Fragment Hits: What do They Look Like and How do They Bind?

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.

A small step towards an important goal: fragment screen of the c-di-AMP-synthesizing enzyme CdaA

CdaA is the most widespread diadenylate cyclase in many bacterial species, including several multidrug-resistant human pathogens. The enzymatic product of CdaA, cyclic di-AMP, is a secondary messenger that is essential for the viability of many bacteria. Its absence in humans makes CdaA a very promising and attractive target for the development of new antibiotics. Here, the structural results are presented of a crystallographic fragment screen against CdaA from Listeria monocytogenes, a saprophytic Gram-positive bacterium and an opportunistic food-borne pathogen that can cause listeriosis in humans and animals. Two of the eight fragment molecules reported here were localized in the highly conserved ATP-binding site. These fragments could serve as potential starting points for the development of antibiotics against several CdaA-dependent bacterial species.

Fragment library screening by X-ray crystallography and binding site analysis on thioredoxin glutathione reductase of Schistosoma mansoni

Schistosomiasis is caused by parasites of the genus Schistosoma, which infect more than 200 million people. Praziquantel (PZQ) has been the main drug for controlling schistosomiasis for over four decades, but despite that it is ineffective against juvenile worms and size and taste issues with its pharmaceutical forms impose challenges for treating school-aged children. It is also important to note that PZQ resistant strains can be generated in laboratory conditions and observed in the field, hence its extensive use in mass drug administration programs raises concerns about resistance, highlighting the need to search for new schistosomicidal drugs. Schistosomes survival relies on the redox enzyme thioredoxin glutathione reductase (TGR), a validated target for the development of new anti-schistosomal drugs. Here we report a high-throughput fragment screening campaign of 768 compounds against S. mansoni TGR (SmTGR) using X-ray crystallography. We observed 49 binding events involving 35 distinct molecular fragments which were found to be distributed across 16 binding sites. Most sites are described for the first time within SmTGR, a noteworthy exception being the "doorstop pocket" near the NADPH binding site. We have compared results from hotspots and pocket druggability analysis of SmTGR with the experimental binding sites found in this work, with our results indicating only limited coincidence between experimental and computational results. Finally, we discuss that binding sites at the doorstop/NADPH binding site and in the SmTGR dimer interface, should be prioritized for developing SmTGR inhibitors as new antischistosomal drugs.

Leveraging nitrogen occurrence in approved drugs to identify structural patterns

BACKGROUND

The process of drug development and discovery is costly and slow. Although an understanding of molecular design principles and biochemical processes has progressed, it is essential to minimize synthesis-testing cycles. An effective approach is to analyze key heteroatoms, including oxygen and nitrogen. Herein, we present an analysis focusing on the utilization of nitrogen atoms in approved drugs.

RESEARCH DESIGN AND METHODS

The present work examines the frequency, distribution, prevalence, and diversity of nitrogen atoms in a dataset comprising 2,049 small molecules approved by different regulatory agencies (FDA and others). Various types of nitrogen atoms, such as sp3-, sp2-, sp-hybridized, planar, ring, and non-ring are included in this investigation.

RESULTS

The results unveil both previously reported and newly discovered patterns of nitrogen atom distribution around the center of mass in the majority of drug molecules.

CONCLUSIONS

This study has highlighted intriguing trends in the role of nitrogen atoms in drug design and development. The majority of drugs contain 1-3 nitrogen atoms within 5Å from the center of mass (COM) of a molecule, with a higher preference for the ring and planar nitrogen atoms. The results offer invaluable guidance for the multiparameter optimization process, thus significantly contributing toward the conversion of lead compounds into potential drug candidates.

Efficient Ligand Discovery Using Sulfur(VI) Fluoride Reactive Fragments

Sulfur(VI) fluorides (SFs) have emerged as valuable electrophiles for the design of "beyond-cysteine" covalent inhibitors and offer potential for expansion of the liganded proteome. Since SFs target a broad range of nucleophilic amino acids, they deliver an approach for the covalent modification of proteins without requirement for a proximal cysteine residue. Further to this, libraries of reactive fragments present an innovative approach for the discovery of ligands and tools for proteins of interest by leveraging a breadth of mass spectrometry analytical approaches. Herein, we report a screening approach that exploits the unique properties of SFs for this purpose. Libraries of SF-containing reactive fragments were synthesized, and a direct-to-biology workflow was taken to efficiently identify hit compounds for CAII and BCL6. The most promising hits were further characterized to establish the site(s) of covalent modification, modification kinetics, and target engagement in cells. Crystallography was used to gain a detailed molecular understanding of how these reactive fragments bind to their target. It is anticipated that this screening protocol can be used for the accelerated discovery of "beyond-cysteine" covalent inhibitors.

Updates on drug designing approach through computational strategies: a review

The drug discovery and development (DDD) process in pursuit of novel drug candidates is a challenging procedure requiring lots of time and resources. Therefore, computer-aided drug design (CADD) methodologies are used extensively to promote proficiency in drug development in a systematic and time-effective manner. The point in reference is SARS-CoV-2 which has emerged as a global pandemic. In the absence of any confirmed drug moiety to treat the infection, the science fraternity adopted hit and trial methods to come up with a lead drug compound. This article is an overview of the virtual methodologies, which assist in finding novel hits and help in the progression of drug development in a short period with a specific medicinal solution.

