Development of SV2A Ligands for Epilepsy Treatment: A Review of Levetiracetam, Brivaracetam, and Padsevonil

Epilepsy is a common neurological disorder that is primarily treated with antiseizure medications (ASMs). Although dozens of ASMs are available in the clinic, approximately 30% of epileptic patients have medically refractory seizures; other limitations in most traditional ASMs include poor tolerability and drug-drug interactions. Therefore, there is an urgent need to develop alternative ASMs. Levetiracetam (LEV) is a first-line ASM that is well tolerated, has promising efficacy, and has little drug-drug interaction. Although it is widely accepted that LEV acts through a unique therapeutic target synaptic vesicle protein (SV) 2A, the molecular basis of its action remains unknown. Even so, the next-generation SV2A ligands against epilepsy based on the structure of LEV have achieved clinical success. This review highlights the research and development (R&D) process of LEV and its analogs, brivaracetam and padsevonil, to provide ideas and experience for the R&D of novel ASMs.

Development of Computational Approaches with a Fragment-Based Drug Design Strategy: In Silico Hsp90 Inhibitors Discovery

A semi-exhaustive approach and a heuristic search algorithm use a fragment-based drug design (FBDD) strategy for designing new inhibitors in an in silico process. A deconstruction reconstruction process uses a set of known Hsp90 ligands for generating new ones. The deconstruction process consists of cutting off a known ligand in fragments. The reconstruction process consists of coupling fragments to develop a new set of ligands. For evaluating the approaches, we compare the binding energy of the new ligands with the known ligands.

Deep scaffold hopping with multimodal transformer neural networks

Scaffold hopping is a central task of modern medicinal chemistry for rational drug design, which aims to design molecules of novel scaffolds sharing similar target biological activities toward known hit molecules. Traditionally, scaffolding hopping depends on searching databases of available compounds that can't exploit vast chemical space. In this study, we have re-formulated this task as a supervised molecule-to-molecule translation to generate hopped molecules novel in 2D structure but similar in 3D structure, as inspired by the fact that candidate compounds bind with their targets through 3D conformations. To efficiently train the model, we curated over 50 thousand pairs of molecules with increased bioactivity, similar 3D structure, but different 2D structure from public bioactivity database, which spanned 40 kinases commonly investigated by medicinal chemists. Moreover, we have designed a multimodal molecular transformer architecture by integrating molecular 3D conformer through a spatial graph neural network and protein sequence information through Transformer. The trained DeepHop model was shown able to generate around 70% molecules having improved bioactivity together with high 3D similarity but low 2D scaffold similarity to the template molecules. This ratio was 1.9 times higher than other state-of-the-art deep learning methods and rule- and virtual screening-based methods. Furthermore, we demonstrated that the model could generalize to new target proteins through fine-tuning with a small set of active compounds. Case studies have also shown the advantages and usefulness of DeepHop in practical scaffold hopping scenarios.

Rational Design of Potent Inhibitors of a Metallohydrolase Using a Fragment-Based Approach

Metallohydrolases form a large group of enzymes that have fundamental importance in a broad range of biological functions. Among them, the purple acid phosphatases (PAPs) have gained attention due to their crucial role in the acquisition and use of phosphate by plants and also as a promising target for novel treatments of bone-related disorders and cancer. To date, no crystal structure of a mammalian PAP with drug-like molecules bound near the active site is available. Herein, we used a fragment-based design approach using structures of a mammalian PAP in complex with the Maybridge^TM fragment CC063346, the amino acid L-glutamine and the buffer molecule HEPES, as well as various solvent molecules to guide the design of highly potent and efficient mammalian PAP inhibitors. These inhibitors have improved aqueous solubility when compared to the clinically most promising PAP inhibitors available to date. Furthermore, drug-like fragments bound in newly discovered binding sites mapped out additional scaffolds for further inhibitor discovery, as well as scaffolds for the design of inhibitors with novel modes of action.

