Lead Generation and Examples

Site Identification and Next Choice Protocol for Hit-to-Lead Optimization

Time efficiency and cost savings are major challenges in drug discovery and development. In this process, the hit-to-lead stage is expected to improve efficiency because it primarily exploits the trial-and-error approach of medicinal chemists. This study proposes a site identification and next choice (SINCHO) protocol to improve the hit-to-lead efficiency. This protocol selects an anchor atom and growth site pair, which is desirable for a hit-to-lead strategy starting from a 3D complex structure. We developed and fine-tuned the protocol using a training data set and assessed it using a test data set of the preceding hit-to-lead strategy. The protocol was tested for experimentally determined structures and molecular dynamics (MD) ensembles. The protocol had a high prediction accuracy for applying MD ensembles, owing to the consideration of protein flexibility. The SINCHO protocol enables medicinal chemists to visualize and modify functional groups in a hit-to-lead manner.

In Silico Substrate-Binding Profiling for SARS-CoV-2 Main Protease (Mpro) Using Hexapeptide Substrates

The SARS-CoV-2 main protease (M^pro) is essential for the life cycle of the COVID-19 virus. It cleaves the two polyproteins at 11 positions to generate mature proteins for virion formation. The cleavage site on these polyproteins is known to be Leu-Gln↓(Ser/Ala/Gly). A range of hexapeptides that follow the known sequence for recognition and cleavage was constructed using RDKit libraries and complexed with the crystal structure of M^pro (PDB ID 6XHM) through extensive molecular docking calculations. A subset of 131 of these complexes underwent 20 ns molecular dynamics simulations. The analyses of the trajectories from molecular dynamics included principal component analysis (PCA), and a method to compare PCA plots from separate trajectories was developed in terms of encoding PCA progression during the simulations. The hexapeptides formed stable complexes as expected, with reproducible molecular docking of the substrates given the extensiveness of the procedure. Only Lys-Leu-Gln*** (KLQ***) sequence complexes were studied for molecular dynamics. In this subset of complexes, the PCA analysis identified four classifications of protein motions across these sequences. KLQ*** complexes illustrated the effect of changes in substrate on the active site, with implications for understanding the substrate recognition of M^pro and informing the development of small molecule inhibitors.

Structure optimization of new tumor-selective Passerini α-acyloxy carboxamides as Caspase-3/7 activators

Selective elimination of tumors has always been the mainstay of oncology research. The on-going research underlying the cellular apoptotic mechanisms reveal caspases activation, especially the key effector caspase-3, as a personalized tumor-selective therapeutic strategy. Our continued research protocol has exploited new optimized Passerini α-acyloxy carboxamides as efficient apoptotic inducers via caspase-3/7 dependent mechanism with highly selective anticancer profiles. The adopted design rationale relied on excluding structural alerts of previous leads, while merging various pharmacophoric motifs of natural and synthetic caspase activators via optimized one-pot Passerini reaction conditions. The prepared compounds resulting from Passerini reaction were screened for their cytotoxic activities against colorectal Caco-2 and liver HepG-2 cancer cells compared to normal fibroblasts utilizing MTT assay. Notably, all compounds exhibited promising low-range submicromolar IC₅₀ against the studied cancer cell lines, with outstanding tumor selectivity (SI values up to 266). Hence, they were superior to 5-fluorouracil. Notably, 7a, 7g, and 7j conferred the highest potencies against Caco-2 and HepG-2 cells and were selected for further mechanistic studies. Caspas-3/7 activation assay of the hit compounds and flow cytometric analysis of the treated apoptotic cancer cells demonstrated their significant caspase activation potential (up to 4.2 folds) and apoptotic induction capacities (up to 58.7%). Further assessment of Bcl2 expression was performed being a physiological caspase-3 substrate. Herein, the three studied Passerini adducts were able to downregulate Bcl2 in the treated Caco-2 cells. Importantly, the mechanistic studies results of the three hits echoed their preliminary MTT antiproliferative potencies data highlighting their caspase-3 dependent apoptotic induction. Finally, the in silico predicted physicochemical and pharmacokinetic profiles, as well as ligand efficiency metrics were drug-like.