Proteome-Wide Fragment-Based Ligand and Target Discovery

Chemical probes are invaluable tools to investigate biological processes and can serve as lead molecules for the development of new therapies. However, despite their utility, only a fraction of human proteins have selective chemical probes, and more generally, our knowledge of the "chemically-tractable" proteome is limited, leaving many potential therapeutic targets unexploited. To help address these challenges, powerful chemical proteomic approaches have recently been developed to globally survey the ability of proteins to bind small molecules (i. e., ligandability) directly in native systems. In this review, we discuss the utility of such approaches, with a focus on the integration of chemoproteomic methods with fragment-based ligand discovery (FBLD), to facilitate the broad mapping of the ligandable proteome while also providing starting points for progression into lead chemical probes.

Green Drug Discovery: Novel Fragment Space from the Biomass-Derived Molecule Dihydrolevoglucosenone (CyreneTM)

Biomass-derived molecules can provide a basis for sustainable drug discovery. However, their full exploration is hampered by the dominance of millions of old-fashioned screening compounds in classical high-throughput screening (HTS) libraries frequently utilized. We propose a fragment-based drug discovery (FBDD) approach as an efficient method to navigate biomass-derived drug space. Here, we perform a proof-of-concept study with dihydrolevoglucosenone (Cyrene^TM), a pyrolysis product of cellulose. Diverse synthetic routes afforded a 100-membered fragment library with a diversity in functional groups appended. The library overall performs well in terms of novelty, physicochemical properties, aqueous solubility, stability, and three-dimensionality. Our study suggests that Cyrene-based fragments are a valuable green addition to the drug discovery toolbox. Our findings can help in paving the way for new hit drug candidates that are based on renewable resources.

Is the Stalk of the SARS-CoV-2 Spike Protein Druggable?

The spike protein is key to SARS-CoV-2 high infectivity because it facilitates the receptor binding domain (RBD) encounter with ACE2. As targeting subunit S1 has not yet delivered an ACE2-binding inhibitor, we have assessed the druggability of the conserved segment of the spike protein stalk within subunit S2 by means of an integrated computational approach that combines the molecular docking of an optimized library of fragments with high-throughput molecular dynamics simulations. The high propensity of the spike protein to mutate in key regions that are responsible for the recognition of the human angiotensin-converting enzyme 2 (hACE2) or for the recognition of antibodies, has made subunit S1 of the spike protein difficult to target. Despite the inherent flexibility of the stalk region, our results suggest two hidden interhelical binding sites, whose accessibility is only partially hampered by glycan residues.

Trifluoromethylation of Carbonyl and Unactivated Olefin Derivatives by C(sp3 )-C Bond Cleavage

Herein, we report a Cu-mediated trifluoromethylation of carbonyl-type compounds and unactivated olefins enabled by visible-light irradiation via σ C(sp³ )-C bond-functionalization. The reaction is distinguished by its modularity, mild conditions and wide scope-even in the context of late-stage functionalization-thus offering a complementary approach en route to valuable C(sp³ )-CF₃ architectures from easily accessible precursors.

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 KRAS^G12C inhibitor sotorasib highlighting the utility of FBDD against targets that were long considered undruggable.

Fragment Libraries Designed to Be Functionally Diverse Recover Protein Binding Information More Efficiently Than Standard Structurally Diverse Libraries

Current fragment-based drug design relies on the efficient exploration of chemical space by using structurally diverse libraries of small fragments. However, structurally dissimilar compounds can exploit the same interactions and thus be functionally similar. Using three-dimensional structures of many fragments bound to multiple targets, we examined if a better strategy for selecting fragments for screening libraries exists. We show that structurally diverse fragments can be described as functionally redundant, often making the same interactions. Ranking fragments by the number of novel interactions they made, we show that functionally diverse selections of fragments substantially increase the amount of information recovered for unseen targets compared to the amounts recovered by other methods of selection. Using these results, we design small functionally efficient libraries that can give significantly more information about new protein targets than similarly sized structurally diverse libraries. By covering more functional space, we can generate more diverse sets of drug leads.

Exploring the kinase-inhibitor fragment interaction space facilitates the discovery of kinase inhibitor overcoming resistance by mutations

Protein kinases play crucial roles in many cellular signaling processes, making them become important targets for drug discovery. But drug resistance mediated by mutation puts a barrier to the therapeutic effect of kinase inhibitors. Fragment-based drug discovery has been successfully applied to overcome such resistance. However, the complicate kinase-inhibitor fragment interaction and fragment-to-lead process seriously limit the efficiency of kinase inhibitor discovery against resistance caused by mutation. Here, we constructed a comprehensive web platform KinaFrag for the fragment-based kinase inhibitor discovery to overcome resistance. The kinase-inhibitor fragment space was investigated from 7783 crystal kinase-inhibitor fragment complexes, and the structural requirements of kinase subpockets were analyzed. The core fragment-based virtual screening workflow towards specific subpockets was developed to generate new kinase inhibitors. A series of tropomyosin receptor kinase (TRK) inhibitors were designed, and the most potent compound YT9 exhibits up to 70-fold activity improvement than marketed drugs larotrectinib and selitrectinib against G595R, G667C and F589L mutations of TRKA. YT9 shows promising antiproliferative against tumor cells in vitro and effectively inhibits tumor growth in vivo for wild type TRK and TRK mutants. Our results illustrate the great potential of KinaFrag in the kinase inhibitor discovery to combat resistance mediated by mutation. KinaFrag is freely available at http://chemyang.ccnu.edu.cn/ccb/database/KinaFrag/.