Meta Learning for Low-Resource Molecular Optimization

The goal of molecular optimization (MO) is to discover molecules that acquire improved pharmaceutical properties over a known starting molecule. Despite many recent successes of new approaches for MO, these methods were typically developed for particular properties with rich annotated training examples. Thus, these approaches are difficult to implement in real scenes where only a small amount of pharmaceutical data is usually available due to the expense and significant effort required for the data collection. Here, we propose a new approach, Meta-MO, for molecular optimization with a handful of training samples based on the well-recognized first-order meta-learning algorithms. By using a set of meta tasks with rich training samples, Meta-MO trains a meta model through the meta-learning optimization and adapts the learned model to new low-resource MO tasks. Meta-MO was shown to consistently outperform several pretraining and multitask training procedures, providing an average improvement in the success rate of 4.3% on a large-scale bioactivity data set with diverse target variations. We also observed that Meta-MO resulted in the best performing models across fine-tuning sets with only dozens of samples. To the best of our knowledge, this is the first study to apply meta learning to MO tasks. More importantly, such a strategy could be further extended to many low-resource scenarios in real-world drug design.

SyntaLinker: automatic fragment linking with deep conditional transformer neural networks

Linking fragments to generate a focused compound library for a specific drug target is one of the challenges in fragment-based drug design (FBDD). Hereby, we propose a new program named SyntaLinker, which is based on a syntactic pattern recognition approach using deep conditional transformer neural networks. This state-of-the-art transformer can link molecular fragments automatically by learning from the knowledge of structures in medicinal chemistry databases (e.g. ChEMBL database). Conventionally, linking molecular fragments was viewed as connecting substructures that were predefined by empirical rules. In SyntaLinker, however, the rules of linking fragments can be learned implicitly from known chemical structures by recognizing syntactic patterns embedded in SMILES notations. With deep conditional transformer neural networks, SyntaLinker can generate molecular structures based on a given pair of fragments and additional restrictions. Case studies have demonstrated the advantages and usefulness of SyntaLinker in FBDD.

Optimization of novel reversible Bruton's tyrosine kinase inhibitors identified using Tethering-fragment-based screens

Since the approval of ibrutinib for the treatment of B-cell malignancies in 2012, numerous clinical trials have been reported using covalent inhibitors to target Bruton's tyrosine kinase (BTK) for oncology indications. However, a formidable challenge for the pharmaceutical industry has been the identification of reversible, selective, potent molecules for inhibition of BTK. Herein, we report application of Tethering-fragment-based screens to identify low molecular weight fragments which were further optimized to improve on-target potency and ADME properties leading to the discovery of reversible, selective, potent BTK inhibitors suitable for pre-clinical proof-of-concept studies.

Molecular Insights into the Fungus-Specific Serine/Threonine Protein Phosphatase Z1 in Candida albicans

The opportunistic pathogen Candida is one of the most common causes of nosocomial bloodstream infections. Because candidemia is associated with high mortality rates and because the incidences of multidrug-resistant Candida are increasing, efforts to identify novel targets for the development of potent antifungals are warranted. Here, we describe the structure and function of the first member of a family of protein phosphatases that is specific to fungi, protein phosphatase Z1 (PPZ1) from Candida albicans We show that PPZ1 not only is active but also is as susceptible to inhibition by the cyclic peptide inhibitor microcystin-LR as its most similar human homolog, protein phosphatase 1α (PP1α [GLC7 in the yeast Saccharomyces cerevisiae]). Unexpectedly, we also discovered that, despite its 66% sequence identity to PP1α, the catalytic domain of PPZ1 contains novel structural elements that are not present in PP1α. We then used activity and pulldown assays to show that these structural differences block a large subset of PP1/GLC7 regulatory proteins from effectively binding PPZ1, demonstrating that PPZ1 does not compete with GLC7 for its regulatory proteins. Equally important, these unique structural elements provide new pockets suitable for the development of PPZ1-specific inhibitors. Together, these studies not only reveal why PPZ1 does not negatively impact GLC7 activity in vivo but also demonstrate that the family of fungus-specific phosphatases-especially PPZ1 from C. albicans-are highly suitable targets for the development of novel drugs that specifically target C. albicans without cross-reacting with human phosphatases.

IMPORTANCE

Candida albicans is a medically important human pathogen that is the most common cause of fungal infections in humans. In particular, approximately 46,000 cases of health care-associated candidiasis occur each year in the United States. Because these infections are associated with high mortality rates and because multiple species of Candida are becoming increasingly resistant to antifungals, there are increasing efforts to identify novel targets that are essential for C. albicans virulence. Here we use structural and biochemical approaches to elucidate how a member of a fungus-specific family of enzymes, serine/threonine phosphatase PPZ1, functions in C. albicans We discovered multiple unique features of PPZ1 that explain why it does not cross-react with, and in turn compete for, PP1-specific regulators, a long-standing question in the field. Most importantly, however, these unique features identified PPZ1 as a potential target for the development of novel antifungal therapeutics that will provide new, safe, and potent treatments for candidiasis in humans.

