamides as multi-cyclin-dependent kinase inhibitors

Abnormal proliferation mediated by disruption of the mechanisms that keep the cell cycle under control is a hallmark of virtually all cancer cells. Compounds targeting complexes between cyclin-dependent kinases (CDKs) and cyclins (Cy) and inhibiting their activity are regarded as promising antitumor agents to complement the existing therapies. An expansion of pyrazolo[4,3-h]quinazoline chemical class oriented to the development of three points of variability was undertaken leading to a series of compounds able to inhibit CDKs both in vitro and in vivo. Starting from the CDK selective but poorly soluble hit compound 1, we succeeded in obtaining several compounds showing enhanced inhibitory activity both on CDKs and on tumor cells and displaying improved physical properties and pharmacokinetic behavior. Our study led to the identification of compound 59 as a highly potent, orally bioavailable CDK inhibitor that exhibited significant in vivo efficacy on the A2780 ovarian carcinoma xenograft model. The demonstrated mechanisms of action of compound 59 on cancer cell lines and its ability to inhibit tumor growth in vivo render this compound very interesting as potential antineoplastic agent.

Optimization of 6,6-dimethyl pyrrolo[3,4-c]pyrazoles: Identification of PHA-793887, a potent CDK inhibitor suitable for intravenous dosing

We have recently reported CDK inhibitors based on the 6-substituted pyrrolo[3,4-c]pyrazole core structure. Improvement of inhibitory potency against multiple CDKs, antiproliferative activity against cancer cell lines and optimization of the physico-chemical properties led to the identification of highly potent compounds. Compound 31 (PHA-793887) showed good efficacy in the human ovarian A2780, colon HCT-116 and pancreatic BX-PC3 carcinoma xenograft models and was well tolerated upon daily treatments by iv administration. It was identified as a drug candidate for clinical evaluation in patients with solid tumors.

6-Substituted Pyrrolo[3,4-c]pyrazoles: An Improved Class of CDK2 Inhibitors

We have recently reported a new class of CDK2/cyclin A inhibitors based on a bicyclic tetrahydropyrrolo[3,4-c]pyrazole scaffold. The introduction of small alkyl or cycloalkyl groups in position 6 of this scaffold allowed variation at the other two diversity points. Conventional and polymer-assisted solution phase chemistry provided a way of generating compounds with improved biochemical and cellular activity. Optimization of the physical properties and pharmacokinetic profile led to a compound which exhibited good efficacy in vivo on A2780 human ovarian carcinoma.

Polyfluorinated Amino Acids for Sensitive 19F NMR-Based Screening and Kinetic Measurements

Two novel series of polyfluorinated amino acids (PFAs) were designed and synthesized according to a very short and scalable synthetic sequence. The advantages and limitations of these moieties for screening purposes are presented and discussed. The potential applications of these PFAs were tested with their incorporation into small arginine-containing peptides that represent suitable substrates for the enzyme trypsin. The enzymatic reactions were monitored by 19F NMR spectroscopy, using the 3-FABS (three fluorine atoms for biochemical screening) technique. The high sensitivity achieved with these PFAs permits a reduction in substrate concentration required for 3-FABS. This is relevant in the utilization of 3-FABS in fragment-based screening for identification of small scaffolds that bind weakly to the receptor of interest. The large dispersion of 19F isotropic chemical shifts allows the simultaneous measurement of the efficiency of the different substrates, thus identifying the best substrate for screening purposes. Furthermore, the knowledge of KM and Kcat for the different substrates allows the identification of the structural motifs responsible for the binding affinity to the receptor and those affecting the chemical steps in enzymatic catalysis. This enables the construction of suitable pharmacophores that can be used for designing nonpeptidic inhibitors with high affinity for the enzyme or molecules that mimic the transition state. The novel PFAs can also find useful application in the FAXS (fluorine chemical shift anisotropy and exchange for screening) experiment, a 19F-based competition binding assay for the detection of molecules that inhibit the interaction between two proteins.

NMR-based quality control approach for the identification of false positives and false negatives in high throughput screening

The quality of the data generated in a high throughput screening (HTS) run is fundamental for selecting bona fide inhibitors and for ensuring the capture of the full richness of inhibitors present in a chemical library. For this purpose a quality control filter based on three one dimensional (1D) proton NMR experiments is proposed. The approach called SPAM (Solubility, Purity and Aggregation of the Molecule) Filter requires the acquisition of a 1D reference spectrum, a WaterLOGSY spectrum and/or a selective longitudinal relaxation filter spectrum for the identified hits dissolved in aqueous solution and in the presence of a water soluble reference molecule. This palette of experiments permits the rapid characterization of the identity, purity, solubility and aggregation state of the active compound. This knowledge is crucial for deriving accurate IC(50) and K(1) values of the inhibitors, for identifying false negatives and for detecting promiscuous inhibitors. Only compounds that pass through the SPAM Filter can be considered as starting points for medicinal chemistry efforts directed toward lead optimization. Examples of this approach in the identification of false positives in a screening run against the enzyme thymidine phosphorylase (TP) and the rescue of a false negative in a screening run against the Ser/Thr kinase AKT1 are presented.

Virtual screening to enrich a compound collection with CDK2 inhibitors using docking, scoring, and composite scoring models

Docking programs can generate subsets of a compound collection with an increased percentage of actives against a target (enrichment) by predicting their binding mode (pose) and affinity (score), and retrieving those with the highest scores. Using the QXP and GOLD programs, we compared the ability of six single scoring functions (PLP, Ligscore, Ludi, Jain, ChemScore, PMF) and four composite scoring models (Mean Rank: MR, Rank-by-Vote: Vt, Bayesian Statistics: BS and PLS Discriminant Analysis: DA) to separate compounds that are active against CDK2 from inactives. We determined the enrichment for the entire set of actives (IC50 < 10 microM) and for three activity subsets. In all cases, the enrichment for each subset was lower than for the entire set of actives. QXP outperformed GOLD at pose prediction, but yielded only moderately better enrichments. Five to six scoring functions yielded good enrichments with GOLD poses, while typically only two worked well with QXP poses. For each program, two scoring functions generally performed better than the others (Ligscore2 and Ludi for GOLD; QXP and Jain for QXP). Composite scoring functions yielded better results than single scoring functions. The consensus approaches MR and Vt worked best when separating micromolar inhibitors from inactives. The statistical approaches BS and DA, which require training data, performed best when distinguishing between low and high nanomolar inhibitors. The key observation that all hit rate profiles for all four activity intervals for all scoring schemes for both programs are significantly better than random, is evidence that docking can be successfully applied to enrich compound collections.