Computational Cosolvent Mapping Analysis Leads to Identify Salicylic Acid Analogs as Weak Inhibitors of ST2 and IL33 Binding

Cytokine signaling initiated by the binding of the cytokine receptors to cytokines plays important roles in immune regulation and diseases. Structurally, cytokine receptors interact with cytokines via an extensive, rugged interface that represents a challenge in inhibitor development. Our computational analysis has previously indicated that butyric acid, mimicking acidic residues, preferentially binds to sites in ST2 (Stimulation-2) that interact with acidic residues of IL33, the endogenous cytokine for ST2. To investigate if a charged group in small molecules facilitates ligand binding to ST2, we developed a biochemical homogeneous time resolved fluorescence assay to determine the inhibition of ST2/IL33 binding by five molecules containing an aromatic ring and a charged group. Three molecules, including niacin, salicylic acid, and benzamidine, exhibit inhibition activities at millimolar concentrations. We further employed the computational cosolvent mapping analysis to identify a shared mode of interaction between niacin, salicylic acid, and ST2. The mode of interaction was further confirmed by four analogous compounds that exhibited similar or improved activities. Our study provided the evidence of inhibition of ST2 and IL33 binding by salicylic acid and analogs. The results suggest that biological activity of salicylic acid may be partly mediated through modulating extracellular cytokine receptors and cytokine interaction.

Decomposing compounds enables reconstruction of interaction fingerprints for structure-based drug screening

Background

Structure-based drug repositioning has emerged as a promising alternative to conventional drug development. Regardless of the many success stories reported over the past years and the novel breakthroughs on the AI-based system AlphaFold for structure prediction, the availability of structural data for protein–drug complexes remains very limited. Whereas the chemical libraries contain millions of drug compounds, the vast majority of them do not have structures to crystallized targets,and it is, therefore, impossible to characterize their binding to targets from a structural view. However, the concept of building blocks offers a novel perspective on the structural problem. A drug compound is considered a complex of small chemical blocks or fragments, which confer the relevant properties to the drug and have a high proportion of functional groups involved in protein binding. Based on this, we propose a novel approach to expand the scope of structure-based repositioning approaches by transferring the structural knowledge from a fragment to a compound level.

Results

We fragmented over 100,000 compounds in the Protein Data Bank (PDB) and characterized the structural binding mode of 153,000 fragments to their crystallized targets. Using the fragment’s data, we were able to artificially reconstruct the binding mode of over 7,800 complexes between ChEMBL compounds and their known targets, for which no structural data is available. We proved that the conserved binding tendency of fragments, when binding to the same targets, highly influences the drug’s binding specificity and carries the key information to reconstruct full drugs binding mode. Furthermore, our approach was able to reconstruct multiple compound-target pairs at optimal thresholds and high similarity to the actual binding mode.

Conclusions

Such reconstructions are of great value and benefit structure-based drug repositioning since they automatically enlarge the technique’s scope and allow exploring the so far ‘unexplored compounds’ from a structural perspective. In general, the transfer of structural information is a promising technique that could be applied to any chemical library, to any compound that has no crystal structure available in PDB, and even to transfer any other feature that may be relevant for the drug discovery process and that due to data limitations is not yet fully available. In that sense, the results of this work document the full potential of structure-based screening even beyond PDB.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13321-022-00592-w.

Puckering the planar landscape of fragments: design and synthesis of a 3D cyclobutane fragment library

Fragment‐based drug discovery (FBDD) has a growing need for unique screening libraries. The cyclobutane moiety was identified as an underrepresented yet attractive three‐dimensional (3D) scaffold. Synthetic strategies were developed via a key 3‐azido‐cyclobutanone intermediate, giving potential access to a range of functional groups with accessible growth vectors. A focused set of 33 novel 3D cyclobutane fragments was synthesised, comprising three functionalities: secondary amines, amides, and sulfonamides. This library was designed using Principal Component Analysis (PCA) and an expanded version of the rule of three (RO3), followed by Principal Moment of Inertia (PMI) analysis to achieve both chemical diversity and high 3D character. Cis and trans ring isomers of library members were generated to maximise the shape diversity obtained, while limiting molecular complexity through avoiding enantiomers. Property analyses of the cyclobutane library indicated that it fares favourably against existing synthetic 3D fragment libraries in terms of shape and physicochemical properties.