Compound high-quality criteria: a new vision to guide the development of drugs, current situation

For several decades, the pharmaceutical industry has suffered due to major issues such as reductions of the number of FDA approved drugs and biologics. Several analyses have been highlighted that the 'druglikeness' is one of the strategies to improve succeed rates of screening such as, for instance, high-throughput screening (HTS), and then hits (as starting point), leads and clinical candidates. It is clear that the improvement of compound quality accelerates the drug discovery projects. The monitoring of several indices to avoid 'molecular obesity' (ADMET problems) of final drugs from good-quality 'low-fat' starting points represents today a powerful strategy of optimization process. The development of the new guides to find drugs highlighting attempts at improving the attrition rate from hits to final medicines by focusing on how to improve the druggability of hits, leads and drugs during the drug discovery process represents a key approach to design next better generation of medicines.

The Role of Biotin in Bacterial Physiology and Virulence: a Novel Antibiotic Target for Mycobacterium tuberculosis

Biotin is an essential cofactor for enzymes present in key metabolic pathways such as fatty acid biosynthesis, replenishment of the tricarboxylic acid cycle, and amino acid metabolism. Biotin is synthesized de novo in microorganisms, plants, and fungi, but this metabolic activity is absent in mammals, making biotin biosynthesis an attractive target for antibiotic discovery. In particular, biotin biosynthesis plays important metabolic roles as the sole source of biotin in all stages of the Mycobacterium tuberculosis life cycle due to the lack of a transporter for scavenging exogenous biotin. Biotin is intimately associated with lipid synthesis where the products form key components of the mycobacterial cell membrane that are critical for bacterial survival and pathogenesis. In this review we discuss the central role of biotin in bacterial physiology and highlight studies that demonstrate the importance of its biosynthesis for virulence. The structural biology of the known biotin synthetic enzymes is described alongside studies using structure-guided design, phenotypic screening, and fragment-based approaches to drug discovery as routes to new antituberculosis agents.

Evolutions in fragment-based drug design: the deconstruction-reconstruction approach

Recent advances in the understanding of molecular recognition and protein-ligand interactions have facilitated rapid development of potent and selective ligands for therapeutically relevant targets. Over the past two decades, a variety of useful approaches and emerging techniques have been developed to promote the identification and optimization of leads that have high potential for generating new therapeutic agents. Intriguingly, the innovation of a fragment-based drug design (FBDD) approach has enabled rapid and efficient progress in drug discovery. In this critical review, we focus on the construction of fragment libraries and the advantages and disadvantages of various fragment-based screening (FBS) for constructing such libraries. We also highlight the deconstruction-reconstruction strategy by utilizing privileged fragments of reported ligands.

Catalytic activation of pre-substrates via dynamic fragment assembly on protein templates

Sensitive detection of small molecule fragments binding to defined sites of biomacromolecules is still a considerable challenge. Here we demonstrate that protein-binding fragments are able to induce enzymatic reactions on the protein surface via dynamic fragment ligation. Fragments binding to the S1 pocket of serine proteases containing a nitrogen, oxygen or sulphur nucleophile are found to activate electrophilic pre-substrates through a reversible, covalent ligation reaction. The dynamic ligation reaction positions the pre-substrate molecule at the active site of the protein thereby inducing its enzymatic cleavage. Catalytic activation of pre-substrates is confirmed by fluorescence spectroscopy and by high-performance liquid chromatography. The approach is investigated with 3 pre-substrates and 14 protein-binding fragments and the specific activation and the templating effect exerted by the enzyme is quantified for each protease-fragment-pre-substrate combination. The described approach enables the site-specific identification of protein-binding fragments, the functional characterization of enzymatic sites and the quantitative analysis of protein template-assisted ligation reactions.

