Fragment Linking Strategies for Structure-Based Drug Design

Structure-Based Design and Development of Phosphine Oxides as a Novel Chemotype for Antibiotics that Dysregulate Bacterial ClpP Proteases

A series of arylsulfones and heteroarylsulfones have previously been demonstrated to dysregulate the conserved bacterial ClpP protease, causing the unspecific degradation of essential cellular housekeeping proteins and ultimately resulting in cell death. A cocrystal structure of a 2-β-sulfonylamide analog, ACP1-06, with Escherichia coli ClpP showed that its 2-pyridyl sulfonyl substituent adopts two orientations in the binding site related through a sulfone bond rotation. From this, a new bis-aryl phosphine oxide scaffold, designated as ACP6, was designed based on a "conformation merging" approach of the dual orientation of the ACP1-06 sulfone. One analog, ACP6-12, exhibited over a 10-fold increase in activity over the parent ACP1-06 compound, and a cocrystal X-ray structure with ClpP confirmed its predicted binding conformation. This allowed for a comparative analysis of how different ligand classes bind to the hydrophobic binding site. The study highlights the successful application of structure-based rational design of novel phosphine oxide-based antibiotics.

Extensive exploration of structure activity relationships for the SARS-CoV-2 macrodomain from shape-based fragment merging and active learning

The macrodomain contained in the SARS-CoV-2 non-structural protein 3 (NSP3) is required for viral pathogenesis and lethality. Inhibitors that block the macrodomain could be a new therapeutic strategy for viral suppression. We previously performed a large-scale X-ray crystallography-based fragment screen and discovered a sub-micromolar inhibitor by fragment linking. However, this carboxylic acid-containing lead had poor membrane permeability and other liabilities that made optimization difficult. Here, we developed a shape-based virtual screening pipeline - FrankenROCS - to identify new macrodomain inhibitors using fragment X-ray crystal structures. We used FrankenROCS to exhaustively screen the Enamine high-throughput screening (HTS) collection of 2.1 million compounds and selected 39 compounds for testing, with the most potent compound having an IC50 value equal to 130 μM. We then paired FrankenROCS with an active learning algorithm (Thompson sampling) to efficiently search the Enamine REAL database of 22 billion molecules, testing 32 compounds with the most potent having an IC50 equal to 220 μM. Further optimization led to analogs with IC50 values better than 10 μM, with X-ray crystal structures revealing diverse binding modes despite conserved chemical features. These analogs represent a new lead series with improved membrane permeability that is poised for optimization. In addition, the collection of 137 X-ray crystal structures with associated binding data will serve as a resource for the development of structure-based drug discovery methods. FrankenROCS may be a scalable method for fragment linking to exploit ever-growing synthesis-on-demand libraries.

Structure-Informed Design of an Ultra Bright RNA-activated Fluorophore

Fluorogenic RNAs such as the Mango aptamers are uniquely powerful tools for imaging RNA. A central challenge has been to develop brighter, more specific, and higher affinity aptamer-ligand systems for cellular imaging. Here, we report an ultra-bright fluorophore for the Mango II system discovered using a structure-informed, fragment-based small molecule microarray approach. The new dye, Structure informed, Array-enabled LigAnD 1 (SALAD1) exhibits 3.5-fold brighter fluorescence than TO1-Biotin and subnanomolar aptamer affinity. Improved performance comes solely from alteration of dye-RNA interactions, without alteration of the chromophore itself. Multiple high-resolution structures reveal a unique and specific binding mode for the new dye resulting from improved pocket occupancy, a more defined binding pose, and a novel bonding interaction with potassium. The dye notably improves in-cell confocal RNA imaging. This work provides both introduces a new RNA-activated fluorophore and also a powerful demonstration of how to leverage fragment-based ligand discovery against RNA targets.

Using DNA-encoded libraries of fragments for hit discovery of challenging therapeutic targets

INTRODUCTION

The effectiveness of Fragment-based drug design (FBDD) for targeting challenging therapeutic targets has been hindered by two factors: the small library size and the complexity of the fragment-to-hit optimization process. The DNA-encoded library (DEL) technology offers a compelling and robust high-throughput selection approach to potentially address these limitations.

AREA COVERED

In this review, the authors propose the viewpoint that the DEL technology matches perfectly with the concept of FBDD to facilitate hit discovery. They begin by analyzing the technical limitations of FBDD from a medicinal chemistry perspective and explain why DEL may offer potential solutions to these limitations. Subsequently, they elaborate in detail on how the integration of DEL with FBDD works. In addition, they present case studies involving both de novo hit discovery and full ligand discovery, especially for challenging therapeutic targets harboring broad drug-target interfaces.

EXPERT OPINION

The future of DEL-based fragment discovery may be promoted by both technical advances and application scopes. From the technical aspect, expanding the chemical diversity of DEL will be essential to achieve success in fragment-based drug discovery. From the application scope side, DEL-based fragment discovery holds promise for tackling a series of challenging targets.

Design, quality and validation of the EU-OPENSCREEN fragment library poised to a high-throughput screening collection

The EU-OPENSCREEN (EU-OS) European Research Infrastructure Consortium (ERIC) is a multinational, not-for-profit initiative that integrates high-capacity screening platforms and chemistry groups across Europe to facilitate research in chemical biology and early drug discovery. Over the years, the EU-OS has assembled a high-throughput screening compound collection, the European Chemical Biology Library (ECBL), that contains approximately 100 000 commercially available small molecules and a growing number of thousands of academic compounds crowdsourced through our network of European and non-European chemists. As an extension of the ECBL, here we describe the computational design, quality control and use case screenings of the European Fragment Screening Library (EFSL) composed of 1056 mini and small chemical fragments selected from a substructure analysis of the ECBL. Access to the EFSL is open to researchers from both academia and industry. Using EFSL, eight fragment screening campaigns using different structural and biophysical methods have successfully identified fragment hits in the last two years. As one of the highlighted projects for antibiotics, we describe the screening by Bio-Layer Interferometry (BLI) of the EFSL, the identification of a 35 μM fragment hit targeting the beta-ketoacyl-ACP synthase 2 (FabF), its binding confirmation to the protein by X-ray crystallography (PDB 8PJ0), its subsequent rapid exploration of its surrounding chemical space through hit-picking of ECBL compounds that contain the fragment hit as a core substructure, and the final binding confirmation of two follow-up hits by X-ray crystallography (PDB 8R0I and 8R1V).

