An electrophilic warhead library for mapping the reactivity and accessibility of tractable cysteines in protein kinases

High-Throughput Discovery and Characterization of Covalent Inhibitors for Protein Tyrosine Phosphatases

Covalent inhibition has gained increasing interest in targeting the undruggable protein tyrosine phosphatases (PTPs). However, a systematic method for discovering and characterizing covalent PTP inhibitors has yet to be established. Here, we describe a workflow involving high-throughput screening of covalent fragment libraries and a novel biochemical assay that enables the acquisition of kinetics parameters of PTP inhibition by covalent inhibitors with higher throughput.

Target discovery of bioactive natural products with native-compound-coupled CNBr-activated Sepharose 4B beads (NCCB): Applications, mechanisms and outlooks

Natural products (NPs) represent a treasure trove for drug discovery and development due to their chemical structural diversity and a broad spectrum of biological activities. Uncovering the biological targets and understanding their molecular mechanism of actions are crucial steps in the development of clinical therapeutics. However, the structural complexity of NPs and intricate nature of biological system present formidable challenges in target identification of NPs. Although significant advances have been made in the development of new chemical tools, these methods often require high levels of synthetic skills for preparing chemical probes. This can be costly and time-consuming relaying on operationally complicated procedures and instruments. In recent efforts, we and others have successfully developed an operationally simple and practical chemical tool known as native-compound-coupled CNBr-activated Sepharose 4B beads (NCCB) for NP target identification. In this approach, a native compound readily reacts with commercial CNBr-activated Sepharose 4B beads with a process that is easily performed in any biology laboratory. Based on NCCB, our group has identified the direct targets of more than 60 NPs. In this review, we will elucidate the application scopes, including flavonoids, quinones, terpenoids and others, characteristics, chemical mechanisms, procedures, advantages, disadvantages, and future directions of NCCB in specific target discovery.

Nucleophilic covalent ligand discovery for the cysteine redoxome

With an eye toward expanding chemistries used for covalent ligand discovery, we elaborated an umpolung strategy that exploits the 'polarity reversal' of sulfur when cysteine is oxidized to sulfenic acid, a widespread post-translational modification, for selective bioconjugation with C-nucleophiles. Here we present a global map of a human sulfenome that is susceptible to covalent modification by members of a nucleophilic fragment library. More than 500 liganded sulfenic acids were identified on proteins across diverse functional classes, and, of these, more than 80% were not targeted by electrophilic fragment analogs. We further show that members of our nucleophilic fragment library can impair functional protein-protein interactions involved in nuclear oncoprotein transport and DNA damage repair. Our findings reveal a vast expanse of ligandable sulfenic acids in the human proteome and highlight the utility of nucleophilic small molecules in the fragment-based covalent ligand discovery pipeline, presaging further opportunities using non-traditional chemistries for targeting proteins.

Cytomegalovirus cyclin-dependent kinase ortholog vCDK/pUL97 undergoes regulatory interaction with human cyclin H and CDK7 to codetermine viral replication efficiency

Human cytomegalovirus (HCMV) infection is shaped by a tightly regulated interplay between viral and cellular proteins. Distinct kinase activities, such as the viral cyclin-dependent kinase ortholog (vCDK) pUL97 and cellular CDK7 are both crucial for efficient viral replication. Previously, we reported that both kinases, vCDK/pUL97 and CDK7, interact with cyclin H, thereby achieving an enhanced level of kinase activity and overall functionality in viral replication. Here we provide a variety of novel results, as generated on a methodologically extended basis, and present a concept for the codetermination of viral replication efficiency through these kinase activities: (i) cyclin H expression, in various human cell types, is substantially upregulated by strains of HCMV including the clinically relevant HCMV Merlin; (ii) vCDK/pUL97 interacts with human cyclin H in both HCMV-infected and plasmid-transfected cell systems; (iii) a doxycycline-inducible shRNA-dependent knock-down (KD) of cyclin H significantly reduces pUL97 activity (qSox in vitro kinase assay); (iv) accordingly, pUL97 in vitro kinase activity is seen significantly increased upon addition of recombinant cyclin H; (v) as a point of specific importance, human CDK7 activity shows an increase by vCDK/pUL97-mediated trans-stimulation (whereas pUL97 is not stimulated by CDK7); (vi) phosphosite-specific antibodies indicate an upregulated CDK7 phosphorylation upon HCMV infection, as mediated through a pUL97-specific modulatory effect (i.e. shown by pUL97 inhibitor treatment or pUL97-deficient viral mutant); (vii) finally, an efficient KD of cyclin H in primary fibroblasts generally results in an impaired HCMV replication efficiency as measured on protein and genomic levels. These results show evidence for the codetermination of viral replication by vCDK/pUL97, cyclin H and CDK7, thus supporting the specific importance of cyclin H as a central regulatory factor, and suggesting novel targeting options for antiviral drugs.

