Fragment-based Drug Discovery Research Articles

Discovery of a fragment hit compound targeting D-Ala:D-Ala ligase of bacterial peptidoglycan biosynthesis

Bacterial resistance is an increasing threat to healthcare systems, highlighting the need for discovering new antibacterial agents. An established technique, fragment-based drug discovery, was used to target a bacterial enzyme Ddl involved in the biosynthesis of peptidoglycan. We assembled general and focused fragment libraries that were screened in a biochemical inhibition assay. Screening revealed a new fragment-hit inhibitor of DdlB with a Ki value of 20.7 ± 4.5 µM. Binding to the enzyme was confirmed by an orthogonal biophysical method, surface plasmon resonance, making the hit a promising starting point for fragment development.

Screening and Identification of Lassa Virus Entry Inhibitors from a Fragment-Based Drug Discovery Library

Lassa virus (LASV) is a highly pathogenic virus that is categorized as a biosafety level-4 pathogen. Currently, there are no approved drugs or vaccines specific to LASV. In this study, high-throughput screening of a fragment-based drug discovery library was performed against LASV entry using a pseudotype virus bearing the LASV envelope glycoprotein complex (GPC). Two compounds, F1920 and F1965, were identified as LASV entry inhibitors that block GPC-mediated membrane fusion. Analysis of adaptive mutants demonstrated that the transient mutants L442F and I445S, as well as the constant mutant F446L, were located on the same side on the transmembrane domain of the subunit GP2 of GPC, and all the mutants conferred resistance to both F1920 and F1965. Furthermore, F1920 antiviral activity extended to other highly pathogenic mammarenaviruses, whereas F1965 was LASV-specific. Our study showed that both F1920 and F1965 provide a potential backbone for the development of lead drugs for preventing LASV infection.

DRlinker: Deep Reinforcement Learning for Optimization in Fragment Linking Design.

Fragment-based drug discovery is a widely used strategy for drug design in both academic and pharmaceutical industries. Although fragments can be linked to generate candidate compounds by the latest deep generative models, generating linkers with specified attributes remains underdeveloped. In this study, we presented a novel framework, DRlinker, to control fragment linking toward compounds with given attributes through reinforcement learning. The method has been shown to be effective for many tasks from controlling the linker length and log P, optimizing predicted bioactivity of compounds, to various multiobjective tasks. Specifically, our model successfully generated 91.0% and 93.9% of compounds complying with the desired linker length and log P and improved the 7.5 pChEMBL value in bioactivity optimization. Finally, a quasi-scaffold-hopping study revealed that DRlinker could generate nearly 30% molecules with high 3D similarity but low 2D similarity to the lead inhibitor, demonstrating the benefits and applicability of DRlinker in actual fragment-based drug design.

Allosteric quinoxaline-based inhibitors of the flavivirus NS2B/NS3 protease

Viruses from the Flavivirus genus infect millions of people worldwide and cause severe diseases, including recent epidemics of dengue virus (DENV), and Zika virus (ZIKV). There is currently no antiviral treatment against flavivirus infections, despite considerable efforts to develop inhibitors against essential viral enzymes including NS2B/NS3 protease. Targeting the flavivirus NS2B/NS3 protease proved to be challenging because of the conformational dynamics, topology, and electrostatic properties of the active site. Here, we report the identification of quinoxaline-based allosteric inhibitors by fragment-based drug discovery approach as a promising new drug-like scaffold to target the NS2B/NS3 protease. Enzymatic assays and mutational analysis of the allosteric site in ZIKV NS2B/NS3 protease support noncompetitive inhibition mechanism as well as engineered DENV protease construct indicating the compounds likely compete with the NS2B cofactor for binding to the protease domain. Furthermore, antiviral activity confirmed the therapeutic potential of this new inhibitor scaffold.

Implications of Fragment-Based Drug Discovery in Tuberculosis and HIV.

