Application of CoLD-CoP to Detecting Competitively and Cooperatively Binding Ligands.

NMR utilization in fragment-based drug discovery requires techniques to detect weakly binding fragments and to subsequently identify cooperatively binding fragments. Such cooperatively binding fragments can then be optimized or linked in order to develop viable drug candidates. Similarly, ligands or substrates that bind macromolecules (including enzymes) in competition with the endogenous ligand or substrate are valuable probes of macromolecular chemistry and function. The lengthy and costly process of identifying competitive or cooperative binding can be streamlined by coupling computational biochemistry and spectroscopy tools. The Clustering of Ligand Diffusion Coefficient Pairs (CoLD-CoP) method, previously developed by Snyder and co-workers, detects weakly binding ligands by analyzing pairs of diffusion spectra, obtained in the absence and the presence of a protein. We extended the CoLD-CoP method to analyze spectra pairs (each in the presence of a protein) with or without a critical ligand, to detect both competitive and cooperative binding.

Repurposing Anidulafungin for Alzheimer's Disease via Fragment-Based Drug Discovery.

The misfolding and aggregation of beta-amyloid (Aß) peptides have been implicated as key pathogenic events in the early stages of Alzheimer's disease (AD). Inhibiting Aß aggregation represents a potential disease-modifying therapeutic approach to AD treatment. Previous studies have identified various molecules that inhibit Aß aggregation, some of which share common chemical substructures (fragments) that may be key to their inhibitory activity. Employing fragment-based drug discovery (FBDD) methods may facilitate the identification of these fragments, which can subsequently be used to screen new inhibitors and provide leads for further drug development. In this study, we used an in silico FBDD approach to identify 17 fragment clusters that are significantly enriched among Aß aggregation inhibitors. These fragments were then used to screen anti-infective agents, a promising drug class for repurposing against amyloid aggregation. This screening process identified 16 anti-infective drugs, 5 of which were chosen for further investigation. Among the 5 candidates, anidulafungin, an antifungal compound, showed high efficacy in inhibiting Aß aggregation in vitro. Kinetic analysis revealed that anidulafungin selectively blocks the primary nucleation step of Aß aggregation, substantially delaying Aß fibril formation. Cell viability assays demonstrated that anidulafungin can reduce the toxicity of oligomeric Aß on BV2 microglia cells. Molecular docking simulations predicted that anidulafungin interacted with various Aß species, including monomers, oligomers, and fibrils, potentially explaining its activity against Aß aggregation and toxicity. This study suggests that anidulafungin is a potential drug to be repurposed for AD, and FBDD is a promising approach for discovering drugs to combat Aß aggregation.

How to Find a Fragment: Methods for Screening and Validation in Fragment-Based Drug Dscovery.

Fragment-based drug discovery (FBDD) is a crucial strategy for developing new drugs that have been applied to diverse targets, from neglected infectious diseases to cancer. With at least seven drugs already launched to the market, this approach has gained interest in both academics and industry in the last 20 years. FBDD relies on screening small libraries with about 1000-2000 compounds of low molecular weight (about 300 Da) using several biophysical methods. Because of the reduced size of the compounds, the chemical space and diversity can be better explored than large libraries used in high throughput screenings. This review summarises the most common biophysical techniques used in fragment screening and orthogonal validation. We also explore the advantages and drawbacks of the different biophysical techniques and examples of applications and strategies.

Dataset for discovering new hypertension small molecules using machine learning-aided computational fragment-based design.

