Covalent inhibitors design and discovery

Kinase inhibitors: 20 years of success and many new challenges and recent trends in their patents

INTRODUCTION

Protein kinases (PKs) play key roles in cellular signaling and regulation cascades and therefore are listed among the most investigated enzymes with the intent to develop drugs that are able to modulate their catalytic features. Specifically, PKs are involved in chronic diseases of large impact in the society such as cancers and neurodegeneration. Since the approval of Fasudil for the management of cerebral vasospasm, frantic efforts are currently ongoing for the development of selective PK-modulating agents.

AREAS COVERED

A selection of the most relevant patents in the European Patent Office for biomedical innovation and/or industrial development covering the years 2020-2023 on PK modulators either of the antibody and small-molecule type is reported. In addition to the examined patents, we also reported the contributions claiming the use of antibody-targeted PKs for lab bench identification kits.

EXPERT OPINION

The field of PK modulators for biomedical purposes is particularly crowded with contributions, making it rich in valuable information for the development of potential drugs. An emerging frontier is represented by PK activators that aims to complement the use of PK inhibitors with the final intent of finely adjusting any PK-related disruption responsible for triggering any disease.

Exploring the binding dynamics of covalent inhibitors within active site of PLpro in SARS-CoV-2

In the global fight against the COVID-19 pandemic caused by the highly transmissible SARS-CoV-2 virus, the search for potent medications is paramount. With a focused investigation on the SARS-CoV-2 papain-like protease (PLpro) as a promising therapeutic target due to its pivotal role in viral replication and immune modulation, the catalytic triad of PLpro comprising Cys111, His272, and Asp286, highlights Cys111 as an intriguing nucleophilic center for potential covalent bonds with ligands. The detailed analysis of the binding site unveils crucial interactions with both hydrophobic and polar residues, demonstrating the structural insights of the cavity and deepening our understanding of its molecular landscape. The sequence of PLpro among variants of concern (Alpha, Beta, Gamma, Delta and Omicron) and the recent variant of interest, JN.1, remains conserved with no mutations at the active site. Moreover, a thorough exploration of apo, non-covalently bound, and covalently bound PLpro conformations exposes significant conformational changes in loop regions, offering invaluable insights into the intricate dynamics of ligand-protein complex formation. Employing strategic in silico medication repurposing, this study swiftly identifies potential molecules for target inhibition. Within the domain of covalent docking studies and molecular dynamics, using reported inhibitors and clinically tested molecules elucidate the formation of stable covalent bonds with the cysteine residue, laying a robust foundation for potential therapeutic applications. These details not only deepen our comprehension of PLpro inhibition but also play a pivotal role in shaping the dynamic landscape of COVID-19 treatment strategies.

Covalent targeted radioligands potentiate radionuclide therapy

Targeted radionuclide therapy, in which radiopharmaceuticals deliver potent radionuclides to tumours for localized irradiation, has addressed unmet clinical needs and improved outcomes for patients with cancer1-4. A therapeutic radiopharmaceutical must achieve both sustainable tumour targeting and fast clearance from healthy tissue, which remains a major challenge5,6. A targeted ligation strategy that selectively fixes the radiopharmaceutical to the target protein in the tumour would be an ideal solution. Here we installed a sulfur (VI) fluoride exchange (SuFEx) chemistry-based linker on radiopharmaceuticals to prevent excessively fast tumour clearance. When the engineered radiopharmaceutical binds to the tumour-specific protein, the system undergoes a binding-to-ligation transition and readily conjugates to the tyrosine residues through the 'click' SuFEx reaction. The application of this strategy to a fibroblast activation protein (FAP) inhibitor (FAPI) triggered more than 80% covalent binding to the protein and almost no dissociation for six days. In mice, SuFEx-engineered FAPI showed 257% greater tumour uptake than did the original FAPI, and increased tumour retention by 13-fold. The uptake in healthy tissues was rapidly cleared. In a pilot imaging study, this strategy identified more tumour lesions in patients with cancer than did other methods. SuFEx-engineered FAPI also successfully achieved targeted β- and α-radionuclide therapy, causing nearly complete tumour regression in mice. Another SuFEx-engineered radioligand that targets prostate-specific membrane antigen (PSMA) also showed enhanced therapeutic efficacy. Considering the broad scope of proteins that can potentially be ligated to SuFEx warheads, it might be possible to adapt this strategy to other cancer targets.

Reactivities of acrylamide warheads toward cysteine targets: a QM/ML approach to covalent inhibitor design

Covalent inhibition offers many advantages over non-covalent inhibition, but covalent warhead reactivity must be carefully balanced to maintain potency while avoiding unwanted side effects. While warhead reactivities are commonly measured with assays, a computational model to predict warhead reactivities could be useful for several aspects of the covalent inhibitor design process. Studies have shown correlations between covalent warhead reactivities and quantum mechanic (QM) properties that describe important aspects of the covalent reaction mechanism. However, the models from these studies are often linear regression equations and can have limitations associated with their usage. Applications of machine learning (ML) models to predict covalent warhead reactivities with QM descriptors are not extensively seen in the literature. This study uses QM descriptors, calculated at different levels of theory, to train ML models to predict reactivities of covalent acrylamide warheads. The QM/ML models are compared with linear regression models built upon the same QM descriptors and with ML models trained on structure-based features like Morgan fingerprints and RDKit descriptors. Experiments show that the QM/ML models outperform the linear regression models and the structure-based ML models, and literature test sets demonstrate the power of the QM/ML models to predict reactivities of unseen acrylamide warhead scaffolds. Ultimately, these QM/ML models are effective, computationally feasible tools that can expedite the design of new covalent inhibitors.

Time-series analysis of rhenium(I) organometallic covalent binding to a model protein for drug development

Metal-based complexes with their unique chemical properties, including multiple oxidation states, radio-nuclear capabilities and various coordination geometries yield value as potential pharmaceuticals. Understanding the interactions between metals and biological systems will prove key for site-specific coordination of new metal-based lead compounds. This study merges the concepts of target coordination with fragment-based drug methodologies, supported by varying the anomalous scattering of rhenium along with infrared spectroscopy, and has identified rhenium metal sites bound covalently with two amino acid types within the model protein. A time-based series of lysozyme-rhenium-imidazole (HEWL-Re-Imi) crystals was analysed systematically over a span of 38 weeks. The main rhenium covalent coordination is observed at His15, Asp101 and Asp119. Weak (i.e. noncovalent) interactions are observed at other aspartic, asparagine, proline, tyrosine and tryptophan side chains. Detailed bond distance comparisons, including precision estimates, are reported, utilizing the diffraction precision index supplemented with small-molecule data from the Cambridge Structural Database. Key findings include changes in the protein structure induced at the rhenium metal binding site, not observed in similar metal-free structures. The binding sites are typically found along the solvent-channel-accessible protein surface. The three primary covalent metal binding sites are consistent throughout the time series, whereas binding to neighbouring amino acid residues changes through the time series. Co-crystallization was used, consistently yielding crystals four days after setup. After crystal formation, soaking of the compound into the crystal over 38 weeks is continued and explains these structural adjustments. It is the covalent bond stability at the three sites, their proximity to the solvent channel and the movement of residues to accommodate the metal that are important, and may prove useful for future radiopharmaceutical development including target modification.

