Covalent Drugs Research Articles

Lysine-Reactive N-Acyl-N-aryl Sulfonamide Warheads: Improved Reaction Properties and Application in the Covalent Inhibition of an Ibrutinib-Resistant BTK Mutant.

The covalent inhibition of a target protein has gained widespread attention in the field of drug discovery. Most of the current covalent drugs utilize the high reactivity of cysteines toward modest electrophiles. However, there is a growing need for warheads that can target lysine residues to expand the range of covalently druggable proteins and to deal with emerging proteins with mutations resistant to cysteine-targeted covalent drugs. We have recently developed an N-acyl-N-alkyl sulfonamide (NASA) as a lysine-targeted electrophile. Despite its successful application, this NASA warhead suffered from instability in physiological environments, such as serum-containing medium, because of its high intrinsic reactivity. In this study, we sought to modify the structure of the NASA warhead and found that N-acyl-N-aryl sulfonamides (ArNASAs) are promising electrophiles for use in a lysine-targeted covalent inhibition strategy. We prepared a focused library of ArNASA derivatives with diverse structures and reactivity and identified several warhead candidates with suppressed hydrolysis-mediated inactivation and reduced nonspecific reactions with off-target proteins, without sacrificing the reactivity toward the target. These reaction properties enabled the improved covalent inhibition of intracellular heat shock protein 90 (HSP90) in the presence of serum and the development of the first irreversible inhibitor for ibrutinib-resistant Bruton's tyrosine kinase (BTK) bearing the C481S mutation. This study clearly demonstrated the use of a set of ArNASA warheads to create highly potent covalent drugs and highlighted the importance of enriching the current arsenal of lysine-reactive warheads.

Landscape of In Silico Tools for Modeling Covalent Modification of Proteins: A Review on Computational Covalent Drug Discovery.

Covalent drug discovery has been a challenging research area given the struggle of finding a sweet balance between selectivity and reactivity for these drugs, the lack of which often leads to off-target activities and hence undesirable side effects. However, there has been a resurgence in covalent drug design following the success of several covalent drugs such as boceprevir (2011), ibrutinib (2013), neratinib (2017), dacomitinib (2018), zanubrutinib (2019), and many others. Design of covalent drugs includes many crucial factors, where "evaluation of the binding affinity" and "a detailed mechanistic understanding on covalent inhibition" are at the top of the list. Well-defined experimental techniques are available to elucidate these factors; however, often they are expensive and/or time-consuming and hence not suitable for high throughput screens. Recent developments in in silico methods provide promise in this direction. In this report, we review a set of recent publications that focused on developing and/or implementing novel in silico techniques in "Computational Covalent Drug Discovery (CCDD)". We also discuss the advantages and disadvantages of these approaches along with what improvements are required to make it a great tool in medicinal chemistry in the near future.

Offsetting Low-Affinity Carbohydrate Binding with Covalency to Engage Sugar-Specific Proteins for Tumor-Immune Proximity Induction.

Carbohydrate-binding receptors are often used by the innate immune system to potentiate inflammation, target endocytosis/destruction, and adaptive immunity (e.g., CD206, DC-SIGN, MBL, and anticarbohydrate antibodies). To access this class of receptors for cancer immunotherapy, a growing repertoire of bifunctional proximity-inducing therapeutics use high-avidity multivalent carbohydrate binding domains to offset the intrinsically low affinity associated with monomeric carbohydrate-protein binding interactions (Kd ≈ 10-3-10-6 M). For applications aimed at recruiting anticarbohydrate antibodies to tumor cells, large synthetic scaffolds are used that contain both a tumor-binding domain (TBD) and a multivalent antibody-binding domain (ABD) comprising multiple l-rhamnose monosaccharides. This allows for stable bridging between tumor cells and antibodies, which activates tumoricidal immune function. Problematically, such multivalent macromolecules can face limitations including synthetic and/or structural complexity and the potential for off-target immune engagement. We envisioned that small bifunctional "proximity-inducing" molecules containing a low-affinity monovalent ABD could efficiently engage carbohydrate-binding receptors for tumor-immune proximity by coupling weak binding with covalent engagement. Typical covalent drugs and electrophilic chimeras use high-affinity ligands to promote the fast covalent engagement of target proteins (i.e., large kinact/KI), driven by a favorably small KI for binding. We hypothesized the much less favorable KI associated with carbohydrate-protein binding interactions can be offset by a favorably large kinact for the covalent labeling step. In the current study, we test this hypothesis in the context of a model system that uses rhamnose-specific antibodies to induce tumor-immune proximity and tumoricidal function. We discovered that synthetic chimeric molecules capable of preorganizing an optimal electrophile (i.e., SuFEx vs activated ester) for protein engagement can rapidly covalently engage natural sources of antirhamnose antibody using only a single low-affinity rhamnose monosaccharide ABD. Strikingly, we observe chimeric molecules lacking an electrophile, which can only noncovalently bind the antibody, completely lack tumoricidal function. This is in stark contrast to previous work targeting small molecule hapten and peptide-specific antibodies. Our findings underscore the utility of covalency as a strategy to engage low-affinity carbohydrate-specific proteins for tumor-immune proximity induction.