On the influence of water on THz vibrational spectral features of molecular crystals

The nanoscale structure of molecular assemblies plays a major role in many (μ)-biological mechanisms. Molecular crystals are one of the most simple of these assemblies and are widely used in a variety of applications from pharmaceuticals and agrochemicals, to nutraceuticals and cosmetics. The collective vibrations in such molecular crystals can be probed using terahertz spectroscopy, providing unique characteristic spectral fingerprints. However, the association of the spectral features to the crystal conformation, crystal phase and its environment is a difficult task. We present a combined computational-experimental study on the incorporation of water in lactose molecular crystals, and show how simulations can be used to associate spectral features in the THz region to crystal conformations and phases. Using periodic DFT simulations of lactose molecular crystals, the role of water in the observed lactose THz spectrum is clarified, presenting both direct and indirect contributions. A specific experimental setup is built to allow the controlled heating and corresponding dehydration of the sample, providing the monitoring of the crystal phase transformation dynamics. Besides the observation that lactose phases and phase transformation appear to be more complex than previously thought - including several crystal forms in a single phase and a non-negligible water content in the so-called anhydrous phase - we draw two main conclusions from this study. Firstly, THz modes are spread over more than one molecule and require periodic computation rather than a gas-phase one. Secondly, hydration water does not only play a perturbative role but also participates in the facilitation of the THz vibrations.

Small-Molecule Lead-Finding Trends across the Roche and Genentech Research Organizations

The origin of small-molecule leads that were pursued across the independent research organizations Roche and Genentech from 2009 to 2020 is described. The identified chemical series are derived from a variety of lead-finding methods, which include public information, high-throughput screening (both full file and focused), fragment-based design, DNA-encoded library technology, use of legacy internal data, in-licensing, and de novo design (often structure-based). The translation of the lead series into in vivo tool compounds and development candidates is discussed as are the associated biological target classes and corresponding therapeutic areas. These analyses identify important trends regarding the various lead-finding approaches, which will likely impact their future application in the Roche and Genentech research groups. They also highlight commonalities and differences across the two independent research organizations. Several caveats associated with the employed data collection and analysis methodologies are included to enhance the interpretation of the presented information.

Quadruple Target Evaluation of Diversity-Optimized Halogen-Enriched Fragments (HEFLibs) Reveals Substantial Ligand Efficiency for AP2-Associated Protein Kinase 1 (AAK1)

Fragment-based drug discovery is one of the most utilized approaches for the identification of novel weakly binding ligands, by efficiently covering a wide chemical space with rather few compounds and by allowing more diverse binding modes to be found. This approach has led to various clinical candidates and approved drugs. Halogen bonding, on the other hand, has gained traction in molecular design and lead optimization, but could offer additional benefits in early drug discovery. Screening halogen-enriched fragments (HEFLibs) could alleviate problems associated with the late introduction of such a highly geometry dependent interaction. Usually, the binding mode is then already dominated by other strong interactions. Due to the fewer competing interactions in fragments, the halogen bond should more often act as an anchor point for the binding mode. Previously, we proposed a fragment library with a focus on diverse binding modes that involve halogens for gaining initial affinity and selectivity. Herein, we demonstrate the applicability of these HEFLibs with a small set of diverse enzymes: the histone-lysine N-methyltransferase DOT1L, the indoleamine 2,3-dioxygenase 1 (IDO1), the AP2-associated protein kinase 1 (AAK1), and the calcium/calmodulin-dependent protein kinase type 1G (CAMK1G). We were able to identify various binding fragments via STD-NMR. Using ITC to verify these initial hits, we determined affinities for many of these fragments. The best binding fragments exhibit affinities in the one-digit micromolar range and ligand efficiencies up to 0.83 for AAK1. A small set of analogs was used to study structure-affinity relationships and hereby analyze the specific importance of each polar interaction. This data clearly suggests that the halogen bond is the most important interaction of fragment 9595 with AAK1.

Urokinase plasminogen activator as an anti-metastasis target: inhibitor design principles, recent amiloride derivatives, and issues with human/mouse species selectivity

The urokinase plasminogen activator (uPA) is a widely studied anticancer drug target with multiple classes of inhibitors reported to date. Many of these inhibitors contain amidine or guanidine groups, while others lacking these groups show improved oral bioavailability. Most of the X-ray co-crystal structures of small molecule uPA inhibitors show a key salt bridge with the side chain carboxylate of Asp189 in the S1 pocket of uPA. This review summarises the different classes of uPA inhibitors, their binding interactions and experimentally measured inhibitory potencies and highlights species selectivity issues with attention to recently described 6-substituted amiloride and 5‑N,N-(hexamethylene)amiloride (HMA) derivatives.

HT-SuMD: making molecular dynamics simulations suitable for fragment-based screening. A comparative study with NMR

Fragment-based lead discovery (FBLD) is one of the most efficient methods to develop new drugs. We present here a new computational protocol called High-Throughput Supervised Molecular Dynamics (HT-SuMD), which makes it possible to automatically screen up to thousands of fragments, representing therefore a new valuable resource to prioritise fragments in FBLD campaigns. The protocol was applied to Bcl-XL, an oncological protein target involved in the regulation of apoptosis through protein-protein interactions. Initially, HT-SuMD performances were validated against a robust NMR-based screening, using the same set of 100 fragments. These independent results showed a remarkable agreement between the two methods. Then, a virtual screening on a larger library of additional 300 fragments was carried out and the best hits were validated by NMR. Remarkably, all the in silico selected fragments were confirmed as Bcl-XL binders. This represents, to date, the largest computational fragments screening entirely based on MD.