Reversible Covalent Inhibition─Desired Covalent Adduct Formation by Mass Action

Covalent inhibition has seen a resurgence in the last several years. Although long-plagued by concerns of off-target effects due to nonspecific reactions leading to covalent adducts, there has been success in developing covalent inhibitors, especially within the field of anticancer therapy. Covalent inhibitors can have an advantage over noncovalent inhibitors since the formation of a covalent adduct may serve as an additional mode of selectivity due to the intrinsic reactivity of the target protein that is absent in many other proteins. Unfortunately, many covalent inhibitors form irreversible adducts with off-target proteins, which can lead to considerable side-effects. By designing the inhibitor to form reversible covalent adducts, one can leverage competing on/off kinetics in complex formation by taking advantage of the law of mass action. Although covalent adducts do form with off-target proteins, the reversible nature of inhibition prevents accumulation of the off-target adduct, thus limiting side-effects. In this perspective, we outline important characteristics of reversible covalent inhibitors, including examples and a guide for inhibitor development.

Molecular Insights into the Impact of Mutations on the Binding Affinity of Targeted Covalent Inhibitors of BTK

Targeted covalent inhibitors (TCIs) have witnessed a significant resurgence in recent years, particularly in the kinase drug discovery field for treating diverse clinical indications. The inhibition of Bruton's tyrosine kinase (BTK) for treating B-cell cancers is a classic example where TCIs such as ibrutinib have had breakthroughs in targeted therapy. However, selectivity remains challenging, and the emergence of resistance mutations is a critical concern for clinical efficacy. Computational methods that can accurately predict the impact of mutations on inhibitor binding affinity could prove helpful in informing targeted approaches─providing insights into drug resistance mechanisms. In addition, such systems could help guide the systematic evaluation and impact of mutations in disease models for optimal experimental design. Here, we have employed in silico physics-based methods to understand the effects of mutations on the binding affinity and conformational dynamics of select TCIs of BTK. The TCIs studied include ibrutinib, acalabrutinib, and zanubrutinib─all of which are FDA-approved drugs for treating multiple forms of leukemia and lymphoma. Our results offer useful molecular insights into the structural determinants, thermodynamics, and conformational energies that impact ligand binding for this biological target of clinical relevance.

Profiling nuclear cysteine ligandability and effects on nuclear localization using proximity labeling-coupled chemoproteomics

The nucleus controls cell growth and division through coordinated interactions between nuclear proteins and chromatin. Mutations that impair nuclear protein association with chromatin are implicated in numerous diseases. Covalent ligands are a promising strategy to pharmacologically target nuclear proteins, such as transcription factors, which lack ordered small-molecule binding pockets. To identify nuclear cysteines that are susceptible to covalent liganding, we couple proximity labeling (PL), using a histone H3.3-TurboID (His-TID) construct, with chemoproteomics. Using covalent scout fragments, KB02 and KB05, we identified ligandable cysteines on proteins involved in spindle assembly, DNA repair, and transcriptional regulation, such as Cys101 of histone acetyltransferase 1 (HAT1). Furthermore, we show that covalent fragments can affect the abundance, localization, and chromatin association of nuclear proteins. Notably, the Parkinson disease protein 7 (PARK7) showed increased nuclear localization and chromatin association upon KB02 modification at Cys106. Together, this platform provides insights into targeting nuclear cysteines with covalent ligands.

Constructing Innovative Covalent and Noncovalent Compound Libraries: Insights from 3D Protein-Ligand Interactions

Noncovalent interactions between small-molecule drugs and protein targets assume a pivotal role in drug design. Moreover, the design of covalent inhibitors, forming covalent bonds with amino acid residues, requires rational reactivity for their covalent warheads, presenting a key challenge as well. Understanding the intricacies of these interactions provides a more comprehensive understanding of molecular binding mechanisms, thereby guiding the rational design of potent inhibitors. In this study, we adopted the fragment-based drug design approach, introducing a novel methodology to extract noncovalent and covalent fragments according to distinct three-dimensional (3D) interaction modes from noncovalent and covalent compound libraries. Additionally, we systematically replaced existing ligands with rational fragment substitutions, based on the spatial orientation of fragments in 3D space. Furthermore, we adopted a molecular generation approach to create innovative covalent inhibitors. This process resulted in the recombination of a noncovalent compound library and several covalent compound libraries, constructed by two commonly encountered covalent amino acids: cysteine and serine. We utilized noncovalent ligands in KLIFS and covalent ligands in CovBinderInPDB as examples to recombine noncovalent and covalent libraries. These recombined compound libraries cover a substantial portion of the chemical space present in the original compound libraries and exhibit superior performance in terms of molecular scaffold diversity compared to the original compound libraries and other 11 commercial libraries. We also recombined BTK-focused libraries, and 23 compounds within our libraries have been validated by former researchers to possess potential biological activity. The establishment of these compound libraries provides valuable resources for virtual screening of covalent and noncovalent drugs targeting similar molecular targets.

Discovery of a septin-4 covalent binder with antimetastatic activity in a mouse model of melanoma

Cancer spreading through metastatic processes is one of the major causes of tumour-related mortality. Metastasis is a complex phenomenon which involves multiple pathways ranging from cell metabolic alterations to changes in the biophysical phenotype of cells and tissues. In the search for new effective anti-metastatic agents, we modulated the chemical structure of the lead compound AA6, in order to find the structural determinants of activity, and to identify the cellular target responsible of the downstream anti-metastatic effects observed. New compounds synthesized were able to inhibit in vitro B16-F10 melanoma cell invasiveness, and one selected compound, CM365, showed in vivo anti-metastatic effects in a lung metastasis mouse model of melanoma. Septin-4 was identified as the most likely molecular target responsible for these effects. This study showed that CM365 is a promising molecule for metastasis prevention, remarkably effective alone or co-administered with drugs normally used in cancer therapy, such as paclitaxel.