Development of covalent inhibitors: Principle, design, and application in cancer

AbstractCovalent inhibitors have been a rapidly growing field in drug discovery due to their therapeutic potential and unique advantages in cancer therapy. As opposed to noncovalent inhibitory drugs, covalent inhibitors reversibly or irreversibly modify proximal nucleophilic amino acid residues on proteins, aiming to selectively recognize and bind to protein targets and addressing some of the challenges faced by noncovalent drugs. Most successful targeted covalent inhibitors depend primarily on binding‐site cysteine residues, but this has limitations for certain protein targets that lack targetable cysteine residues. Recently, the rational design of covalent inhibitors or covalent probes targeting other nucleophilic residues, such as lysine, tyrosine, serine, has turned out to be another promising strategy for cancer therapy. Thus, the development of novel strategies to extend the scope of covalent binding and improve the binding properties is required. This review gives a summary of the development of covalent inhibitors targeting noncysteine from different aspects, including target identification, structure–activity relationships, drug discovery strategies, and binding properties, in the hope of providing a scientific reference for future covalent drug discovery as a means of expanding research in cancer therapy.

Covalent Stapling of the Cereblon Sensor Loop Histidine Using Sulfur-Heterocycle Exchange.

Site-specific modification of amino acid residues in protein binding pockets using sulfonyl exchange chemistry expands the druggable proteome by enabling the development of covalent modulators that target residues beyond cysteine. Sulfonyl fluoride and triazole electrophiles were incorporated previously into the cereblon (CRBN) molecular glue degrader EM12, to covalently engage His353 within the CRBN sensor loop, but these probes had poor human plasma stability. Attenuation of intrinsic reactivity through the development of sulfonyl pyrazoles, imidazoles, and nucleobases enhanced plasma stability, and several compounds retained efficient labeling of His353. For example, sulfonyl imidazole EM12-SO2Im covalently blocked the CRBN binding site and possessed excellent metabolic stability in human plasma, liver microsomes, and hepatocytes. These results highlight the potential suitability of sulfonyl imidazole and related sulfur(VI)-diazole exchange (SuDEx) warheads for covalent drug development and further exemplify the therapeutic promise of site-specific histidine targeting.

ABPP-CoDEL: Activity-Based Proteome Profiling-Guided Discovery of Tyrosine-Targeting Covalent Inhibitors from DNA-Encoded Libraries.

DNA-encoded chemical library (DEL) has been extensively used for lead compound discovery for decades in academia and industry. Incorporating an electrophile warhead into DNA-encoded compounds recently permitted the discovery of covalent ligands that selectively react with a particular cysteine residue. However, noncysteine residues remain underexplored as modification sites of covalent DELs. Herein, we report the design and utility of tyrosine-targeting DELs of 67 million compounds. Proteome-wide reactivity analysis of tyrosine-reactive sulfonyl fluoride (SF) covalent probes suggested three enzymes (phosphoglycerate mutase 1, glutathione s-transferase 1, and dipeptidyl peptidase 3) as models of tyrosine-targetable proteins. Enrichment with SF-functionalized DELs led to the identification of a series of tyrosine-targeting covalent inhibitors of the model enzymes. In-depth mechanistic investigation revealed their novel modes of action and reactive ligand-accessible hotspots of the enzymes. Our strategy of combining activity-based proteome profiling and covalent DEL enrichment (ABPP-CoDEL), which generated selective covalent binders against a variety of target proteins, illustrates the potential use of this methodology in further covalent drug discovery.

Reformulating Reactivity Design for Data-Efficient Machine Learning.