Replacing sulfa drugs with novel DHPS inhibitors

More research effort needs to be invested in antimicrobial drug development to address the increasing threat of multidrug-resistant organisms. The enzyme DHPS has been a validated drug target for over 70 years as the target for the highly successful sulfa drugs. The use of sulfa drugs has been compromised by the widespread presence of resistant organisms and the adverse side effects associated with their use. Despite the large amount of structural information available for DHPS, few recent publications address the possibility of using this knowledge for novel drug design. This article reviews the relevant papers and patents that report promising new small-molecule inhibitors of DHPS, and discuss these data in light of new insights into the DHPS catalytic mechanism and recently determined crystal structures of DHPS bound to potent small-molecule inhibitors. This new functional understanding confirms that DHPS deserves further consideration as an antimicrobial drug target.

Design and synthesis of potential dual NK(1)/NK(3) receptor antagonists

The tachykinin NK1 and NK3 receptors are a novel drug target for schizophrenia in order to treat not only the positive and cognitive symptoms, but also the associated co-morbid depression and sleep disturbances associated with the disease. A novel class of peptidomimetic derivatives based on a versatile phenylglycine central core was synthesized and tested in vitro as dual NK1/NK3 receptor antagonists. From this series emerged compounds with good NK1 receptor affinity, although only modest dual NK1/NK3 receptor affinity was observed with one of these analogs.

Finding novel pharmaceuticals in the systems biology era using multiple effective drug targets, phenotypic screening and knowledge of transporters: where drug discovery went wrong and how to fix it

Despite the sequencing of the human genome, the rate of innovative and successful drug discovery in the pharmaceutical industry has continued to decrease. Leaving aside regulatory matters, the fundamental and interlinked intellectual issues proposed to be largely responsible for this are: (a) the move from 'function-first' to 'target-first' methods of screening and drug discovery; (b) the belief that successful drugs should and do interact solely with single, individual targets, despite natural evolution's selection for biochemical networks that are robust to individual parameter changes; (c) an over-reliance on the rule-of-5 to constrain biophysical and chemical properties of drug libraries; (d) the general abandoning of natural products that do not obey the rule-of-5; (e) an incorrect belief that drugs diffuse passively into (and presumably out of) cells across the bilayers portions of membranes, according to their lipophilicity; (f) a widespread failure to recognize the overwhelmingly important role of proteinaceous transporters, as well as their expression profiles, in determining drug distribution in and between different tissues and individual patients; and (g) the general failure to use engineering principles to model biology in parallel with performing 'wet' experiments, such that 'what if?' experiments can be performed in silico to assess the likely success of any strategy. These facts/ideas are illustrated with a reasonably extensive literature review. Success in turning round drug discovery consequently requires: (a) decent systems biology models of human biochemical networks; (b) the use of these (iteratively with experiments) to model how drugs need to interact with multiple targets to have substantive effects on the phenotype; (c) the adoption of polypharmacology and/or cocktails of drugs as a desirable goal in itself; (d) the incorporation of drug transporters into systems biology models, en route to full and multiscale systems biology models that incorporate drug absorption, distribution, metabolism and excretion; (e) a return to 'function-first' or phenotypic screening; and (f) novel methods for inferring modes of action by measuring the properties on system variables at all levels of the 'omes. Such a strategy offers the opportunity of achieving a state where we can hope to predict biological processes and the effect of pharmaceutical agents upon them. Consequently, this should both lower attrition rates and raise the rates of discovery of effective drugs substantially.

Identification of Cys255 in HIF-1α as a novel site for development of covalent inhibitors of HIF-1α/ARNT PasB domain protein-protein interaction

The heterodimer HIF-1α (hypoxia inducible factor)/HIF-β (also known as ARNT-aryl hydrocarbon nuclear translocator) is a key mediator of cellular response to hypoxia. The interaction between these monomer units can be modified by the action of small molecules in the binding interface between their C-terminal heterodimerization (PasB) domains. Taking advantage of the presence of several cysteine residues located in the allosteric cavity of HIF-1α PasB domain, we applied a cysteine-based reactomics "hotspot identification" strategy to locate regions of HIF-1α PasB domain critical for its interaction with ARNT. COMPOUND 5 was identified using a mass spectrometry-based primary screening strategy and was shown to react specifically with Cys255 of the HIF-1α PasB domain. Biophysical characterization of the interaction between PasB domains of HIF-1α and ARNT revealed that covalent binding of COMPOUND 5 to Cys255 reduced binding affinity between HIF-1α and ARNT PasB domains approximately 10-fold. Detailed NMR structural analysis of HIF-1α-PasB-COMPOUND 5 conjugate showed significant local conformation changes in the HIF-1α associated with key residues involved in the HIF-1α/ARNT PasB domain interaction as revealed by the crystal structure of the HIF-1α/ARNT PasB heterodimer. Our screening strategy could be applied to other targets to identify pockets surrounding reactive cysteines suitable for development of small molecule modulators of protein function.

