Fragment-based Drug Discovery Campaigns Research Articles

HEIDI: an experiment-management platform enabling high-throughput fragment and compound screening.

The Swiss Light Source facilitates fragment-based drug-discovery campaigns foracademic and industrial users through the Fast Fragment and Compound Screening (FFCS) software suite. This framework is further enriched by the option to utilize the Smart Digital User (SDU) software for automated data collection across the PXI, PXII and PXIII beamlines. In this work, the newly developed HEIDI webpage (https://heidi.psi.ch) is introduced: a platform crafted using state-of-the-art software architecture and web technologies for sample management of rotational data experiments. The HEIDI webpage features a data-review tab for enhanced result visualization and provides programmatic access through a representational state transfer application programming interface (REST API). The migration of the local FFCS MongoDB instance to the cloud is highlighted and detailed. This transition ensures secure, encrypted and consistently accessible data through a robust and reliable REST API tailored for the FFCS software suite. Collectively, these advancements not only significantly elevate the user experience, but also pave the way for future expansions and improvements in the capabilities of the system.

Biocatalytic strategy for the construction of sp3-rich polycyclic compounds from directed evolution and computational modelling.

Catalysis with engineered enzymes has provided more efficient routes for the production of active pharmaceutical agents. However, the potential of biocatalysis to assist in early-stage drug discovery campaigns remains largely untapped. In this study, we have developed a biocatalytic strategy for the construction of sp3-rich polycyclic compounds via the intramolecular cyclopropanation of benzothiophenes and related heterocycles. Two carbene transferases with complementary regioisomer selectivity were evolved to catalyse the stereoselective cyclization of benzothiophene substrates bearing diazo ester groups at the C2 or C3 position of the heterocycle. The detailed mechanisms of these reactions were elucidated by a combination of crystallographic and computational analyses. Leveraging these insights, the substrate scope of one of the biocatalysts could be expanded to include previously unreactive substrates, highlighting the value of integrating evolutionary and rational strategies to develop enzymes for new-to-nature transformations. The molecular scaffolds accessed here feature a combination of three-dimensional and stereochemical complexity with 'rule-of-three' properties, which should make them highly valuable for fragment-based drug discovery campaigns.

Fragment-Based Drug Discovery Campaigns Guided by Native Mass Spectrometry

Fragment-Based Drug Discovery Campaigns Guided by Native Mass Spectrometry

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.

Implementing a Scoring Function Based on Interaction Fingerprint for Autogrow4: Protein Kinase CK1δ as a Case Study.

In the last 20 years, fragment-based drug discovery (FBDD) has become a popular and consolidated approach within the drug discovery pipeline, due to its ability to bring several drug candidates to clinical trials, some of them even being approved and introduced to the market. A class of targets that have proven to be particularly suitable for this method is represented by kinases, as demonstrated by the approval of BRAF inhibitor vemurafenib. Within this wide and diverse set of proteins, protein kinase CK1δ is a particularly interesting target for the treatment of several widespread neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis. Computational methodologies, such as molecular docking, are already routinely and successfully applied in FBDD campaigns alongside experimental techniques, both in the hit-discovery and in the hit-optimization stage. Concerning this, the open-source software Autogrow, developed by the Durrant lab, is a semi-automated computational protocol that exploits a combination between a genetic algorithm and a molecular docking software for de novo drug design and lead optimization. In the current work, we present and discuss a modified version of the Autogrow code that implements a custom scoring function based on the similarity between the interaction fingerprint of investigated compounds and a crystal reference. To validate its performance, we performed both a de novo and a lead-optimization run (as described in the original publication), evaluating the ability of our fingerprint-based protocol to generate compounds similar to known CK1δ inhibitors based on both the predicted binding mode and the electrostatic and shape similarity in comparison with the standard Autogrow protocol.

Structural Characterization of Mycobacterium abscessus Phosphopantetheine Adenylyl Transferase Ligand Interactions: Implications for Fragment-Based Drug Design.

Anti-microbial resistance is a rising global healthcare concern that needs urgent attention as growing number of infections become difficult to treat with the currently available antibiotics. This is particularly true for mycobacterial infections like tuberculosis and leprosy and those with emerging opportunistic pathogens such as Mycobacterium abscessus, where multi-drug resistance leads to increased healthcare cost and mortality. M. abscessus is a highly drug-resistant non-tuberculous mycobacterium which causes life-threatening infections in people with chronic lung conditions such as cystic fibrosis. In this study, we explore M. abscessus phosphopantetheine adenylyl transferase (PPAT), an enzyme involved in the biosynthesis of Coenzyme A, as a target for the development of new antibiotics. We provide structural insights into substrate and feedback inhibitor binding modes of M. abscessus PPAT, thereby setting the basis for further chemical exploration of the enzyme. We then utilize a multi-dimensional fragment screening approach involving biophysical and structural analysis, followed by evaluation of compounds from a previous fragment-based drug discovery campaign against M. tuberculosis PPAT ortholog. This allowed the identification of an early-stage lead molecule exhibiting low micro molar affinity against M. abscessus PPAT (Kd 3.2 ± 0.8 µM) and potential new ways to design inhibitors against this enzyme. The resulting crystal structures reveal striking conformational changes and closure of solvent channel of M. abscessus PPAT hexamer providing novel strategies of inhibition. The study thus validates the ligandability of M. abscessus PPAT as an antibiotic target and identifies crucial starting points for structure-guided drug discovery against this bacterium.