Machine learning (ML) can deliver rapid and accurate reaction barrier predictions for use in rational reactivity design. However, model training requires large data sets of typically thousands or tens of thousands of barriers that are very expensive to obtain computationally or experimentally. Furthermore, bespoke data sets are required for each region of interest in reaction space as models typically struggle to generalize. We have therefore reformulated the ML barrier prediction problem toward a much more data-efficient process: finding a reaction from a prespecified set with a desired target value. Our reformulation enables the rapid selection of reactions with purpose-specific activation barriers, for example, in the design of reactivity and selectivity in synthesis, catalyst design, toxicology, and covalent drug discovery, requiring just tens of accurately measured barriers. Importantly, our reformulation does not require generalization beyond the domain of the data set at hand, and we show excellent results for the highly toxicologically and synthetically relevant data sets of aza-Michael addition and transition-metal-catalyzed dihydrogen activation, typically requiring less than 20 accurately measured density functional theory (DFT) barriers. Even for incomplete data sets of E2 and SN2 reactions, with high numbers of missing barriers (74% and 56% respectively), our chosen ML search method still requires significantly fewer data points than the hundreds or thousands needed for more conventional uses of ML to predict activation barriers. Finally, we include a case study in which we use our process to guide the optimization of the dihydrogen activation catalyst. Our approach was able to identify a reaction within 1 kcal mol-1 of the target barrier by only having to run 12 DFT reaction barrier calculations, which illustrates the usage and real-world applicability of this reformulation for systems of high synthetic importance.

Assigning functionality to cysteines by base editing of cancer dependency genes.

Covalent chemistry represents an attractive strategy for expanding the ligandability of the proteome, and chemical proteomics has revealed numerous electrophile-reactive cysteines on diverse human proteins. Determining which of these covalent binding events affect protein function, however, remains challenging. Here we describe a base-editing strategy to infer the functionality of cysteines by quantifying the impact of their missense mutation on cancer cell proliferation. The resulting atlas, which covers more than 13,800 cysteines on more than 1,750 cancer dependency proteins, confirms the essentiality of cysteines targeted by covalent drugs and, when integrated with chemical proteomic data, identifies essential, ligandable cysteines in more than 160 cancer dependency proteins. We further show that a stereoselective and site-specific ligand targeting an essential cysteine in TOE1 inhibits the nuclease activity of this protein through an apparent allosteric mechanism. Our findings thus describe a versatile method and valuable resource to prioritize the pursuit of small-molecule probes with high function-perturbing potential.

Discovery of dihydropyridinone derivative as a covalent EZH2 degrader

EZH2 is overexpressed in multiple types of cancer and high expression level of EZH2 correlates with poor prognosis. Besides the regulation of H3K27 trimethylation, EZH2 itself regulates its downstream proteins in a PRC2- and methylation-independent way. Starting from an approved EZH2 inhibitor EPZ-6438, we used covalent drug design and medicinal chemistry approaches to discover a novel covalent EZH2 degrader 38, which forms a covalent bond with EZH2 Cys663 and showed strong biochemical activities against EZH2 WT and mutants. Compound 38 exhibited potent antiproliferation effects against both B-cell lymphoma and TNBC cell lines by reducing the levels of H3K27me3 and EZH2. The mass spectrometry, washout and competition experiments confirmed the covalent binding of 38 to EZH2. This study demonstrates that covalent EZH2 degraders could provide an opportunity for the development of promising new drug candidates.

Species-specific lipophilicities of fluorinated diketones in complex equilibria systems and their potential as multifaceted reversible covalent warheads

Combined molecular, physicochemical and chemical properties of electrophilic warheads can be applied to create covalent drugs with diverse facets. Here we study these properties in fluorinated diketones (FDKs) and their multicomponent equilibrium systems in the presence of protic nucleophiles, revealing the potential of the CF2(CO)2 group to act as a multifaceted warhead for reversible covalent drugs. The equilibria compositions of various FDKs in water/octanol contain up to nine species. A simultaneous direct species-specific 19F-NMR-based log P determination of these complex equilibria systems was achieved and revealed in some cases lipophilic to hydrophilic shifts, indicating possible adaptation to different environments. This was also demonstrated in 19F-MAS-NMR-based water-membrane partitioning measurements. An interpretation of the results is suggested by the aid of a DFT study and 19F-DOSY-NMR spectroscopy. In dilute solutions, a model FDK reacted with protected cysteine to form two hemi-thioketal regioisomers, indicating possible flexible regio-reactivity of CF2(CO)2 warheads toward cysteine residues.

An Innovative Approach to Address Neurodegenerative Diseases through Kinase-Targeted Therapies: Potential for Designing Covalent Inhibitors.