Deciphering the Lexicon of Protein Targets: A Review on Multifaceted Drug Discovery in the Era of Artificial Intelligence

Understanding protein sequence and structure is essential for understanding protein-protein interactions (PPIs), which are essential for many biological processes and diseases. Targeting protein binding hot spots, which regulate signaling and growth, with rational drug design is promising. Rational drug design uses structural data and computational tools to study protein binding sites and protein interfaces to design inhibitors that can change these interactions, thereby potentially leading to therapeutic approaches. Artificial intelligence (AI), such as machine learning (ML) and deep learning (DL), has advanced drug discovery and design by providing computational resources and methods. Quantum chemistry is essential for drug reactivity, toxicology, drug screening, and quantitative structure-activity relationship (QSAR) properties. This review discusses the methodologies and challenges of identifying and characterizing hot spots and binding sites. It also explores the strategies and applications of artificial-intelligence-based rational drug design technologies that target proteins and protein-protein interaction (PPI) binding hot spots. It provides valuable insights for drug design with therapeutic implications. We have also demonstrated the pathological conditions of heat shock protein 27 (HSP27) and matrix metallopoproteinases (MMP2 and MMP9) and designed inhibitors of these proteins using the drug discovery paradigm in a case study on the discovery of drug molecules for cancer treatment. Additionally, the implications of benzothiazole derivatives for anticancer drug design and discovery are deliberated.

Fragment growth-based discovery of novel TNIK inhibitors for the treatment of colorectal cancer

Traf2-and Nck-interacting protein kinase (TNIK) plays an important role in regulating signal transduction of the Wnt/β-catenin pathway and is considered an important target for the treatment of colorectal cancer. Inhibiting TNIK has potential to block abnormal Wnt/β-catenin signal transduction caused by colorectal cancer mutations. We discovered a series of 6-(1-methyl-1H-imidazole-5-yl) quinoline derivatives as TNIK inhibitors through Deep Fragment Growth and virtual screening. Among them, 35b exhibited excellent TNIK kinase and HCT116 cell inhibitory activity with IC50 values of 6 nM and 2.11 μM, respectively. 35b also shown excellent kinase selectivity, PK profiles, and oral bioavailability (84.64%). At a p. o. dosage of 50 mg/kg twice daily 35b suppressed tumor growth on the HCT116 xenograft model. Taken together, 35b is a promising lead compound of TNIK inhibitors, which merits further investigation.

A Novel NMR-Based Protocol to Screen Ultralow Molecular Weight Fragments

Fragment-based lead discovery has emerged as one of the most efficient screening strategies for finding hit molecules in drug discovery. Recently, a novel strategy based on a class of fragments characterized by an ultralow molecular weight (ULMW) has been proposed. These fragments bind to the target with a very low affinity, requiring reliable biophysical methods for detection. The most notable application of ULMW used a set of 81 fragments, named MiniFrags, and screened them by X-ray crystallography. We extended the utilization of this novel class of fragments to another gold standard technique for fragment-based screening: nuclear magnetic resonance (NMR). Here, we present a novel NMR protocol to detect and analyze such weak interactions in a challenging real-world scenario: a flexible target with a flat, water-exposed binding site. We identified a subset of 69 highly water-soluble MiniFrags that were screened against the antiapoptotic protein human Bfl-1.

Target-based drug design strategies to overcome resistance to antiviral agents: opportunities and challenges

Viral infections have a major impact in human health. Ongoing viral transmission and escalating selective pressure have the potential to favor the emergence of vaccine- and antiviral drug-resistant viruses. Target-based approaches for the design of antiviral drugs can play a pivotal role in combating drug-resistant challenges. Drug design computational tools facilitate the discovery of novel drugs. This review provides a comprehensive overview of current drug design strategies employed in the field of antiviral drug resistance, illustrated through the description of a series of successful applications. These strategies include technologies that enhance compound-target affinity while minimizing interactions with mutated binding pockets. Furthermore, emerging approaches such as virtual screening, targeted protein/RNA degradation, and resistance analysis during drug design have been harnessed to curtail the emergence of drug resistance. Additionally, host targeting antiviral drugs offer a promising avenue for circumventing viral mutation. The widespread adoption of these refined drug design strategies will effectively address the prevailing challenge posed by antiviral drug resistance.

Linking ATP and allosteric sites to achieve superadditive binding with bivalent EGFR kinase inhibitors

Bivalent molecules consisting of groups connected through bridging linkers often exhibit strong target binding and unique biological effects. However, developing bivalent inhibitors with the desired activity is challenging due to the dual motif architecture of these molecules and the variability that can be introduced through differing linker structures and geometries. We report a set of alternatively linked bivalent EGFR inhibitors that simultaneously occupy the ATP substrate and allosteric pockets. Crystal structures show that initial and redesigned linkers bridging a trisubstituted imidazole ATP-site inhibitor and dibenzodiazepinone allosteric-site inhibitor proved successful in spanning these sites. The re-engineered linker yielded a compound that exhibited significantly higher potency (~60 pM) against the drug-resistant EGFR L858R/T790M and L858R/T790M/C797S, which was superadditive as compared with the parent molecules. The enhanced potency is attributed to factors stemming from the linker connection to the allosteric-site group and informs strategies to engineer linkers in bivalent agent design.

