Drug-target residence time and its implications for lead optimization

Direct screening of a target-specific covalent binder: stringent regulation of warhead reactivity in a matchmaking environment

A peptide-type covalent binder for a target protein was obtained by direct and stringent screening of a warhead-modified peptide library on the robust T7 phage. The aryl fluorosulfate (fosylate) warhead was activated only in a matchmaking microenvironment created between the target protein and an appropriate peptide during the reactivity/affinity-based co-selection process of extended phage display.

Solution-State Preorganization of Cyclic β-Hairpin Ligands Determines Binding Mechanism and Affinities for MDM2

Understanding mechanisms of protein folding and binding is crucial to designing their molecular function. Molecular dynamics (MD) simulations and Markov state model (MSM) approaches provide a powerful way to understand complex conformational change that occurs over long time scales. Such dynamics are important for the design of therapeutic peptidomimetic ligands, whose affinity and binding mechanism are dictated by a combination of folding and binding. To examine the role of preorganization in peptide binding to protein targets, we performed massively parallel explicit-solvent MD simulations of cyclic β-hairpin ligands designed to mimic the p53 transactivation domain and competitively bind mouse double minute 2 homologue (MDM2). Disrupting the MDM2-p53 interaction is a therapeutic strategy to prevent degradation of the p53 tumor suppressor in cancer cells. MSM analysis of over 3 ms of aggregate trajectory data enabled us to build a detailed mechanistic model of coupled folding and binding of four cyclic peptides which we compare to experimental binding affinities and rates. The results show a striking relationship between the relative preorganization of each ligand in solution and its affinity for MDM2. Specifically, changes in peptide conformational populations predicted by the MSMs suggest that entropy loss upon binding is the main factor influencing affinity. The MSMs also enable detailed examination of non-native interactions which lead to misfolded states and comparison of structural ensembles with experimental NMR measurements. In contrast to an MSM study of p53 transactivation domain (TAD) binding to MDM2, MSMs of cyclic β-hairpin binding show a conformational selection mechanism. Finally, we make progress toward predicting accurate off rates of cyclic peptides using multiensemble Markov models (MEMMs) constructed from unbiased and biased simulated trajectories.

Accurate quantitative determination of affinity and binding kinetics for tight binding inhibition of xanthine oxidase

The accurate quantitative determination of affinity and binding kinetics (BK) for tight binding inhibition is extraordinary important from both the continuous optimization of compounds, particularly in developing structure-activity relationships (SAR), and the prediction of in vivo target occupancy (TO). Due to the unique properties for tight binding inhibition that the inhibitors are characterized by the ultrahigh-affinity, relatively fast association to the target enzyme combined with extremely slow dissociation of the inhibitor-enzyme binary complex, the classical steady state equilibrium methods are no longer valid. Here, we made several recommendations of how to design the optimal experiments and apply special mathematical calculation approaches to quantitatively evaluate the accurate affinity and BK as the examples of two tight binding inhibitors against the xanthine oxidase (XO), as well as compared the differences in the results calculated from the different data analytical methods and analyzed the influence of these differences on the XO engagement in human. Analysis of the results displayed that the accurate apparent dissociation constant (K_i^*,app) was 0.2 ± 0.06 nM for topiroxotstat and was 0.45 ± 0.2 nM for febuxostat; that on-rate (k_on) was (4.3 ± 1.1) × 10⁶ M^-1s^-1 for topiroxotstat and was(133.3 ± 3.5) × 10⁶ M^-1s^-1 for febuxostat, and off-rate (k_off) was (1.0±0.2) × 10^-5 s^-1 for topiroxotstat and was ≤ 0.16 × 10^-5 s^-1for febuxostat. Moreover, there were significant differences in the K_i^*,app and k_off values estimated using the appropriate specialized methods for tight binding inhibition versus classical steady state equilibrium methods, with the substantial differences of 14-fold and 32-fold reduction for topiroxostat, respectively, and of 9.6-fold and ≥ 213-fold reduction for febuxostat, while the k_on values remain the moderate differences for the two inhibitors. The obvious greater AUC of XO engagement time courses and longer durations of above 70% engagement by the appropriate specialized methods for tight binding inhibition were observed that the results display the differences of 70.1% and 88%, respectively for topiroxostat and of 38.1% and 35.0%, respectively for febuxostat in human liver cell than by classical steady state equilibrium methods. Again, our studies provide several valuable recommendations of the optimal experiment protocols and appropriate analytical approaches for accurately quantitatively assessing the affinity and BK parameters as well as demonstrate the ability of our recommended methods to generate reliable data for tight binding inhibitors against XO.

Improvement of Oral Bioavailability of Pyrazolo-Pyridone Inhibitors of the Interaction of DCN1/2 and UBE2M

The cullin-RING ubiquitin ligases (CRLs) are ubiquitin E3 enzymes that play a key role in controlling proteasomal degradation and are activated by neddylation. We previously reported inhibitors that target CRL activation by disrupting the interaction of defective in cullin neddylation 1 (DCN1), a CRL neddylation co-E3, and UBE2M, a neddylation E2. Our first-generation inhibitors possessed poor oral bioavailability and fairly rapid clearance that hindered the study of acute inhibition of DCN-controlled CRL activity in vivo. Herein, we report studies to improve the pharmacokinetic performance of the pyrazolo-pyridone inhibitors. The current best inhibitor, 40, inhibits the interaction of DCN1 and UBE2M, blocks NEDD8 transfer in biochemical assays, thermally stabilizes cellular DCN1, and inhibits anchorage-independent growth in a DCN1 amplified squamous cell carcinoma cell line. Additionally, we demonstrate that a single oral 50 mg/kg dose sustains plasma exposures above the biochemical IC₉₀ for 24 h in mice.

Discovery of a covalent inhibitor of heat shock protein 90 with antitumor activity that blocks the co-chaperone binding via C-terminal modification

Heat shock protein (Hsp90), a critical molecular chaperone that regulates the maturation of a large number of oncogenic client proteins, plays an essential role in the growth of neoplastic cells. Herein, DDO-6600 is identified to covalent modification of Cys598 on Hsp90 from in silico study and is verified by a series of biological assays. We demonstrated that DDO-6600 covalently bound to Cys598 on the Hsp90 C terminus and exhibited antiproliferative activities against multiple tumor cells without inhibiting ATPase activity. Further studies showed that DDO-6600 disrupted the interaction between Hsp90 and Cdc37, which induced the degradation of kinase client proteins in multiple tumor cell lines, promoted apoptosis, and inhibited cell motility. Our findings offer mechanic insights into the covalent modification of Hsp90 and provide an alternative strategy for the development of Hsp90 covalent regulators or chemical probes to explore the therapeutical potential of Hsp90.