The significance of G protein-coupled receptor crystallography for drug discovery

Crucial as molecular sensors for many vital physiological processes, seven-transmembrane domain G protein-coupled receptors (GPCRs) comprise the largest family of proteins targeted by drug discovery. Together with structures of the prototypical GPCR rhodopsin, solved structures of other liganded GPCRs promise to provide insights into the structural basis of the superfamily's biochemical functions and assist in the development of new therapeutic modalities and drugs. One of the greatest technical and theoretical challenges to elucidating and exploiting structure-function relationships in these systems is the emerging concept of GPCR conformational flexibility and its cause-effect relationship for receptor-receptor and receptor-effector interactions. Such conformational changes can be subtle and triggered by relatively small binding energy effects, leading to full or partial efficacy in the activation or inactivation of the receptor system at large. Pharmacological dogma generally dictates that these changes manifest themselves through kinetic modulation of the receptor's G protein partners. Atomic resolution information derived from increasingly available receptor structures provides an entrée to the understanding of these events and practically applying it to drug design. Supported by structure-activity relationship information arising from empirical screening, a unified structural model of GPCR activation/inactivation promises to both accelerate drug discovery in this field and improve our fundamental understanding of structure-based drug design in general. This review discusses fundamental problems that persist in drug design and GPCR structural determination.

Design and synthesis of novel lactate dehydrogenase A inhibitors by fragment-based lead generation

Lactate dehydrogenase A (LDHA) catalyzes the conversion of pyruvate to lactate, utilizing NADH as a cofactor. It has been identified as a potential therapeutic target in the area of cancer metabolism. In this manuscript we report our progress using fragment-based lead generation (FBLG), assisted by X-ray crystallography to develop small molecule LDHA inhibitors. Fragment hits were identified through NMR and SPR screening and optimized into lead compounds with nanomolar binding affinities via fragment linking. Also reported is their modification into cellular active compounds suitable for target validation work.

From fragment screening to in vivo efficacy: optimization of a series of 2-aminoquinolines as potent inhibitors of beta-site amyloid precursor protein cleaving enzyme 1 (BACE1)

Using fragment-based screening of a focused fragment library, 2-aminoquinoline 1 was identified as an initial hit for BACE1. Further SAR development was supported by X-ray structures of BACE1 cocrystallized with various ligands and molecular modeling studies to expedite the discovery of potent compounds. These strategies enabled us to integrate the C-3 side chain on 2-aminoquinoline 1 extending deep into the P2' binding pocket of BACE1 and enhancing the ligand's potency. We were able to improve the BACE1 potency to subnanomolar range, over 10(6)-fold more potent than the initial hit (900 μM). Further elaboration of the physical properties of the lead compounds to those more consistent with good blood-brain barrier permeability led to inhibitors with greatly improved cellular activity and permeability. Compound 59 showed an IC(50) value of 11 nM on BACE1 and cellular activity of 80 nM. This compound was advanced into rat pharmacokinetic and pharmacodynamic studies and demonstrated significant reduction of Aβ levels in cerebrospinal fluid (CSF).

Targeting metalloproteins by fragment-based lead discovery

It has been estimated that nearly one-third of functional proteins contain a metal ion. These constitute a wide variety of possible drug targets including metalloproteinases, dehydrogenases, oxidoreductases, hydrolases, deacetylases, or many others in which the metal ion is either of catalytic or of structural nature. Despite the predominant role of a metal ion in so many classes of drug targets, current high-throughput screening techniques do not usually produce viable hits against these proteins, likely due to the lack of proper metal-binding pharmacophores in the current screening libraries. Herein, we describe a novel fragment-based drug discovery approach using a metal-targeting fragment library that is based on a variety of distinct classes of metal-binding groups designed to reliably anchor the fragments at the target's metal ions. We show that the approach can effectively identify novel, potent and selective agents that can be readily developed into metalloprotein-targeted therapeutics.