Recent developments of P-glycoprotein inhibitors and its structure-activity relationship (SAR) studies

P-glycoprotein (P-gp) over-expression is a key factor in multi-drug resistance (MDR), which is a major factor in the failure of cancer treatment. P-gp inhibitors have been demonstrated to have powerful pharmacological properties and may be used as a therapeutic approach to overcome the MDR in cancer cells. Combining clinical investigations with biochemical and computational research may potentially lead to a clearer understanding of the pharmacological properties and the mechanisms of action of these P-gp inhibitors. The task of turning these discoveries into effective therapeutic candidates for a variety of malignancies, including resistant and metastatic kinds, falls on medicinal chemists. A variety of P-gp inhibitors with great potency, high selectivity, and minimal toxicity have been identified in recent years. The latest advances in drug design, characterization, structure-activity relationship (SAR) research, and modes of action of newly synthesized, powerful small molecules P-gp inhibitors over the previous ten years are highlighted in this review. P-gp transporter over-expression has been linked to MDR, therefore the development of P-gp inhibitors will expand our understanding of the processes and functions of P-gp-mediated drug efflux, which will be helpful for drug discovery and clinical cancer therapies.

Dibenzylideneacetone Overcomes Botrytis cinerea Infection in Cherry Tomatoes by Inhibiting Chitinase Activity

Chitinase, a crucial component of the fungal cell wall and septa, plays an important role in fungal germination by hydrolyzing chitin to provide carbon and energy for fungal growth and reproduction. In this study, we initially screened dibenzylideneacetone (DBA), a small molecule with inhibitory activity against Botrytis cinerea Chitinase, exhibiting an IC50 of 13.10 μg/mL. By constructing a three-dimensional (3D) model of the B. cinerea Chitinase and utilizing computational biology approaches, we found DBA bound to the active site pocket and formed strong π-π interactions and hydrophobic interactions with Chitinase, indicative of its competitive inhibitory mode. Site-directed mutagenesis also revealed that TRP-382, TRP-135, and ALA-215 were key amino acid residues involved in DBA binding. Subsequent antifungal assays showed that DBA had an MIC of 32 μg/mL against B. cinerea and EC50 values of 16.29 and 14.64 μg/mL in inhibiting mycelial growth and spore germination, respectively. Importantly, in vivo experiments demonstrated that DBA treatment significantly extended the shelf life of cherry tomatoes by 2-fold. Therefore, DBA represents a promising antifungal agent for fruit preservation applications.

Light-Driven Enantioselective Carbene-Catalyzed Radical-Radical Coupling

An enantioselective carbene-catalyzed radical-radical coupling of acyl imidazoles and racemic Hantzsch esters is disclosed. This method involves the coupling of an N-heterocyclic carbene-derived ketyl radical and a secondary sp3 -carbon radical and allows access to chiral α-aryl aliphatic ketones in moderate-to-good yields and enantioselectivities without any competitive epimerization. The utility of this protocol is highlighted by the late-stage functionalization of various pharmaceutical compounds and is further demonstrated by the transformation of the enantioenriched products to biologically relevant molecules. Computational investigations reveal the N-heterocyclic carbene controls the double-facial selectivity of the ketyl radical and the alkyl radicals, respectively.

Assembly of spirocyclic pyrazolone-pyrrolo[4,3,2-de]quinoline skeleton via cascade [1,5] hydride transfer/cyclization by C(sp3)-H functionalization

Herein, a highly efficient, scalable, and cascade [1,5] hydride transfer/cyclization method for constructing unique spirocyclic pyrazolone-pyrrolo[4,3,2-de]quinoline structures via C(sp3)-H functionalization is achieved, using pyrazolones and oxindoles attached to C4 amines. This strategy represents a limited approach utilizing C-H activation to construct spirocyclic pyrazolone scaffolds with moderate to excellent reaction performance.

Linking ATP and allosteric sites to achieve superadditive binding with bivalent EGFR kinase inhibitors

Bivalent molecules consisting of groups connected through bridging linkers often exhibit strong target binding and unique biological effects. However, developing bivalent inhibitors with the desired activity is challenging due to the dual motif architecture of these molecules and the variability that can be introduced through differing linker structures and geometries. We report a set of alternatively linked bivalent EGFR inhibitors that simultaneously occupy the ATP substrate and allosteric pockets. Crystal structures show that initial and redesigned linkers bridging a trisubstituted imidazole ATP-site inhibitor and dibenzodiazepinone allosteric-site inhibitor proved successful in spanning these sites. The reengineered linker yielded a compound that exhibited significantly higher potency (~60 pM) against the drug-resistant EGFR L858R/T790M and L858R/T790M/C797S, which was superadditive as compared with the parent molecules. The enhanced potency is attributed to factors stemming from the linker connection to the allosteric-site group and informs strategies to engineer linkers in bivalent agent design.

Advancement of Computational Design Drug Delivery System in COVID-19: Current Updates and Future Crosstalk- A Critical update

Positive strides have been achieved in developing vaccines to combat the coronavirus-2019 infection (COVID-19) pandemic. Still, the outline of variations, particularly the most current delta divergent, has posed significant health encounters for people. Therefore, developing strong treatment strategies, such as an anti-COVID-19 medicine plan, may help deal with the pandemic more effectively. During the COVID-19 pandemic, some drug design techniques were effectively used to develop and substantiate relevant critical medications. Extensive research, both experimental and computational, has been dedicated to comprehending and characterizing the devastating COVID-19 disease. The urgency of the situation has led to the publication of over 130,000 COVID-19-related research papers in peer-reviewed journals and preprint servers. A significant focus of these efforts has been the identification of novel drug candidates and the repurposing of existing drugs to combat the virus. Many projects have utilized computational or computer-aided approaches to facilitate their studies. In this overview, we will explore the key computational methods and their applications in the discovery of small-molecule therapeutics for COVID-19, as reported in the research literature. We believe that the true effectiveness of computational tools lies in their ability to provide actionable and experimentally testable hypotheses, which in turn facilitate the discovery of new drugs and combinations thereof. Additionally, we recognize that open science and the rapid sharing of research findings are vital in expediting the development of much-needed therapeutics for COVID-19.