Warhead Reactivity Limits the Speed of Inhibition of the Cysteine Protease Rhodesain

Viral and parasitic pathogens rely critically on cysteine proteases for host invasion, replication, and infectivity. Their inhibition by synthetic inhibitors, such as vinyl sulfone compounds, has emerged as a promising treatment strategy. However, the individual reaction steps of protease inhibition are not fully understood. Using the trypanosomal cysteine protease rhodesain as a medically relevant target, we design photoinduced electron transfer (PET) fluorescence probes to detect kinetics of binding of reversible and irreversible vinyl sulfones directly in solution. Intriguingly, the irreversible inhibitor, apart from its unlimited residence time in the enzyme, reacts 5 times faster than the reversible one. Results show that the reactivity of the warhead, and not binding of the peptidic recognition unit, limits the rate constant of protease inhibition. The use of a reversible inhibitor decreases the risk of off-target side effects not only by allowing its release from an off-target but also by reducing the rate constant of binding.

Progress toward B-Cell Lymphoma 6 BTB Domain Inhibitors for the Treatment of Diffuse Large B-Cell Lymphoma and Beyond

B-cell lymphoma 6 (BCL6) is a master regulator of germinal center formation that produce antibody-secreting plasma cells and memory B-cells for sustained immune responses. The BTB domain of BCL6 (BCL6^BTB) forms a homodimer that mediates transcriptional repression by recruiting its corepressor proteins to form a biologically functional transcriptional complex. The protein-protein interaction (PPI) between the BCL6^BTB and its corepressors has emerged as a therapeutic target for the treatment of DLBCL and a number of other human cancers. This Perspective provides an overview of recent advances in the development of BCL6^BTB inhibitors from reversible inhibitors, irreversible inhibitors, to BCL6 degraders. Inhibitor design and medicinal chemistry strategies for the development of novel compounds will be provided. The binding mode of new inhibitors to BCL6^BTB are highlighted. Also, the in vitro and in vivo assays used for the evaluation of new compounds will be discussed.

A Long Residence Time Enoyl-Reductase Inhibitor Explores an Extended Binding Region with Isoenzyme-Dependent Tautomer Adaptation and Differential Substrate-Binding Loop Closure

The enoyl-acyl carrier protein (ACP) reductase (ENR) is a key enzyme within the bacterial fatty-acid synthesis pathway. It has been demonstrated that small-molecule inhibitors carrying the diphenylether (DPE) scaffold bear a great potential for the development of highly specific and effective drugs against this enzyme class. Interestingly, different substitution patterns of the DPE scaffold have been shown to lead to varying effects on the kinetic and thermodynamic behavior toward ENRs from different organisms. Here, we investigated the effect of a 4'-pyridone substituent in the context of the slow tight-binding inhibitor SKTS1 on the inhibition of the Staphylococcus aureus enoyl-ACP-reductase saFabI and the closely related isoenzyme from Mycobacterium tuberculosis, InhA, and explored a new interaction site of DPE inhibitors within the substrate-binding pocket. Using high-resolution crystal structures of both complexes in combination with molecular dynamics (MD) simulations, kinetic measurements, and quantum mechanical (QM) calculations, we provide evidence that the 4'-pyridone substituent adopts different tautomeric forms when bound to the two ENRs. We furthermore elucidate the structural determinants leading to significant differences in the residence time of SKTS1 on both enzymes.

Perspectives on High-Throughput Ligand/Protein Docking With Martini MD Simulations

Molecular docking is central to rational drug design. Current docking techniques suffer, however, from limitations in protein flexibility and solvation models and by the use of simplified scoring functions. All-atom molecular dynamics simulations, on the other hand, feature a realistic representation of protein flexibility and solvent, but require knowledge of the binding site. Recently we showed that coarse-grained molecular dynamics simulations, based on the most recent version of the Martini force field, can be used to predict protein/ligand binding sites and pathways, without requiring any a priori information, and offer a level of accuracy approaching all-atom simulations. Given the excellent computational efficiency of Martini, this opens the way to high-throughput drug screening based on dynamic docking pipelines. In this opinion article, we sketch the roadmap to achieve this goal.

Analyzing the Long Time-Scale Dynamics of Uremic Toxins Bound to Sudlow Site II in Human Serum Albumin

Protein bound uremic toxins (PBUTs), a series of chemicals that remain a challenge for removal strategies used on patients suffering with chronic kidney disease, could be strong candidates for MD study in order to better understand the interactions and time scales associated with binding mode transitions. Currently, traditional dialysis methods cannot satisfactorily remove PBUTs from the bloodstream. This is at least partly due to these toxin's high level of affinity for protein binding sites, particularly the prominent human serum albumin (HSA) and two of its drug binding sites (Sudlow site I and II). We investigate the dynamics of binding site transitions and interactions by MD simulations targeting four well-known toxins: indoxyl sulfate (IS), p-cresyl sulfate (PCS), indole-3-acetic acid (IAA), and hippurate acid (HIP). Long-time scale dynamics are obtained by the use of time-structure independent component analysis (tICA) for dimensionality reduction followed by spectral analysis of a Markov state model (MSM) scored using the generalized matrix Rayleigh quotient (GMRQ). Our results add new insights to prior findings related to the key role of charge-pairing in governing toxin-protein interactions. We find that IAA, the bulkiest hydrophobic toxin studied, observes the slowest process of at least 3 times slower than the smaller, less hydrophobic toxins. In general, we find that the processes slower than 15 ns are correlated with a transition from dominantly hydrophobic interactions deep in the binding pocket to a gain in hydrogen bonding partners near the mouth of the pocket. Our results indicate that aromatic residues such as PHE play a part in a type of toxin stabilization akin to π-stacking. In conclusion, this work presents mechanistic descriptions of interactions/transitions for a set of important PBUTs that bind Sudlow site II on time scales relevant to the underlying binding kinetics of most interest.

Concentration sensing in crowded environments

Signal transduction within crowded cellular compartments is essential for the physiological function of cells. Although the accuracy with which receptors can probe the concentration of ligands has been thoroughly investigated in dilute systems, the effect of macromolecular crowding on the inference of concentration remains unclear. In this work, we develop an algorithm to simulate reversible reactions between reacting Brownian particles. Our algorithm facilitates the calculation of reaction rates and correlation times for ligand-receptor systems in the presence of macromolecular crowding. Using this method, we show that it is possible for crowding to increase the accuracy of estimated ligand concentration based on receptor occupancy. In particular, we find that crowding can enhance the effective association rates between small ligands and receptors to a degree sufficient to overcome the increased chance of rebinding due to caging by crowding molecules. For larger ligands, crowding decreases the accuracy of the receptor's estimate primarily by decreasing the microscopic association and dissociation rates.

Kinetics-Driven Drug Design Strategy for Next-Generation Acetylcholinesterase Inhibitors to Clinical Candidate

The acetylcholinesterase (AChE) inhibitors remain key therapeutic drugs for the treatment of Alzheimer's disease (AD). However, the low-safety window limits their maximum therapeutic benefits. Here, a novel kinetics-driven drug design strategy was employed to discover new-generation AChE inhibitors that possess a longer drug-target residence time and exhibit a larger safety window. After detailed investigations, compound 12 was identified as a highly potent, highly selective, orally bioavailable, and brain preferentially distributed AChE inhibitor. Moreover, it significantly ameliorated cognitive impairments in different mouse models with a lower effective dose than donepezil. The X-ray structure of the cocrystal complex provided a precise binding mode between 12 and AChE. Besides, the data from the phase I trials demonstrated that 12 had good safety, tolerance, and pharmacokinetic profiles at all preset doses in healthy volunteers, providing a solid basis for its further investigation in phase II trials for the treatment of AD.