Small-molecule inhibitors of IL-2/IL-2R: lessons learned and applied

The IL-2:IL-2R protein-protein interaction is of central importance to both healthy and diseased immune responses, and is one of the earliest examples of successful small-molecule inhibitor discovery against this target class. Drug-like inhibitors of IL-2 have been identified through a combination of fragment discovery, structure-based design, and medicinal chemistry; this discovery approach illustrates the importance of using a diverse range of complementary screening methods and analytical tools to achieve a comprehensive understanding of molecular recognition. The IL-2 story also provides insight into the dynamic nature of protein-protein interaction surfaces, their potential druggability, and the physical and chemical properties of effective small-molecule ligands. These lessons, from IL-2 and similar discovery programs, underscore an increasing awareness of the principles governing the development of drugs for protein-protein interactions.

Design of a multi-purpose fragment screening library using molecular complexity and orthogonal diversity metrics

Fragment Based Drug Discovery (FBDD) continues to advance as an efficient and alternative screening paradigm for the identification and optimization of novel chemical matter. To enable FBDD across a wide range of pharmaceutical targets, a fragment screening library is required to be chemically diverse and synthetically expandable to enable critical decision making for chemical follow-up and assessing new target druggability. In this manuscript, the Pfizer fragment library design strategy which utilized multiple and orthogonal metrics to incorporate structure, pharmacophore and pharmacological space diversity is described. Appropriate measures of molecular complexity were also employed to maximize the probability of detection of fragment hits using a variety of biophysical and biochemical screening methods. In addition, structural integrity, purity, solubility, fragment and analog availability as well as cost were important considerations in the selection process. Preliminary analysis of primary screening results for 13 targets using NMR Saturation Transfer Difference (STD) indicates the identification of uM-mM hits and the uniqueness of hits at weak binding affinities for these targets.

Introduction to fragment-based drug discovery

Fragment-based drug discovery (FBDD) has emerged in the past decade as a powerful tool for discovering drug leads. The approach first identifies starting points: very small molecules (fragments) that are about half the size of typical drugs. These fragments are then expanded or linked together to generate drug leads. Although the origins of the technique date back some 30 years, it was only in the mid-1990s that experimental techniques became sufficiently sensitive and rapid for the concept to be become practical. Since that time, the field has exploded: FBDD has played a role in discovery of at least 18 drugs that have entered the clinic, and practitioners of FBDD can be found throughout the world in both academia and industry. Literally dozens of reviews have been published on various aspects of FBDD or on the field as a whole, as have three books (Jahnke and Erlanson, Fragment-based approaches in drug discovery, 2006; Zartler and Shapiro, Fragment-based drug discovery: a practical approach, 2008; Kuo, Fragment based drug design: tools, practical approaches, and examples, 2011). However, this chapter will assume that the reader is approaching the field with little prior knowledge. It will introduce some of the key concepts, set the stage for the chapters to follow, and demonstrate how X-ray crystallography plays a central role in fragment identification and advancement.

Fragment-Based Screening by Biochemical Assays

Fragment-based screening (FBS) has gained acceptance in the pharmaceutical industry as an attractive approach for the identification of new chemical starting points for drug discovery programs in addition to classical strategies such as high-throughput screening. There is the concern that screening of fragments at high µM concentrations in biochemical assays results in increased false-positive and false-negative rates. Here the authors systematically compare the data quality of FBS obtained by enzyme activity-based fluorescence intensity, fluorescence lifetime, and mobility shift assays with the data quality from surface plasmon resonance (SPR) and nuclear magnetic resonance (NMR) methods. The serine protease trypsin and the matrix metalloprotease MMP12 were selected as model systems. For both studies, 352 fragments were selected each. From the data generated, all 3 biochemical protease assay methods can be used for screening of fragments with low false-negative and low false-positive rates, comparable to those achieved with the SPR-based assays. It can also be concluded that only fragments with a solubility higher than the screening concentration determined by means of NMR should be used for FBS purposes. Extrapolated to 10,000 fragments, the biochemical assays speed up the primary FBS process by approximately a factor of 10 and reduce the protease consumption by approximately 10,000-fold compared to NMR protein observation experiments.