This dataset demonstrates the use of computational fragmentation-based and machine learning-aided drug discovery to generate new lead molecules for the treatment of hypertension. Specifically, the focus is on agents targeting the renin-angiotensin-aldosterone system (RAAS), commonly classified as Angiotensin-Converting Enzyme Inhibitors (ACEIs) and Angiotensin II Receptor Blockers (ARBs). The preliminary dataset was a target-specific, user-generated fragment library of 63 molecular fragments of the 26 approved ACEI and ARB molecules obtained from the ChEMBL and DrugBank molecular databases. This fragment library provided the primary input dataset to generate the new lead molecules presented in the dataset. The newly generated molecules were screened to check whether they met the criteria for oral drugs and comprised the ACEI or ARB core functional group criterion. Using unsupervised machine learning, the molecules that met the criterion were divided into clusters of drug classes based on their functional group allocation. This process led to three final output datasets, one containing the new ACEI molecules, another for the new ARB molecules, and the last for the new unassigned class molecules. This data can aid in the timely and efficient design of novel antihypertensive drugs. It can also be used in precision hypertension medicine for patients with treatment resistance, non-response or co-morbidities. Although this dataset is specific to antihypertensive agents, the model can be reused with minimal changes to produce new lead molecules for other health conditions.

Evaluation of a Covalent Library of Diverse Warheads (CovLib) Binding to JNK3, USP7, or p53.

Purpose: Over the last few years, covalent fragment-based drug discovery has gained significant importance. Thus, striving for more warhead diversity, we conceived a library consisting of 20 covalently reacting compounds. Our covalent fragment library (CovLib) contains four different warhead classes, including five α-cyanoacacrylamides/acrylates (CA), three epoxides (EO), four vinyl sulfones (VS), and eight electron-deficient heteroarenes with a leaving group (SNAr/SN). Methods: After predicting the theoretical solubility of the fragments by LogP and LogS during the selection process, we determined their experimental solubility using a turbidimetric solubility assay. The reactivities of the different compounds were measured in a high-throughput 5,5'-dithiobis-(2-nitrobenzoic acid) DTNB assay, followed by a (glutathione) GSH stability assay. We employed the CovLib in a (differential scanning fluorimetry) DSF-based screening against different targets: c-Jun N-terminal kinase 3 (JNK3), ubiquitin-specific protease 7 (USP7), and the tumor suppressor p53. Finally, the covalent binding was confirmed by intact protein mass spectrometry (MS). Results: In general, the purchased fragments turned out to be sufficiently soluble. Additionally, they covered a broad spectrum of reactivity. All investigated α-cyanoacrylamides/acrylates and all structurally confirmed epoxides turned out to be less reactive compounds, possibly due to steric hindrance and reversibility (for α-cyanoacrylamides/acrylates). The SNAr and vinyl sulfone fragments are either highly reactive or stable. DSF measurements with the different targets JNK3, USP7, and p53 identified reactive fragment hits causing a shift in the melting temperatures of the proteins. MS confirmed the covalent binding mode of all these fragments to USP7 and p53, while additionally identifying the SNAr-type electrophile SN002 as a mildly reactive covalent hit for p53. Conclusion: The screening and target evaluation of the CovLib revealed first interesting hits. The highly cysteine-reactive fragments VS004, SN001, SN006, and SN007 covalently modify several target proteins and showed distinct shifts in the melting temperatures up to +5.1 °C and -9.1 °C.

Accessing Active Fragments for Drug Discovery Utilising Nitroreductase Biocatalysis.

Biocatalysis has played a limited role in the early stages of drug discovery. This is often attributed to the limited substrate scope of enzymes not affording access to vast areas of novel chemical space. Here, we have shown a promiscuous nitroreductase enzyme (NR-55) can be used to produce a panel of functionalised anilines from a diverse panel of aryl nitro starting materials. After screening on analytical scale, we show that sixteen substrates could be scaled to 1 mmol scale, with several poly-functional anilines afforded with ease under the standard conditions. The aniline products were also screened for activity against several cell lines of interest, with modest activity observed for one compound. This study demonstrates the potential for nitroreductase biocatalysis to provide access to functional fragments under benign conditions.

Fragment Screening to Identify Inhibitors Targeting Ribosome Binding of Shiga Toxin 2.