Integrated Covalent Drug Design Workflow Using Site Identification by Ligand Competitive Saturation

Covalent drug design is an important component in drug discovery. Traditional drugs interact with their target in a reversible equilibrium, while irreversible covalent drugs increase the drug-target interaction duration by forming a covalent bond with targeted residues and thus may offer a more effective therapeutic approach. To facilitate the design of this class of ligands, computational methods can be used to help identify reactive nucleophilic residues, frequently cysteines, on a target protein for covalent binding, to test various warhead groups for their potential reactivities, and to predict noncovalent contributions to binding that can facilitate drug-target interactions that are important for binding specificity. To further aid covalent drug design, we extended a functional group mapping approach based on explicit solvent all-atom molecular simulations (SILCS: site identification by ligand competitive saturation) that intrinsically considers protein flexibility, functional group, and protein desolvation along with functional group-protein interactions. Through docking of a library of representative warhead fragments using SILCS-Monte Carlo (SILCS-MC), reactive cysteines can be correctly identified for proteins being tested. Furthermore, a machine learning model was trained to quantify the effectiveness of various warhead groups for proteins using metrics from SILCS-MC as well as experimental model compound warhead reactivity data. The ability to rank covalent molecular binders with similar warheads using SILCS ligand grid free energy (LGFE) ranking was also tested for several proteins. Based on these tools, an integrated SILCS-based workflow was developed, named SILCS-Covalent, which can both qualitatively and quantitatively inform covalent drug discovery.

Assessment of Covalently Binding Warhead Compounds in the Validation of the Cytomegalovirus Nuclear Egress Complex as an Antiviral Target

Herpesviral nuclear egress is a regulated process of viral capsid nucleocytoplasmic release. Due to the large capsid size, a regular transport via the nuclear pores is unfeasible, so that a multistage-regulated export pathway through the nuclear lamina and both leaflets of the nuclear membrane has evolved. This process involves regulatory proteins, which support the local distortion of the nuclear envelope. For human cytomegalovirus (HCMV), the nuclear egress complex (NEC) is determined by the pUL50-pUL53 core that initiates multicomponent assembly with NEC-associated proteins and capsids. The transmembrane NEC protein pUL50 serves as a multi-interacting determinant that recruits regulatory proteins by direct and indirect contacts. The nucleoplasmic core NEC component pUL53 is strictly associated with pUL50 in a structurally defined hook-into-groove complex and is considered as the potential capsid-binding factor. Recently, we validated the concept of blocking the pUL50-pUL53 interaction by small molecules as well as cell-penetrating peptides or an overexpression of hook-like constructs, which can lead to a pronounced degree of antiviral activity. In this study, we extended this strategy by utilizing covalently binding warhead compounds, originally designed as binders of distinct cysteine residues in target proteins, such as regulatory kinases. Here, we addressed the possibility that warheads may likewise target viral NEC proteins, building on our previous crystallization-based structural analyses that revealed distinct cysteine residues in positions exposed from the hook-into-groove binding surface. To this end, the antiviral and NEC-binding properties of a selection of 21 warhead compounds were investigated. The combined findings are as follows: (i) warhead compounds exhibited a pronounced anti-HCMV potential in cell-culture-based infection models; (ii) computational analysis of NEC primary sequences and 3D structures revealed cysteine residues exposed to the hook-into-groove interaction surface; (iii) several of the active hit compounds exhibited NEC-blocking activity, as shown at the single-cell level by confocal imaging; (iv) the clinically approved warhead drug ibrutinib exerted a strong inhibitory impact on the pUL50-pUL53 core NEC interaction, as demonstrated by the NanoBiT assay system; and (v) the generation of recombinant HCMV ∆UL50-ΣUL53, allowing the assessment of viral replication under conditional expression of the viral core NEC proteins, was used for characterizing viral replication and a mechanistic evaluation of ibrutinib antiviral efficacy. Combined, the results point to a rate-limiting importance of the HCMV core NEC for viral replication and to the option of exploiting this determinant by the targeting of covalently NEC-binding warhead compounds.