Inhibition of thrombin activity by a covalent-binding aptamer and reversal by the complementary strand antidote

Alleviating the potential risk of irreversible adverse drug effects has been an important and challenging issue for the development of covalent drugs. Here we created a DNA-aptamer-type covalent drug by introducing a sulfonyl fluoride warhead at appropriate positions of the thrombin binding aptamer to create weaponized covalent drugs. We showed the de-activation of thrombin by the novel modality, followed by its re-activation by the complementary strand antidote at an arbitrary time. We envision that such on-demand reversal of covalent drugs will alleviate the major concern of potentially irreversible ADEs and accelerate the translational application of covalent aptamer drugs.

Whole Cell Active Inhibitors of Mycobacterial Lipoamide Dehydrogenase Afford Selectivity over the Human Enzyme through Tight Binding Interactions

Tuberculosis remains a leading cause of death from a single bacterial infection worldwide. Efforts to develop new treatment options call for expansion into an unexplored target space to expand the drug pipeline and bypass resistance to current antibiotics. Lipoamide dehydrogenase is a metabolic and antioxidant enzyme critical for mycobacterial growth and survival in mice. Sulfonamide analogs were previously identified as potent and selective inhibitors of mycobacterial lipoamide dehydrogenase in vitro but lacked activity against whole mycobacteria. Here we present the development of analogs with improved permeability, potency, and selectivity, which inhibit the growth of Mycobacterium tuberculosis in axenic culture on carbohydrates and within mouse primary macrophages. They increase intrabacterial pyruvate levels, supporting their on-target activity within mycobacteria. Distinct modalities of binding between the mycobacterial and human enzymes contribute to improved potency and hence selectivity through induced-fit tight binding interactions within the mycobacterial but not human enzyme, as indicated by kinetic analysis and crystallography.

Drugging DNA Damage Repair Pathways for Trinucleotide Repeat Expansion Diseases

DNA damage repair (DDR) mechanisms have been implicated in a number of neurodegenerative diseases (both genetically determined and sporadic). Consistent with this, recent genome-wide association studies in Huntington’s disease (HD) and other trinucleotide repeat expansion diseases have highlighted genes involved in DDR mechanisms as modifiers for age of onset, rate of progression and somatic instability. At least some clinical genetic modifiers have been shown to have a role in modulating trinucleotide repeat expansion biology and could therefore provide new disease-modifying therapeutic targets. In this review, we focus on key considerations with respect to drug discovery and development using DDR mechanisms as a target for trinucleotide repeat expansion diseases. Six areas are covered with specific reference to DDR and HD: 1) Target identification and validation; 2) Candidate selection including therapeutic modality and delivery; 3) Target drug exposure with particular focus on blood-brain barrier penetration, engagement and expression of pharmacology; 4) Safety; 5) Preclinical models as predictors of therapeutic efficacy; 6) Clinical outcome measures including biomarkers.

Histone Parylation factor 1 contributes to the inhibition of PARP1 by cancer drugs

Poly-(ADP-ribose) polymerase 1 and 2 (PARP1 and PARP2) are key enzymes in the DNA damage response. Four different inhibitors (PARPi) are currently in the clinic for treatment of ovarian and breast cancer. Recently, histone PARylation Factor 1 (HPF1) has been shown to play an essential role in the PARP1- and PARP2-dependent poly-(ADP-ribosylation) (PARylation) of histones, by forming a complex with both enzymes and altering their catalytic properties. Given the proximity of HPF1 to the inhibitor binding site both PARPs, we hypothesized that HPF1 may modulate the affinity of inhibitors toward PARP1 and/or PARP2. Here we demonstrate that HPF1 significantly increases the affinity for a PARP1 - DNA complex of some PARPi (i.e., olaparib), but not others (i.e., veliparib). This effect of HPF1 on the binding affinity of Olaparib also holds true for the more physiologically relevant PARP1 - nucleosome complex but does not extend to PARP2. Our results have important implications for the interpretation of PARP inhibition by current PARPi as well as for the design and analysis of the next generation of clinically relevant PARP inhibitors.

An Oculus to Profile and Probe Target Engagement In Vivo: How T-REX Was Born and Its Evolution into G-REX

Here we provide a personal account of innovation and design principles underpinning a method to interrogate precision electrophile signaling that has come to be known as "REX technologies". This Account is framed in the context of trying to improve methods of target mining and understanding of individual target-ligand engagement by a specific natural electrophile and the ramifications of this labeling event in cells and organisms. We start by explaining from a practical standpoint why gleaning such understanding is critical: we are constantly assailed by a battery of electrophilic molecules that exist as a consequence of diet, food preparation, ineluctable endogenous metabolic processes, and potentially disease. The resulting molecules, which are detectable in the body, appear to be able to modify function of specific proteins. Aside from potentially being biologically relevant in their own right, these labeling events are essentially identical to protein-covalent drug interactions. Thus, on what proteins and even in what ways a covalent drug will work can be understood through the eyes of natural electrophiles; extending this logic leads to the postulate that target identification of specific electrophiles can inform on drug design. However, when we entered this field, there was no way to interrogate how a specific labeling event impacted a specific protein in an unperturbed cell. Methods to evaluate stoichiometry of labeling, and even chemospecificity of a specific phenotype were limited. There were further no generally accepted ways to study electrophile signaling that did not hugely disturb physiology.We developed T-REX, a method to study single-protein-specific electrophile engagement, to interrogate how single-protein electrophile labeling shapes pathway flux. Using T-REX, we discovered that labeling of several proteins by a specific electrophile, even at low occupancy, leads to biologically relevant signaling outputs. Further experimentation using T-REX showed that in some instances, single-protein isoforms were electrophile responsive against other isoforms, such as Akt3. Selective electrophile-labeling of Akt3 elicited inhibition of Akt-pathway flux in cells and in zebrafish embryos. Using these data, we rationally designed a molecule to selectively target Akt3. This was a fusion of the naturally derived electrophile and an isoform-nonspecific, reversible Akt inhibitor in phase-II trials, MK-2206. The resulting molecule was a selective inhibitor of Akt3 and was shown to fare better than MK-2206 in breast cancer xenograft mouse models. Recently, we have also developed a means to screen electrophile sensors that is unbiased and uses a precise burst of electrophiles. Using this method, dubbed G-REX, in conjunction with T-REX, we discovered new DNA-damage response upregulation pathways orchestrated by simple natural electrophiles. We thus emphasize how deriving a quantitative understanding of electrophile signaling that is linked to thorough and precise mechanistic studies can open doors to numerous medicinally and biologically relevant insights, from gleaning better understanding of target engagement and target mining to rational design of targeted covalent medicines.