Shiga toxins are the main virulence factors of Shiga toxin producing E. coli (STEC) and S. dysenteriae. There is no effective therapy to counter the disease caused by these toxins. The A1 subunits of Shiga toxins bind the C-termini of ribosomal P-stalk proteins to depurinate the sarcin/ricin loop. The ribosome binding site of Shiga toxin 2 has not been targeted by small molecules. We screened a fragment library against the A1 subunit of Shiga toxin 2 (Stx2A1) and identified a fragment, BTB13086, which bound at the ribosome binding site and mimicked the binding mode of the P-stalk proteins. We synthesized analogs of BTB13086 and identified a series of molecules with similar affinity and inhibitory activity. These are the first compounds that bind at the ribosome binding site of Stx2A1 and inhibit activity. These compounds hold great promise for further inhibitor development against STEC infection.

High-confidence placement of low-occupancy fragments into electron density using the anomalous signal of sulfur and halogen atoms.

Fragment-based drug design using X-ray crystallography is a powerful technique to enable the development of new lead compounds, or probe molecules, against biological targets. This study addresses the need to determine fragment binding orientations for low-occupancy fragments with incomplete electron density, an essential step before further development of the molecule. Halogen atoms play multiple roles in drug discovery due to their unique combination of electronegativity, steric effects and hydrophobic properties. Fragments incorporating halogen atoms serve as promising starting points in hit-to-lead development as they often establish halogen bonds with target proteins, potentially enhancing binding affinity and selectivity, as well as counteracting drug resistance. Here, the aim was to unambiguously identify the binding orientations of fragment hits for SARS-CoV-2 nonstructural protein 1 (nsp1) which contain a combination of sulfur and/or chlorine, bromine and iodine substituents. The binding orientations of carefully selected nsp1 analogue hits were focused on by employing their anomalous scattering combined with Pan-Dataset Density Analysis (PanDDA). Anomalous difference Fourier maps derived from the diffraction data collected at both standard and long-wavelength X-rays were compared. The discrepancies observed in the maps of iodine-containing fragments collected at different energies were attributed to site-specific radiation-damage stemming from the strong X-ray absorption of I atoms, which is likely to cause cleavage of the C-I bond. A reliable and effective data-collection strategy to unambiguously determine the binding orientations of low-occupancy fragments containing sulfur and/or halogen atoms while mitigating radiation damage is presented.

Optimizing NMR fragment-based drug screening for membrane protein targets.

NMR spectroscopy has played a pivotal role in fragment-based drug discovery by coupling detection of weak ligand-target binding with structural mapping of the binding site. Fragment-based screening by NMR has been successfully applied to many soluble protein targets, but only to a limited number of membrane proteins, despite the fact that many drug targets are membrane proteins. This is partly because of difficulties preparing membrane proteins for NMR-especially human membrane proteins-and because of the inherent complexity associated with solution NMR spectroscopy on membrane protein samples, which require the inclusion of membrane-mimetic agents such as micelles, nanodiscs, or bicelles. Here, we developed a generalizable protocol for fragment-based screening of membrane proteins using NMR. We employed two human membrane protein targets, both in fully protonated detergent micelles: the single-pass C-terminal domain of the amyloid precursor protein, C99, and the tetraspan peripheral myelin protein 22 (PMP22). For both we determined the optimal NMR acquisition parameters, protein concentration, protein-to-micelle ratio, and upper limit to the concentration of D6-DMSO in screening samples. Furthermore, we conducted preliminary screens of a plate-format molecular fragment mixture library using our optimized conditions and were able to identify hit compounds that selectively bound to the respective target proteins. It is hoped that the approaches presented here will be useful in complementing existing methods for discovering lead compounds that target membrane proteins.

Fragment-based drug discovery for disorders of the central nervous system: designing better drugs piece by piece.