Covalent inhibitors: An ambitious approach for the discovery of newer oncotherapeutics

Covalent inhibitors have been used to treat several diseases for over a century. However, strategic approaches for the rational design of covalent drugs have taken a definitive shape in recent times. Since the first appearance of covalent inhibitors in the late 18th century, the field has grown tremendously and around 30% of marketed drugs are covalent inhibitors especially, for oncology indications. However, the off-target toxicity and safety concerns can be significant issues related to the covalent drugs. Covalent kinase inhibitor (CKI) targeted oncotherapeutics has advanced dramatically over the last two decades since the discovery of afatinib (Gilotrif®), an EGFR inhibitor. Since then, US FDA has approved 10 CKIs for diverse cancer targets. The present review broadly summarizes the ongoing development in the discovery of newer CKIs from 2016 till the end of 2022. We believe that these efforts will assist the modern medicinal chemist actively working in the field of CKI discovery for varied indications.

Covalent drugs based on small molecules and peptides for disease theranostics

Biomacromolecules, such as proteins, nucleic acids and polysaccharides, are widely distributed in the human body, and some of them have been recognized as the targets of drugs for disease theranostics. Drugs typically act on targets in two ways: non-covalent bond and covalent bond. Non-covalent bond-based drugs have some disadvantages, such as structural instability and environmental sensitivity. Covalent interactions between drugs and targets have a longer action time, higher affinity and controllability than non-covalent interactions of conventional drugs. With the development of artificial intelligence, covalent drugs have received more attention and have been developed rapidly in pharmaceutical research in recent years. From the perspective of covalent drugs, this review summarizes the design methods and the effects of covalent drugs. Finally, we discuss the application of covalent peptide drugs and expect to provide a new reference for cancer treatment.

Ligand-Based Design of Selective Peptidomimetic uPA and TMPRSS2 Inhibitors with Arg Bioisosteres

Trypsin-like serine proteases are involved in many important physiological processes like blood coagulation and remodeling of the extracellular matrix. On the other hand, they are also associated with pathological conditions. The urokinase-pwlasminogen activator (uPA), which is involved in tissue remodeling, can increase the metastatic behavior of various cancer types when overexpressed and dysregulated. Another member of this protease class that received attention during the SARS-CoV 2 pandemic is TMPRSS2. It is a transmembrane serine protease, which enables cell entry of the coronavirus by processing its spike protein. A variety of different inhibitors have been published against both proteases. However, the selectivity over other trypsin-like serine proteases remains a major challenge. In the current study, we replaced the arginine moiety at the P1 site of peptidomimetic inhibitors with different bioisosteres. Enzyme inhibition studies revealed that the phenylguanidine moiety in the P1 site led to strong affinity for TMPRSS2, whereas the cyclohexylguanidine derivate potently inhibited uPA. Both inhibitors exhibited high selectivity over other structurally similar and physiologically important proteases.

Synthesis and Biological Evaluation of Oxindole Sulfonamide Derivatives as Bruton's Tyrosine Kinase Inhibitors

Bruton's tyrosine kinase (BTK) is a promising molecular target for several human B-cell-related autoimmune disorders, inflammation, and haematological malignancies. The pathogenic alterations in various cancer tissues depend on mutant BTK for cell proliferation and survival, and BTK is also overexpressed in a range of hematopoietic cells. Due to this, BTK is emerging as a potential drug target to treat various human diseases, and several reversible and irreversible inhibitors have been developed and are being developed. As a result, BTK inhibition, clinically validated as an anticancer treatment, is finding great interest in B-cell malignancies and solid tumours. This study focuses on the design and synthesis of new oxindole sulfonamide derivatives as promising inhibitors of BTK with negligible off-target effects. The most cytotoxic compounds with greater basicity were PID-4 (2.29±0.52 μM), PID-6 (9.37±2.47 μM), and PID-19 (2.64±0.88 μM). These compounds caused a selective inhibition of Burkitt's lymphoma RAMOS cells without significant cytotoxicity in non-BTK cancerous and non-cancerous cell lines. Further, PID-4 showed promising activity in inhibiting BTK and downstream signalling cascades. As a potent inhibitor of Burkitt's lymphoma cells, PID-4 is a promising lead for developing novel chemotherapeutics.

Two-Step Covalent Docking with Attracting Cavities

Due to their various advantages, interest in the development of covalent drugs has been renewed in the past few years. It is therefore important to accurately describe and predict their interactions with biological targets by computer-aided drug design tools such as docking algorithms. Here, we report a covalent docking procedure for our in-house docking code Attracting Cavities (AC), which mimics the two-step mechanism of covalent ligand binding. Ligand binding to the protein cavity is driven by nonbonded interactions, followed by the formation of a covalent bond between the ligand and the protein through a chemical reaction. To test the performance of this method, we developed a diverse, high-quality, openly accessible re-docking benchmark set of 95 covalent complexes bound by 8 chemical reactions to 5 different reactive amino acids. Combination with structures from previous studies resulted in a set of 304 complexes, on which AC obtained a success rate (rmsd ≤ 2 Å) of 78%, outperforming two state-of-the-art covalent docking codes, genetic optimization for ligand docking (GOLD (66%)) and AutoDock (AD (35%)). Using a more stringent success criterion (rmsd ≤ 1.5 Å), AC reached a success rate of 71 vs 55% for GOLD and 26% for AD. We additionally assessed the cross-docking performance of AC on a set of 76 covalent complexes of the SARS-CoV-2 main protease. On this challenging test set of mainly small and highly solvent-exposed ligands, AC yielded success rates of 58 and 28% for re-docking and cross-docking, respectively, compared to 45 and 17% for GOLD.

Development of HC-258, a Covalent Acrylamide TEAD Inhibitor That Reduces Gene Expression and Cell Migration

The transcription factor YAP-TEAD is the downstream effector of the Hippo pathway which controls cell proliferation, apoptosis, tissue repair, and organ growth. Dysregulation of the Hippo pathway has been correlated with carcinogenic processes. A co-crystal structure of TEAD with its endogenous ligand palmitic acid (PA) as well as with flufenamic acid (FA) has been disclosed. Here we report the development of HC-258, which derives from FA and possesses an oxopentyl chain that mimics a molecule of PA as well as an acrylamide that reacts covalently with TEAD's cysteine. HC-258 reduces the CTGF, CYR61, AXL, and NF2 transcript levels and inhibits the migration of MDA-MB-231 breast cancer cells. Co-crystallization with hTEAD2 confirmed that HC-258 binds within TEAD's PA pocket, where it forms a covalent bond with its cysteine.

The expanding repertoire of covalent warheads for drug discovery

The reactive functionalities of drugs that engage in covalent interactions with the enzyme/receptor residue in either a reversible or an irreversible manner are called 'warheads'. Covalent warheads that were previously neglected because of safety concerns have recently gained center stage as a result of their various advantages over noncovalent drugs, including increased selectivity, increased residence time, and higher potency. With the approval of several covalent inhibitors over the past decade, research in this area has accelerated. Various strategies are being continuously developed to tune the characteristics of warheads to improve their potency and mitigate toxicity. Here, we review research progress in warhead discovery over the past 5 years to provide valuable insights for future drug discovery.