An innovative kinome platform to accelerate small-molecule inhibitor discovery and optimization from hits to leads

Kinases, accounting for 20% of the human genome, have been the focus of pharmaceutical drug discovery efforts for over three decades. Despite concerns surrounding the tractability of kinases as drug targets, it is evident that kinase drug discovery offers great potential, underscored by the US Food and Drug Administration (FDA) approval of 48 small-molecule kinase inhibitors. Despite these successes, it is challenging to identify novel kinome selective inhibitors with good pharmacokinetic/pharmacodynamic (PK/PD) properties, and resistance to kinase inhibitor treatment frequently arises. A new era of kinase drug discovery predicates the need for diverse and powerful tools to discover the next generation of kinase inhibitors. Here, we outline key tenets of the Bristol Meyers Squibb (BMS) kinase platform, to enable efficient generation of highly optimized kinase inhibitors.

Milling of poorly soluble crystalline drug compounds to generate appropriate particle sizes for inhaled sustained drug delivery

One of the simplest design concepts of inhaled sustained drug delivery to the lung is to utilize the slow dissolution of drug crystals with poor aqueous solubility. An optimum dissolution rate, and thereby a delivery profile locally in the lung tissue, can be achieved in a reliable way by selecting a compound with an appropriate combination of solubility and particle size. It is in our experience relatively straightforward to manufacture monomodal particle size distributions of poorly soluble drug crystals in the mass median diameter range of either a few micrometers or a few hundred nanometers, but very challenging to manufacture a monomodal distribution in the range intermediate to these two. In this manuscript, we describe an investigation with the objective of generating desired particle sizes in the whole size range from a few micrometers to a few hundred nanometers for inhaled sustained drug delivery, by utilizing Adaptive Focused Acoustic (AFA) milling and planetary bead-milling. By combining the two different milling techniques it was possible to produce two to three distinctly different monomodal or almost monomodal particle size distributions in the desired particle size range of each of the model drug compounds in milligram scale. The dissolution kinetics of the different particle sizes of the model drugs were measured experimentally as well as predicted theoretically, showcasing that the dissolution kinetics can be characterized, predicted and significantly changed in a controlled way by modifying the particle size. For one of the model drugs, it was shown in an in vivo rat study that the inhaled sustained drug delivery profile in the lung tissue could be significantly changed by modifying the particle size of the drug.

Qualitative Prediction of Ligand Dissociation Kinetics from Focal Adhesion Kinase Using Steered Molecular Dynamics

Most early-stage drug discovery projects focus on equilibrium binding affinity to the target alongside selectivity and other pharmaceutical properties. Since many approved drugs have nonequilibrium binding characteristics, there has been increasing interest in optimizing binding kinetics early in the drug discovery process. As focal adhesion kinase (FAK) is an important drug target, we examine whether steered molecular dynamics (SMD) can be useful for identifying drug candidates with the desired drug-binding kinetics. In simulating the dissociation of 14 ligands from FAK, we find an empirical power–law relationship between the simulated time needed for ligand unbinding and the experimental rate constant for dissociation, with a strong correlation depending on the SMD force used. To improve predictions, we further develop regression models connecting experimental dissociation rate with various structural and energetic quantities derived from the simulations. These models can be used to predict dissociation rates from FAK for related compounds.

Structural Investigations of the Inhibition of Escherichia coli AmpC β-Lactamase by Diazabicyclooctanes

β-Lactam antibiotics are presently the most important treatments for infections by pathogenic Escherichia coli, but their use is increasingly compromised by β-lactamases, including the chromosomally encoded class C AmpC serine-β-lactamases (SBLs). The diazabicyclooctane (DBO) avibactam is a potent AmpC inhibitor; the clinical success of avibactam combined with ceftazidime has stimulated efforts to optimize the DBO core. We report kinetic and structural studies, including four high-resolution crystal structures, concerning inhibition of the AmpC serine-β-lactamase from E. coli (AmpC _EC ) by clinically relevant DBO-based inhibitors: avibactam, relebactam, nacubactam, and zidebactam. Kinetic analyses and mass spectrometry-based assays were used to study their mechanisms of AmpC _EC inhibition. The results reveal that, under our assay conditions, zidebactam manifests increased potency (apparent inhibition constant [K _iapp], 0.69 μM) against AmpC _EC compared to that of the other DBOs (K _iapp = 5.0 to 7.4 μM) due to an ∼10-fold accelerated carbamoylation rate. However, zidebactam also has an accelerated off-rate, and with sufficient preincubation time, all the DBOs manifest similar potencies. Crystallographic analyses indicate a greater conformational freedom of the AmpC _EC -zidebactam carbamoyl complex compared to those for the other DBOs. The results suggest the carbamoyl complex lifetime should be a consideration in development of DBO-based SBL inhibitors for the clinically important class C SBLs.

An Appraisal of Computer Simulation Approaches in Elucidating Biomolecular Recognition Pathways

Computer simulation approaches in biomolecular recognition processes have come a long way. In this Perspective, we highlight a series of recent success stories in which computer simulations have played a remarkable role in elucidating the atomic resolution mechanism of kinetic processes of protein-ligand binding in a quantitative fashion. In particular, we show that a robust combination of unbiased simulation, harnessed by a high-fidelity computing environment, and Markov state modeling approaches has been instrumental in revealing novel protein-ligand recognition pathways in multiple systems. We also elucidate the role of recent developments in enhanced sampling approaches in providing the much-needed impetus in accelerating simulation of the ligand recognition process. We identify multiple key issues, including force fields and the sampling bottleneck, which are currently preventing the field from achieving quantitative reconstruction of experimental measurements. Finally, we suggest a possible way forward via adoption of multiscale approaches and coarse-grained simulations as next steps toward efficient elucidation of ligand binding kinetics.

A Protocol to Use Comparative Binding Energy Analysis to Estimate Drug-Target Residence Time

Comparative Binding Energy (COMBINE) analysis is an approach for deriving a target-specific scoring function to compute binding free energy, drug-binding kinetics, or a related property by exploiting the information contained in the three-dimensional structures of receptor-ligand complexes. Here, we describe the process of setting up and running COMBINE analysis to derive a Quantitative Structure-Kinetics Relationship (QSKR) for the dissociation rate constants (k_off) of inhibitors of a drug target. The derived QSKR model can be used to estimate residence times (τ, τ=1/k_off) for similar inhibitors binding to the same target, and it can also help to identify key receptor-ligand interactions that distinguish inhibitors with short and long residence times. Herein, we demonstrate the protocol for the application of COMBINE analysis on a dataset of 70 inhibitors of heat shock protein 90 (HSP90) belonging to 11 different chemical classes. The procedure is generally applicable to any drug target with known structural information on its complexes with inhibitors.