Fragment-based drug discovery (FBDD) has emerged as a powerful strategy to confront the challenges faced by conventional drug development approaches, particularly in the context of central nervous system (CNS) disorders. FBDD involves the screening of libraries that comprise thousands of small molecular fragments, each no greater than 300 Da in size. Unlike the generally larger molecules from high-throughput screening that limit customisation, fragments offer a more strategic starting point. These fragments are inherently compact, providing a strong foundation with good binding affinity for the development of drug candidates. The minimal elaboration required to transition the hit into a drug-like molecule is not only accelerated, but also it allows for precise modifications to enhance both their activity and pharmacokinetic properties. This shift towards a fragment-centric approach has seen commercial success and holds considerable promise in the continued streamlining of the drug discovery and development process. In this review, we highlight how FBDD can be integrated into the CNS drug discovery process to enhance the exploration of a target. Furthermore, we provide recent examples where FBDD has been an integral component in CNS drug discovery programs, enabling the improvement of pharmacokinetic properties that have previously proven challenging. The FBDD optimisation process provides a systematic approach to explore this vast chemical space, facilitating the discovery and design of compounds piece by piece that are capable of modulating crucial CNS 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.

Ligandability at the membrane interface of GPx4 revealed through a reverse micelle fragment screening platform.

While they account for a large portion of drug targets, membrane proteins (MPs) present a unique challenge for drug discovery. Peripheral membrane proteins (PMPs), a class of proteins that bind reversibly to membranes, are also difficult targets, particularly those that function only while bound to membranes. The protein-membrane interface in PMPs is often where functional interactions and catalysis occur, making it a logical target for inhibition. However, interfaces are underexplored spaces in inhibitor design and there is a need for enhanced methods for small-molecule ligand discovery. In an effort to better initiate drug discovery efforts for PMPs, this study presents a screening methodology using membrane-mimicking reverse micelles (mmRM) and NMR-based fragment screening to assess ligandability in the protein-membrane interface. The proof-of-principle target, glutathione peroxidase 4 (GPx4), is a lipid hydroperoxidase which is essential for the oxidative protection of membranes and thereby the prevention of ferroptosis. GPx4 inhibition is promising for therapy-resistant cancer therapy, but current inhibitors are generally covalent ligands with limited clinical utility. Presented here is the discovery of non-covalent small-molecule ligands for membrane-bound GPx4 revealed through the mmRM fragment screening methodology. The fragments were tested against GPx4 in bulk aqueous conditions and displayed little to no binding to the protein without embedment into the membrane. The 9 hits had varying affinities and partitioning coefficients and revealed properties of fragments that bind within the protein-membrane interface. Additionally, a secondary screen confirmed the potential to progress the fragments by enhancing the affinity from > 200 µM to ~15 µM with the addition of certain hydrophobic groups. This study presents an advancement of screening capabilities for membrane associated proteins, reveals ligandability within the GPx4 protein-membrane interface, and may serve as a starting point for developing non-covalent inhibitors of GPx4.

14-3-3 Protein-Protein Interactions: From Mechanistic Understanding to Their Small-Molecule Stabilization.

Protein-protein interactions (PPIs) are of utmost importance for maintenance of cellular homeostasis. Herein, a central role can be found for 14-3-3 proteins. These hub-proteins are known to bind hundreds of interaction partners, thereby regulating their activity, localization, and/or stabilization. Due to their ability to bind a large variety of client proteins, studies of 14-3-3 protein complexes flourished over the last decades, aiming to gain greater molecular understanding of these complexes and their role in health and disease. Because of their crucial role within the cell, 14-3-3 protein complexes are recognized as highly interesting therapeutic targets, encouraging the discovery of small molecule modulators of these PPIs. We discuss various examples of 14-3-3-mediated regulation of its binding partners on a mechanistic level, highlighting the versatile and multi-functional role of 14-3-3 within the cell. Furthermore, an overview is given on the development of stabilizers of 14-3-3 protein complexes, from initially used natural products to fragment-based approaches. These studies show the potential of 14-3-3 PPI stabilizers as novel agents in drug discovery and as tool compounds to gain greater molecular understanding of the role of 14-3-3-based protein regulation.

