ChemoDOTS: a web server to design chemistry-driven focused libraries.

In drug discovery, the successful optimization of an initial hit compound into a lead molecule requires multiple cycles of chemical modification. Consequently, there is a need to efficiently generate synthesizable chemical libraries to navigate the chemical space surrounding the primary hit. To address this need, we introduce ChemoDOTS, an easy-to-use web server for hit-to-lead chemical optimization freely available at https://chemodots.marseille.inserm.fr/. With this tool, users enter an activated form of the initial hit molecule then choose from automatically detected reactive functions. The server proposes compatible chemical transformations via an ensemble of encoded chemical reactions widely used in the pharmaceutical industry during hit-to-lead optimization. After selection of the desired reactions, all compatible chemical building blocks are automatically coupled to the initial hit to generate a raw chemical library. Post-processing filters can be applied to extract a subset of compounds with specific physicochemical properties. Finally, explicit stereoisomers and tautomers are computed, and a 3D conformer is generated for each molecule. The resulting virtual library is compatible with most docking software for virtual screening campaigns. ChemoDOTS rapidly generates synthetically feasible, hit-focused, large, diverse chemical libraries with finely-tuned physicochemical properties via a user-friendly interface providing a powerful resource for researchers engaged in hit-to-lead optimization.

Discovery of Conformationally Constrained ALK2 Inhibitors.

Despite decades of research on new diffuse intrinsic pontine glioma (DIPG) treatments, little or no progress has been made on improving patient outcomes. In this work, we explored novel scaffold modifications of M4K2009, a 3,5-diphenylpyridine ALK2 inhibitor previously reported by our group. Here we disclose the design, synthesis, and evaluation of a first-in-class set of 5- to 7-membered ether-linked and 7-membered amine-linked constrained inhibitors of ALK2. This rigidification strategy led us to the discovery of the ether-linked inhibitors M4K2308 and M4K2281 and the amine-linked inhibitors M4K2304 and M4K2306, each with superior potency against ALK2. Notably, M4K2304 and M4K2306 exhibit exceptional selectivity for ALK2 over ALK5, surpassing the reference compound. Preliminary studies on their in vivo pharmacokinetics, including blood-brain barrier penetration, revealed that these constrained scaffolds have favorable exposure and do open a novel chemical space for further optimization and future evaluation in orthotopic models of DIPG.

From a drug repositioning to a structure-based drug design approach to tackle acute lymphoblastic leukemia.

Cancer cells utilize the main de novo pathway and the alternative salvage pathway for deoxyribonucleotide biosynthesis to achieve adequate nucleotide pools. Deoxycytidine kinase is the rate-limiting enzyme of the salvage pathway and it has recently emerged as a target for anti-proliferative therapies for cancers where it is essential. Here, we present the development of a potent inhibitor applying an iterative multidisciplinary approach, which relies on computational design coupled with experimental evaluations. This strategy allows an acceleration of the hit-to-lead process by gradually implementing key chemical modifications to increase affinity and activity. Our lead compound, OR0642, is more than 1000 times more potent than its initial parent compound, masitinib, previously identified from a drug repositioning approach. OR0642 in combination with a physiological inhibitor of the de novo pathway doubled the survival rate in a human T-cell acute lymphoblastic leukemia patient-derived xenograft mouse model, demonstrating the proof-of-concept of this drug design strategy.

Discovery of Nanomolar DCAF1 Small Molecule Ligands.

DCAF1 is a substrate receptor of two distinct E3 ligases (CRL4DCAF1 and EDVP), plays a critical physiological role in protein degradation, and is considered a drug target for various cancers. Antagonists of DCAF1 could be used toward the development of therapeutics for cancers and viral treatments. We used the WDR domain of DCAF1 to screen a 114-billion-compound DNA encoded library (DEL) and identified candidate compounds using similarity search and machine learning. This led to the discovery of a compound (Z1391232269) with an SPR KD of 11 µM. Structure-guided hit optimization led to the discovery of OICR-8268 (26e) with an SPR KD of 38 nM and cellular target engagement with EC50 of 10 µM as measured by cellular thermal shift assay (CETSA). OICR-8268 is an excellent tool compound to enable the development of next-generation DCAF1 ligands toward cancer therapeutics, further investigation of DCAF1 functions in cells, and the development of DCAF1-based PROTACs.

Discovery of a PDZ Domain Inhibitor Targeting the Syndecan/Syntenin Protein-Protein Interaction: A Semi-Automated "Hit Identification-to-Optimization" Approach.

The rapid identification of early hits by fragment-based approaches and subsequent hit-to-lead optimization represents a challenge for drug discovery. To address this challenge, we created a strategy called "DOTS" that combines molecular dynamic simulations, computer-based library design (chemoDOTS) with encoded medicinal chemistry reactions, constrained docking, and automated compound evaluation. To validate its utility, we applied our DOTS strategy to the challenging target syntenin, a PDZ domain containing protein and oncology target. Herein, we describe the creation of a "best-in-class" sub-micromolar small molecule inhibitor for the second PDZ domain of syntenin validated in cancer cell assays. Key to the success of our DOTS approach was the integration of protein conformational sampling during hit identification stage and the synthetic feasibility ranking of the designed compounds throughout the optimization process. This approach can be broadly applied to other protein targets with known 3D structures to rapidly identify and optimize compounds as chemical probes and therapeutic candidates.