Fragment dissolved molecular dynamics: a systematic and efficient method to locate binding sites

Diverse computational methods to support fragment-based drug discovery (FBDD) are available in the literature. Despite their demonstrated efficacy in supporting FBDD campaigns, they exhibit some drawbacks such as protein denaturation or ligand aggregation that have not yet been clearly overcome in the framework of biomolecular simulations. In the present work, we discuss a systematic semi-automatic novel computational procedure, designed to surpass these difficulties. The method, named fragment dissolved Molecular Dynamics (fdMD), utilizes simulation boxes of solvated small fragments, adding a repulsive Lennard-Jones potential term to avoid aggregation, which can be easily used to solvate the targets of interest. This method has the advantage of solvating the target with a low number of ligands, thus preventing the denaturation of the target, while simultaneously generating a database of ligand-solvated boxes that can be used in further studies. A number of scripts are made available to analyze the results and obtain the descriptors proposed as a means to trustfully discard spurious binding sites. To test our method, four test cases of different complexity have been solvated with ligand boxes and four molecular dynamics runs of 200 ns length have been run for each system, which have been extended up to 1 μs when needed. The reported results point out that the selected number of replicas are enough to identify the correct binding sites irrespective of the initial structure, even in the case of proteins having several close binding sites for the same ligand. We also propose a set of descriptors to analyze the results, among which the average MMGBSA and the average KDEEP energies have emerged as the most robust ones.

Applications of Solution NMR in Drug Discovery

During the past decades, solution nuclear magnetic resonance (NMR) spectroscopy has demonstrated itself as a promising tool in drug discovery. Especially, fragment-based drug discovery (FBDD) has benefited a lot from the NMR development. Multiple candidate compounds and FDA-approved drugs derived from FBDD have been developed with the assistance of NMR techniques. NMR has broad applications in different stages of the FBDD process, which includes fragment library construction, hit generation and validation, hit-to-lead optimization and working mechanism elucidation, etc. In this manuscript, we reviewed the current progresses of NMR applications in fragment-based drug discovery, which were illustrated by multiple reported cases. Moreover, the NMR applications in protein-protein interaction (PPI) modulators development and the progress of in-cell NMR for drug discovery were also briefly summarized.

Auto In Silico Ligand Directing Evolution to Facilitate the Rapid and Efficient Discovery of Drug Lead

Motivated by the growing demand for reducing the chemical optimization burden of H2L, we developed auto in silico ligand directing evolution (AILDE, http://chemyang.ccnu.edu.cn/ccb/server/AILDE), an efficient and general approach for the rapid identification of drug leads in accessible chemical space. This computational strategy relies on minor chemical modifications on the scaffold of a hit compound, and it is primarily intended for identifying new lead compounds with minimal losses or, in some cases, even increases in ligand efficiency. We also described how AILDE greatly reduces the chemical optimization burden in the design of mesenchymal-epithelial transition factor (c-Met) kinase inhibitors. We only synthesized eight compounds and found highly efficient compound 5g, which showed an ∼1,000-fold improvement in in vitro activity compared with the hit compound. 5g also displayed excellent in vivo antitumor efficacy as a drug lead. We believe that AILDE may be applied to a large number of studies for rapid design and identification of drug leads.

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AILDE was developed for the rapid identification of drug leads

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A potent drug lead targeted to c-Met was found by synthesizing only eight compounds

Concepts and Core Principles of Fragment-Based Drug Design

In this review, a general introduction to fragment-based drug design and the underlying concepts is given. General considerations and methodologies ranging from library selection/construction over biophysical screening and evaluation methods to in-depth hit qualification and subsequent optimization strategies are discussed. These principles can be generally applied to most classes of drug targets. The examples given for fragment growing, merging, and linking strategies at the end of the review are set in the fields of enzyme-inhibitor design and macromolecule–macromolecule interaction inhibition. Building upon the foundation of fragment-based drug discovery (FBDD) and its methodologies, we also highlight a few new trends in FBDD.