Natural and synthetic inhibitors of kallikrein-related peptidases (KLKs)

Including the true tissue kallikrein KLK1, kallikrein-related peptidases (KLKs) represent a family of fifteen mammalian serine proteases. While the physiological roles of several KLKs have been at least partially elucidated, their activation and regulation remain largely unclear. This obscurity may be related to the fact that a given KLK fulfills many different tasks in diverse fetal and adult tissues, and consequently, the timescale of some of their physiological actions varies significantly. To date, a variety of endogenous inhibitors that target distinct KLKs have been identified. Among them are the attenuating Zn(2+) ions, active site-directed proteinaceous inhibitors, such as serpins and the Kazal-type inhibitors, or the huge, unspecific compartment forming α(2)-macroglobulin. Failure of these inhibitory systems can lead to certain pathophysiological conditions. One of the most prominent examples is the Netherton syndrome, which is caused by dysfunctional domains of the Kazal-type inhibitor LEKTI-1 which fail to appropriately regulate KLKs in the skin. Small synthetic inhibitory compounds and natural polypeptidic exogenous inhibitors have been widely employed to characterize the activity and substrate specificity of KLKs and to further investigate their structures and biophysical properties. Overall, this knowledge leads not only to a better understanding of the physiological tasks of KLKs, but is also a strong fundament for the synthesis of small compound drugs and engineered biomolecules for pharmaceutical approaches. In several types of cancer, KLKs have been found to be overexpressed, which makes them clinically relevant biomarkers for prognosis and monitoring. Thus, down regulation of excessive KLK activity in cancer and in skin diseases by small inhibitor compounds may represent attractive therapeutical approaches.

A rapid oxime linker-based library approach to identification of bivalent inhibitors of the Yersinia pestis protein-tyrosine phosphatase, YopH

A bivalent tethered approach toward YopH inhibitor development is presented that joins aldehydes with mixtures of bis-aminooxy-containing linkers using oxime coupling. The methodology is characterized by its facility and ease of use and its ability to rapidly identify low micromolar affinity inhibitors. The generality of the approach may potentially make it amenable to the development of bivalent inhibitors directed against other phosphatases.

Review article: high-throughput affinity-based technologies for small-molecule drug discovery

High-throughput affinity-based technologies are rapidly growing in use as primary screening methods in drug discovery. In this review, their principles and applications are described and their impact on small-molecule drug discovery is evaluated. In general, these technologies can be divided into 2 groups: those that detect binding interactions by measuring changes to the protein target and those that detect bound compounds. Technologies detecting binding interactions by focusing on the protein have limited throughput but can reveal mechanistic information about the binding interaction; technologies detecting bound compounds have very high throughput, some even significantly higher than current high-throughput screening technologies, but offer limited information about the binding interaction. In addition, the appropriate use of affinity-based technologies is discussed. Finally, nanotechnology is predicted to generate a significant impact on the future of affinity-based technologies.

Analysis of flavonoid-based pharmacophores that inhibit aggrecanases (ADAMTS-4 and ADAMTS-5) and matrix metalloproteinases through the use of topologically constrained peptide substrates

Polyphenolic natural products from green tea and red wine have been identified as metalloproteinase inhibitors. Members from the flavonoid and stilbene families found to possess metalloproteinase inhibitory activities include (-)-epigallocatechin gallate, (-)-epicatechin gallate and piceatannol, but their minimally active pharmacophores have not been evaluated. The present study has examined compounds that are structural components of or structurally related to (-)-epigallocatechin gallate, (-)-epicatechin gallate and piceatannol for inhibition of aggrecanases and four representative matrix metalloproteinases. Piceatannol and pyrogallol were found to inhibit all aggrecanases and matrix metalloproteinases studied, indicating a crucial reliance on multiple hydroxyl groups for (-)-epigallocatechin gallate, (-)-epicatechin gallate and piceatannol activity. Differences in K(i) values for pyrogallol as determined with two structurally distinct substrates indicated the likelihood that this compound binds in a non-competitive modality. Further analysis showed that pyrogallol acts as an exosite inhibitor, consistent with the action of (-)-epigallocatechin gallate. In contrast, piceatannol was shown to be a competitive binding inhibitor and showed no differences in apparent K(i) values as determined by distinct substrates, illustrating the benefits of using two structurally distinct substrates to assist the analysis of protease inhibitors. The compounds identified here could be utilized to develop novel metalloproteinase probes or as fragment components of more active inhibitors.