Assessment of fragment docking and scoring with the endothiapepsin model system.

Fragment-based screening has become indispensable in drug discovery. Yet, the weak binding affinities of these small molecules still represent a challenge for the reliable detection of fragment hits. The extent of this issue was illustrated in the literature for the aspartic protease endothiapepsin: When seven biochemical and biophysical in vitro screening methods were applied to screen a library of 361 fragments, very poor overlap was observed between the hit fragments identified by the individual approaches, resulting in high levels of false positive and/or false negative results depending on the mutually compared methods. Here, the reported in vitro findings are juxtaposed with the results from in silico docking and scoring approaches. The docking programs GOLD and Glide were considered with the scoring functions ASP, ChemScore, ChemPLP, GoldScore, DSXCSD, and GlideScore. First, the ranking power and scoring power were assessed for the named scoring functions. Second, the capability of reproducing the crystallized fragment binding modes was tested in a structure-based redocking approach. The redocking success notably depended on the ligand efficiency of the considered fragments. Third, a blinded virtual screening approach was employed to evaluate whether in silico screening can compete with in vitro methods in the enrichment of fragment databases.

Fragment-based Drug Discovery Strategy and its Application to the Design of SARS-CoV-2 Main Protease Inhibitor.

Severe Acute Respiratory Syndrome Coronavirus Type 2 (SARS-CoV-2) emerged at the end of 2019, causing a highly infectious and pathogenic disease known as 2019 coronavirus disease. This disease poses a serious threat to human health and public safety. The SARS-CoV-2 main protease (Mpro) is a highly sought-after target for developing drugs against COVID-19 due to its exceptional specificity. Its crystal structure has been extensively documented. Numerous strategies have been employed in the investigation of Mpro inhibitors. This paper is primarily concerned with Fragment-based Drug Discovery (FBDD), which has emerged as an effective approach to drug design in recent times. Here, we summarize the research on the approach of FBDD and its application in developing inhibitors for SARS-CoV-2 Mpro.

Extracting binding energies and binding modes from biomolecular simulations of fragment binding to endothiapepsin.

Fragment-based drug discovery (FBDD) aims to discover a set of small binding fragments that may be subsequently linked together. Therefore, in-depth knowledge of the individual fragments' structural and energetic binding properties is essential. In addition to experimental techniques, the direct simulation of fragment binding by molecular dynamics (MD) simulations became popular to characterize fragment binding. However, former studies showed that long simulation times and high computational demands per fragment are needed, which limits applicability in FBDD. Here, we performed short, unbiased MD simulations of direct fragment binding to endothiapepsin, a well-characterized model system of pepsin-like aspartic proteases. To evaluate the strengths and limitations of short MD simulations for the structural and energetic characterization of fragment binding, we predicted the fragments' absolute free energies and binding poses based on the direct simulations of fragment binding and compared the predictions to experimental data. The predicted absolute free energies are in fair agreement with the experiment. Combining the MD data with binding mode predictions from molecular docking approaches helped to correctly identify the most promising fragments for further chemical optimization. Importantly, all computations and predictions were done within 5 days, suggesting that MD simulations may become a viable tool in FBDD projects.

Identification of small-molecule binding sites of a ubiquitin-conjugating enzyme-UBE2T through fragment-based screening.

UBE2T is an attractive target for drug development due to its linkage with several types of cancers. However, the druggability of ubiquitin-conjugating E2 (UBE2T) is low because of the lack of a deep and hydrophobic pocket capable of forming strong binding interactions with drug-like small molecules. Here, we performed fragment screening using 19 F-nuclear magnetic resonance (NMR) and validated the hits with 1 H-15 N-heteronuclear single quantum coherence (HSQC) experiment and X-ray crystallographic studies. The cocrystal structures obtained revealed the binding modes of the hit fragments and allowed for the characterization of the fragment-binding sites. Further screening of structural analogues resulted in the identification of a compound series with inhibitory effect on UBE2T activity. Our current study has identified two new binding pockets in UBE2T, which will be useful for the development of small molecules to regulate the function of this protein. In addition, the compounds identified in this study can serve as chemical starting points for the development of UBE2T modulators.