Battle tactics against MMP-9; discovery of novel non-hydroxamate MMP-9 inhibitors endowed with PI3K/AKT signaling attenuation and caspase 3/7 activation via Ugi bis-amide synthesis

Matrix metalloproteinases (MMPs) are major modulators of the tumor microenvironment. They participate in extracellular matrix turnover, tumor growth, angiogenesis and metastasis. Accordingly, MMPs inhibition seems to be ideal solution to control cancer. Many MMPs inhibitors have been introduced ranging from hydroxamate-based peptidomimetics to the next generation non-hydroxamate inhibitors. Among MMPs, MMP-9 is attractive druggable anticancer target. Studies showed that inhibiting AKT, the central signaling node of MMP-9 upregulation, provides additional MMP-9 blockade. Furthermore, caspase-dependent AKT cleavage leads to cell death. Herein, Ugi MCR was utilized as a rapid combinatorial approach to generate various decorated bis-amide scaffolds as dual MMP-9/AKT inhibitors endowed with caspase 3/7 activation potential. The target adducts were designed to mimic the thematic structural features of non-hydroxamate MMP inhibitors. p-Nitrophenyl isonitrile 1 was utilized as structure entry to Ugi products with some structural similarities to amide-based caspase 3/7 activators. Besides, various acids, amines and aldehydes were employed as Ugi educts to enrich the SAR data. All adducts were screened for cytotoxicity against normal fibroblasts and three cancer cell lines; MCF-7, NFS-60 and HepG-2 utilizing MTT assay. 8, 11 and 28 were more active and safer than doxorubicin with single-digit nM IC₅₀ and promising selectivity. Mechanistically, they exhibited dual MMP-9/AKT inhibition at single-digit nM IC₅₀ with excellent selectivity over MMP-1,-2 and -13, and induced >51% caspase 3/7 activation. Consequently, they induced >49% apoptosis as detected by flow cytometric analysis, and inhibited cell migration (metastasis) up to 97% in cancer cells. Docking simulations were nearly consistent with enzymatic evaluation, also declared possible binding modes and essential structure features of active compounds. In silico physicochemical properties, ligand efficiency and drug-likeness metrics were reasonable for all adducts. Interestingly, 8 and 28 can be considered as drug-like candidates.

Homology models of mouse and rat estrogen receptor-α ligand-binding domain created by in silico mutagenesis of a human template: molecular docking with 17ß-estradiol, diethylstilbestrol, and paraben analogs

Crystal structures exist for human, but not rodent, estrogen receptor-α ligand-binding domain (ERα-LBD). Consequently, rodent studies involving binding of compounds to ERα-LBD are limited in their molecular-level interpretation and extrapolation to humans. Because the sequences of rodent and human ERα-LBDs are > 95% identical, we expected their 3D structures and ligand binding to be highly similar. To test this hypothesis, we used the human ERα-LBD structure (PDB 3UUD) as a template to produce rat and mouse homology models. Employing the rodent models and human structure, we generated docking poses of 23 Group A ligands (17ß-estradiol, diethylstilbestrol, and 21 paraben analogs) in AutoDock Vina for interspecies comparisons. Ligand RMSDs (Å) (median, 95% CI) were 0.49 (0.21-1.82) (human-mouse) and 1.19 (0.22-1.82) (human-rat), well below the 2.0-2.5 Å range for equivalent docking poses. Numbers of interspecies ligand-receptor residue contacts were highly similar, with Sorensen Sc (%) = 96.8 (90.0-100) (human-mouse) and 97.7 (89.5-100) (human-rat). Likewise, numbers of interspecies ligand-receptor residue contacts were highly correlated: Pearson r = 0.913 (human-mouse) and 0.925 (human-rat). Numbers of interspecies ligand-receptor atom contacts were even more tightly correlated: r = 0.979 (human-mouse) and 0.986 (human-rat). Pyramid plots of numbers of ligand-receptor atom contacts by residue exhibited high interspecies symmetry and had Spearman r s = 0.977 (human-mouse) and 0.966 (human-rat). Group B ligands included 15 ring-substituted parabens recently shown experimentally to exhibit decreased binding to human ERα and to exert increased antimicrobial activity. Ligand efficiencies calculated from docking ligands into human ERα-LBD were well correlated with those derived from published experimental data (Pearson partial r p = 0.894 and 0.918; Groups A and B, respectively). Overall, the results indicate that our constructed rodent ERα-LBDs interact with ligands in like manner to the human receptor, thus providing a high level of confidence in extrapolations of rodent to human ligand-receptor interactions.