Tuberculosis (TB) remains a global health problem and the emergence of HIV has further worsened it. Long chemotherapy and the emergence of drug-resistance strains of Mycobacterium tuberculosis as well as HIV has aggravated the problem. This demands urgent the need to develop new anti-tuberculosis and antiretrovirals to treat TB and HIV. The lack of diversity in drugs designed using traditional approaches is a major disadvantage and limits the treatment options. Therefore, new technologies and approaches are required to solve the current issues and enhance the production of drugs. Interestingly, fragment-based drug discovery (FBDD) has gained an advantage over high-throughput screenings as FBDD has enabled rapid and efficient progress to develop potent small molecule compounds that specifically bind to the target. Several potent inhibitor compounds of various targets have been developed using FBDD approach and some of them are under progression to clinical trials. In this review, we emphasize some of the important targets of mycobacteria and HIV. We also discussed about the target-based druggable molecules that are identified using the FBDD approach, use of these druggable molecules to identify novel binding sites on the target and assays used to evaluate inhibitory activities of these identified druggable molecules on the biological activity of the targets.

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

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

Fragment-Sized Thiazoles in Fragment-Based Drug Discovery Campaigns: Friend or Foe?

Thiazoles exhibit a wide range of biological activities and therefore represent useful and attractive building blocks. To evaluate their usefulness and pinpoint their liabilities in fragment screening campaigns, we assembled a focused library of 49 fragment-sized thiazoles and thiadiazoles with various substituents, namely amines, bromides, carboxylic acids, and nitriles. The library was profiled in a cascade of biochemical inhibition assays, redox activity, thiol reactivity, and stability assays. Our study indicates that when thiazole derivatives are identified as screening hits, their reactivity should be carefully addressed and correlated with specific on-target engagement. Importantly, nonspecific inhibition should be excluded using experimental approaches and in silico predictions. To help with validation of hits identified in fragment screening campaigns, we can apply our high-throughput profiling workflow to focus on the most tractable compounds with a clear mechanism of action.

Discovery of Novel and Potent Inhibitors Against Mutational Variants of IDH1 Protein for Glioma Therapy: A Fragment-Based Approach

Somatic mutations in the isoenzymes of isocitrate dehydrogenases (IDHs) account for the pathogenesis of various malignancies including gliomas. To date, ivosidenib is the only FDA-approved drug candidate widely used to target mutated isocitrate dehydrogenase 1 (mIDH1). However, the impotence of the existing drug to evade the blood barrier remains an obstacle to harness ivosidenib as therapeutics against glioma. Thus, in this study, we elucidate a fragment-based drug discovery strategy to design novel lead molecules against the mIDH1 protein. Initially, a fragment library was constructed using 27 known mIDH1 inhibitors from the literature. The vast chemical classes of constructed library consisting of 1109 fragments were then used for breeding. A total of 18,000 breed compounds were generated and the resultant compounds were scrutinized based on the breed score ([Formula: see text]) and Tanimoto coefficient ([Formula: see text]). The binding affinity and the energetics of the resultant molecules (2069) were investigated using molecular docking and MM-GBSA calculations. Eventually, the compounds with higher affinity were included in the mutational analysis incorporating the second site mutations namely IDH1S280F and IDH1R119P. The bioavailability analysis and toxicity profiling were carried out for screened hybrid molecules. The pipeline of the integrated in-silico approach identified hybrid 209, hybrid 237 and hybrid 504 as the drug-like candidates against the mutational variants of mIDH1 protein. Interestingly, all three compounds exhibited greater binding affinity and better brain penetrating capability. The machine learning-based anti-cancerous sensitivity prediction tool affirmed the inhibitory effect of the resultant hits against various glioma cell lines. In the end, the structural stability of the screened molecules was examined using the molecular dynamic simulation study for a stipulated time of 100[Formula: see text]ns. Indeed, this evidence speculates that the identified hybrid molecules could serve as important leads for the management of glioma in the near future.

Development of Noncovalent Small-Molecule Keap1-Nrf2 Inhibitors by Fragment-Based Drug Discovery.

Targeting the protein-protein interaction (PPI) between the transcription factor nuclear factor erythroid 2-related factor 2 (Nrf2) and its repressor, Kelch-like ECH-associated protein 1 (Keap1), constitutes a promising strategy for treating diseases involving oxidative stress and inflammation. Here, a fragment-based drug discovery (FBDD) campaign resulted in novel, high-affinity (Ki = 280 nM), and cell-active noncovalent small-molecule Keap1-Nrf2 PPI inhibitors. We screened 2500 fragments using orthogonal assays─fluorescence polarization (FP), thermal shift assay (TSA), and surface plasmon resonance (SPR)─and validated the hits by saturation transfer difference (STD) NMR, leading to 28 high-priority hits. Thirteen co-structures showed fragments binding mainly in the P4 and P5 subpockets of Keap1's Kelch domain, and three fluorenone-based fragments featuring a novel binding mode were optimized by structure-based drug discovery. We thereby disclose several fragment hits, including their binding modes, and show how FBDD can be performed to find new small-molecule Keap1-Nrf2 PPI inhibitors.