C-H functionalisation tolerant to polar groups could transform fragment-based drug discovery (FBDD)

We have analysed 131 fragment-to-lead (F2L) examples targeting a wide variety of protein families published by academic and industrial laboratories between 2015-2019. Our assessment of X-ray structural data identifies the most common polar functional groups involved in fragment-protein binding are: N-H (hydrogen bond donors on aromatic and aliphatic N-H, amides and anilines; totalling 35%), aromatic nitrogen atoms (hydrogen bond acceptors; totalling 23%), and carbonyl oxygen group atoms (hydrogen bond acceptors on amides, ureas and ketones; totalling 22%). Furthermore, the elaboration of each fragment into its corresponding lead is analysed to identify the nominal synthetic growth vectors. In ∼80% of cases, growth originates from an aromatic or aliphatic carbon on the fragment and more than 50% of the total bonds formed are carbon-carbon bonds. This analysis reveals that growth from carbocentric vectors is key and therefore robust C-H functionalisation methods that tolerate the innate polar functionality on fragments could transform fragment-based drug discovery (FBDD). As a further resource to the community, we have provided the full data of our analysis as well as an online overlay page of the X-ray structures of the fragment hit and leads: https://astx.com/interactive/F2L-2021/.

Automated Generation of Novel Fragments Using Screening Data, a Dual SMILES Autoencoder, Transfer Learning and Syntax Correction

Fragment-based hit identification (FBHI) allows proportionately greater coverage of chemical space using fewer molecules than traditional high-throughput screening approaches. However, effectively exploiting this advantage is highly dependent on the library design. Solubility, stability, chemical complexity, chemical/shape diversity, and synthetic tractability for fragment elaboration are all critical aspects, and molecule design remains a time-consuming task for computational and medicinal chemists. Artificial neural networks have attracted considerable attention in automated de novo design applications and could also prove useful for fragment library design. Chemical autoencoders are neural networks consisting of encoder and decoder parts, which respectively compress and decompress molecular representations. The decoder is applied to samples drawn from the space of compressed representations to generate novel molecules that can be scored for properties of interest. Here, we report an autoencoder model using a recurrent neural network architecture, which was trained using 486,565 fragments curated from commercial sources, to simultaneously reconstruct both SMILES and chemical fingerprints. To explore its utility in fragment design, we applied transfer learning to the fingerprint decoder layers to train a classifier using 66 frequent hitter fragments identified from our screening campaigns. Using a particle swarm optimization sampling approach, we compare the performance of this "dual" model to an architecture encoding SMILES only. The dual model produced valid SMILES with improved features, considering a range of properties including aromatic ring counts, heavy atom count, synthetic accessibility, and a new fragment complexity score we term Feature Complexity (FeCo). Additionally, we demonstrate that generative performance is further enhanced by use of a simple syntax-correction procedure during training, in which invalid and undesirable SMILES are spiked into the training set. Finally, we used the syntax-corrected model to generate a library of novel candidate privileged fragments.

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.

Exploring protein hotspots by optimized fragment pharmacophores

Fragment-based drug design has introduced a bottom-up process for drug development, with improved sampling of chemical space and increased effectiveness in early drug discovery. Here, we combine the use of pharmacophores, the most general concept of representing drug-target interactions with the theory of protein hotspots, to develop a design protocol for fragment libraries. The SpotXplorer approach compiles small fragment libraries that maximize the coverage of experimentally confirmed binding pharmacophores at the most preferred hotspots. The efficiency of this approach is demonstrated with a pilot library of 96 fragment-sized compounds (SpotXplorer0) that is validated on popular target classes and emerging drug targets. Biochemical screening against a set of GPCRs and proteases retrieves compounds containing an average of 70% of known pharmacophores for these targets. More importantly, SpotXplorer0 screening identifies confirmed hits against recently established challenging targets such as the histone methyltransferase SETD2, the main protease (3CLPro) and the NSP3 macrodomain of SARS-CoV-2.

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.

Pillar[5]arene-Derived endo-Functionalized Molecular Tube for Mimicking Protein-Ligand Interactions

Artificial tubular molecular pockets bearing polar functionalities on their inner surface are useful model systems for understanding the mechanisms of protein-ligand interactions in living systems. We herein report a pillar[5]arene-derived molecular tube, [P4-(OH)BPO], whose endo conformational isomer endo-[P4-(OH)BPO] possesses an inwardly pointing hydrogen-bond (H-bond) donor (OH) in its deep cavity and a strong H-bond acceptor (C═O) on its predominantly hydrophobic inner surface, rendering it a perfect protein binding pocket mimetic. A fragment-based drug design model was established using endo-[P4-(OH)BPO] and a library of various shape-complementary fragment ligands (1-38). On the basis of the binding affinity data for "fragment-pocket" complexes G⊂endo-[P4-(OH)BPO] (G = 1-38), two rationally designed "lead molecules" (39 and 40) were identified as being able to enhance binding affinity significantly by forming H-bonds with both the donor and acceptor of endo-[P4-(OH)BPO]. The described work opens new avenues for developing pillar[n]arene-derived protein binding pocket-mimetic systems for studies of protein-ligand interactions and mechanisms of enzymatic reactions.