Dissecting the molecular determinants of clinical PARP1 inhibitor selectivity for tankyrase1

Poly-ADP-ribosyltransferases play a critical role in DNA repair and cell death, and poly(ADP-ribosyl) polymerase 1 (PARP1) is a particularly important therapeutic target for the treatment of breast cancer because of its synthetic lethal relationship with breast cancer susceptibility proteins 1 and 2. Numerous PARP1 inhibitors have been developed, and their efficacy in cancer treatment is attributed to both the inhibition of enzymatic activity and their ability to trap PARP1 on to the damaged DNA, which is cytotoxic. Of the clinical PARP inhibitors, talazoparib is the most effective at trapping PARP1 on damaged DNA. Biochemically, talazoparib is also suspected to be a potent inhibitor of PARP5a/b (tankyrase1/2 [TNKS1/2]), which is an important regulator of Wnt/β-catenin pathway. Here we show using competition experiments in cell lysate that, at a clinically relevant concentration, talazoparib can potentially bind and engage TNKS1. Using surface plasmon resonance, we measured the dissociation constants of talazoparib, olaparib, niraparib, and veliparib for their interaction with PARP1 and TNKS1. The results show that talazoparib has strong affinity for PARP1 as well as uniquely strong affinity for TNKS1. Finally, we used crystallography and hydrogen deuterium exchange mass spectroscopy to dissect the molecular mechanism of differential selectivity of these PARP1 inhibitors. From these data, we conclude that subtle differences between the ligand-binding sites of PARP1 and TNKS1, differences in the electrostatic nature of the ligands, protein dynamics, and ligand conformational energetics contribute to the different pharmacology of these PARP1 inhibitors. These results will help in the design of drugs to treat Wnt/β-catenin pathway-related cancers, such as colorectal cancers.

Identification and characterization of second-generation EZH2 inhibitors with extended residence times and improved biological activity

The histone methyltransferase EZH2 has been the target of numerous small-molecule inhibitor discovery efforts over the last 10+ years. Emerging clinical data have provided early evidence for single agent activity with acceptable safety profiles for first-generation inhibitors. We have developed kinetic methodologies for studying EZH2-inhibitor-binding kinetics that have allowed us to identify a unique structural modification that results in significant increases in the drug-target residence times of all EZH2 inhibitor scaffolds we have studied. The unexpected residence time enhancement bestowed by this modification has enabled us to create a series of second-generation EZH2 inhibitors with sub-pM binding affinities. We provide both biophysical evidence validating this sub-pM potency and biological evidence demonstrating the utility and relevance of such high-affinity interactions with EZH2.

A general method for quantifying ligand binding to unmodified receptors using Gaussia luciferase

Reliable measurement of ligand binding to cell surface receptors is of outstanding biological and pharmacological importance. Resonance energy transfer-based assays are powerful approaches to achieve this goal, but the currently available methods are hindered by the necessity of receptor tagging, which can potentially alter ligand binding properties. Therefore, we developed a tag-free system to measure ligand‒receptor interactions in live cells using the Gaussia luciferase (GLuc) as a bioluminescence resonance energy transfer donor. GLuc is as small as the commonly applied Nanoluciferase but has enhanced brightness, and its proper substrate is the frequently used coelenterazine. In our assay, bystander bioluminescence resonance energy transfer is detected between a GLuc-based extracellular surface biosensor and fluorescent ligands bound to their unmodified receptors. The broad spectrum of applications includes equilibrium and kinetic ligand binding measurements for both labeled and competitive unlabeled ligands, and the assay can be utilized for different classes of plasma membrane receptors. Furthermore, the assay is suitable for high-throughput screening, as evidenced by the identification of novel α1 adrenergic receptor ligands. Our data demonstrate that GLuc-based biosensors provide a simple, sensitive, and cost-efficient platform for drug characterization and development.

Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development

Molecular dynamics (MD) simulations have become increasingly useful in the modern drug development process. In this review, we give a broad overview of the current application possibilities of MD in drug discovery and pharmaceutical development. Starting from the target validation step of the drug development process, we give several examples of how MD studies can give important insights into the dynamics and function of identified drug targets such as sirtuins, RAS proteins, or intrinsically disordered proteins. The role of MD in antibody design is also reviewed. In the lead discovery and lead optimization phases, MD facilitates the evaluation of the binding energetics and kinetics of the ligand-receptor interactions, therefore guiding the choice of the best candidate molecules for further development. The importance of considering the biological lipid bilayer environment in the MD simulations of membrane proteins is also discussed, using G-protein coupled receptors and ion channels as well as the drug-metabolizing cytochrome P450 enzymes as relevant examples. Lastly, we discuss the emerging role of MD simulations in facilitating the pharmaceutical formulation development of drugs and candidate drugs. Specifically, we look at how MD can be used in studying the crystalline and amorphous solids, the stability of amorphous drug or drug-polymer formulations, and drug solubility. Moreover, since nanoparticle drug formulations are of great interest in the field of drug delivery research, different applications of nano-particle simulations are also briefly summarized using multiple recent studies as examples. In the future, the role of MD simulations in facilitating the drug development process is likely to grow substantially with the increasing computer power and advancements in the development of force fields and enhanced MD methodologies.

Covalent Inhibition of Bacterial Urease by Bifunctional Catechol-Based Phosphonates and Phosphinates

In this study, a new class of bifunctional inhibitors of bacterial ureases, important molecular targets for antimicrobial therapies, was developed. The structures of the inhibitors consist of a combination of a phosphonate or (2-carboxyethyl)phosphinate functionality with a catechol-based fragment, which are designed for complexation of the catalytic nickel ions and covalent bonding with the thiol group of Cys322, respectively. Compounds with three types of frameworks, including β-3,4-dihydroxyphenyl-, α-3,4-dihydroxybenzyl-, and α-3,4-dihydroxybenzylidene-substituted derivatives, exhibited complex and varying structure-dependent kinetics of inhibition. Among irreversible binders, methyl β-(3,4-dihydroxyphenyl)-β-(2-carboxyethyl)phosphorylpropionate was observed to be a remarkably reactive inhibitor of Sporosarcina pasteurii urease (k_inact/K_I = 10 420 s^-1 M^-1). The high potential of this group of compounds was also confirmed in Proteus mirabilis whole-cell-based inhibition assays. Some compounds followed slow-binding and reversible kinetics, e.g., methyl β-(3,4-dihydroxyphenyl)-β-phosphonopropionate, with K_i* = 0.13 μM, and an atypical low dissociation rate (residence time τ = 205 min).