Linkers in fragment-based drug design: an overview of the literature

INTRODUCTION

In fragment-based drug design, fragment linking is a popular strategy where two fragments binding to different sub-pockets of a target are linked together. This attractive method remains challenging especially due to the design of ideal linkers.

AREAS COVERED

The authors review the types of linkers and chemical reactions commonly used to the synthesis of linkers, including those utilized in protein-templated fragment self-assembly, where fragments are directly linked in the presence of the protein. Finally, they detail computational workflows and software including generative models that have been developed for fragment linking.

EXPERT OPINION

The authors believe that fragment linking offers key advantages for compound design, particularly for the design of bivalent inhibitors linking two distinct pockets of the same or different subunits. On the other hand, more studies are needed to increase the potential of protein-templated approaches in FBDD. Important computational tools such as structure-based de novo software are emerging to select suitable linkers. Fragment linking will undoubtedly benefit from developments in computational approaches and machine learning models.

Fragment-Based Dynamic Combinatorial Chemistry for Identification of Selective α-Glucosidase Inhibitors

Efforts to combine advantages of fragment-based drug design (FBDD) and dynamic combinatorial chemistry (DCC) for the development of selective α-glucosidase inhibitors were described. Starting from 5 rationally designed fragments, two iterative dynamic combinatorial libraries (DCLs) comprising 29 acylhydrazone products were generated and screened using α-glucosidase and α-amylase as the templates. The optimal ligand identified showed substantial α-glucosidase inhibition with high selectivity over α-amylase as well as low cytotoxicity. Furthermore, inhibition type and detailed ligand/enzyme binding interactions were elucidated by the binding kinetic study and docking simulation, respectively.

Fragment-based drug discovery-the importance of high-quality molecule libraries

Fragment-based drug discovery (FBDD) is now established as a complementary approach to high-throughput screening (HTS). Contrary to HTS, where large libraries of drug-like molecules are screened, FBDD screens involve smaller and less complex molecules which, despite a low affinity to protein targets, display more 'atom-efficient' binding interactions than larger molecules. Fragment hits can, therefore, serve as a more efficient start point for subsequent optimisation, particularly for hard-to-drug targets. Since the number of possible molecules increases exponentially with molecular size, small fragment libraries allow for a proportionately greater coverage of their respective 'chemical space' compared with larger HTS libraries comprising larger molecules. However, good library design is essential to ensure optimal chemical and pharmacophore diversity, molecular complexity, and physicochemical characteristics. In this review, we describe our views on fragment library design, and on what constitutes a good fragment from a medicinal and computational chemistry perspective. We highlight emerging chemical and computational technologies in FBDD and discuss strategies for optimising fragment hits. The impact of novel FBDD approaches is already being felt, with the recent approval of the covalent KRASG12C inhibitor sotorasib highlighting the utility of FBDD against targets that were long considered undruggable.

The IQA Energy Partition in a Drug Design Setting: A Hepatitis C Virus RNA-Dependent RNA Polymerase (NS5B) Case Study

The interaction of the thumb site II of the NS5B protein of hepatitis C virus and a pair of drug candidates was studied using a topological energy decomposition method called interacting quantum atoms (IQA). The atomic energies were then processed by the relative energy gradient (REG) method, which extracts chemical insight by computation based on minimal assumptions. REG reveals the most important IQA energy contributions, by atom and energy type (electrostatics, sterics, and exchange–correlation), that are responsible for the behaviour of the whole system, systematically from a short-range ligand–pocket interaction until a distance of approximately 22 Å. The degree of covalency in various key interatomic interactions can be quantified. No exchange–correlation contribution is responsible for the changes in the energy profile of both pocket–ligand systems investigated in the ligand–pocket distances equal to or greater than that of the global minimum. Regarding the hydrogen bonds in the system, a “neighbour effect” was observed thanks to the REG method, which states that a carbon atom would rather not have its covalent neighbour oxygen form a hydrogen bond. The combination of IQA and REG enables the automatic identification of the pharmacophore in the ligands. The coarser Interacting Quantum Fragments (IQF) enables the determination of which amino acids of the pocket contribute most to the binding and the type of energy of said binding. This work is an example of the contribution topological energy decomposition methods can make to fragment-based drug design.

Targeting the ubiquitin system by fragment-based drug discovery

The ubiquitin system contains a wealth of potential drug targets for many diseases and conditions, including neurodegenerative, immune, metabolic and developmental diseases, as well as multiple cancers. Despite years of research, relatively few clinical inhibitors or specific chemical probes for proteins within the ubiquitin system exist, with many interesting target proteins yet to be explored. Fragment-based drug discovery (FBDD) offers efficient and broad coverage of chemical space with small libraries, using covalent and non-covalent approaches. Coupled with advances in structural biology and proteomics, FBDD now provides a thorough screening platform for inhibitor discovery within the ubiquitin system. In this mini review, we summarise the current scope of FBDD and how it has been applied to ubiquitin-activating (E1), ubiquitin-conjugating (E2), ubiquitin ligase (E3) and deubiquitinating (DUB) enzymes. We also discuss the newest frontiers of FBDD and how they could be applied to enable inhibitor and novel chemical probe discovery and provide functional insight into the ubiquitin system.