Efficient Approach To Discover Novel Agrochemical Candidates: Intermediate Derivatization Method

Intensive competition of intellectual property, easy development of agrochemical resistance, and stricter regulations of environmental concerns make the successful rate for agrochemical discovery extremely lower using traditional agrochemical discovery methods. Therefore, there is an urgent need to find a novel approach to guide agrochemical discovery with high efficiency to quickly keep pace with the changing market. On the basis of these situations, here we summarize the intermediate derivatization method (IDM) between conventional methods in agrochemicals and novel ones in pharmaceuticals. This method is relatively efficient with short time in discovery phase, reduced cost, especially good innovated structure, and better performance. In this paper, we summarize and illustrate "what is the IDM" and "why to use" and "how to use" it to accelerate the discovery of new biologically active molecules, focusing on agrochemicals. Furthermore, we display several research projects in our novel agrochemical discovery programs with improved success rate under guidance of this strategy in recent years.

Structural insights into the novel inhibition mechanism of Trypanosoma cruzi spermidine synthase

Trypanosoma cruzi causes Chagas disease, a severe disease affecting 8-10 million people in Latin America. While nifurtimox and benznidazole are used to treat this disease, their efficacy is limited and adverse effects are observed. New therapeutic targets and novel drugs are therefore urgently required. Enzymes in the polyamine-trypanothione pathway are promising targets for the treatment of Chagas disease. Spermidine synthase is a key enzyme in this pathway that catalyzes the transfer of an aminopropyl group from decarboxylated S-adenosylmethionine (dcSAM) to putrescine. Fragment-based drug discovery was therefore conducted to identify novel, potent inhibitors of spermidine synthase from T. cruzi (TcSpdSyn). Here, crystal structures of TcSpdSyn in complex with dcSAM, trans-4-methylcyclohexylamine and hit compounds from fragment screening are reported. The structure of dcSAM complexed with TcSpdSyn indicates that dcSAM stabilizes the conformation of the `gatekeeping' loop to form the putrescine-binding pocket. The structures of fragments bound to TcSpdSyn revealed two fragment-binding sites: the putrescine-binding pocket and the dimer interface. The putrescine-binding pocket was extended by an induced-fit mechanism. The crystal structures indicate that the conformation of the dimer interface is required to stabilize the gatekeeping loop and that fragments binding to this interface inhibit TcSpdSyn by disrupting its conformation. These results suggest that utilizing the dynamic structural changes in TcSpdSyn that occur upon inhibitor binding will facilitate the development of more selective and potent inhibitors.

Ligand deconstruction: Why some fragment binding positions are conserved and others are not

Fragment-based drug discovery (FBDD) relies on the premise that the fragment binding mode will be conserved on subsequent expansion to a larger ligand. However, no general condition has been established to explain when fragment binding modes will be conserved. We show that a remarkably simple condition can be developed in terms of how fragments coincide with binding energy hot spots--regions of the protein where interactions with a ligand contribute substantial binding free energy--the locations of which can easily be determined computationally. Because a substantial fraction of the free energy of ligand binding comes from interacting with the residues in the energetically most important hot spot, a ligand moiety that sufficiently overlaps with this region will retain its location even when other parts of the ligand are removed. This hypothesis is supported by eight case studies. The condition helps identify whether a protein is suitable for FBDD, predicts the size of fragments required for screening, and determines whether a fragment hit can be extended into a higher affinity ligand. Our results show that ligand binding sites can usefully be thought of in terms of an anchor site, which is the top-ranked hot spot and dominates the free energy of binding, surrounded by a number of weaker satellite sites that confer improved affinity and selectivity for a particular ligand and that it is the intrinsic binding potential of the protein surface that determines whether it can serve as a robust binding site for a suitably optimized ligand.