Emerging drug design strategies in anti-influenza drug discovery

Influenza is an acute respiratory infection caused by influenza viruses (IFV), According to the World Health Organization (WHO), seasonal IFV epidemics result in approximately 3-5 million cases of severe illness, leading to about half a million deaths worldwide, along with severe economic losses and social burdens. Unfortunately, frequent mutations in IFV lead to a certain lag in vaccine development as well as resistance to existing antiviral drugs. Therefore, it is of great importance to develop anti-IFV drugs with high efficiency against wild-type and resistant strains, needed in the fight against current and future outbreaks caused by different IFV strains. In this review, we summarize general strategies used for the discovery and development of antiviral agents targeting multiple IFV strains (including those resistant to available drugs). Structure-based drug design, mechanism-based drug design, multivalent interaction-based drug design and drug repurposing are amongst the most relevant strategies that provide a framework for the development of antiviral drugs targeting IFV.

Covalent-reversible peptide-based protease inhibitors. Design, synthesis, and clinical success stories

Dysregulated human peptidases are implicated in a large variety of diseases such as cancer, hypertension, and neurodegeneration. Viral proteases for their part are crucial for the pathogens' maturation and assembly. Several decades of research were devoted to exploring these precious therapeutic targets, often addressing them with synthetic substrate-based inhibitors to elucidate their biological roles and develop medications. The rational design of peptide-based inhibitors offered a rapid pathway to obtain a variety of research tools and drug candidates. Non-covalent modifiers were historically the first choice for protease inhibition due to their reversible enzyme binding mode and thus presumably safer profile. However, in recent years, covalent-irreversible inhibitors are having a resurgence with dramatic increase of their related publications, preclinical and clinical trials, and FDA-approved drugs. Depending on the context, covalent modifiers could provide more effective and selective drug candidates, hence requiring lower doses, thereby limiting off-target effects. Additionally, such molecules seem more suitable to tackle the crucial issue of cancer and viral drug resistances. At the frontier of reversible and irreversible based inhibitors, a new drug class, the covalent-reversible peptide-based inhibitors, has emerged with the FDA approval of Bortezomib in 2003, shortly followed by 4 other listings to date. The highlight in the field is the breathtakingly fast development of the first oral COVID-19 medication, Nirmatrelvir. Covalent-reversible inhibitors can hipothetically provide the safety of the reversible modifiers combined with the high potency and specificity of their irreversible counterparts. Herein, we will present the main groups of covalent-reversible peptide-based inhibitors, focusing on their design, synthesis, and successful drug development programs.

Repurposing FDA approved drug molecules against A B C classes of β-lactamases: a computational biology and molecular dynamics simulations study

β-lactamase are the main resistance factor for β-lactam antibiotics in Gram-negative bacteria. Since β-lactam antibiotics are being utilised as an antimicrobial agents extensively for the past 70 years, a large number of β-lactam-inactivating β-lactamases have been produced by bacteria. Here, we employed a structure-based drug discovery approach to identify and assess the efficacy of a potential medication that might block the β-lactamases which hydrolyse antibiotics. The FDA-approved medications were subjected to virtual screening, molecular docking, molecular dynamics simulations, density functional theory, and covalent docking against the β-lactamases. We identified diosmin, hidrosmin, monoxuritin and solasulfone as β-lactamase inhibitors which are authorised for therapeutic use in humans. These medications interact in a remarkable variety of non-covalent ways with the conserved residues in the substrate-binding pocket of the β-lactamases. Diosmin has been identified as an inhibitor that binds covalently to the NDM-1 a class B metallo-betalactamase. After experimental validation and clinical demonstration, this study offers adequate evidence for the therapeutic use of these drugs for controlling multidrug resistance.Communicated by Ramaswamy H. Sarma.

Discovery of Nedd4 auto-ubiquitination inhibitors

E3 ubiquitin ligases are critical to the protein degradation pathway by catalyzing the final step in protein ubiquitination by mediating ubiquitin transfer from E2 enzymes to target proteins. Nedd4 is a HECT domain-containing E3 ubiquitin ligase with a wide range of protein targets, the dysregulation of which has been implicated in myriad pathologies, including cancer and Parkinson's disease. Towards the discovery of compounds disrupting the auto-ubiquitination activity of Nedd4, we developed and optimized a TR-FRET assay for high-throughput screening. Through selective screening of a library of potentially covalent compounds, compounds 25 and 81 demonstrated apparent IC50 values of 52 µM and 31 µM, respectively. Tandem mass spectrometry (MS/MS) analysis confirmed that 25 and 81 were covalently bound to Nedd4 cysteine residues (Cys182 and Cys867). In addition, 81 also adducted to Cys627. Auto-ubiquitination assays of Nedd4 mutants featuring alanine substitutions for each of these cysteines suggested that the mode of inhibition of these compounds occurs through blocking the catalytic Cys867. The discovery of these inhibitors could enable the development of therapeutics for various diseases caused by Nedd4 E3 ligase dysregulation.

Computational and biophysical methods for the discovery and optimization of covalent drugs

Drugs that act by covalently attaching to their targets have been used to treat human diseases for over a hundred years. However, the deliberate design of covalent drugs was discouraged due to concerns of toxicity and off-target effects. Recent successes in covalent drug discovery have sparked fresh interest in this field. New screening and testing methods aimed at covalent inhibitors can play pivotal roles in facilitating the discovery process. This feature article focuses on computational and biophysical advances originating from our labs over the past decade and how these approaches have contributed to the design of prolyl oligopeptidase (POP) and SARS-CoV-2 3CLpro covalent inhibitors.

Non-equilibrium modalities of inhibition: Characterizing irreversible inhibition for the ErbB receptor family members

Most drug target interactions for clinically approved small-molecules are non-equilibrium slow-onset, tight-binding or irreversible in nature, with pronounced element of time-dependence of inhibition. Analysis of such modality of inhibition requires a continuous enzyme kinetic measurement that can yield complete progress curves and an automated high-throughput analysis pipeline. Given the increasing emphasis on designing non-equilibrium modes of inhibiting an enzyme target (especially irreversible), the above specified pipeline for data generation and analysis is essential for extracting parameters to guide decisions in early drug discovery. In this manuscript, the methodology and data analysis protocol from our irreversible inhibitor characterization campaigns for the ErbB receptor family members is presented. Guidance is provided on the appropriate design of assay to generate quality data, setting up the analysis and estimation of inactivation rate (kinact) and the pseudo-equilibrium binding affinity (KI) constant (or their ratio kinact/KI) in a high-throughput manner for the inhibitor interacting with the protein target of interest.