Development of urease inhibitors by fragment-based dynamic combinatorial chemistry

In this study, fragment-based dynamic combinatorial chemistry (DCC) was explored for the development of novel urease inhibitors. Based on a rationally designed fragment, two iteratively evolved dynamic combinatorial libraries (DCLs) were generated and screened in the presence of urease template. The best ligand identified revealed not only strong urease inhibition but also low cytotoxicity. Additionally, possible inhibitory mechanism was elucidated in the binding kinetic study and docking simulation.

Development of potent inhibitors by fragment-linking strategies

Fragment-based drug discovery (FBDD) is a method of identifying small molecule hits that can be elaborated rationally through fragment growing, merging, and linking, to afford high affinity ligands for biological targets. Despite the promised theoretical potential of fragment linking, examples are still surprisingly sparse and remain overshadowed by the successes of fragment growing. The aim of this review is to outline a number of key examples of fragment linking strategies and discuss their strengths and limitations. Structure-based approaches including X-ray crystallography and in silico methods fragment optimisation are discussed, as well as fragment linking guided by NMR experiments. Target-guided approaches, exploiting the biological target to assemble its own inhibitors through dynamic combinatorial chemistry (DCC) and kinetic target-guided synthesis (KTGS), are identified as alternative efficient methods for fragment linking.

Development of nano Bio LC columns for the search of acethylcholinesterase molecular targets

A novel acetylcholinesterase (AChE) Nano LC capillary column (75μm i.d * 50 mm length) was developed for the fast screening of AChE inhibitors and the evaluation of their molecular recognition mechanism. Biotinylated AChE was immobilized on a streptavidin Nano LC capillary column. Because of the very strong streptavidin biotin interaction, the AChE immobilization step performed by frontal analysis is very fast (required less than 10 min) and the amount of immobilized AChE was in the microgram range (1μg). The yellow anion obtained from the enzymatic reaction detected at 412 nm was achieved within 60 s and the immobilized acetylcholinesterase retained 96% of the initial activity beyond 90 days. This column was successfully applied for the discrimination of weak affinity ligands to AChE from non-binders which is the heart of the Fragment Based Drug Design (FBDD). This column was used for the determination of the IC₅₀ values of a series of inhibitor molecules. In addition, it was demonstrated that competitive experiments could be performed with our miniaturized system to confirm the existence and the binding pocket of a ligand to AChE contained in a methanol plant extract. The results revealed that our AChE Nano LC capillary column developed in this work represents a useful tool for the rapid screening of inhibitor candidates and evaluation of action mechanism. This article is protected by copyright. All rights reserved.

Using Structure-guided Fragment-Based Drug Discovery to Target Pseudomonas aeruginosa Infections in Cystic Fibrosis

Cystic fibrosis (CF) is progressive genetic disease that predisposes lungs and other organs to multiple long-lasting microbial infections. Pseudomonas aeruginosa is the most prevalent and deadly pathogen among these microbes. Lung function of CF patients worsens following chronic infections with P. aeruginosa and is associated with increased mortality and morbidity. Emergence of multidrug-resistant, extensively drug-resistant and pandrug-resistant strains of P. aeruginosa due to intrinsic and adaptive antibiotic resistance mechanisms has failed the current anti-pseudomonal antibiotics. Hence new antibacterials are urgently needed to treat P. aeruginosa infections. Structure-guided fragment-based drug discovery (FBDD) is a powerful approach in the field of drug development that has succeeded in delivering six FDA approved drugs over the past 20 years targeting a variety of biological molecules. However, FBDD has not been widely used in the development of anti-pseudomonal molecules. In this review, we first give a brief overview of our structure-guided FBDD pipeline and then give a detailed account of FBDD campaigns to combat P. aeruginosa infections by developing small molecules having either bactericidal or anti-virulence properties. We conclude with a brief overview of the FBDD efforts in our lab at the University of Cambridge towards targeting P. aeruginosa infections.

Substrate-Inspired Fragment Merging and Growing Affords Efficacious LasB Inhibitors

Extracellular virulence factors have emerged as attractive targets in the current antimicrobial resistance crisis. The Gram-negative pathogen Pseudomonas aeruginosa secretes the virulence factor elastase B (LasB), which plays an important role in the infection process. Here, we report a sub-micromolar, non-peptidic, fragment-like inhibitor of LasB discovered by careful visual inspection of structural data. Inspired by the natural LasB substrate, the original fragment was successfully merged and grown. The optimized inhibitor is accessible via simple chemistry and retained selectivity with a substantial improvement in activity, which can be rationalized by the crystal structure of LasB in complex with the inhibitor. We also demonstrate an improved in vivo efficacy of the optimized hit in Galleria mellonella larvae, highlighting the significance of this class of compounds as promising drug candidates.

Peptide Tethering: Pocket-Directed Fragment Screening for Peptidomimetic Inhibitor Discovery

Constrained peptides have proven to be a rich source of ligands for protein surfaces, but are often limited in their binding potency. Deployment of nonnatural side chains that access unoccupied crevices on the receptor surface offers a potential avenue to enhance binding affinity. We recently described a computational approach to create topographic maps of protein surfaces to guide the design of nonnatural side chains [J. Am. Chem. Soc. 2017, 139, 15560]. The computational method, AlphaSpace, was used to predict peptide ligands for the KIX domain of the p300/CBP coactivator. KIX has been the subject of numerous ligand discovery strategies, but potent inhibitors of its interaction with transcription factors remain difficult to access. Although the computational approach provided a significant enhancement in the binding affinity of the peptide, fine-tuning of nonnatural side chains required an experimental screening method. Here we implement a peptide-tethering strategy to screen fragments as nonnatural side chains on conformationally defined peptides. The combined computational-experimental approach offers a general framework for optimizing peptidomimetics as inhibitors of protein-protein interactions.