Cell-based and virtual fragment screening for adrenergic α2C receptor agonists

Fragment-based drug discovery has emerged as an alternative to conventional lead identification and optimization strategies generally supported by biophysical detection techniques. Membrane targets like G protein-coupled receptors (GPCRs), however, offer challenges in lack of generic immobilization or stabilization methods for the dynamic, membrane-bound supramolecular complexes. Also modeling of different functional states of GPCRs proved to be a challenging task. Here we report a functional cell-based high concentration screening campaign for the identification of adrenergic α2C receptor agonists compared with the virtual screening of the same ligand set against an active-like homology model of the α2C receptor. The conventional calcium mobilization-based assay identified active fragments with a similar incidence to several other reported fragment screens on GPCRs. 16 out of 3071 screened fragments turned out as specific ligands of α2C, two of which were identified by virtual screening as well and several of the hits possessed surprisingly high affinity and ligand efficiency. Our results indicate that in vitro biological assays can be utilized in the fragment hit identification process for GPCR targets.

The importance of hydration thermodynamics in fragment-to-lead optimization

Using a computational approach to assess changes in solvation thermodynamics upon ligand binding, we investigated the effects of water molecules on the binding energetics of over 20 fragment hits and their corresponding optimized lead compounds. Binding activity and X-ray crystallographic data of published fragment-to-lead optimization studies from various therapeutically relevant targets were studied. The analysis reveals a distinct difference between the thermodynamic profile of water molecules displaced by fragment hits and those displaced by the corresponding optimized lead compounds. Specifically, fragment hits tend to displace water molecules with notably unfavorable excess entropies-configurationally constrained water molecules-relative to those displaced by the newly added moieties of the lead compound during the course of fragment-to-lead optimization. Herein we describe the details of this analysis with the goal of providing practical guidelines for exploiting thermodynamic signatures of binding site water molecules in the context of fragment-to-lead optimization.

Virtual fragment screening on GPCRs: a case study on dopamine D3 and histamine H4 receptors

Prospective structure based virtual fragment screening methodologies on two GPCR targets namely the dopamine D3 and the histamine H4 receptors with a library of 12,905 fragments were evaluated. Fragments were docked to the X-ray structure and the homology model of the D3 and H4 receptors, respectively. Representative receptor conformations for ensemble docking were obtained from molecular dynamics trajectories. In vitro confirmed hit rates ranged from 16% to 32%. Hits had high ligand efficiency (LE) values in the range of 0.31-0.74 and also acceptable lipophilic efficiency. The X-ray structure, the homology model and structural ensembles were all found suitable for docking based virtual screening of fragments against these GPCRs. However, there was little overlap among different hit sets and methodologies were thus complementary to each other.

Non-peptidic cruzain inhibitors with trypanocidal activity discovered by virtual screening and in vitro assay

A multi-step cascade strategy using integrated ligand- and target-based virtual screening methods was developed to select a small number of compounds from the ZINC database to be evaluated for trypanocidal activity. Winnowing the database to 23 selected compounds, 12 non-covalent binding cruzain inhibitors with affinity values (K_i) in the low micromolar range (3–60 µM) acting through a competitive inhibition mechanism were identified. This mechanism has been confirmed by determining the binding mode of the cruzain inhibitor Nequimed176 through X-ray crystallographic studies. Cruzain, a validated therapeutic target for new chemotherapy for Chagas disease, also shares high similarity with the mammalian homolog cathepsin L. Because increased activity of cathepsin L is related to invasive properties and has been linked to metastatic cancer cells, cruzain inhibitors from the same library were assayed against it. Affinity values were in a similar range (4–80 µM), yielding poor selectivity towards cruzain but raising the possibility of investigating such inhibitors for their effect on cell proliferation. In order to select the most promising enzyme inhibitors retaining trypanocidal activity for structure-activity relationship (SAR) studies, the most potent cruzain inhibitors were assayed against T. cruzi-infected cells. Two compounds were found to have trypanocidal activity. Using compound Nequimed42 as precursor, an SAR was established in which the 2-acetamidothiophene-3-carboxamide group was identified as essential for enzyme and parasite inhibition activities. The IC₅₀ value for compound Nequimed42 acting against the trypomastigote form of the Tulahuen lacZ strain was found to be 10.6±0.1 µM, tenfold lower than that obtained for benznidazole, which was taken as positive control. In addition, by employing the strategy of molecular simplification, a smaller compound derived from Nequimed42 with a ligand efficiency (LE) of 0.33 kcal mol⁻¹ atom⁻¹ (compound Nequimed176) is highlighted as a novel non-peptidic, non-covalent cruzain inhibitor as a trypanocidal agent candidate for optimization.