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.

NMR Reporter Assays for the Quantification of Weak-Affinity Receptor-Ligand Interactions.

Biophysical methods are widely employed in academia and the pharmaceutical industry to detect and quantify weak molecular interactions. Such methods find broad application in fragment-based drug discovery (FBDD). In an FBDD campaign, a suitable affinity determination method is key to advancing a project beyond the initial screening phase. Protein-observed (PO) nuclear magnetic resonance (NMR) finds widespread use due to its ability to sensitively detect very weak interactions at residue-level resolution. When there are issues precluding the use of PO-NMR, ligand-observed (LO) NMR reporter assays can be a useful alternative. Such assays can measure affinities in a similar range to PO-NMR while offering some distinct advantages, especially with regard to protein consumption and compound throughput. In this paper, we take a closer look at setting up such assays for routine use, with the aim of getting high-quality, accurate data and good throughput. We assess some of the key characteristics of these assays in the mathematical framework established for fluorescence polarization assays with which the readers may be more familiar. We also provide guidance on setting up such assays and compare their performance with other affinity determination methods that are commonly used in drug discovery.

Applied Biophysical Methods in Fragment-Based Drug Discovery.

Fragment-based drug discovery (FBDD) has come of age in the last decade with the FDA approval of four fragment-derived drugs. Biophysical methods are at the heart of hit discovery and validation in FBDD campaigns. The three most commonly used methods, thermal shift, surface plasmon resonance, and nuclear magnetic resonance, can be daunting for the novice user. We aim here to provide the nonexpert user of these methods with a summary of problems and challenges that might be faced, but also highlight the potential gains that each method can contribute to an FBDD project. While our view on FBDD is slightly biased toward enabling structure-guided drug discovery, most of the points we address in this review are also valid for non-structure-focused FBDD.

Application of Native ESI-MS to Characterize Interactions between Compounds Derived from Fragment-Based Discovery Campaigns and Two Pharmaceutically Relevant Proteins

Native electrospray ionization mass spectrometry (ESI-MS) was applied to analyze the binding of compounds generated during fragment-based drug discovery (FBDD) campaigns against two functionally distinct proteins, the X-linked inhibitor of apoptosis protein (XIAP) and cyclin-dependent kinase 2 (CDK2). Compounds of different molecular weights and a wide range of binding affinities obtained from the hits to leads and lead optimization stages of FBDD campaigns were studied, and their dissociation constants (Kd) were measured by native ESI-MS. We demonstrate that native ESI-MS has the potential to be applied to the stages of an FBDD campaign downstream of primary screening for the detection and quantification of protein–ligand binding. Native ESI-MS was used to derive Kd values for compounds binding to XIAP, and the dissociation of the complex between XIAP and a peptide derived from the second mitochondria-derived activator of caspases (SMAC) protein induced by one of the test compounds was also investigated. Affinities of compounds binding to CDK2 gave Kd values in the low nanomolar to low millimolar range, and Kd values generated by MS and isothermal titration calorimetry (ITC) followed the same trend for both proteins. Practical considerations for the application of native ESI-MS are discussed in detail.

The Fragment Network: A Chemistry Recommendation Engine Built Using a Graph Database.

The hit validation stage of a fragment-based drug discovery campaign involves probing the SAR around one or more fragment hits. This often requires a search for similar compounds in a corporate collection or from commercial suppliers. The Fragment Network is a graph database that allows a user to efficiently search chemical space around a compound of interest. The result set is chemically intuitive, naturally grouped by substitution pattern and meaningfully sorted according to the number of observations of each transformation in medicinal chemistry databases. This paper describes the algorithms used to construct and search the Fragment Network and provides examples of how it may be used in a drug discovery context.

Applications of 19F-NMR in Fragment-Based Drug Discovery

19F-NMR has proved to be a valuable tool in fragment-based drug discovery. Its applications include screening libraries of fluorinated fragments, assessing competition among elaborated fragments and identifying the binding poses of promising hits. By observing fluorine in both the ligand and the target protein, useful information can be obtained on not only the binding pose but also the dynamics of ligand-protein interactions. These applications of 19F-NMR will be illustrated in this review with studies from our fragment-based drug discovery campaigns against protein targets in parasitic and infectious diseases.