Pharmacophoric analogs of sotorasib-entrapped KRAS G12C in its inactive GDP-bound conformation: covalent docking and molecular dynamics investigations

For decades, KRAS G12C was considered an undruggable target. However, in recent times, a covalent inhibitor known as sotorasib was discovered and approved for the treatment of patients with KRAS G12C-driven cancers. Ever since the discovery of this drug, several preclinical efforts have focused on identifying novel therapeutic candidates that could act as covalent binders of KRAS G12C. Despite these intensive efforts, only a few KRAS G12C inhibitors have entered clinical trials. Hence, this highlights the need to develop effective drug candidates that could be used in the treatment of KRAS G12C-driven cancers. Herein, we embarked on a virtual screening campaign that involves the identification of pharmacophores of sotorasib that could act as covalent arsenals against the KRAS G12C target. To our knowledge, this is the first computational study that involves the compilation of sotorasib pharmacophores from an online chemical database against KRAS G12C. After this library of chemical entities was compiled, we conducted a covalent docking-based virtual screening that revealed three promising drug candidates (CID_146235944, CID_160070181, and CID_140956845) binding covalently to the crucial nucleophilic side chain of Cys12 and interact with the residues that form the cryptic allosteric pocket of KRAS G12C in its inactive GDP-bound conformation. Subsequently, ADMET profiling portrayed the covalent inhibitors as lead-like candidates, while 100 ns molecular dynamics was used to substantiate their stability. Although our overall computational study has shown the promising potential of the lead-like candidates in impeding oncogenic RAS signaling, more experimental efforts are needed to validate and establish their preclinical relevance. Implication of KRAS G12C in cancer and computational approach towards impeding the KRAS G12C RAS signaling.

Protein-protein interactions: developing small-molecule inhibitors/stabilizers through covalent strategies

The development of small-molecule inhibitors or stabilizers of selected protein-protein interactions (PPIs) of interest holds considerable promise for the development of research tools as well as candidate therapeutics. In this context, the covalent modification of selected residues within the target protein has emerged as a promising mechanism of action to obtain small-molecule modulators of PPIs with appropriate selectivity and duration of action. Different covalent labeling strategies are now available that can potentially allow for a rational, ground-up discovery and optimization of ligands as PPI inhibitors or stabilizers. This review article provides a synopsis of recent developments and applications of such tactics, with a particular focus on site-directed fragment tethering and proximity-enabled approaches.

Covalent S-Adenosylhomocysteine-Based DNA Methyltransferase 2 Inhibitors with a New Type of Aryl Warhead

The DNA methyltransferase 2 (DNMT2) is an RNA modifying enzyme associated with pathophysiological processes, such as mental and metabolic disorders or cancer. Although the development of methyltransferase inhibitors remains challenging, DNMT2 is not only a promising target for drug discovery, but also for the development of activity-based probes. Here, we present covalent SAH-based DNMT2 inhibitors decorated with a new type of aryl warhead. Based on a noncovalent DNMT2 inhibitor with N-benzyl substituent, the Topliss scheme was followed for optimization. The results showed that electron-deficient benzyl moieties highly increased affinity. By decorating the structures with strong electron-withdrawing moieties and leaving groups, we adjusted the electrophilicity to create covalent DNMT2 inhibitors. A 4-bromo-3-nitrophenylsulfonamide-decorated SAH derivative (80) turned out to be the most potent (IC50 = 1.2 ± 0.1 μM) and selective inhibitor. Protein mass spectrometry confirmed the covalent reaction with the catalytically active cysteine-79.

Structure-based discovery of IHMT-IDH1-053 as a potent irreversible IDH1 mutant selective inhibitor

Through a structure-based irreversible drug design approach, we have discovered a highly potent IDH1-mutant inhibitor compound 16 (IHMT-IDH1-053) (IC₅₀ = 4.7 nM), which displays high selectivity against IDH1 mutants over IDH1 wt and IDH2 wt/mutants. The crystal structure demonstrates that 16 binds to the IDH1 R132H protein in the allosteric pocket adjacent to the NAPDH binding pocket through a covalent bond with residue Cys269. 16 inhibits 2-hydroxyglutarate (2-HG) production in IDH1 R132H mutant transfected 293T cells (IC₅₀ = 28 nM). In addition, it inhibits the proliferation of HT1080 cell line and primary AML cells which both bear IDH1 R132 mutants. In vivo, 16 inhibits 2-HG level in a HT1080 xenograft mouse model. Our study suggested that 16 would be a new pharmacological tool to study IDH1 mutant-related pathology and the covalent binding mode provided a novel approach for designing irreversible IDH1 inhibitors.

An update on the discovery and development of reversible covalent inhibitors

Small molecule drugs that covalently bind irreversibly to their target proteins have several advantages over conventional reversible inhibitors. They include increased duration of action, less-frequent drug dosing, reduced pharmacokinetic sensitivity, and the potential to target intractable shallow binding sites. Despite these advantages, the key challenges of irreversible covalent drugs are their potential for off-target toxicities and immunogenicity risks. Incorporating reversibility into covalent drugs would lead to less off-target toxicity by forming reversible adducts with off-target proteins and thus reducing the risk of idiosyncratic toxicities caused by the permanent modification of proteins, which leads to higher levels of potential haptens. Herein, we systematically review electrophilic warheads employed during the development of reversible covalent drugs. We hope the structural insights of electrophilic warheads would provide helpful information to medicinal chemists and aid in designing covalent drugs with better on-target selectivity and improved safety.

Graphical Abstract

Technologies for Direct Detection of Covalent Protein—Drug Adducts

In the past two decades, drug candidates with a covalent binding mode have gained the interest of medicinal chemists, as several covalent anticancer drugs have successfully reached the clinic. As a covalent binding mode changes the relevant parameters to rank inhibitor potency and investigate structure-activity relationship (SAR), it is important to gather experimental evidence on the existence of a covalent protein–drug adduct. In this work, we review established methods and technologies for the direct detection of a covalent protein–drug adduct, illustrated with examples from (recent) drug development endeavors. These technologies include subjecting covalent drug candidates to mass spectrometric (MS) analysis, protein crystallography, or monitoring intrinsic spectroscopic properties of the ligand upon covalent adduct formation. Alternatively, chemical modification of the covalent ligand is required to detect covalent adducts by NMR analysis or activity-based protein profiling (ABPP). Some techniques are more informative than others and can also elucidate the modified amino acid residue or bond layout. We will discuss the compatibility of these techniques with reversible covalent binding modes and the possibilities to evaluate reversibility or obtain kinetic parameters. Finally, we expand upon current challenges and future applications. Overall, these analytical techniques present an integral part of covalent drug development in this exciting new era of drug discovery.