"Magic Chloro": Profound Effects of the Chlorine Atom in Drug Discovery

Chlorine is one of the most common atoms present in small-molecule drugs beyond carbon, hydrogen, nitrogen, and oxygen. There are currently more than 250 FDA-approved chlorine-containing drugs, yet the beneficial effect of the chloro substituent has not yet been reviewed. The seemingly simple substitution of a hydrogen atom (R = H) with a chlorine atom (R = Cl) can result in remarkable improvements in potency of up to 100,000-fold and can lead to profound effects on pharmacokinetic parameters including clearance, half-life, and drug exposure in vivo. Following the literature terminology of the "magic methyl effect" in drugs, the term "magic chloro effect" has been coined herein. Although reports of 500-fold or 1000-fold potency improvements are often serendipitous discoveries that can be considered "magical" rather than planned, hypotheses made to explain the magic chloro effect can lead to lessons that accelerate the cycle of drug discovery.

HCovDock: an efficient docking method for modeling covalent protein-ligand interactions

Covalent inhibitors have received extensive attentions in the past few decades because of their long residence time, high binding efficiency and strong selectivity. Therefore, it is valuable to develop computational tools like molecular docking for modeling of covalent protein-ligand interactions or screening of potential covalent drugs. Meeting the needs, we have proposed HCovDock, an efficient docking algorithm for covalent protein-ligand interactions by integrating a ligand sampling method of incremental construction and a scoring function with covalent bond-based energy. Tested on a benchmark containing 207 diverse protein-ligand complexes, HCovDock exhibits a significantly better performance than seven other state-of-the-art covalent docking programs (AutoDock, Cov_DOX, CovDock, FITTED, GOLD, ICM-Pro and MOE). With the criterion of ligand root-mean-squared distance < 2.0 Å, HCovDock obtains a high success rate of 70.5% and 93.2% in reproducing experimentally observed structures for top 1 and top 10 predictions. In addition, HCovDock is also validated in virtual screening against 10 receptors of three proteins. HCovDock is computationally efficient and the average running time for docking a ligand is only 5 min with as fast as 1 sec for ligands with one rotatable bond and about 18 min for ligands with 23 rotational bonds. HCovDock can be freely assessed at http://huanglab.phys.hust.edu.cn/hcovdock/.

Advanced approaches of developing targeted covalent drugs

In recent years, the development of targeted covalent inhibitors has gained popularity around the world. Specific groups (electrophilic warheads) form irreversible bonds with the side chain of nucleophilic amino acid residues, thus changing the function of biological targets such as proteins. Since the first targeted covalent inhibitor was disclosed in the 1990s, great efforts have been made to develop covalent ligands from known reversible leads or drugs by addition of tolerated electrophilic warheads. However, high reactivity and "off-target" toxicity remain challenging issues. This review covers the concept of targeted covalent inhibition to diseases, discusses traditional and interdisciplinary strategies of cysteine-focused covalent drug discovery, and exhibits newly disclosed electrophilic warheads majorly targeting the cysteine residue. Successful applications to address the challenges of designing effective covalent drugs are also introduced.

Reactivity of Covalent Fragments and Their Role in Fragment Based Drug Discovery

Fragment based drug discovery has long been used for the identification of new ligands and interest in targeted covalent inhibitors has continued to grow in recent years, with high profile drugs such as osimertinib and sotorasib gaining FDA approval. It is therefore unsurprising that covalent fragment-based approaches have become popular and have recently led to the identification of novel targets and binding sites, as well as ligands for targets previously thought to be 'undruggable'. Understanding the properties of such covalent fragments is important, and characterizing and/or predicting reactivity can be highly useful. This review aims to discuss the requirements for an electrophilic fragment library and the importance of differing warhead reactivity. Successful case studies from the world of drug discovery are then be examined.