Recent Development in Small Molecules for SARS-CoV-2 and the Opportunity for Fragment-Based Drug Discovery.

The ongoing pandemic of Covid-19 caused by SARS-CoV-2 is a major threat to global public health, drawing attention to develop new therapeutics for treatment. Much research work is focused on identifying or repurposing new small molecules to serve as potential inhibitors by interacting with viral or host-cell molecular targets and understanding the nature of the virus in the host cells. Identifying small molecules as potent inhibitors at an early stage is advantageous in developing a molecule with higher potency and then finding a lead compound for the development of drug discovery. Small molecules can show their inhibition property by targeting either the SARS-CoV-2 main protease (Mpro) enzyme, papain-like protease (PLpro) enzyme, or helicase (Hel), or blocking the spike (S) protein angiotensin-converting enzyme 2 (ACE2) receptor. A very recent outbreak of a new variant (B.1.617.2-termed as Delta variant) of SARS-CoV-2 worldwide posed a greater challenge as it is resistant to clinically undergoing vaccine trials. Thus, the development of new drug molecules is of potential interest to combat SARS-CoV-2 disease, and for that, the fragment-based drug discovery (FBDD) approach could be one of the ways to bring out an effective solution. Two cysteine protease enzymes would be an attractive choice of target for fragment-based drug discovery to tune the molecular structure at an early stage with suitable functionality. In this short review, the recent development in small molecules as inhibitors against Covid-19 is discussed, and the opportunity for FBDD is envisioned optimistically to provide an outlook regarding Covid-19 that may pave the way in the direction of the Covid-19 drug development paradigm.

232 (PB112) - Low SKP2 expression is predictive of sensitivity to an MDM2 antagonist in p53 wild-type AML

Background: Non-mutational aberrations of p53 function are a common event in AML. Using fragment-based drug discovery we have identified a Murine double minute 2 (MDM2) antagonist that potently activates p53 pathway. Here, we present the discovery of a novel patient selection strategy for MDM2 antagonist-induced apoptosis in wild-type p53 AML. Material and Methods: Cell panel screen and bioinformatics analyses of p53 wild-type AML cell lines that undergo apoptosis following Compound 1 (MDM2 antagonist) treatment versus those that do not were employed to identify novel patient selection strategy. Correlation between low levels of SKP2 (S-Phase Kinase Associated Protein 2) and induction of apoptosis following Compound 1 treatment was tested in vitro using Western Blot and flow cytometry analysis. Genetic manipulation of SKP2 levels using knockdown and over-expression approaches in wild-type p53 AML cells were used to validate the role of SKP2 expression in in vitro and in vivo experiments. Finally, bone marrow-derived primary AML blasts were tested to confirm the novel patient selection strategy. Results: Cell panel screen of p53 wild-type cell lines showed a wide range of sensitivity to Compound 1 suggesting that additional biomarkers are required to ensure patient stratification. Further bioinformatics analysis of apoptotic and non-apoptotic AML cancer cell lines following treatment with Compound 1 demonstrated differential gene expression levels and identified several potential predictive biomarkers. Western blot and flow cytometry analyses demonstrated that basal SKP2 expression level is lower in apoptotic AML cell lines than in non-apoptotic cells. Over-expression of SKP2 levels in MV4-11 cells reduced MDM2 antagonist-dependent cell death in previously apoptotic cell line. Similarly, SKP2 knockdown in OCI-AML3 cells increased MDM2 antagonist-induced cytotoxicity. Studies performed in mouse systemic AML model in vivo also demonstrated that high levels of SKP2 reduced p53 response to Compound 1. Finally, the correlation of SKP2 expression and Compound 1 sensitivity was confirmed in primary AML blasts isolated from patients. Conclusions: This work demonstrates in vitro and in vivo activity of MDM2 antagonist in AML models with low basal SKP2 levels. These pre-clinical data validate low levels of SKP2 as a novel patient selection strategy in AML and support the clinical investigation of MDM2 antagonist as therapeutic strategy for the treatment of SKP2low p53wt AML. No conflict of interest.