Chagas disease (American trypanosomiasis) is a parasitic infection that kills millions of mostly poverty-stricken people in Latin America. In recent years it has also spread to nonendemic countries – the United States, Canada, Europe, Australia and Japan – as a result of immigration. The only available drugs for its treatment were introduced more than forty years ago, have low efficacy, and cause various severe side effects. This dire public health situation has prompted us to search for new small molecules to act as drug candidates to treat Chagas disease. The T. cruzi enzyme cruzain, a key biological catalyst used by the protozoan to digest host proteins, is a validated drug target for Chagas disease. By combining in silico molecular design, X-ray crystallography and biological screening, we found a new class of non-covalent small molecules that inhibit cruzain in low micromolar concentrations.

Fragment-based screening maps inhibitor interactions in the ATP-binding site of checkpoint kinase 2

Checkpoint kinase 2 (CHK2) is an important serine/threonine kinase in the cellular response to DNA damage. A fragment-based screening campaign using a combination of a high-concentration AlphaScreen™ kinase assay and a biophysical thermal shift assay, followed by X-ray crystallography, identified a number of chemically different ligand-efficient CHK2 hinge-binding scaffolds that have not been exploited in known CHK2 inhibitors. In addition, it showed that the use of these orthogonal techniques allowed efficient discrimination between genuine hit matter and false positives from each individual assay technology. Furthermore, the CHK2 crystal structures with a quinoxaline-based fragment and its follow-up compound highlight a hydrophobic area above the hinge region not previously explored in rational CHK2 inhibitor design, but which might be exploited to enhance both potency and selectivity of CHK2 inhibitors.

Fragment-based lead discovery on G-protein-coupled receptors

INTRODUCTION

G-protein-coupled receptors (GPCRs) form one of the largest groups of potential targets for novel medications. Low druggability of many GPCR targets and inefficient sampling of chemical space in high-throughput screening expertise however often hinder discovery of drug discovery leads for GPCRs. Fragment-based drug discovery is an alternative approach to the conventional strategy and has proven its efficiency on several enzyme targets. Based on developments in biophysical screening techniques, receptor stabilization and in vitro assays, virtual and experimental fragment screening and fragment-based lead discovery recently became applicable for GPCR targets.

AREAS COVERED

This article provides a review of the biophysical as well as biological detection techniques suitable to study GPCRs together with their applications to screen fragment libraries and identify fragment-size ligands of cell surface receptors. The article presents several recent examples including both virtual and experimental protocols for fragment hit discovery and early hit to lead progress.

EXPERT OPINION

With the recent progress in biophysical detection techniques, the advantages of fragment-based drug discovery could be exploited for GPCR targets. Structural information on GPCRs will be more abundantly available for early stages of drug discovery projects, providing information on the binding process and efficiently supporting the progression of fragment hit to lead. In silico approaches in combination with biological assays can be used to address structurally challenging GPCRs and confirm biological relevance of interaction early in the drug discovery project.