Development of a High-Throughput Affinity Mass Spectrometry (AMS) Platform Using Laser Diode Thermal Desorption Ionization Coupled to Mass Spectrometry (LDTD-MS)

Affinity selection mass spectrometry (MS) or, simply, affinity mass spectrometry (AMS) is a label-free technology that has been used to identify high-affinity ligands of target proteins of interest by screening against small-molecule compound libraries and identifying molecules that are enriched in the presence of the target protein. We have previously applied Agilent Technology's (Santa Clara, CA) RapidFire solid-phase extraction (SPE)-based high-throughput MS technology to screen small-molecule libraries using AMS. However, SPE-based technologies rely on fluidics for desalting and separation prior to mass analysis with attendant high solvent consumption, relatively high sample volume requirements, risk of sample carryover, and frequent maintenance. To address these challenges, we have established an AMS platform using a laser diode thermal desorption-atmospheric pressure chemical ionization (LDTD-APCI) ionization source (Phytronix, Quebec, Canada) coupled with a SCIEX 5600+ TripleTOF MS (Framingham, MA). We also validated a data-independent acquisition (DIA) Sequential Window Acquisition of All Theoretical Mass Spectra (SWATH-MS) method for the robust detection and analysis of small-molecule affinity hits. An informatics platform developed in-house has resulted in a streamlined data analysis workflow for high-throughput AMS screening campaigns and reduced data processing time without compromising data quality. Finally, 68,000 compounds were screened in a single plate and affinity selected hits were confirmed in an orthogonal enzyme activity assay.

New small molecule fluorescent probes for G protein-coupled receptors: valuable tools for drug discovery

G protein-coupled receptors (GPCRs) are essential signaling proteins and tractable therapeutic targets. To develop new drug candidates, GPCR drug discovery programs require versatile, sensitive pharmacological tools for ligand binding and compound screening. With the availability of new imaging modalities and proximity-based ligand binding technologies, fluorescent ligands offer many advantages and are increasingly being used, yet labeling small molecules remains considerably more challenging relative to peptides. Focusing on recent fluorescent small molecule studies for family A GPCRs, this review addresses some of the key challenges, synthesis approaches and structure-activity relationship considerations, and discusses advantages of using high-resolution GPCR structures to inform conjugation strategies. While no single approach guarantees successful labeling without loss of affinity or selectivity, the choice of fluorophore, linker type and site of attachment have proved to be critical factors that can significantly affect their utility in drug discovery programs, and as discussed, can sometimes lead to very unexpected results.

Thermodynamics and Kinetics of Drug-Target Binding by Molecular Simulation

Computational studies play an increasingly important role in chemistry and biophysics, mainly thanks to improvements in hardware and algorithms. In drug discovery and development, computational studies can reduce the costs and risks of bringing a new medicine to market. Computational simulations are mainly used to optimize promising new compounds by estimating their binding affinity to proteins. This is challenging due to the complexity of the simulated system. To assess the present and future value of simulation for drug discovery, we review key applications of advanced methods for sampling complex free-energy landscapes at near nonergodicity conditions and for estimating the rate coefficients of very slow processes of pharmacological interest. We outline the statistical mechanics and computational background behind this research, including methods such as steered molecular dynamics and metadynamics. We review recent applications to pharmacology and drug discovery and discuss possible guidelines for the practitioner. Recent trends in machine learning are also briefly discussed. Thanks to the rapid development of methods for characterizing and quantifying rare events, simulation's role in drug discovery is likely to expand, making it a valuable complement to experimental and clinical approaches.

Inhibitory activity against carbonic anhydrase IX and XII as a candidate selection criterion in the development of new anticancer agents

Analysis of the literature data reveals that while inhibition of cancer-related carbonic anhydrase IX and XII isoforms continues to be an important enrichment factor for designing anticancer agent development libraries, exclusive reliance on the in vitro inhibition of these two recombinant isozymes in nominating candidate compounds for evaluation of their effects on cancer cells may lead not only to identifying numerous compounds devoid of the desired cellular efficacy but also to overlooking many promising candidates which may not display the best potency in biochemical inhibition assay. However, SLC-0111, now in phase Ib/II clinical trials, was developed based on the excellent agreement between the in vitro, in vivo and more recently, in-patient data.

Ranking of Ligand Binding Kinetics Using a Weighted Ensemble Approach and Comparison with a Multiscale Milestoning Approach

To improve lead optimization efforts in finding the right ligand, pharmaceutical industries need to know the ligand's binding kinetics, such as binding and unbinding rate constants, which often correlate with the ligand's efficacy in vivo. To predict binding kinetics efficiently, enhanced sampling methods, such as milestoning and the weighted ensemble (WE) method, have been used in molecular dynamics (MD) simulations of these systems. However, a comparison of these enhanced sampling methods in ranking ligands has not been done. Hence, a WE approach called the concurrent adaptive sampling (CAS) algorithm that uses MD simulations was used to rank seven ligands for β-cyclodextrin, a system in which a multiscale milestoning approach called simulation enabled estimation of kinetic rates (SEEKR) was also used, which uses both MD and Brownian dynamics simulations. Overall, the CAS algorithm can successfully rank ligands using the unbinding rate constant k_off values and binding free energy ΔG values, as SEEKR did, with reduced computational cost that is about the same as SEEKR. We compare the CAS algorithm simulations with different parameters and discuss the impact of parameters in ranking ligands and obtaining rate constant and binding free energy estimates. We also discuss similarities and differences and advantages and disadvantages of SEEKR and the CAS algorithm for future use.

The Active Site of a Prototypical "Rigid" Drug Target is Marked by Extensive Conformational Dynamics

Drug discovery, in particular optimization of candidates using medicinal chemistry, is generally guided by structural biology. However, for optimizing binding kinetics, relevant for efficacy and off-target effects, information on protein motion is important. Herein, we demonstrate for the prototypical textbook example of an allegedly "rigid protein" that substantial active-site dynamics have generally remained unrecognized, despite thousands of medicinal-chemistry studies on this model over decades. Comparing cryogenic X-ray structures, solid-state NMR on micro-crystalline protein at room temperature, and solution NMR structure and dynamics, supported by MD simulations, we show that under physiologically relevant conditions the pocket is in fact shaped by pronounced open/close conformational-exchange dynamics. The study, which is of general significance for pharmacological research, evinces a generic pitfall in drug discovery routines.

Covalent allosteric modulation: An emerging strategy for GPCRs drug discovery

Designing covalent allosteric modulators brings new opportunities to the field of drug discovery towards G-protein-coupled receptors (GPCRs). Targeting an allosteric binding pocket can allow a modulator to have protein subtype selectivity and low drug resistance. Utilizing covalent warheads further enables the modulator to increase the binding potency and extend the duration of action. This review starts with GPCR allosteric modulation to discuss the structural biology of allosteric binding pockets, the different types of allosteric modulators, as well as the advantages of employing allosteric modulation. This is followed by a discussion on covalent modulators to clarify how covalent ligands can benefit the receptor modulation and to illustrate moieties that can commonly be used as covalent warheads. Finally, case studies are presented on designing class A, B, and C GPCR covalent allosteric modulators to demonstrate successful stories on combining allosteric modulation and covalent binding. Limitations and future perspectives are also covered.