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.

Native Mass Spectrometry-Guided Screening Identifies Hit Fragments for HOP-HSP90 PPI Inhibition.

Contemporary medicinal chemistry considers fragment-based drug discovery (FBDD) and inhibition of protein-protein interactions (PPI) as important means of expanding the volume of druggable chemical space. However, the ability to robustly identify valid fragments and PPI inhibitors is an enormous challenge, requiring the application of sensitive biophysical methodology. Accordingly, in this study, we exploited the speed and sensitivity of nanoelectrospray (nano-ESI) native mass spectrometry to identify a small collection of fragments which bind to the TPR2AB domain of HOP. Follow-up biophysical assessment of a small selection of binding fragments confirmed binding to the single TPR2A domain, and that this binding translated into PPI inhibitory activity between TPR2A and the HSP90 C-terminal domain. An in-silico assessment of binding fragments at the PPI interfacial region, provided valuable structural insight for future fragment elaboration strategies, including the identification of losartan as a weak, albeit dose-dependent inhibitor of the target PPI.

Fragment-Based Drug Discovery against Mycobacteria: The Success and Challenges.

The emergence of drug-resistant mycobacteria, including Mycobacterium tuberculosis (Mtb) and non-tuberculous mycobacteria (NTM), poses an increasing global threat that urgently demands the development of new potent anti-mycobacterial drugs. One of the approaches toward the identification of new drugs is fragment-based drug discovery (FBDD), which is the most ingenious among other drug discovery models, such as structure-based drug design (SBDD) and high-throughput screening. Specialized techniques, such as X-ray crystallography, nuclear magnetic resonance spectroscopy, and many others, are part of the drug discovery approach to combat the Mtb and NTM global menaces. Moreover, the primary drawbacks of traditional methods, such as the limited measurement of biomolecular toxicity and uncertain bioavailability evaluation, are successfully overcome by the FBDD approach. The current review focuses on the recognition of fragment-based drug discovery as a popular approach using virtual, computational, and biophysical methods to identify potent fragment molecules. FBDD focuses on designing optimal inhibitors against potential therapeutic targets of NTM and Mtb (PurC, ArgB, MmpL3, and TrmD). Additionally, we have elaborated on the challenges associated with the FBDD approach in the identification and development of novel compounds. Insights into the applications and overcoming the challenges of FBDD approaches will aid in the identification of potential therapeutic compounds to treat drug-sensitive and drug-resistant NTMs and Mtb infections.

X-ray Screening of an Electrophilic Fragment Library and Application toward the Development of a Novel ERK 1/2 Covalent Inhibitor.

Fragment-based drug discovery (FBDD) has become an established method for the identification of efficient starting points for drug discovery programs. In recent years, electrophilic fragment screening has garnered increased attention from both academia and industry to identify novel covalent hits for tool compound or drug development against challenging drug targets. Herein, we describe the design and characterization of an acrylamide-focused electrophilic fragment library and screening campaign against extracellular signal-regulated kinase 2 (ERK2) using high-throughput protein crystallography as the primary hit-finding technology. Several fragments were found to have covalently modified the adenosine triphosphate (ATP) binding pocket Cys166 residue. From these hits, 22, a covalent ATP-competitive inhibitor with improved potency (ERK2 IC50 = 7.8 μM), was developed.

Magnet for the Needle in Haystack: "Crystal Structure First" Fragment Hits Unlock Active Chemical Matter Using Targeted Exploration of Vast Chemical Spaces.

Fragment-based drug discovery (FBDD) has successfully led to approved therapeutics for challenging and "undruggable" targets. In the context of FBDD, we introduce a novel, multidisciplinary method to identify active molecules from purchasable chemical space. Starting from four small-molecule fragment complexes of protein kinase A (PKA), a template-based docking screen using Enamine's multibillion REAL Space was performed. A total of 93 molecules out of 106 selected compounds were successfully synthesized. Forty compounds were active in at least one validation assay with the most active follow-up having a 13,500-fold gain in affinity. Crystal structures for six of the most promising binders were rapidly obtained, verifying the binding mode. The overall success rate for this novel fragment-to-hit approach was 40%, accomplished in only 9 weeks. The results challenge the established fragment prescreening paradigm since the standard industrial filters for fragment hit identification in a thermal shift assay would have missed the initial fragments.