Computational anti-COVID-19 drug design: progress and challenges

Vaccines have made gratifying progress in preventing the 2019 coronavirus disease (COVID-19) pandemic. However, the emergence of variants, especially the latest delta variant, has brought considerable challenges to human health. Hence, the development of robust therapeutic approaches, such as anti-COVID-19 drug design, could aid in managing the pandemic more efficiently. Some drug design strategies have been successfully applied during the COVID-19 pandemic to create and validate related lead drugs. The computational drug design methods used for COVID-19 can be roughly divided into (i) structure-based approaches and (ii) artificial intelligence (AI)-based approaches. Structure-based approaches investigate different molecular fragments and functional groups through lead drugs and apply relevant tools to produce antiviral drugs. AI-based approaches usually use end-to-end learning to explore a larger biochemical space to design antiviral drugs. This review provides an overview of the two design strategies of anti-COVID-19 drugs, the advantages and disadvantages of these strategies and discussions of future developments.

Fragment-to-Lead Medicinal Chemistry Publications in 2020

Fragment-based drug discovery (FBDD) continues to evolve and make an impact in the pharmaceutical sciences. We summarize successful fragment-to-lead studies that were published in 2020. Having systematically analyzed annual scientific outputs since 2015, we discuss trends and best practices in terms of fragment libraries, target proteins, screening technologies, hit-optimization strategies, and the properties of hit fragments and the leads resulting from them. As well as the tabulated Fragment-to-Lead (F2L) programs, our 2020 literature review identifies several trends and innovations that promise to further increase the success of FBDD. These include developing structurally novel screening fragments, improving fragment-screening technologies, using new computer-aided design and virtual screening approaches, and combining FBDD with other innovative drug-discovery technologies.

Design, synthesis, and biological evaluation of N-(3-cyano-1H-indol-5/6-yl)-6-oxo-1,6-dihydropyrimidine-4-carboxamides and 5-(6-oxo-1,6-dihydropyrimidin-2-yl)-1H-indole-3-carbonitriles as novel xanthine oxidase inhibitors

Xanthine oxidase (XO) has been an important target for the treatment of hyperuricemia and gout. The analysis of potential interactions of pyrimidinone and 3-cyano indole pharmacophores present in the corresponding reported XO inhibitors with parts of the XO active pocket indicated that they both can be used as effective fragments for the fragment-based design of nonpurine XO inhibitors. In this paper, we adopted the fragment-based drug design strategy to link the two fragments with an amide bond to design the type 1 compounds 13a-13w,14c, 14d, 14f, 14g, 14j, 14k, and 15g. Compound 13g displayed an evident XO inhibitory potency (IC₅₀ = 0.16 μM), which was 52.3-fold higher than that of allopurinol (IC₅₀ = 8.37 μM). For comparison, type 2 compounds 5-(6-oxo-1,6-dihydropyrimidin-2-yl)-1H-indole-3-carbonitriles (25c-25g) were also designed by linking the two fragments with a single bond directly. The results showed that compound 25c from the latter series displayed the best inhibitory potency (IC₅₀ = 0.085 μM), and it was 98.5-fold stronger than that of allopurinol (IC₅₀ = 8.37 μM). These results suggested that amide and single bonds were applicable for linking the two fragments together to obtain potent nonpurine XO inhibitors. The structure-activity relationship results revealed that hydrophobic groups at N-atom of the indole moiety were indispensable for the improvement of the inhibitory potency in vitro against XO. In addition, enzyme kinetics studies suggested that compounds 13g and 25c, as the most promising XO inhibitors for the two types of target compounds, acted as mixed-type inhibitors for XO. Moreover, molecular modeling studies suggested that the pyrimidinone and indole moieties of the target compounds could interact well with key amino acid residues in the active pocket of XO. Furthermore, in vivo hypouricemic effect demonstrated that compounds 13g and 25c could effectively reduce serum uric acid levels at an oral dose of 10 mg/kg. Therefore, compounds 13g and 25c could be potential and efficacious agents for the treatment of hyperuricemia and gout.

Discovery of Next-Generation Tropomyosin Receptor Kinase Inhibitors for Combating Multiple Resistance Associated with Protein Mutation

Tropomyosin receptor kinase (TRK) inhibition is an effective therapeutic approach for treatment of a variety of cancers. Despite the use of first-generation TRK inhibitor (TRKI) larotrectinib (1) resulting in significant therapeutic response in patients, acquired resistance develops invariably. The emergence of secondary mutations occurring at the solvent-front, xDFG, and gatekeeper regions of TRK represents a common mechanism for acquired resistance. However, xDFG mutations remain insensitive to second-generation macrocyclic TRKIs selitrectinib (3) and repotrectinib (4) designed to overcome the resistance mediated by solvent-front and gatekeeper mutations. Here, we report the structure-based drug design and discovery of a next-generation TRKI. The structure-activity relationship studies culminated in the identification of a promising drug candidate 8 that showed excellent in vitro potency on a panel of TRK mutants, especially TRKA^G667C in the xDFG motif, and improved in vivo efficacy than 1 and 3 in TRK wild-type and mutant fusion-driven tumor xenograft models, respectively.

Efficient NMR Screening Approach to Discover Small Molecule Fragments Binding Structured RNA

We describe a scalable nuclear magnetic resonance (NMR) screening approach to identify and prioritize small molecule fragments that bind to structured RNAs. This approach is target agnostic and, therefore, amenable to many RNA structures and libraries, and it provides initial hits for further synthetic elaboration and structure-based drug discovery efforts. We demonstrate the approach on the pre-miR-21 stem-loop, which is of significant interest in oncology and metabolic diseases. We screened the pre-miR-21 hairpin using a small (420 compounds) commercially available fragment library and identified 18 hits in the first round of triage screening. This was further refined to four fragments which passed all screening cascade filters. Among these four hits, a thiadiazole fragment was demonstrated to bind the Dicer cleavage site of pre-miR-21 by target-detected NMR experiments and through the observation of clear intermolecular NOEs.