In Silico Drug Repositioning to Target the SARS-CoV-2 Main Protease as Covalent Inhibitors Employing a Combined Structure-Based Virtual Screening Strategy of Pharmacophore Models and Covalent Docking

The epidemic caused by the SARS-CoV-2 coronavirus, which has spread rapidly throughout the world, requires urgent and effective treatments considering that the appearance of viral variants limits the efficacy of vaccines. The main protease of SARS-CoV-2 (M^pro) is a highly conserved cysteine proteinase, fundamental for the replication of the coronavirus and with a specific cleavage mechanism that positions it as an attractive therapeutic target for the proposal of irreversible inhibitors. A structure-based strategy combining 3D pharmacophoric modeling, virtual screening, and covalent docking was employed to identify the interactions required for molecular recognition, as well as the spatial orientation of the electrophilic warhead, of various drugs, to achieve a covalent interaction with Cys145 of M^pro. The virtual screening on the structure-based pharmacophoric map of the SARS-CoV-2 M^pro in complex with an inhibitor N3 (reference compound) provided high efficiency by identifying 53 drugs (FDA and DrugBank databases) with probabilities of covalent binding, including N3 (Michael acceptor) and others with a variety of electrophilic warheads. Adding the energy contributions of affinity for non-covalent and covalent docking, 16 promising drugs were obtained. Our findings suggest that the FDA-approved drugs Vaborbactam, Cimetidine, Ixazomib, Scopolamine, and Bicalutamide, as well as the other investigational peptide-like drugs (DB04234, DB03456, DB07224, DB7252, and CMX-2043) are potential covalent inhibitors of SARS-CoV-2 M^pro.

Docking Ligands into Flexible and Solvated Macromolecules. 8. Forming New Bonds─Challenges and Opportunities

Over the years, structure-based design programs and specifically docking small molecules to proteins have become prominent in drug discovery. However, many of these computational tools have been developed to primarily dock enzyme inhibitors (and ligands to other protein classes) relying heavily on hydrogen bonds and electrostatic and hydrophobic interactions. In reality, many drug targets either feature metal ions, can be targeted covalently, or are simply not even proteins (e.g., nucleic acids). Herein, we describe several new features that we have implemented into Fitted to broaden its applicability to a wide range of covalent enzyme inhibitors and to metalloenzymes, where metal coordination is essential for drug binding. This updated version of our docking program was tested for its ability to predict the correct binding mode of drug-sized molecules in a large variety of proteins. We also report new datasets that were essential to demonstrate areas of success and those where additional efforts are required. This resource could be used by other program developers to assess their own software.

Electrophilic warheads in covalent drug discovery: an overview

INTRODUCTION

Covalent drugs have been used for more than hundred years, but gathered larger interest in the last two decades. There are currently over a 100 different electrophilic warheads used in covalent ligands, and there are several considerations tailoring their reactivity against the target of interest, which is still a challenging task.

AREAS COVERED

This review aims to give an overview of electrophilic warheads used for protein labeling in chemical biology and medicinal chemistry. The warheads are discussed by targeted residues, mechanism and selectivity, and analyzed through three different datasets including our collection of warheads, the CovPDB database, and the FDA approved covalent drugs. Moreover, the authors summarize general practices that facilitate the selection of the appropriate warhead for the target of interest.

EXPERT OPINION

In spite of the numerous electrophilic warheads, only a fraction of them is used in current drug discovery projects. Recent studies identified new tractable residues by applying a wider array of warhead chemistries. However, versatile, selective warheads are not available for all targetable amino acids, hence discovery of new warheads for these residues is needed. Broadening the toolbox of the warheads could result in novel inhibitors even for challenging targets developing with significant therapeutic potential.

Design, synthesis and in vitro evaluation of novel SARS-CoV-2 3CLpro covalent inhibitors

Severe diseases such as the ongoing COVID-19 pandemic, as well as the previous SARS and MERS outbreaks, are the result of coronavirus infections and have demonstrated the urgent need for antiviral drugs to combat these deadly viruses. Due to its essential role in viral replication and function, 3CL^pro (main coronaviruses cysteine-protease) has been identified as a promising target for the development of antiviral drugs. Previously reported SARS-CoV 3CL^pro non-covalent inhibitors were used as a starting point for the development of covalent inhibitors of SARS-CoV-2 3CL^pro. We report herein our efforts in the design and synthesis of submicromolar covalent inhibitors when the enzymatic activity of the viral protease was used as a screening platform.