Inter-Ligand STD NMR: An Efficient 1D NMR Approach to Probe Relative Orientation of Ligands in a Multi-Subsite Protein Binding Pocket.

In recent years, Saturation Transfer Difference NMR (STD NMR) has been proven to be a powerful and versatile ligand-based NMR technique to elucidate crucial aspects in the investigation of protein-ligand complexes. Novel STD NMR approaches relying on “multi-frequency” irradiation have enabled us to even elucidate specific ligand-amino acid interactions and explore the binding of fragments in previously unknown binding subsites. Exploring multi-subsite protein binding pockets is especially important in Fragment Based Drug Discovery (FBDD) to design leads of increased specificity and efficacy. We hereby propose a novel multi-frequency STD NMR approach based on direct irradiation of one of the ligands in a multi-ligand binding process, to probe the vicinity and explore the relative orientation of fragments in adjacent binding sub-sites, which we called Inter-Ligand STD NMR (IL-STD NMR). We proved its applicability on (i) a standard protein-ligand system commonly used for ligand-observed NMR benchmarking: Naproxen as bound to Bovine Serum Albumin, and (ii) the biologically relevant system of Cholera Toxin Subunit B and two inhibitors adjacently bound within the GM1 binding site. Relative to Inter-Ligand NOE (ILOE), the current state-of-the-art methodology to probe relative orientations of adjacent ligands, IL-STD NMR requires about one tenth of the experimental time and protein consumption, making it a competitive methodology with the potential to be applied in the pharmaceutical industries.

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 was 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 of fragment optimization 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.

Towards systematic exploration of chemical space: building the fragment library module in molecular property diagnostic suite.

A fragment-based drug discovery (FBDD) approach has traditionally been of utmost significance in drug design studies. It allows the exploration of large chemical space to find novel scaffolds and chemotypes which can be improved into selective inhibitors with good affinity. In the current work, several public domain chemical libraries (ChEMBL, DrugCentral, PDB ligands, COCONUT, and SAVI) comprising bioactive and virtual molecules were retrieved to develop a fragment library. A systematic fragmentation method that breaks a given molecule into rings, linkers, and substituents was used to cleave the molecules and the fragments were analyzed. Further, only the ring framework was taken into the consideration to develop a fragment library that consists of a total number of 107,614 unique fragments. This set represents a rich diverse structure framework that covers a wide variety of yet-to-be-explored fragments for a wide range of small molecule-based applications. This fragment library is an integral part of the molecular property diagnostic suite (MPDS) suite that can be used with other modeling and informatics methods for FBDD approaches. The fragment library module of MPDS can be accessed at http://mpds.neist.res.in:8085.Graphical abstract Supplementary InformationThe online version contains supplementary material available at 10.1007/s11030-022-10506-5.

A fragment-based drug discovery strategy applied to the identification of NDM-1 β-lactamase inhibitors

Hydrolysis of β-lactam drugs, a major class of antibiotics, by serine or metallo-β-lactamases (SBL or MBL) is one of the main mechanisms for antibiotic resistance. New Delhi Metallo-β-lactamase-1 (NDM-1), an acquired metallo-carbapenemase first reported in 2009, is currently considered one of the most clinically relevant targets for the development of β-lactam-β-lactamase inhibitor combinations active on NDM-producing clinical isolates. Identification of scaffolds that could be further rationally pharmacomodulated to design new and efficient NDM-1 inhibitors is thus urgently needed. Fragment-based drug discovery (FBDD) has become of great interest for the development of new drugs for the past few years and combination of several FBDD strategies, such as virtual and NMR screening, can reduce the drawbacks of each of them independently. Our methodology starting from a high throughput virtual screening on NDM-1 of a large library (more than 700,000 compounds) allowed, after slicing the hit molecules into fragments, to build a targeted library. These hit fragments were included in an in-house untargeted library fragments that was screened by Saturation Transfer Difference (STD) Nuclear Magnetic Resonance (NMR). 37 fragments were finally identified and used to establish a pharmacophore. 10 molecules based on these hit fragments were synthesized to validate our strategy. Indenone 89 that combined two identified fragments shows an inhibitory activity on NDM-1 with a Ki value of 4 μM.