Structure-Activity Relationship Studies Based on Quinazoline Derivatives as EGFR Kinase Inhibitors (2017-Present)

The epidermal growth factor receptor (EGFR) plays a critical role in the tumorigenesis of various forms of cancer. Targeting the mutant forms of EGFR has been identified as an attractive therapeutic approach and led to the approval of three generations of inhibitors. The quinazoline core has emerged as a favorable scaffold for the development of novel EGFR inhibitors due to increased affinity for the active site of EGFR kinase. Currently, there are five first-generation (gefitinib, erlotinib, lapatinib, vandetanib, and icotinib) and two second-generation (afatinib and dacomitinib) quinazoline-based EGFR inhibitors approved for the treatment of various types of cancers. The aim of this review is to outline the structural modulations favorable for the inhibitory activity toward both common mutant (del19 and L858R) and resistance-conferring mutant (T790M and C797S) EGFR forms, and provide an overview of the newly synthesized quinazoline derivatives as potentially competitive, covalent or allosteric inhibitors of EGFR.

Design, synthesis, and biological testing of biphenylmethyloxazole inhibitors targeting HIV-1 reverse transcriptase

We report non-nucleoside inhibitors of HIV-1 reverse transcriptase (NNRTIs) using a biphenylmethyloxazole pharmacophore. A crystal structure of benzyloxazole 1 was obtained and suggested the potential viability of biphenyl analogues. In particular, 6a, 6b, and 7 turned out to be potent NNRTIs with low-nanomolar activity in enzyme inhibition and infected T-cell assays, and with low cytotoxicity. Though modeling further suggested that analogues with fluorosulfate and epoxide warheads might provide covalent modification of Tyr188, synthesis and testing did not find evidence for this outcome.

SiteRadar: Utilizing Graph Machine Learning for Precise Mapping of Protein-Ligand-Binding Sites

Identifying ligand-binding sites on the protein surface is a crucial step in the structure-based drug design. Although multiple techniques have been proposed, including those using machine learning algorithms, the existing solutions do not provide significant advantages over nonmachine learning approaches and there is still a big room for improvement. The low ability to identify protein-ligand-binding sites makes available approaches inapplicable to automated drug design. Here, we present SiteRadar, a new algorithm for mapping cavities that are likely to bind a small-molecule ligand. SiteRadar shows higher accuracy in binding site identification compared with FPocket and PUResNet. SiteRadar demonstrates an ability to detect up to 74% of true ligand-binding sites according to the top N + 2 metric and usually covers approximately 80% of ligand atoms. Therefore, SiteRadar can be regarded as a promising solution for implementation into algorithms for automated drug design.

Nitriles: an attractive approach to the development of covalent inhibitors

Nitriles have broad applications in medicinal chemistry, with more than 60 small molecule drugs on the market containing the cyano functional group. In addition to the well-known noncovalent interactions that nitriles can perform with macromolecular targets, they are also known to improve drug candidates' pharmacokinetic profiles. Moreover, the cyano group can be used as an electrophilic warhead to covalently bind an inhibitor to a target of interest, forming a covalent adduct, a strategy that can present benefits over noncovalent inhibitors. This approach has gained much notoriety in recent years, mainly with diabetes and COVID-19-approved drugs. Nevertheless, the application of nitriles in covalent ligands is not restricted to it being the reactive center, as it can also be employed to convert irreversible inhibitors into reversible ones, a promising strategy for kinase inhibition and protein degradation. In this review, we introduce and discuss the roles of the cyano group in covalent inhibitors, how to tune its reactivity and the possibility of achieving selectivity only by replacing the warhead. Finally, we provide an overview of nitrile-based covalent compounds in approved drugs and inhibitors recently described in the literature.

Pseudo-irreversible butyrylcholinesterase inhibitors: Structure-activity relationships, computational and crystallographic study of the N-dialkyl O-arylcarbamate warhead

Alongside reversible butyrylcholinesterase inhibitors, a plethora of covalent butyrylcholinesterase inhibitors have been reported in the literature, typically pseudo-irreversible carbamates. For these latter, however, most cases lack full confirmation of their covalent mode of action. Additionally, the available reports regarding the structure-activity relationships of the O-arylcarbamate warhead are incomplete. Therefore, a follow-up on a series of pseudo-irreversible covalent carbamate human butyrylcholinesterase inhibitors and the structure-activity relationships of the N-dialkyl O-arylcarbamate warhead are presented in this study. The covalent mechanism of binding was tested by IC₅₀ time-dependency profiles, and sequentially and increasingly confirmed by kinetic analysis, whole protein LC-MS, and crystallographic analysis. Computational studies provided valuable insights into steric constraints and identified problematic, bulky carbamate warheads that cannot reach and carbamoylate the catalytic Ser198. Quantum mechanical calculations provided further evidence that steric effects appear to be a key factor in determining the covalent binding behaviour of these carbamate cholinesterase inhibitors and their duration of action. Additionally, the introduction of a clickable terminal alkyne moiety into one of the carbamate N-substituents and in situ derivatisation with azide-containing fluorophore enabled fluorescent labelling of plasma human butyrylcholinesterase. This proof-of-concept study highlights the potential of this novel approach and for these compounds to be further developed as clickable molecular probes for investigating tissue localisation and activity of cholinesterases.

BIreactive: Expanding the Scope of Reactivity Predictions to Propynamides

We present the first comprehensive study on the prediction of reactivity for propynamides. Covalent inhibitors like propynamides often show improved potency, selectivity, and unique pharmacologic properties compared to their non-covalent counterparts. In order to achieve this, it is essential to tune the reactivity of the warhead. This study shows how three different in silico methods can predict the in vitro properties of propynamides, a covalent warhead class integrated into approved drugs on the market. Whereas the electrophilicity index is only applicable to individual subclasses of substitutions, adduct formation and transition state energies have a good predictability for the in vitro reactivity with glutathione (GSH). In summary, the reported methods are well suited to estimate the reactivity of propynamides. With this knowledge, the fine tuning of the reactivity is possible which leads to a speed up of the design process of covalent drugs.

Serendipitous Identification of a Covalent Activator of Liver Pyruvate Kinase

Enzymes are effective biological catalysts that accelerate almost all metabolic reactions in living organisms. Synthetic modulators of enzymes are useful tools for the study of enzymatic reactions and can provide starting points for the design of new drugs. Here, we report on the discovery of a class of biologically active compounds that covalently modifies lysine residues in human liver pyruvate kinase (PKL), leading to allosteric activation of the enzyme (EC₅₀ =0.29 μM). Surprisingly, the allosteric activation control point resides on the lysine residue K282 present in the catalytic site of PKL. These findings were confirmed by structural data, MS/MS experiments, and molecular modelling studies. Altogether, our study provides a molecular basis for the activation mechanism and establishes a framework for further development of human liver pyruvate kinase covalent activators.