Construction of 2-alkynyl aza-spiro[4,5]indole scaffolds via sequential C-H activations for modular click chemistry libraries

Herein, we have developed a strategy of sequential C-H activations of indole to construct novel 2-alkynyl aza-spiro[4,5]indole scaffolds, which incorporated both alkyne and spiro-units into indole. Gram-scale synthesis and a one-pot, three-step synthesis demonstrated the utility of this protocol. Hybrid conjugates with an oseltamivir derivative further offered a powerful tool for the construction of a versatile spiroindole-containing library via click chemistry.

Discovery of new non-pyrimidine scaffolds as Plasmodium falciparum DHFR inhibitors by fragment-based screening

In various malaria-endemic regions, the appearance of resistance has precluded the use of pyrimidine-based antifolate drugs. Here, a three-step fragment screening was used to identify new non-pyrimidine Plasmodium falciparum dihydrofolate reductase (PfDHFR) inhibitors. Starting from a 1163-fragment commercial library, a two-step differential scanning fluorimetry screen identified 75 primary fragment hits. Subsequent enzyme inhibition assay identified 11 fragments displaying IC₅₀ in the 28-695 μM range and selectivity for PfDHFR. In addition to the known pyrimidine, three new anti-PfDHFR chemotypes were identified. Fragments from each chemotype were successfully co-crystallized with PfDHFR, revealing a binding in the active site, in the vicinity of catalytic residues, which was confirmed by molecular docking on all fragment hits. Finally, comparison with similar non-hit fragments provides preliminary input on available growth vectors for future drug development.

Schistosomiasis Drug Discovery in the Era of Automation and Artificial Intelligence

Schistosomiasis is a parasitic disease caused by trematode worms of the genus Schistosoma and affects over 200 million people worldwide. The control and treatment of this neglected tropical disease is based on a single drug, praziquantel, which raises concerns about the development of drug resistance. This, and the lack of efficacy of praziquantel against juvenile worms, highlights the urgency for new antischistosomal therapies. In this review we focus on innovative approaches to the identification of antischistosomal drug candidates, including the use of automated assays, fragment-based screening, computer-aided and artificial intelligence-based computational methods. We highlight the current developments that may contribute to optimizing research outputs and lead to more effective drugs for this highly prevalent disease, in a more cost-effective drug discovery endeavor.

Racemases and epimerases operating through a 1,1-proton transfer mechanism: reactivity, mechanism and inhibition

Racemases and epimerases catalyse changes in the stereochemical configurations of chiral centres and are of interest as model enzymes and as biotechnological tools. They also occupy pivotal positions within metabolic pathways and, hence, many of them are important drug targets. This review summarises the catalytic mechanisms of PLP-dependent, enolase family and cofactor-independent racemases and epimerases operating by a deprotonation/reprotonation (1,1-proton transfer) mechanism and methods for measuring their catalytic activity. Strategies for inhibiting these enzymes are reviewed, as are specific examples of inhibitors. Rational design of inhibitors based on substrates has been extensively explored but there is considerable scope for development of transition-state mimics and covalent inhibitors and for the identification of inhibitors by high-throughput, fragment and virtual screening approaches. The increasing availability of enzyme structures obtained using X-ray crystallography will facilitate development of inhibitors by rational design and fragment screening, whilst protein models will facilitate development of transition-state mimics.

Fragment-based drug design facilitates selective kinase inhibitor discovery

Protein kinases (PKs) are important drug targets, but kinases selectivity poses a challenge to protein kinase inhibitors (PKIs) design. Fragment-based drug discovery (FBDD) has achieved great success in the discovery of highly specific PKIs. It makes full use of kinase-fragment interaction in target kinase subpockets to obtain promising selectivity. However, it's difficult to understand the complicated kinase-fragment interaction space, and systemic discussion of these interactions is still lacking. Herein, we introduce the advantages of the FBDD strategy in PKIs design. Key features of the selectivity of kinase-fragment interactions are summarized and analyzed. Some promising PKIs are introduced as case studies to help understand the fragment-to-lead (F2L) optimization process. Novel strategies and technologies for FBDD in PKIs discovery are also outlooked.

MCSS-Based Predictions of Binding Mode and Selectivity of Nucleotide Ligands

Computational fragment-based approaches are widely used in drug design and discovery. One of their limitations is the lack of performance of docking methods, mainly the scoring functions. With the emergence of fragment-based approaches for single-stranded RNA ligands, we analyze the performance in docking and screening powers of an MCSS-based approach. The performance is evaluated on a benchmark of protein-nucleotide complexes where the four RNA residues are used as fragments. The screening power can be considered the major limiting factor for the fragment-based modeling or design of sequence-selective oligonucleotides. We show that the MCSS sampling is efficient even for such large and flexible fragments. Hybrid solvent models based on some partial explicit representations improve both the docking and screening powers. Clustering of the n best-ranked poses can also contribute to a lesser extent to better performance. A detailed analysis of molecular features suggests various ways to optimize the performance further.

Triazole-containing hybrids with anti-Mycobacterium tuberculosis potential - Part I: 1,2,3-Triazole

Tuberculosis regimens currently applied in clinical practice require months of multidrug therapy, which imposes a major challenge of patient compliance and drug resistance development. Moreover, because of the increasing emergence of hard-to-treat tuberculosis, this disease continues to be a significant threat to the human population. 1,2,3-triazole as a privileged structure has been widely used as an effective template for drug discovery, and 1,2,3-triazole-containing hybrids that can simultaneously act on dual or multiple targets in Mycobacterium tuberculosis have the potential to circumvent drug resistance, enhance efficacy, reduce side effects and improve pharmacokinetic as well as pharmacodynamic profiles. Thus, 1,2,3-triazole-containing hybrids are useful scaffolds for the development of antitubercular agents. This review aims to highlight recent advances of 1,2,3-triazole-containing hybrids with potential activity against various forms of M. tuberculosis, covering articles published between 2015 and 2020. The structure-activity relationship and the mechanism of action are also discussed to facilitate further rational design of more effective drug candidates.