Multiple Target Drug Design Using LigBuilder 3

Designing drugs that directly interact with multiple targets is a promising approach for treating complicated diseases. In order to successfully bind to multiple targets of different families and achieve the desired ligand efficiency, multi-target-directed ligands (MTDLs) require a higher level of diversity and complexity. De novo design strategies for creating more diverse chemical entities with desired properties may present an improved approach for developing MTDLs. In this chapter, we describe a computational protocol for developing MTDLs using the first reported multi-target de novo program, LigBuilder 3, which combines a binding site prediction module with de novo drug design and optimization modules. As an illustration of each detailed procedure, we design dual-functional compounds of two well-characterized virus enzymes, HIV protease and reverse transcriptase (PR and RT, respectively), using fragments extracted from known inhibitors. LigBuilder 3 is accessible at http://www.pkumdl.cn/ligbuilder3/ .

Into the Fray! A Beginner's Guide to Medicinal Chemistry

Modern medicinal chemistry is a complex, multidimensional discipline that operates at the interface of the chemical and biological sciences. The medicinal chemistry contribution to drug discovery is typically described in the context of the well-recited linear progression of the drug discovery pipeline. However, compound optimization is idiosyncratic to each project, and clear definitions of hit and lead molecules and the subsequent progress along the pipeline becomes easily blurred. In addition, this description lacks insight into the entangled relationship between chemical and pharmacological properties, and thus provides limited guidance on how innovative medicinal chemistry strategies can be applied to solve optimization problems, regardless of the stage in the pipeline. Through discussion and illustrative examples, this article seeks to provide insights into the finesse of medicinal chemistry and the subtlety of balancing chemical properties pharmacology. In so doing, it aims to serve as an accessible and simple-to-digest guide for anyone who wishes to learn about the underlying principles of medicinal chemistry, in a context that has been decoupled from the pipeline description.

Investigating the effects of the core nitrogen atom configuration on the thermodynamic solubility of 6,5-bicyclic heterocycles

Physicochemical properties, such as solubility, are important when prioritising compounds for progression on a drug discovery project. There is limited literature around the systematic effects of core changes on thermodynamic solubility. This work details the synthesis of nitrogen containing 6,5-bicyclic heterocyclic cores which are common scaffolds in medicinal chemistry and the analysis of their physicochemical properties, particularly, thermodynamic solubility. Crystalline solids were obtained where possible to enable a robust comparison of the thermodynamic solubility. Other parameters such as pK_a, melting point and lipophilicity were also measured to determine the key factors affecting the observed solubility.

Lewis Acid Promoted Dearomatization of Naphthols

Two-step dearomative functionalization of naphthols promoted by Lewis acids and copper(I) catalysis was developed. Initially, Lewis acid complexation inverted the electronic properties of the ring and established an equilibrium with the dearomatized counterpart. Subsequent trapping of the dearomatized intermediate with organometallics as well as organophosphines was demonstrated and provided the corresponding dearomatized products.

Discovery of allosteric binding sites by crystallographic fragment screening

Understanding allosteric regulation of proteins is fundamental to our study of protein structure and function. Moreover, allosteric binding pockets have become a major target of drug discovery efforts in recent years. However, even though the function of almost every protein can be influenced by allostery, it remains a challenge to discover, rationalise and validate putative allosteric binding pockets. This review examines how the discovery and analysis of putative allosteric binding sites have been influenced by the availability of centralised facilities for crystallographic fragment screening, along with newly developed computational methods for modelling low occupancy features. We discuss the experimental parameters required for success, and how new methods could influence the field in the future. Finally, we reflect on the general problem of how to translate these findings into actual ligand development programs.

The exploration of aza-quinolines as hematopoietic prostaglandin D synthase (H-PGDS) inhibitors with low brain exposure

GlaxoSmithKline and Astex Pharmaceuticals recently disclosed the discovery of the potent H-PGDS inhibitor GSK2894631A 1a (IC₅₀ = 9.9 nM) as part of a fragment-based drug discovery collaboration with Astex Pharmaceuticals. This molecule exhibited good murine pharmacokinetics, allowing it to be utilized to explore H-PGDS pharmacology in vivo. Yet, with prolonged dosing at higher concentrations, 1a induced CNS toxicity. Looking to attenuate brain penetration in this series, aza-quinolines, were prepared with the intent of increasing polar surface area. Nitrogen substitutions at the 6- and 8-positions of the quinoline were discovered to be tolerated by the enzyme. Subsequent structure activity studies in these aza-quinoline scaffolds led to the identification of 1,8-naphthyridine 1y (IC₅₀ = 9.4 nM) as a potent peripherally restricted H-PGDS inhibitor. Compound 1y is efficacious in four in vivo inflammatory models and exhibits no CNS toxicity.

Fragment-to-Lead Medicinal Chemistry Publications in 2019

Fragment-based drug discovery (FBDD) has grown and matured to a point where it is valuable to keep track of its extent and details of application. This Perspective summarizes successful fragment-to-lead stories published in 2019. It is the fifth in a series that started with literature published in 2015. The analysis of screening methods, optimization strategies, and molecular properties of hits and leads are presented in the hope of informing best practices for FBDD. Moreover, FBDD is constantly evolving, and the latest technologies and emerging trends are summarized. These include covalent FBDD, FBDD for the stabilization of proteins or protein-protein interactions, FBDD for enzyme activators, new screening technologies, and advances in library design and chemical synthesis.