Roadmap to Pyruvate Kinase M2 Modulation - A Computational Chronicle

Pyruvate kinase M2 (PKM2) has surfaced as a potential target for anti-cancer therapy. PKM2 is known to be overexpressed in the tumor cells and is a critical metabolic conduit in supplying the augmented bioenergetic demands of the recalcitrant cancer cells. The presence of PKM2 in structurally diverse tetrameric as well as dimeric forms has opened new avenues to design novel modulators. It is also a truism to state that drug discovery has advanced significantly from various computational techniques like molecular docking, virtual screening, molecular dynamics, and pharmacophore mapping. The present review focuses on the role of computational tools in exploring novel modulators of PKM2. The structural features of various isoforms of PKM2 have been discussed along with reported modulators. An extensive analysis of the structure-based and ligand- based in silico methods aimed at PKM2 modulation has been conducted with an in-depth review of the literature. The role of advanced tools like QSAR and quantum mechanics has been established with a brief discussion of future perspectives.

Targeting immunoproteasome in neurodegeneration: A glance to the future

The immunoproteasome is a specialized form of proteasome equipped with modified catalytic subunits that was initially discovered to play a pivotal role in MHC class I antigen processing and immune system modulation. However, over the last years, this proteolytic complex has been uncovered to serve additional functions unrelated to antigen presentation. Accordingly, it has been proposed that immunoproteasome synergizes with canonical proteasome in different cell types of the nervous system, regulating neurotransmission, metabolic pathways and adaptation of the cells to redox or inflammatory insults. Hence, studying the alterations of immunoproteasome expression and activity is gaining research interest to define the dynamics of neuroinflammation as well as the early and late molecular events that are likely involved in the pathogenesis of a variety of neurological disorders. Furthermore, these novel functions foster the perspective of immunoproteasome as a potential therapeutic target for neurodegeneration. In this review, we provide a brain and retina-wide overview, trying to correlate present knowledge on structure-function relationships of immunoproteasome with the variety of observed neuro-modulatory functions.

Discovery of novel SARS-CoV-2 3CL protease covalent inhibitors using deep learning-based screen

SARS-CoV-2 3CL protease is one of the key targets for drug development against COVID-19. Most known SARS-CoV-2 3CL protease inhibitors act by covalently binding to the active site cysteine. Yet, computational screens against this enzyme were mainly focused on non-covalent inhibitor discovery. Here, we developed a deep learning-based stepwise strategy for selective covalent inhibitor screen. We used a deep learning framework that integrated a directed message passing neural network with a feed-forward neural network to construct two different classifiers for either covalent or non-covalent inhibition activity prediction. These two classifiers were trained on the covalent and non-covalent 3CL protease inhibitors dataset, respectively, which achieved high prediction accuracy. We then successively applied the covalent inhibitor model and the non-covalent inhibitor model to screen a chemical library containing compounds with covalent warheads of cysteine. We experimentally tested the inhibition activity of 32 top-ranking compounds and 12 of them were active, among which 6 showed IC₅₀ values less than 12 μM and the strongest one inhibited SARS-CoV-2 3CL protease with an IC₅₀ of 1.4 μM. Further investigation demonstrated that 5 of the 6 active compounds showed typical covalent inhibition behavior with time-dependent activity. These new covalent inhibitors provide novel scaffolds for developing highly active SARS-CoV-2 3CL covalent inhibitors.

Advances in covalent drug discovery

Covalent drugs have been used to treat diseases for more than a century, but tools that facilitate the rational design of covalent drugs have emerged more recently. The purposeful addition of reactive functional groups to existing ligands can enable potent and selective inhibition of target proteins, as demonstrated by the covalent epidermal growth factor receptor (EGFR) and Bruton's tyrosine kinase (BTK) inhibitors used to treat various cancers. Moreover, the identification of covalent ligands through 'electrophile-first' approaches has also led to the discovery of covalent drugs, such as covalent inhibitors for KRAS(G12C) and SARS-CoV-2 main protease. In particular, the discovery of KRAS(G12C) inhibitors validates the use of covalent screening technologies, which have become more powerful and widespread over the past decade. Chemoproteomics platforms have emerged to complement covalent ligand screening and assist in ligand discovery, selectivity profiling and target identification. This Review showcases covalent drug discovery milestones with emphasis on the lessons learned from these programmes and how an evolving toolbox of covalent drug discovery techniques facilitates success in this field.

Covalent Warheads Targeting Cysteine Residue: The Promising Approach in Drug Development

Cysteine is one of the least abundant amino acids in proteins of many organisms, which plays a crucial role in catalysis, signal transduction, and redox regulation of gene expression. The thiol group of cysteine possesses the ability to perform nucleophilic and redox-active functions that are not feasible for other natural amino acids. Cysteine is the most common covalent amino acid residue and has been shown to react with a variety of warheads, especially Michael receptors. These unique properties have led to widespread interest in this nucleophile, leading to the development of a variety of cysteine-targeting warheads with different chemical compositions. Herein, we summarized the various covalent warheads targeting cysteine residue and their application in drug development.

Targeting SARS-CoV-2 Main Protease for Treatment of COVID-19: Covalent Inhibitors Structure-Activity Relationship Insights and Evolution Perspectives

The viral main protease is one of the most attractive targets among all key enzymes involved in the SARS-CoV-2 life cycle. Covalent inhibition of the cysteine145 of SARS-CoV-2 MPRO with selective antiviral drugs will arrest the replication process of the virus without affecting human catalytic pathways. In this Perspective, we analyzed the in silico, in vitro, and in vivo data of the most representative examples of covalent SARS-CoV-2 MPRO inhibitors reported in the literature to date. In particular, the studied molecules were classified into eight different categories according to their reactive electrophilic warheads, highlighting the differences between their reversible/irreversible mechanism of inhibition. Furthermore, the analyses of the most recurrent pharmacophoric moieties and stereochemistry of chiral carbons were reported. The analyses of noncovalent and covalent in silico protocols, provided in this Perspective, would be useful for the scientific community to discover new and more efficient covalent SARS-CoV-2 MPRO inhibitors.

Assessment of Reversibility for Covalent Cysteine Protease Inhibitors Using Quantum Mechanics/Molecular Mechanics Free Energy Surfaces

We have used molecular dynamics (MD) simulations with hybrid quantum mechanics/molecular mechanics (QM/MM) potentials to investigate the reaction mechanism for covalent inhibition of cathepsin K and assess the reversibility of inhibition. The computed free energy profiles suggest that a nucleophilic attack by the catalytic cysteine on the inhibitor warhead and proton transfer from the catalytic histidine occur in a concerted manner. The results indicate that the reaction is more strongly exergonic for the alkyne-based inhibitors, which bind irreversibly to cathepsin K, than for the nitrile-based inhibitor odanacatib, which binds reversibly. Gas-phase energies were also calculated for the addition of methanethiol to structural prototypes for a number of warheads of interest in cysteine protease inhibitor design in order to assess electrophilicity. The approaches presented in this study are particularly applicable to assessment of novel warheads, and computed transition state geometries can be incorporated into molecular models for covalent docking.