Consensus Virtual Screening Identified [1,2,4]Triazolo[1,5-b]isoquinolines As MELK Inhibitor Chemotypes

Maternal Embryonic Leucine‐zipper Kinase (MELK) is a current oncotarget involved in a diverse range of human cancers, with the usage of MELK inhibitors being explored clinically. Here, we aimed to discover new MELK inhibitor chemotypes from our in‐house compound library with a consensus‐based virtual screening workflow, employing three screening concepts. After careful retrospective validation, prospective screening and in vitro enzyme inhibition testing revealed a series of [1,2,4]triazolo[1,5‐b]isoquinolines as a new structural class of MELK inhibitors, with the lead compound of the series exhibiting a sub‐micromolar inhibitory activity. The structure‐activity relationship of the series was explored by testing further analogs based on a structure‐guided selection process. Importantly, the present work marks the first disclosure of the synthesis and bioactivity of this class of compounds.

Prerequisite Binding Modes Determine the Dynamics of Action of Covalent Agonists of Ion Channel TRPA1

Transient receptor potential ankyrin 1 (TRPA1) is a transmembrane protein channeling the influx of calcium ions. As a polymodal nocisensor, TRPA1 can be activated by thermal, mechanical stimuli and a wide range of chemically damaging molecules including small volatile environmental toxicants and endogenous algogenic lipids. After activation by such compounds, the ion channel opens up, its central pore widens allowing calcium influx into the cytosol inducing signal transduction pathways. Afterwards, the calcium influx desensitizes irritant evoked responses and results in an inactive state of the ion channel. Recent experimental determination of structures of apo and holo forms of TRPA1 opened the way towards the design of new agonists, which can activate the ion channel. The present study is aimed at the elucidation of binding dynamics of agonists using experimental structures of TRPA1-agonist complexes at the atomic level applying molecular docking and dynamics methods accounting for covalent and non-covalent interactions. Following a test of docking methods focused on the final, holo structures, prerequisite binding modes were detected involving the apo forms. It was shown how reversible interactions with prerequisite binding sites contribute to structural changes of TRPA1 leading to covalent bonding of agonists. The proposed dynamics of action allowed a mechanism-based forecast of new, druggable binding sites of potent agonists.

Searching Geometric Patterns in Protein Binding Sites and Their Application to Data Mining in Protein Kinase Structures

The ever-growing number of protein-ligand complex structures can give fundamental insights into protein functions and protein-ligand interactions, especially in the field of protein kinase research. The number of tools to mine this data for individually defined structural motifs is restricted due to the challenging task of developing efficient index structures for 3D data in relational databases. Herein we present GeoMine, a database system with web front-end mining of more than 900 000 binding sites. It enables database searches for geometric (interaction) patterns in protein-ligand interfaces by, for example, textual, numerical, substructure, similarity, and 3D searches. GeoMine processes reasonably selective user-defined queries within minutes. We demonstrate its usability for advancing protein kinase research with a special emphasis on unusual interactions, their use in designing selective kinase inhibitors, and the analysis of reactive cysteine residues that are amenable to covalent kinase inhibitors. GeoMine is freely available as part of our modeling support server at https://proteins.plus.

Chemical Probes for Understudied Kinases: Challenges and Opportunities

Over 20 years after the approval of the first-in-class protein kinase inhibitor imatinib, the biological function of a significant fraction of the human kinome remains poorly understood while most research continues to be focused on few well-validated targets. Given the strong genetic evidence for involvement of many kinases in health and disease, the understudied fraction of the kinome holds a large and unexplored potential for future therapies. Specific chemical probes are indispensable tools to interrogate biology enabling proper preclinical validation of novel kinase targets. In this Perspective, we highlight recent case studies illustrating the development of high-quality chemical probes for less-studied kinases and their application in target validation. We spotlight emerging techniques and approaches employed in the generation of chemical probes for protein kinases and beyond and discuss the associated challenges and opportunities.

Extended many-item similarity indices for sets of nucleotide and protein sequences

Quantification of similarities between protein sequences or DNA/RNA strands is a (sub-)task that is ubiquitously present in bioinformatics workflows, and is usually accomplished by pairwise comparisons of sequences, utilizing simple (e.g. percent identity) or more intricate concepts (e.g. substitution scoring matrices). Complex tasks (such as clustering) rely on a large number of pairwise comparisons under the hood, instead of a direct quantification of set similarities. Based on our recently introduced framework that enables multiple comparisons of binary molecular fingerprints (i.e., direct calculation of the similarity of fingerprint sets), here we introduce novel symmetric similarity indices for analogous calculations on sets of character sequences with more than two (t) possible items (e.g. DNA/RNA sequences with t = 4, or protein sequences with t = 20). The features of these new indices are studied in detail with analysis of variance (ANOVA), and demonstrated with three case studies of protein/DNA sequences with varying degrees of similarity (or evolutionary proximity). The Python code for the extended many-item similarity indices is publicly available at: https://github.com/ramirandaq/tn_Comparisons.