Discovery of Pyrazine-Carboxamide-Diphenyl-Ethers as Novel Succinate Dehydrogenase Inhibitors via Fragment Recombination

The discovery of novel succinate dehydrogenase inhibitors (SDHIs) has attracted great attention worldwide. Herein, a fragment recombination strategy was proposed to design new SDHIs by understanding the ligand-receptor interaction mechanism of SDHIs. Three fragments, pyrazine from pyraziflumid, diphenyl-ether from flubeneteram, and a prolonged amide linker from pydiflumetofen and fluopyram, were identified and recombined to produce a pyrazine-carboxamide-diphenyl-ether scaffold as a new SDHI. After substituent optimization, compound 6y was successfully identified with good inhibitory activity against porcine SDH, which was about 2-fold more potent than pyraziflumid. Furthermore, compound 6y exhibited 95% and 80% inhibitory rates against soybean gray mold and wheat powdery mildew at a dosage of 100 mg/L in vivo assay, respectively. The results of the present work showed that the pyrazine-carboxamide-diphenyl-ether scaffold could be used as a new starting point for the discovery of new SDHIs.

Water-soluble inhibitors of ABCG2 (BCRP) - A fragment-based and computational approach

A good balance between hydrophilicity and lipophilicity is a prerequisite for all bioactive compounds. If the hydrophilicity of a compound is low, its solubility in water will be meager. Many drug development failures have been attributed to poor aqueous solubility. ABCG2 inhibitors are especially prone to be insoluble since they have to address the extremely large and hydrophobic multidrug binding site in ABCG2. For instance, our previous, tariquidar-related ABCG2 inhibitor UR-MB108 (1) showed high potency (79 nM), but very low aqueous solubility (78 nM). To discover novel potent ABCG2 inhibitors with improved solubility we pursued a fragment-based approach. Substructures of 1 were optimized and the fragments 'enlarged' to obtain inhibitors, supported by molecular docking studies. Synthesis was achieved, i.a., via Sonogashira coupling, click chemistry and amide coupling. A kinetic solubility assay revealed that 1 and most novel inhibitors did not precipitate during the short time period of the applied biological assays. The solubility of the compounds in aqueous media at equilibrium was investigated in a thermodynamic solubility assay, where UR-Ant116 (40), UR-Ant121 (41), UR-Ant131 (48) and UR-Ant132 (49) excelled with solubilities between 1 μM and 1.5 μM - an up to 19-fold improvement compared to 1. Moreover, these novel N-phenyl-chromone-2-carboxamides inhibited ABCG2 in a Hoechst 33342 transport assay with potencies in the low three-digit nanomolar range, reversed MDR in cancer cells, were non-toxic and proved stable in blood plasma. All properties make them attractive candidates for in vitro assays requiring long-term incubation and in vivo studies, both needing sufficient solubility at equilibrium. 41 and 49 were highly ABCG2-selective, a precondition for developing PET tracers. The triple ABCB1/C1/G2 inhibitor 40 qualifies for potential therapeutic applications, given the concerted role of the three transporter subtypes at many tissue barriers, e.g. the BBB.

Chemical molecular-based approach to overcome multidrug resistance in cancer by targeting P-glycoprotein (P-gp)

Multidrug resistance (MDR) remains one of the major impediments for efficacious cancer chemotherapy. Increased efflux of multiple chemotherapeutic drugs by transmembrane ATP-binding cassette (ABC) transporter superfamily is considered one of the primary causes for cancer MDR, in which the role of P-glycoprotein (P-gp/ABCB1) has been most well-established. The clinical co-administration of P-gp drug efflux inhibitors, in combination with anticancer drugs which are P-gp transport substrates, was considered to be a treatment modality to surmount MDR in anticancer therapy by blocking P-gp-mediated multidrug efflux. Extensive attempts have been carried out to screen for sets of nontoxic, selective, and efficacious P-gp efflux inhibitors. In this review, we highlight the recent achievements in drug design, characterization, structure-activity relationship (SAR) studies, and mechanisms of action of the newly synthetic, potent small molecules P-gp inhibitors in the past 5 years. The development of P-gp inhibitors will increase our knowledge of the mechanisms and functions of P-gp-mediated drug efflux which will benefit drug discovery and clinical cancer therapeutics where P-gp transporter overexpression has been implicated in MDR.

NMR as a "Gold Standard" Method in Drug Design and Discovery

Studying disease models at the molecular level is vital for drug development in order to improve treatment and prevent a wide range of human pathologies. Microbial infections are still a major challenge because pathogens rapidly and continually evolve developing drug resistance. Cancer cells also change genetically, and current therapeutic techniques may be (or may become) ineffective in many cases. The pathology of many neurological diseases remains an enigma, and the exact etiology and underlying mechanisms are still largely unknown. Viral infections spread and develop much more quickly than does the corresponding research needed to prevent and combat these infections; the present and most relevant outbreak of SARS-CoV-2, which originated in Wuhan, China, illustrates the critical and immediate need to improve drug design and development techniques. Modern day drug discovery is a time-consuming, expensive process. Each new drug takes in excess of 10 years to develop and costs on average more than a billion US dollars. This demonstrates the need of a complete redesign or novel strategies. Nuclear Magnetic Resonance (NMR) has played a critical role in drug discovery ever since its introduction several decades ago. In just three decades, NMR has become a "gold standard" platform technology in medical and pharmacology studies. In this review, we present the major applications of NMR spectroscopy in medical drug discovery and development. The basic concepts, theories, and applications of the most commonly used NMR techniques are presented. We also summarize the advantages and limitations of the primary NMR methods in drug development.