Design and Evaluation of the Performance of an NMR Screening Fragment Library

The design of a suitable library is an essential prerequisite to establish a fragment-based screening capability. Several pharmaceutical companies have described their approaches to establishing fragment libraries; however there are few detailed reports of both design and analysis of performance for a fragment library maintained in an academic setting. Here we report our efforts towards the design of a fragment library for nuclear magnetic resonance spectroscopy-based screening, demonstrate the performance of the library through analysis of 14 screens, and present a comparison to previously reported fragment libraries.

Thermodynamics of fragment binding

The ligand binding pockets of proteins have preponderance of hydrophobic amino acids and are typically within the apolar interior of the protein; nevertheless, they are able to bind low complexity, polar, water-soluble fragments. In order to understand this phenomenon, we analyzed high resolution X-ray data of protein-ligand complexes from the Protein Data Bank and found that fragments bind to proteins with two near optimal geometry H-bonds on average. The linear extent of the fragment binding site was found not to be larger than 10 Å, and the H-bonding region was found to be restricted to about 5 Å on average. The number of conserved H-bonds in proteins cocrystallized with multiple different fragments is also near to 2. These fragment binding sites that are able to form limited number of strong H-bonds in a hydrophobic environment are identified as hot spots. An estimate of the free-energy gain of H-bond formation versus apolar desolvation supports that fragment sized compounds need H-bonds to achieve detectable binding. This suggests that fragment binding is mostly enthalpic that is in line with their observed binding thermodynamics documented in Isothermal Titration Calorimetry (ITC) data sets and gives a thermodynamic rationale for fragment based approaches. The binding of larger compounds tends to more rely on apolar desolvation with a corresponding increase of the entropy content of their binding free-energy. These findings explain the reported size-dependence of maximal available affinity and ligand efficiency both behaving differently in the small molecule region featured by strong H-bond formation and in the larger molecule region featured by apolar desolvation.

Design and synthesis of novel lactate dehydrogenase A inhibitors by fragment-based lead generation

Lactate dehydrogenase A (LDHA) catalyzes the conversion of pyruvate to lactate, utilizing NADH as a cofactor. It has been identified as a potential therapeutic target in the area of cancer metabolism. In this manuscript we report our progress using fragment-based lead generation (FBLG), assisted by X-ray crystallography to develop small molecule LDHA inhibitors. Fragment hits were identified through NMR and SPR screening and optimized into lead compounds with nanomolar binding affinities via fragment linking. Also reported is their modification into cellular active compounds suitable for target validation work.

Design and combinatorial synthesis of a novel kinase-focused library using click chemistry-based fragment assembly

Fragment-based lead discovery is a new approach for lead generation that has emerged in the past decade. Because the initial fragments identified in the fragment screening typically show weak binding affinity, an intensive medicinal chemistry effort would be required to grow initial fragments into a potential lead compound. Here we demonstrate a kinase focused evolved fragment (KFEF) library, constructed by click chemistry-based fragment assembly, that is a valuable source of kinase inhibitors. This combinatorial assembly of two fragments, kinase-privileged alkyne fragments and diversified azide fragments, by two cycloaddition reactions shows a unique potential for the one-step synthesis of structurally diverse evolved fragments. The screening of this triazole-based KFEF library allowed the rapid identification of potent lead candidates for FLT3 and GSK3β kinase.

Prediction of Positions of Active Compounds Makes It Possible To Increase Activity in Fragment-Based Drug Development

We have developed a computational method that predicts the positions of active compounds, making it possible to increase activity as a fragment evolution strategy. We refer to the positions of these compounds as the active position. When an active fragment compound is found, the following lead generation process is performed, primarily to increase activity. In the current method, to predict the location of the active position, hydrogen atoms are replaced by small side chains, generating virtual compounds. These virtual compounds are docked to a target protein, and the docking scores (affinities) are examined. The hydrogen atom that gives the virtual compound with good affinity should correspond to the active position and it should be replaced to generate a lead compound. This method was found to work well, with the prediction of the active position being 2 times more efficient than random synthesis. In the current study, 15 examples of lead generation were examined. The probability of finding active positions among all hydrogen atoms was 26%, and the current method accurately predicted 60% of the active positions.