Extended similarity indices: the benefits of comparing more than two objects simultaneously. Part 2: speed, consistency, diversity selection

Despite being a central concept in cheminformatics, molecular similarity has so far been limited to the simultaneous comparison of only two molecules at a time and using one index, generally the Tanimoto coefficent. In a recent contribution we have not only introduced a complete mathematical framework for extended similarity calculations, (i.e. comparisons of more than two molecules at a time) but defined a series of novel idices. Part 1 is a detailed analysis of the effects of various parameters on the similarity values calculated by the extended formulas. Their features were revealed by sum of ranking differences and ANOVA. Here, in addition to characterizing several important aspects of the newly introduced similarity metrics, we will highlight their applicability and utility in real-life scenarios using datasets with popular molecular fingerprints. Remarkably, for large datasets, the use of extended similarity measures provides an unprecedented speed-up over “traditional” pairwise similarity matrix calculations. We also provide illustrative examples of a more direct algorithm based on the extended Tanimoto similarity to select diverse compound sets, resulting in much higher levels of diversity than traditional approaches. We discuss the inner and outer consistency of our indices, which are key in practical applications, showing whether the n-ary and binary indices rank the data in the same way. We demonstrate the use of the new n-ary similarity metrics on t-distributed stochastic neighbor embedding (t-SNE) plots of datasets of varying diversity, or corresponding to ligands of different pharmaceutical targets, which show that our indices provide a better measure of set compactness than standard binary measures. We also present a conceptual example of the applicability of our indices in agglomerative hierarchical algorithms. The Python code for calculating the extended similarity metrics is freely available at: https://github.com/ramirandaq/MultipleComparisons

Targeting Epigenetic Regulators with Covalent Small-Molecule Inhibitors

Epigenetic regulation of gene expression plays a critical role in various physiological processes, and epigenetic dysregulation is implicated in a number of diseases, prominently including cancer. Epigenetic regulators have been validated as potential therapeutic targets, and significant progress has been made in the discovery and development of epigenetic-based inhibitors. However, successful epigenetic drug discovery is still facing challenges, including moderate selectivity, limited efficacy, and acquired drug resistance. Inspired by the advantages of covalent small-molecule inhibitors, targeted covalent inhibition has attracted increasing interest in epigenetic drug discovery. In this review, we comprehensively summarize the structure-based design and characterization of covalent inhibitors targeting epigenetic writers, readers, and erasers and highlight their potential benefits in enhancing selectivity across the enzyme family and improving in vivo efficacy. We also discuss the challenges and opportunities of covalent small-molecule inhibitors and hope to shed light on future epigenetic drug discovery.

Fragment-based covalent ligand discovery

Targeted covalent inhibitors have regained widespread attention in drug discovery and have emerged as powerful tools for basic biomedical research. Fueled by considerable improvements in mass spectrometry sensitivity and sample processing, chemoproteomic strategies have revealed thousands of proteins that can be covalently modified by reactive small molecules. Fragment-based drug discovery, which has traditionally been used in a target-centric fashion, is now being deployed on a proteome-wide scale thereby expanding its utility to both the discovery of novel covalent ligands and their cognate protein targets. This powerful approach is allowing ‘high-throughput’ serendipitous discovery of cryptic pockets leading to the identification of pharmacological modulators of proteins previously viewed as “undruggable”. The reactive fragment toolkit has been enabled by recent advances in the development of new chemistries that target residues other than cysteine including lysine and tyrosine. Here, we review the emerging area of covalent fragment-based ligand discovery, which integrates the benefits of covalent targeting and fragment-based medicinal chemistry. We discuss how the two strategies synergize to facilitate the efficient discovery of new pharmacological modulators of established and new therapeutic target proteins.

Covalent fragment-based ligand discovery greatly facilitates the discovery of useful fragments for drug discovery and helps unveil chemical-tractable biological targets in native biological systems.