Owing to the dysregulation of protein kinase activity in various diseases such as cancer and autoimmune, cardiovascular, neurodegenerative, and inflammatory conditions, the protein kinase family has emerged as a crucial drug target in the 21st century. Notably, many kinases have been targeted to address cancer and neurodegenerative diseases using conventional ATP-mimicking kinase inhibitors. Likewise, irreversible covalent inhibitors have also been developed for different types of cancer. The application of covalent modification to target proteins has led to significant advancements in the treatment of cancer. However, while covalent drugs have significantly impacted medical treatment, their potential for neurodegenerative diseases remains largely unexplored. Neurodegenerative diseases present significant risks to brain function, leading to progressive deterioration in sensory, motor, and cognitive abilities. Alzheimer's disease (AD), Huntington's disease (HD), Parkinson's disease (PD), and multiple sclerosis (MS) are among the various examples of such disorders. Numerous research groups have already reported insights through reviews and research articles on FDA-approved covalent inhibitors, revealing their mechanisms and the specific covalent warheads that preferentially interact with particular amino acid residues in intricate detail. Hence, in this review, we aim to provide a concise summary of these critical topics. This summary endeavors to guide medicinal chemists in their quest to design covalent inhibitors for protein kinases, specifically targeting neurodegenerative diseases.

Synthesis of β,γ-Unsaturated Aliphatic Acids via Ligand-Enabled Dehydrogenation.

α,β-Dehydrogenation of aliphatic acids has been realized through both enolate and β-C-H metalation pathways. However, the synthesis of isolated β,γ-unsaturated aliphatic acids via dehydrogenation has not been achieved to date. Herein, we report the ligand-enabled β,γ-dehydrogenation of abundant and inexpensive free aliphatic acids, which provides a new synthetic disconnection as well as a versatile platform for the downstream functionalization of complex molecules at remote γ-sites. A variety of free aliphatic acids, including acyclic and cyclic systems with ring sizes from five-membered to macrocyclic, undergo efficient dehydrogenation. Notably, this protocol features good chemoselectivity in the presence of more accessible α-C-H bonds and excellent regioselectivity in fused bicyclic scaffolds. The utility of this protocol has been demonstrated by the late-stage functionalization of a series of bioactive terpene natural products at the γ-sites. Further functionalization of the β,γ-double bond allows for the installation of covalent warheads, including epoxides, aziridines, and β-lactones, into complex natural product scaffolds, which are valuable for targeted covalent drug discovery.

Making the Case for Quantum Mechanics in Predictive Toxicology─Nearly 100 Years Too Late?

The use of quantum mechanics (QM) has long been the norm to study covalent-binding phenomena in chemistry and biochemistry. The pharmaceutical industry leverages QM models explicitly in covalent drug discovery and implicitly to characterize short-range interactions in noncovalent binding. Predictive toxicology has resisted widespread adoption of QM, including in the pharmaceutical industry, despite its obvious relevance to the metabolic processes in the upstream of adverse outcome pathways and advances in both QM methods and computational resources, which support fit-for-purpose applications in reasonable timeframes. Here, we make the case for embracing QM as an indispensable part of a toxicologist's toolkit. We argue that QM provides the necessary orthogonality to alert-based expert systems and traditional QSARs, consistent with calls for animal-free integrated testing strategies for safety assessments of commercial chemicals. We outline existing roadblocks to this transition, including the need to train model developers in QM and the shift toward service-based toxicity models that utilize high-performance computing clusters. Lastly, we describe recent examples of successful implementations of QM in hazard assessments and propose how in silico toxicology can be further advanced by integrating QM with artificial intelligence.

Post‐Polymerization Modifications to Prepare Biomedical Nanocarriers with Varying Internal Structures, their Properties and Impact on Protein Corona Formation

AbstractThe reactive ester approach provides access to various types of drug delivery systems. Either amphiphilic block copolymer micelles with hydrophobic cores can be generated for encapsulation of hydrophobic drugs, or they are (reversibly) crosslinked by polar molecules into nano(hydro)gel particles affording hydrophilic cores and coronas. Beyond short oligonucleotides complexation or covalent drug conjugation inside the core, a surface functionalization with targeting units is further possible to address a large variety of drug delivery scenarios. Interestingly, the reactive ester approach can thereby not only govern the nanocarriers' inner structure and surface property, but at the same time also provide strategies to prevent protein corona formation. These features are summarized in this article and underline the concept of reactive ester macromolecules as beneficial tool for assisting in drug delivery.

P25-14: Hepatic safety assessment of covalent inhibitor drug candidates

P25-14: Hepatic safety assessment of covalent inhibitor drug candidates

Discovering covalent inhibitors of protein-protein interactions from trillions of sulfur(VI) fluoride exchange-modified oligonucleotides.