8-Epi-xanthatin induces the apoptosis of DU145 prostate carcinoma cells through signal transducer and activator of transcription 3 inhibition and reactive oxygen species generation

Signal transducer and activator of transcription 3 (STAT3) is aberrantly activated in many human cancers. We tried to find STAT3 inhibitors from natural sources and found that Xanthium fruit extracts decreased phosphorylation of STAT3-Y705. 8-Epi-xanthatin (EXT) was isolated from the extracts. When DU145 cancer cells were treated with EXT, p-STAT3-Y705 was decreased with an IC₅₀ of 3.2 μM. EXT decreased the expression of STAT3 target genes, such as cyclin A, cyclin D1, and BCL-2, and induced PARP cleavage, indicating apoptotic cell death. Downregulation of EXT-induced p-STAT3-Y705 was rescued by pretreating DU145 cells with antioxidants, such as N-acetyl-L-cysteine (NAC), indicating that reactive oxygen species (ROS) were involved in the EXT-induced inhibition of STAT3 activation. Furthermore, we proved the association of EXT with STAT3 protein by using a drug affinity responsive target stability (DARTS) assay and a cellular thermal shift assay (CETSA). EXT inhibited proliferation of DU145 cells with a GI₅₀ of 6 μM and reduced tumor growth in mice xenografted with DU145 cells. Immunoblotting showed that phosphorylation of STAT3-Y705 was lower in EXT-treated tumor tissue than in control tissues. Collectively, we found that EXT binds to, and inhibits, STAT3 activation and could be a lead compound for anticancer therapy.

Pseudoirreversible slow-binding inhibition of trypanothione reductase by a protein-protein interaction disruptor

BACKGROUND AND PURPOSE

Peptide P4 was described as a dimerization disruptor of trypanothione reductase (TryR), a homodimeric enzyme essential for survival of trypanosomatids. Determination of the true inhibitory constant (Ki ) for P4 was not achieved because reaction rates continuously decreased with time, even when substrate concentration was kept constant. The aim of this study was to find a suitable kinetic model that could allow characterization of the complex pattern of TryR inhibition caused by P4.

EXPERIMENTAL APPROACH

After showing the slow-binding and pseudoirreversible activity of P4 against Leishmania infantum trypanothione reductase (Li-TryR), analysis of the curvatures of the reaction progress curves at different inhibitor concentrations allowed us to define the apparent inhibitory constants (Kiapp ) at five different substrate concentrations. Analysis of the changes in Kiapp values allowed precise definition of the type of inhibition.

KEY RESULTS

Li-TryR inhibition by P4 requires two sequential steps that involve rapid generation of a reversible enzyme-inhibitor complex followed by a pseudoirreversible slow inactivation of the enzyme. Recovery of enzyme activity after inhibitor dissociation is barely detectable. P4 is a non-competitive pseudoirreversible inhibitor of Li- TryR that displays an overall inhibition constant (Ki* ) smaller than 0.02 μM.

CONCLUSION AND IMPLICATIONS

Li-TryRdimer disruption by peptide P4 is a pseudoirreversible time-dependent process which is non-competitive with respect to the oxidized trypanothione (TS2 ) substrate. Therefore, unlike reversible Li-TryR competitive inhibitors, enzyme inhibition by P4 is not affected by the TS2 accumulation observed during oxidant processes such as the oxidative burst in host macrophages.

The role of NMR in leveraging dynamics and entropy in drug design

Nuclear magnetic resonance (NMR) spectroscopy has contributed to structure-based drug development (SBDD) in a unique way compared to the other biophysical methods. The potency of a ligand binding to a protein is dictated by the binding free energy, which is an intricate interplay between entropy and enthalpy. In addition to providing the atomic resolution structural information, NMR can help to identify protein-ligand interactions that potentially contribute to the enthalpic component of the free energy. NMR can also illuminate dynamic aspects of the interaction, which correspond to the entropic term of the free energy. The ability of NMR to access both terms in the free energy equation stems from the suite of experiments developed to shed light on various aspects that contribute to both entropy and enthalpy, deepening our understanding of the biological function of macromolecules and assisting to target them in physiological conditions. Here we provide a brief account of the contribution of NMR to SBDD, highlighting hallmark examples and discussing the challenges that demand further method development. In the era of integrated biology, the unique ability of NMR to directly ascertain structural and dynamical aspects of macromolecule and monitor changes in these properties upon engaging a ligand can be combined with computational and other structural and biophysical methods to provide a more complete picture of the energetics of drug engagement with the target. Such efforts can be used to engineer better drugs.

Toward in vivo relevant drug design

Current early and preclinical drug discovery are rooted in decades-old empirical principles describing structure-free energy and structure-function relationships under equilibrium conditions that frequently break down under in vivo conditions. Improved prediction of efficacy and toxicity depends on a paradigm shift to in vivo-relevant principles describing the true nonequilibrium/nonlinear dynamic (NLD) nature of cellular systems. Here, we outline a holistic, in vivo-relevant first principles theory ('Biodynamics'), in which cellular function/dysfunction, and pharmaco-/toxicodynamic effects are considered as emergent behaviors of multimolecular systems powered by covalent and noncovalent free energy sources. The reduction to practice of Biodynamics theory consists of in silico simulations performed at the atomistic and molecular systems levels, versus empirical models fit to in vitro data under the classical paradigm.

Discovery and Characterization of BAY 1214784, an Orally Available Spiroindoline Derivative Acting as a Potent and Selective Antagonist of the Human Gonadotropin-Releasing Hormone Receptor as Proven in a First-In-Human Study in Postmenopausal Women

The growth of uterine fibroids is sex hormone-dependent and commonly associated with highly incapacitating symptoms. Most treatment options consist of the control of these hormonal effects, ultimately blocking proliferative estrogen signaling (i.e., oral contraceptives/antagonization of human gonadotropin-releasing hormone receptor [hGnRH-R] activity). Full hGnRH-R blockade, however, results in menopausal symptoms and affects bone mineralization, thus limiting treatment duration or demanding estrogen add-back approaches. To overcome such issues, we aimed to identify novel, small-molecule hGnRH-R antagonists. This led to the discovery of compound BAY 1214784, an orally available, potent, and selective hGnRH-R antagonist. Altering the geminal dimethylindoline core of the initial hit compound to a spiroindoline system significantly improved GnRH-R antagonist potencies across several species, mandatory for a successful compound optimization in vivo. In a first-in-human study in postmenopausal women, once daily treatment with BAY 1214784 effectively lowered plasma luteinizing hormone levels by up to 49%, at the same time being associated with low pharmacokinetic variability and good tolerability.

A snake toxin as a theranostic agent for the type 2 vasopressin receptor

Rationale: MQ1, a snake toxin which targets with high nanomolar affinity and absolute selectivity for the type 2 vasopressin receptor (V2R), is a drug candidate for renal diseases and a molecular probe for imaging cells or organs expressing V2R.

Methods: MQ1's pharmacological properties were characterized and applied to a rat model of hyponatremia. Its PK/PD parameters were determined as well as its therapeutic index. Fluorescently and radioactively labeled MQ1 were chemically synthesized and associated with moderate loss of affinity. MQ1's dynamic biodistribution was monitored by positron emission tomography. Confocal imaging was used to observe the labeling of three cancer cell lines.