NMR methods in fragment based drug discovery

Nuclear magnetic resonance (NMR) spectroscopy, owing to its ability to provide atomic level information on molecular structure, dynamics and interaction, has become one of the most powerful methods in early drug discovery where hit finding and hit-to-lead generation are mainly pursued. In recent years, drug discovery programs originating from the fragment-based drug discovery (FBDD) strategies have been widely incorporated into academia and industry in which a wide variety of NMR methods become an indispensable arsenal to elucidate the binding of small molecules onto bimolecular targets. In this review, I briefly describe FBDD and introduce NMR methods mainly used in FBDD campaigns of my company. In addition, quality control of fragment library and practical NMR methods in industrial aspect are discussed shortly.

ChemInform Abstract: Interrogating Fragments Using a Protein Thermal Shift Assay

AbstractReview: 31 refs.

“The Whole is Greater than the Sum of Its Parts-” Hit Selection and the Power of Orthogonality

Biophysical methods are essential tools in current front line drug discovery processes. They can be used for optimization of protein constructs and verification of proper and consistent protein folding, identification of optimal assay buffer, screening of fragments and the confirmation of binding to the right or allosteric binding site(s) of the target molecule- each approach providing a wealth of information. With a growing industry need to reduce project attrition (and therefore cost) by providing more physiological mechanistic data to aid in the identification of compounds that translate in vitro activity into in vivo efficacy. Application of panels of biophysical techniques allow cross correlation of data and better control of experimental parameters - increasing reliability and confidence in results whilst eliminating artifacts. In this work we show how SPR, DSC and ITC can be used in the selection and verification of binders in a Fragment Based Drug Discovery campaign by providing quantitative binding information to advance true hits for chemistry and later stage biology in hit to lead development.

Saturation Transfer Difference NMR for Fragment Screening

Fragment screening by saturation transfer difference nuclear magnetic resonance (STD-NMR) is a robust method for identifying small molecule binders and is well suited to a broad set of biological targets. STD-NMR is exquisitely sensitive for detecting weakly binding compounds (a common characteristic of fragments), which is a crucial step in finding promising compounds for a fragment-based drug discovery campaign. This protocol describes the development of a library suitable for STD-NMR fragment screening, as well as preparation of protein samples, optimization of experimental conditions, and procedures for data collection and analysis.

Interrogating Fragments Using a Protein Thermal Shift Assay

Protein thermal shift is a relatively rapid and inexpensive technique for the identification of low molecular weight compound interactions with protein targets. An increase in the melting temperature of the target protein in the presence of a test ligand is indicative of a promising ligand–protein interaction. Due to its simplicity, protein thermal shift is an attractive method for screening libraries and validating hits in drug discovery programs. The methodology has been used successfully in high throughput screens of small molecule libraries, and its application has been extended to report on protein–drug-like-fragment interactions. Here, we review how protein thermal shift has been employed recently in fragment-based drug discovery (FBDD) efforts, and highlight its application to protein–protein interaction targets. Multiple validation of fragment hits by independent means is paramount to ensure efficient and economical progress in a FBDD campaign. We discuss the applicability of thermal shift assays in this light, and discuss more generally what one does when orthogonal approaches disagree.

Mycobacterium tuberculosis cytochrome P450 enzymes: a cohort of novel TB drug targets

TB (tuberculosis) disease remains responsible for the death of over 1.5 million people each year. The alarming emergence of drug-resistant TB has sparked a critical need for new front-line TB drugs with a novel mode of action. In the present paper, we review recent genomic and biochemical evidence implicating Mycobacterium tuberculosis CYP (cytochrome P450) enzymes as exciting potential targets for new classes of anti-tuberculars. We also discuss HTS (high-throughput screening) and fragment-based drug-discovery campaigns that are being used to probe their potential druggability.

Target Immobilization as a Strategy for NMR-Based Fragment Screening: Comparison of TINS, STD, and SPR for Fragment Hit Identification

Fragment-based drug discovery (FBDD) has become a widely accepted tool that is complementary to high-throughput screening (HTS) in developing small-molecule inhibitors of pharmaceutical targets. Because a fragment campaign can only be as successful as the hit matter found, it is critical that the first stage of the process be optimized. Here the authors compare the 3 most commonly used methods for hit discovery in FBDD: high concentration screening (HCS), solution ligand-observed nuclear magnetic resonance (NMR), and surface plasmon resonance (SPR). They selected the commonly used saturation transfer difference (STD) NMR spectroscopy and the proprietary target immobilized NMR screening (TINS) as representative of the array of possible NMR methods. Using a target typical of FBDD campaigns, the authors find that HCS and TINS are the most sensitive to weak interactions. They also find a good correlation between TINS and STD for tighter binding ligands, but the ability of STD to detect ligands with affinity weaker than 1 mM K(D) is limited. Similarly, they find that SPR detection is most suited to ligands that bind with K(D) better than 1 mM. However, the good correlation between SPR and potency in a bioassay makes this a good method for hit validation and characterization studies.