Advances in UDP-N-Acetylglucosamine Enolpyruvyl Transferase (MurA) Covalent Inhibition

Peptidoglycan is a cross-linked polymer responsible for maintaining the bacterial cell wall integrity and morphology in Gram-negative and Gram-positive bacteria. The peptidoglycan pathway consists of the enzymatic reactions held in three steps: cytoplasmic, membrane-associated, and periplasmic. The Mur enzymes (MurA-MurF) are involved in a cytoplasmic stage. The UDP-N-acetylglucosamine enolpyruvyl transferase (MurA) enzyme is responsible for transferring the enolpyruvate group from phosphoenolpyruvate (PEP) to UDP-N-acetylglucosamine (UNAG) to form UDP-N-acetylglucosamine enolpyruvate (EP-UNAG). Fosfomycin is a natural product analogous to PEP that acts on the MurA target enzyme via binding covalently to the key cysteine residue in the active site. Similar to fosfomycin, other MurA covalent inhibitors have been described with a warhead in their structure that forms a covalent bond with the molecular target. In MurA, the nucleophilic thiolate of Cys115 is pointed as the main group involved in the warhead binding. Thus, in this minireview, we briefly describe the main recent advances in the design of MurA covalent inhibitors.

Synthesis and biological evaluation of new series of quinazoline derivatives as EGFR/HER2 dual-target inhibitors

It is generally believed that EGFR/HER2 dual-target inhibitors may overcome the resistance of EGFR TKIs caused by HER2 overexpression. The structure-based synthesis and biological evaluation of quinazoline derivatives as EGFR/HER2 dual-target inhibitors has been studied in this paper. II-1, II-2, III-3, III-4 displayed comparable inhibitory potency against EGFR and HER2 and II-1 showed remarkable antiproliferative activities against NCI-H358/PC-9/Calu-3/NCI-H1781 (EGFR IC₅₀ = 0.30 nM, HER2 IC₅₀ = 6.07 nM, NCI-H358 GI₅₀ = 23.30 nM, PC-9 GI₅₀ = 1.95 nM, Calu-3 GI₅₀ = 23.13 nM NCI-H1781 GI₅₀ = 41.61 nM).

A Comprehensive Guide for Assessing Covalent Inhibition in Enzymatic Assays Illustrated with Kinetic Simulations

Covalent inhibition has become more accepted in the past two decades, as illustrated by the clinical approval of several irreversible inhibitors designed to covalently modify their target. Elucidation of the structure-activity relationship and potency of such inhibitors requires a detailed kinetic evaluation. Here, we elucidate the relationship between the experimental read-out and the underlying inhibitor binding kinetics. Interactive kinetic simulation scripts are employed to highlight the effects of in vitro enzyme activity assay conditions and inhibitor binding mode, thereby showcasing which assumptions and corrections are crucial. Four stepwise protocols to assess the biochemical potency of (ir)reversible covalent enzyme inhibitors targeting a nucleophilic active site residue are included, with accompanying data analysis tailored to the covalent binding mode. Together, this will serve as a guide to make an educated decision regarding the most suitable method to assess covalent inhibition potency. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol I: Progress curve analysis of substrate association competition Basic Data Analysis Protocol 1A: Two-step irreversible covalent inhibition Basic Data Analysis Protocol 1B: One-step irreversible covalent inhibition Basic Data Analysis Protocol 1C: Two-step reversible covalent inhibition Basic Data Analysis Protocol 1D: Two-step irreversible covalent inhibition with substrate depletion Basic Protocol II: Incubation time-dependent potency IC₅₀ (t) Basic Data Analysis Protocol 2: Two-step irreversible covalent inhibition Basic Protocol III: Preincubation time-dependent inhibition without dilution Basic Data Analysis Protocol 3: Preincubation time-dependent inhibition without dilution Basic Data Analysis Protocol 3Ai: Two-step irreversible covalent inhibition Alternative Data Analysis Protocol 3Aii: Two-step irreversible covalent inhibition Basic Data Analysis Protocol 3Bi: One-step irreversible covalent inhibition Alternative Data Analysis Protocol 3Bii: One-step irreversible covalent inhibition Basic Data Analysis Protocol 3C: Two-step reversible covalent inhibition Basic Protocol IV: Preincubation time-dependent inhibition with dilution/competition Basic Data Analysis Protocol 4: Preincubation time-dependent inhibition with dilution Basic Data Analysis Protocol 4Ai: Two-step irreversible covalent inhibition Alternative Data Analysis Protocol 4Aii: Two-step irreversible covalent inhibition Basic Data Analysis Protocol 4Bi: One-step irreversible covalent inhibition Alternative Data Analysis Protocol 4Bii: One-step irreversible covalent inhibition.

Heat Shock Protein 90 (HSP90) Inhibitors as Anticancer Medicines: A Review on the Computer-Aided Drug Discovery Approaches over the Past Five Years

Cancer is a disease caused by the uncontrolled, abnormal growth of cells in different anatomic sites. In 2018, it was predicted that the worldwide cancer burden would rise to 18.1 million new cases and 9.6 million deaths. Anticancer compounds, often known as chemotherapeutic medicines, have gained much interest in recent cancer research. These medicines work through various biological processes in targeting cells at various stages of the cell's life cycle. One of the most significant roadblocks to developing anticancer drugs is that traditional chemotherapy affects normal cells and cancer cells, resulting in substantial side effects. Recently, advancements in new drug development methodologies and the prediction of the targeted interatomic and intermolecular ligand interaction sites have been beneficial. This has prompted further research into developing and discovering novel chemical species as preferred therapeutic compounds against specific cancer types. Identifying new drug molecules with high selectivity and specificity for cancer is a prerequisite in the treatment and management of the disease. The overexpression of HSP90 occurs in patients with cancer, and the HSP90 triggers unstable harmful kinase functions, which enhance carcinogenesis. Therefore, the development of potent HSP90 inhibitors with high selectivity and specificity becomes very imperative. The activities of HSP90 as chaperones and cochaperones are complex due to the conformational dynamism, and this could be one of the reasons why no HSP90 drugs have made it beyond the clinical trials. Nevertheless, HSP90 modulations appear to be preferred due to the competitive inhibition of the targeted N-terminal adenosine triphosphate pocket. This study, therefore, presents an overview of the various computational models implored in the development of HSP90 inhibitors as anticancer medicines. We hereby suggest an extensive investigation of advanced computational modelling of the three different domains of HSP90 for potent, effective inhibitor design with minimal off-target effects.