Molecules that covalently engage target proteins are widely used as activity-based probes and covalent drugs. The performance of these covalent inhibitors is, however, often compromised by the paradox of efficacy and risk, which demands a balance between reactivity and selectivity. The challenge is more evident when targeting protein-protein interactions owing to their low ligandability and undefined reactivity. Here we report sulfur(VI) fluoride exchange (SuFEx) in vitro selection, a general platform for high-throughput discovery of covalent inhibitors from trillions of SuFEx-modified oligonucleotides. With SuFEx in vitro selection, we identified covalent inhibitors that cross-link distinct residues of the SARS-CoV-2 spike protein at its protein-protein interaction interface with the human angiotensin-converting enzyme 2. A separate suite of covalent inhibitors was isolated for the human complement C5 protein. In both cases, we observed a clear disconnection between binding affinity and cross-linking reactivity, indicating that direct search for the aimed reactivity-as enabled by SuFEx in vitro selection-is vital for discovering covalent inhibitors of high selectivity and potency.

Insights into the Inhibitory Mechanisms of the Covalent Drugs for DNMT3A.

The perturbations of DNA methyltransferase 3 alpha (DNMT3A) may cause uncontrolled gene expression, resulting in cancers and tumors. The DNMT inhibitors Azacytidine (AZA) and Zebularine (ZEB) inhibit the DNMT family with no specificities, and consequently would bring side effects during the treatment. Therefore, it is vital to understand the inhibitory mechanisms in DNMT3A to inform the new inhibitor design for DNMTs. Herein, we carried out molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) simulations to investigate the inhibitory mechanisms of the AZA and ZEB. The results were compared to the methyl transfer of cytosine. We showed how the AZA might stop the methyl transfer process, whereas the ZEB might be stuck in a methyl-transferred intermediate (IM3). The IM3 state then fails the elimination due to the unique protein dynamics that result in missing the catalytic water chain. Our results brought atomic-level insights into the mechanisms of the two drugs in DNMT3A, which could benefit the new generation of drug design for the DNMTs.

DOX_BDW: Incorporating Solvation and Desolvation Effects of Cavity Water into Nonfitting Protein-Ligand Binding Affinity Prediction.

Accurate prediction of the protein-ligand binding affinity (PLBA) with an affordable cost is one of the ultimate goals in the field of structure-based drug design (SBDD), as well as a great challenge in the computational and theoretical chemistry. Herein, we have systematically addressed the complicated solvation and desolvation effects on the PLBA brought by the difference of the explicit water in the protein cavity before and after ligands bind to the protein-binding site. Based on the new solvation model, a nonfitting method at the first-principles level for the PLBA prediction was developed by taking the bridging and displaced water (BDW) molecules into account simultaneously. The newly developed method, DOX_BDW, was validated against a total of 765 noncovalent and covalent protein-ligand binding pairs, including the CASF2016 core set, Cov_2022 covalent binding testing set, and six testing sets for the hit and lead compound optimization (HLO) simulation. In all of the testing sets, the DOX_BDW method was able to produce PLBA predictions that were strongly correlated with the corresponding experimental data (R = 0.66-0.85). The overall performance of DOX_BDW is better than the current empirical scoring functions that are heavily parameterized. DOX_BDW is particularly outstanding for the covalent binding situation, implying the need for considering an electronic structure in covalent drug design. Furthermore, the method is especially recommended to be used in the HLO scenario of SBDD, where hundreds of similar derivatives need to be screened and refined. The computational cost of DOX_BDW is affordable, and its accuracy is remarkable.

Nexo launches for covalent oncology drugs

Nexo launches for covalent oncology drugs

Direct K-Ras Inhibitors to Treat Cancers: Progress, New Insights, and Approaches to Treat Resistance.

Here we discuss approaches to K-Ras inhibition and drug resistance scenarios. A breakthrough offered a covalent drug against K-RasG12C. Subsequent innovations harnessed same-allele drug combinations, as well as cotargeting K-RasG12C with a companion drug to upstream regulators or downstream kinases. However, primary, adaptive, and acquired resistance inevitably emerge. The preexisting mutation load can explain how even exceedingly rare mutations with unobservable effects can promote drug resistance, seeding growth of insensitive cell clones, and proliferation. Statistics confirm the expectation that most resistance-related mutations are in cis, pointing to the high probability of cooperative, same-allele effects. In addition to targeted Ras inhibitors and drug combinations, bifunctional molecules and innovative tri-complex inhibitors to target Ras mutants are also under development. Since the identities and potential contributions of preexisting and evolving mutations are unknown, selecting a pharmacologic combination is taxing. Collectively, our broad review outlines considerations and provides new insights into pharmacology and resistance.