Structure based virtual screening identifies small molecule effectors for the sialoglycan binding protein Hsa

Infective endocarditis (IE) is a cardiovascular disease often caused by bacteria of the viridans group of streptococci, which includes Streptococcus gordonii and Streptococcus sanguinis. Previous research has found that serine-rich repeat (SRR) proteins on the S. gordonii bacterial surface play a critical role in pathogenesis by facilitating bacterial attachment to sialylated glycans displayed on human platelets. Despite their important role in disease progression, there are currently no anti-adhesive drugs available on the market. Here, we performed structure-based virtual screening using an ensemble docking approach followed by consensus scoring to identify novel small molecule effectors against the sialoglycan binding domain of the SRR adhesin protein Hsa from the S. gordonii strain DL1. The screening successfully predicted nine compounds which were able to displace the native ligand (sialyl-T antigen) in an in vitro assay and bind competitively to Hsa. Furthermore, hierarchical clustering based on the MACCS fingerprints showed that eight of these small molecules do not share a common scaffold with the native ligand. This study indicates that SRR family of adhesin proteins can be inhibited by diverse small molecules and thus prevent the interaction of the protein with the sialoglycans. This opens new avenues for discovering potential drugs against IE.

The rise of molecular simulations in fragment-based drug design (FBDD): an overview

Fragment-based drug discovery (FBDD) is an innovative approach, progressively more applied in the academic and industrial context, to enhance hit identification for previously considered undruggable biological targets. In particular, FBDD discovers low-molecular-weight (LMW) ligands (<300Da) able to bind to therapeutically relevant macromolecules in an affinity range from the micromolar (μM) to millimolar (mM). X-ray crystallography (XRC) and nuclear magnetic resonance (NMR) spectroscopy are commonly the methods of choice to obtain 3D information about the bound ligand-protein complex, but this can occasionally be problematic, mainly for early, low-affinity fragments. The recent development of computational fragment-based approaches provides a further strategy for improving the identification of fragment hits. In this review, we summarize the state of the art of molecular dynamics simulations approaches used in FBDD, and discuss limitations and future perspectives for these approaches.

Assessment of the Fragment Docking Program SEED

The fragment docking program solvation energy for exhaustive docking (SEED) is evaluated on 15 different protein targets, with a focus on enrichment and the hit rate. It is shown that SEED allows for consistent computational enrichment of fragment libraries, independent of the effective hit rate. Depending on the actual target protein, true positive rates ranging up to 27% are observed at a cutoff value corresponding to the experimental hit rate. The impact of variations in docking protocols and energy filters is discussed in detail. Remaining issues, limitations, and use cases of SEED are also discussed. Our results show that fragment library selection or enhancement for a particular target is likely to benefit from docking with SEED, suggesting that SEED is a useful resource for fragment screening campaigns. A workflow is presented for the use of the program in virtual screening, including filtering and postprocessing to optimize hit rates.

Efficient Synthesis of 1,4-Thiazepanones and 1,4-Thiazepanes as 3D Fragments for Screening Libraries

1,4-Thiazepanes and 1,4-thiazepanones represent seven-membered ring systems with highly 3D character and are currently underrepresented in fragment screening libraries. A nuclear magnetic resonance (NMR) fragment screen identified 1,4-acylthiazepanes as new BET (bromodomain and extraterminal domain) bromodomain ligands; however, an efficient and readily diversified synthesis for library development has not been reported. Here we report a one-pot synthesis using α,β-unsaturated esters and 1,2-amino thiols to form 1,4-thiazepanones as precursors to 1,4-thiazepanes with high 3D character. This reaction proceeds in reasonable time (0.5-3 h) and in good yield and tolerates a broad scope of α,β-unsaturated esters. Several 1,4-thiazepanes were synthesized by a two-step transformation and were characterized as new BET bromodomain ligands using protein-observed 19F NMR. This synthesis should provide ready access to diverse 3D fragments for screening libraries.

In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery

Fragment-based drug (or lead) discovery (FBDD or FBLD) has developed in the last two decades to become a successful key technology in the pharmaceutical industry for early stage drug discovery and development. The FBDD strategy consists of screening low molecular weight compounds against macromolecular targets (usually proteins) of clinical relevance. These small molecular fragments can bind at one or more sites on the target and act as starting points for the development of lead compounds. In developing the fragments attractive features that can translate into compounds with favorable physical, pharmacokinetics and toxicity (ADMET-absorption, distribution, metabolism, excretion, and toxicity) properties can be integrated. Structure-enabled fragment screening campaigns use a combination of screening by a range of biophysical techniques, such as differential scanning fluorimetry, surface plasmon resonance, and thermophoresis, followed by structural characterization of fragment binding using NMR or X-ray crystallography. Structural characterization is also used in subsequent analysis for growing fragments of selected screening hits. The latest iteration of the FBDD workflow employs a high-throughput methodology of massively parallel screening by X-ray crystallography of individually soaked fragments. In this review we will outline the FBDD strategies and explore a variety of in silico approaches to support the follow-up fragment-to-lead optimization of either: growing, linking, and merging. These fragment expansion strategies include hot spot analysis, druggability prediction, SAR (structure-activity relationships) by catalog methods, application of machine learning/deep learning models for virtual screening and several de novo design methods for proposing synthesizable new compounds. Finally, we will highlight recent case studies in fragment-based drug discovery where in silico methods have successfully contributed to the development of lead compounds.