Multiplexed experimental strategies for fragment library screening against challenging drug targets using SPR biosensors.

Surface plasmon resonance (SPR) biosensor methods are ideally suited for fragment-based lead discovery.  However, generally applicable experimental procedures and detailed protocols are lacking, especially for structurally or physico-chemically challenging targets or when tool compounds are not available. Success depends on accounting for the features of both the target and the chemical library, purposely designing screening experiments for identification and validation of hits with desired specificity and mode-of-action, and availability of orthogonal methods capable of confirming fragment hits. The range of targets and libraries amenable to an SPR biosensor-based approach for identifying hits is considerably expanded by adopting multiplexed strategies, using multiple complementary surfaces or experimental conditions. Here we illustrate principles and multiplexed approaches for using flow-based SPR biosensor systems for screening fragment libraries of different sizes (90 and 1056 compounds) against a selection of challenging targets. It shows strategies for the identification of fragments interacting with 1) large and structurally dynamic targets, represented by acetyl choline binding protein (AChBP), a Cys-loop receptor ligand gated ion channel homologue, 2) targets in multi protein complexes, represented by lysine demethylase 1 and a corepressor (LSD1/CoREST), 3) structurally variable or unstable targets, represented by farnesyl pyrophosphate synthase (FPPS), 4) targets containing intrinsically disordered regions, represented by protein tyrosine phosphatase 1B  (PTP1B), and 5) aggregation-prone proteins, represented by an engineered form of human tau  (tau K18M). Practical considerations and procedures accounting for the characteristics of the proteins and libraries, and that increase robustness, sensitivity, throughput and versatility are highlighted. The study shows that the challenges for addressing these types of targets is not identification of potentially useful fragments per se, but establishing methods for their validation and evolution into leads.

r-BRICS - A Revised BRICS Module That Breaks Ring Structures and Carbon Chains.

Molecular fragmentation has been frequently used for machine learning, molecular modeling, and drug discovery studies. However, the current molecular fragmentation tools often lead to large fragments that are useful to limited tasks. Specifically, long aliphatic chains, certain connected ring structures, fused rings, as well as various nitrogen-containing molecular entities often remain intact when using BRICS. With no known methods to solve this issue, we find that the fragments taken from BRICS are inflexible for tasks such as fragment-based machine learning, coarse-graining, and ligand-protein interaction assessment. In this work, a revised BRICS (r-BRICS) module is developed to allow more flexible fragmentation on a wider variety of molecules. It is shown that r-BRICS generates smaller fragments than BRICS, allowing localized fragment assessments. Furthermore, r-BRICS generates a fragment database with significantly more unique small fragments than BRICS, which is potentially useful for fragment-based drug discovery.

Current Research Status and Application Technical Progress of Small Molecule Drug Screening Technology / 医药导报

Small molecule drug screening technology is continuously evolving and expanding along with drug discovery,and the innovation in drug screening technology can improve the research and development efficiency and success rate,shorten the cycle time,and reduce the cost.From traditional screening technologies based on known active compounds and high-throughput screening(HTS)to new technologies such as structure-based drug discovery(SBDD),fragment-based drug discovery(FBDD),DNA encoded compound library(DEL)and proteolysis targeting chimeras(PROTAC),small molecule drug screening technologies are continuously broadening the market potential for small molecule drugs.This article will provide an overview of the current status of small molecule drug screening technology,systematically review each technique along with their advantages and disadvantages,and offer essential insights for the development of new small molecule drug screening technologies.