Results: The inverse agonist property of MQ1 very efficiently prevented dDAVP-induced hyponatremia in rats with low nanomolar/kg doses and with a very large therapeutic index. PK (plasma MQ1 concentrations) and PD (diuresis) exhibited a parallel biphasic decrease. The dynamic biodistribution showed that MQ1 targets the kidneys and then exhibits a blood and kidney biphasic decrease. Whatever the approach used, we found a T1/2α between 0.9 and 3.8 h and a T1/2β between 25 and 46 h and demonstrated that the kidneys were able to retain MQ1. Finally, the presence of functional V2R expressed at the membrane of cancer cells was, for the first time, demonstrated with a specific fluorescent ligand.

Conclusion: As the most selective V2 binder, MQ1 is a new promising drug for aquaresis-related diseases and a molecular probe to visualize in vitro and in vivo V2R expressed physiologically or under pathological conditions.

Slow-binding reversible inhibitor of acetylcholinesterase with long-lasting action for prophylaxis of organophosphate poisoning

Organophosphorus (OP) compounds represent a serious health hazard worldwide. The dominant mechanism of their action results from covalent inhibition of acetylcholinesterase (AChE). Standard therapy of acute OP poisoning is partially effective. However, prophylactic administration of reversible or pseudo-irreversible AChE inhibitors before OP exposure increases the efficiency of standard therapy. The purpose of the study was to test the duration of the protective effect of a slow-binding reversible AChE inhibitor (C547) in a mouse model against acute exposure to paraoxon (POX). It was shown that the rate of inhibition of AChE by POX in vitro after pre-inhibition with C547 was several times lower than without C547. Ex vivo pre-incubation of mouse diaphragm with C547 significantly prevented the POX-induced muscle weakness. Then it was shown that pre-treatment of mice with C547 at the dose of 0.01 mg/kg significantly increased survival after poisoning by 2xLD50 POX. The duration of the pre-treatment was effective up to 96 h, whereas currently used drug for pre-exposure treatment, pyridostigmine at a dose of 0.15 mg/kg was effective less than 24 h. Thus, long-lasting slow-binding reversible AChE inhibitors can be considered as new potential drugs to increase the duration of pre-exposure treatment of OP poisoning.

An updated patent review of anticancer Hsp90 inhibitors (2013-present)

INTRODUCTION

Heat shock protein 90 (Hsp90) is one of the most critical chaperones amenable to mediating the folding and maturation of more than 300 client proteins. In normal cells, Hsp90 chaperone cycle is required for regulating multiple cellular processes to maintain homeostasis. However, extremely overexpressed Hsp90 in neoplastic cells results in the dysregulation of client proteins, many of which are indispensable to the accumulation of cancer hallmarks, such as infinite proliferation and increased invasiveness. Consequently, modulation of Hsp90 activity has been considered as a potential strategy for cancer treatment.

AREAS COVERED

This review recapitulated recent patents' progress in the development of Hsp90 inhibitors with potent antitumor activities during 2013 to present. Besides, the structural-activity relationships of the patented inhibitors and their structural similarity were also discussed.

EXPERT OPINION

Hsp90, as an anticancer target, has been investigated for several decades. The first generation of Hsp90 inhibitors exhibited potent antitumor activities in preclinical trials but were trapped in different phases of clinical trials. The second generation of Hsp90 inhibitors has been identified with increased specificity and security through structure modification. Moreover, these inhibitors may offer opportunities for studies of Hsp90 chaperone and development of Hsp90 inhibition therapy.

Development of High-Specificity Fluorescent Probes to Enable Cannabinoid Type 2 Receptor Studies in Living Cells

Pharmacological modulation of cannabinoid type 2 receptor (CB₂R) holds promise for the treatment of numerous conditions, including inflammatory diseases, autoimmune disorders, pain, and cancer. Despite the significance of this receptor, researchers lack reliable tools to address questions concerning the expression and complex mechanism of CB₂R signaling, especially in cell-type and tissue-dependent contexts. Herein, we report for the first time a versatile ligand platform for the modular design of a collection of highly specific CB₂R fluorescent probes, used successfully across applications, species, and cell types. These include flow cytometry of endogenously expressing cells, real-time confocal microscopy of mouse splenocytes and human macrophages, as well as FRET-based kinetic and equilibrium binding assays. High CB₂R specificity was demonstrated by competition experiments in living cells expressing CB₂R at native levels. The probes were effectively applied to FACS analysis of microglial cells derived from a mouse model relevant to Alzheimer's disease.

A combination of machine learning and infrequent metadynamics to efficiently predict kinetic rates, transition states, and molecular determinants of drug dissociation from G protein-coupled receptors

Determining the drug-target residence time (RT) is of major interest in drug discovery given that this kinetic parameter often represents a better indicator of in vivo drug efficacy than binding affinity. However, obtaining drug-target unbinding rates poses significant challenges, both computationally and experimentally. This is particularly palpable for complex systems like G Protein-Coupled Receptors (GPCRs) whose ligand unbinding typically requires very long timescales oftentimes inaccessible by standard molecular dynamics simulations. Enhanced sampling methods offer a useful alternative, and their efficiency can be further improved by using machine learning tools to identify optimal reaction coordinates. Here, we test the combination of two machine learning techniques, automatic mutual information noise omission and reweighted autoencoded variational Bayes for enhanced sampling, with infrequent metadynamics to efficiently study the unbinding kinetics of two classical drugs with different RTs in a prototypic GPCR, the μ-opioid receptor. Dissociation rates derived from these computations are within one order of magnitude from experimental values. We also use the simulation data to uncover the dissociation mechanisms of these drugs, shedding light on the structures of rate-limiting transition states, which, alongside metastable poses, are difficult to obtain experimentally but important to visualize when designing drugs with a desired kinetic profile.

A structure-kinetic relationship study using matched molecular pair analysis

The lifetime of a binary drug–target complex is increasingly acknowledged as an important parameter for drug efficacy and safety. With a better understanding of binding kinetics and better knowledge about kinetic parameter optimization, intentionally induced prolongation of the drug–target residence time through structural changes of the ligand could become feasible. In this study we assembled datasets from 21 publications and the K4DD (Kinetic for Drug Discovery) database to conduct large scale data analysis. This resulted in 3812 small molecules annotated to 78 different targets from five protein classes (GPCRs: 273, kinases: 3238, other enzymes: 240, HSPs: 160, ion channels: 45). Performing matched molecular pair (MMP) analysis to further investigate the structure–kinetic relationship (SKR) in this data collection allowed us to identify a fundamental contribution of a ligand's polarity to its association rate, and in selected cases, also to its dissociation rate. However, we furthermore observed that the destabilization of the transition state introduced by increased polarity is often accompanied by simultaneous destabilization of the ground state resulting in an unaffected or even worsened residence time. Supported by a set of case studies, we provide concepts on how to alter ligands in ways to trigger on-rates, off-rates, or both.

A large-scale study employing matched molecular pair (MMP) analysis to uncover the contribution of a compound's polarity to its association and dissociation rates.