Kinetic Target-Guided Synthesis: Reaching the Age of Maturity

Kinetic target-guided synthesis (KTGS) is an original discovery strategy allowing a target to catalyze the irreversible synthesis of its own ligands from a pool of reagents. Although pioneered almost two decades ago, it only recently proved its usefulness in medicinal chemistry, as exemplified by the increasing number of protein targets used, the wider range of target and pocket types, and the diversity of therapeutic areas explored. In recent years, two new leads for in vivo studies were released. Amidations and multicomponent reactions expanded the armamentarium of reactions beyond triazole formation and two new examples of in cellulo KTGS were also disclosed. Herein, we analyze the origins and the chemical space of both KTGS ligands and warhead-bearing reagents. We review the KTGS timeline focusing on recent cases in order to give medicinal chemists the full scope of this strategy which has great potential for hit discovery and hit or lead optimization.

Evaluating the Advantages of Using 3D-Enriched Fragments for Targeting BET Bromodomains

Fragment-based ligand discovery has been successful in targeting diverse proteins. Despite drug-like molecules having more 3D character, traditional fragment libraries are largely composed of flat, aromatic fragments. The use of 3D-enriched fragments for enhancing library diversity is underexplored especially against protein-protein interactions. Here, we evaluate using 3D-enriched fragments against bromodomains. Bromodomains are highly ligandable, but selectivity remains challenging, particularly for bromodomain and extraterminal (BET) family bromodomains. We screened a 3D-enriched fragment library against BRD4(D1) via ¹H CPMG NMR with a protein-observed ¹⁹F NMR secondary assay. The screen led to 29% of the hits that are selective over two related bromodomains, BRDT(D1) and BPTF, and the identification of underrepresented chemical bromodomain inhibitor scaffolds. Initial structure-activity relationship studies guided by X-ray crystallography led to a ligand-efficient thiazepane, with good selectivity and affinity for BET bromodomains. These results suggest that the incorporation of 3D-enriched fragments to increase library diversity can benefit bromodomain screening.

Thermodynamic profiling for fragment-based lead discovery and optimization

Introduction: The enthalpic and entropic components of the ligand-protein binding free energy reflect the type and quality of the interactions and relate to the physicochemical properties of the ligands. These findings have significance in medicinal chemistry optimizations since they suggest that the thermodynamic profiling of the binding may help monitor and control the unfavorable size and hydrophobicity increase typically accompanying affinity improvements and leading to suboptimal pharmacokinetic properties.Areas covered: This review describes the ligand-protein binding event in terms of elementary steps, their associated interactions, and their enthalpic and entropic consequences. The relationships among the breaking and forming interactions, the binding thermodynamic profile, and the physicochemical properties of the ligands are also discussed.Expert opinion: Analysis of the size dependence of available affinity and favorable enthalpy highlights the limitation of the simultaneous optimization of these quantities. Indeed, moderate, rather than very high affinities can be conciliated with favorable physicochemical and pharmacokinetic profiles as it is supported by the affinity range of historical oral drugs. Although thermodynamic quantities are not suitable endpoints for medicinal chemistry optimizations owing to the complexity of the binding thermodynamics, thermodynamic profiling together with structural studies can be advantageously used to understand the details of the binding process and to optimize it.

An investigation of structural stability in protein-ligand complexes reveals the balance between order and disorder

The predominant view in structure-based drug design is that small-molecule ligands, once bound to their target structures, display a well-defined binding mode. However, structural stability (robustness) is not necessary for thermodynamic stability (binding affinity). In fact, it entails an entropic penalty that counters complex formation. Surprisingly, little is known about the causes, consequences and real degree of robustness of protein-ligand complexes. Since hydrogen bonds have been described as essential for structural stability, here we investigate 469 such interactions across two diverse structure sets, comprising of 79 drug-like and 27 fragment ligands, respectively. Completely constricted protein-ligand complexes are rare and may fulfill a functional role. Most complexes balance order and disorder by combining a single anchoring point with looser regions. 25% do not contain any robust hydrogen bond and may form loose structures. Structural stability analysis reveals a hidden layer of complexity in protein-ligand complexes that should be considered in ligand design.

New insights and innovation from a million crystal structures in the Cambridge Structural Database

The Cambridge Structural Database (CSD) is the world's largest and most comprehensive collection of organic, organometallic, and metal-organic crystal structure information. Analyses using the data have wide impact across the chemical sciences in allowing understanding of structural preferences. In this short review, we illustrate the more common methods by which CSD data influence molecular design. We show how more data could lead to more refined insights into the future using a simple example of trifluoromethylphenyl fragments, highlighting how with sufficient data one can build a reasonable model of geometric change in a chemical fragment with torsional rotation, and show some recent examples where the CSD has been used in conjunction with other methods to provide design ideas and more computationally tractable workflows for derivation of useful insights into structural design.