Discovery of Small-Molecule Inhibitors of the PTK7/ß-Catenin Interaction Targeting the Wnt Signaling Pathway in Colorectal Cancer.

Colorectal cancer (CRC), the second cause of death due to cancer worldwide, is a major public health issue. The discovery of new therapeutic targets is thus essential. Pseudokinase PTK7 intervenes in the regulation of the Wnt/ß-catenin pathway signaling, in part, through a kinase domain-dependent interaction with the ß-catenin protein. PTK7 is overexpressed in CRC, an event associated with metastatic development and reduced survival of nonmetastatic patients. In addition, numerous alterations have been identified in CRC inducing constitutive activation of the Wnt/ß-catenin pathway signaling through ß-catenin accumulation. Thus, targeting the PTK7/ß-catenin interaction could be of interest for future drug development. We have developed a NanoBRET screening assay recapitulating the interaction between PTK7 and ß-catenin to identify compounds able to disrupt this protein-protein interaction. A high-throughput screening allowed us to identify small-molecule inhibitors targeting the Wnt pathway signaling and inducing antiproliferative and antitumor effects in vitro in CRC cells harboring ß-catenin or adenomatous polyposis coli (APC) mutations. Thus, inhibition of the PTK7/ß-catenin interaction could represent a new therapeutic strategy to inhibit cell growth dependent on the Wnt signaling pathway. Moreover, despite a lack of enzymatic activity of its tyrosine kinase domain, targeting the PTK7 kinase domain-dependent functions appears to be of interest for further therapeutic development.

CRCM5484: A BET-BDII Selective Compound with Differential Anti-leukemic Drug Modulation.

Differentially screening the Fr-PPIChem chemical library on the bromodomain and extra-terminal (BET) BRD4-BDII versus -BDI bromodomains led to the discovery of a BDII-selective tetrahydropyridothienopyrimidinone (THPTP)-based compound. Structure-activity relationship (SAR) and hit-to-lead approaches allowed us to develop CRCM5484, a potent inhibitor of BET proteins with a preferential and 475-fold selectivity for the second bromodomain of the BRD3 protein (BRD3-BDII) over its first bromodomain (BRD3-BDI). Its very low activity was demonstrated in various cell-based assays, corresponding with recent data describing other selective BDII compounds. However, screening on a drug sensitivity and resistance-profiling platform revealed its ability to modulate the anti-leukemic activity in combination with various FDA-approved and/or in-development drugs in a cell- and context-dependent differential manner. Altogether, the results confirm the originality of the THPTP molecular mode of action in the bromodomain (BD) cavity and its potential as a starting scaffold for the development of potent and selective bromodomain inhibitors.

Fragment-based drug design targeting syntenin PDZ2 domain involved in exosomal release and tumour spread.

Syntenin stimulates exosome production and its expression is upregulated in many cancers and implicated in the spread of metastatic tumor. These effects are supported by syntenin PDZ domains interacting with syndecans. We therefore aimed to develop, through a fragment-based drug design approach, novel inhibitors targeting syntenin-syndecan interactions. We describe here the optimization of a fragment, 'hit' C58, identified by in vitro screening of a PDZ-focused fragment library, which binds specifically to the syntenin-PDZ2 domain at the same binding site as the syndecan-2 peptide. X-ray crystallographic structures and computational docking were used to guide our optimization process and lead to compounds 45 and 57 (IC50 = 33 µM and 47 µM; respectively), two representatives of syntenin-syndecan interactions inhibitors, that selectively affect the syntenin-exosome release. These findings demonstrate that it is possible to identify small molecules inhibiting syntenin-syndecan interaction and exosome release that may be useful for cancer therapy.

Rational Design of PDZ Domain Inhibitors: Discovery of Small Organic Compounds Targeting PDZ Domains.

PDZ domains, which belong to protein-protein interaction networks, are critical for regulating important biological processes such as scaffolding, trafficking, and signaling cascades. Interfering with PDZ-mediated interactions could affect these numerous biological processes. Thus, PDZ domains have emerged as promising targets to decipher biological phenomena and potentially treat cancer and neurological diseases. In this minireview, we focus on the discovery and design of small molecule inhibitors to modulate PDZ domains. These compounds interfere with endogenous protein partners from the PDZ domain by binding at the protein-protein interface. While peptides or peptidomimetic ligands were described to modulate PDZ domains, the focus of this review is on small organic compounds.

In silico molecular target prediction unveils mebendazole as a potent MAPK14 inhibitor.

The concept of polypharmacology involves the interaction of drug molecules with multiple molecular targets. It provides a unique opportunity for the repurposing of already-approved drugs to target key factors involved in human diseases. Herein, we used an in silico target prediction algorithm to investigate the mechanism of action of mebendazole, an antihelminthic drug, currently repurposed in the treatment of brain tumors. First, we confirmed that mebendazole decreased the viability of glioblastoma cells in vitro (IC50 values ranging from 288 nm to 2.1 µm). Our in silico approach unveiled 21 putative molecular targets for mebendazole, including 12 proteins significantly upregulated at the gene level in glioblastoma as compared to normal brain tissue (fold change > 1.5; P < 0.0001). Validation experiments were performed on three major kinases involved in cancer biology: ABL1, MAPK1/ERK2, and MAPK14/p38α. Mebendazole could inhibit the activity of these kinases in vitro in a dose-dependent manner, with a high potency against MAPK14 (IC50  = 104 ± 46 nm). Its direct binding to MAPK14 was further validated in vitro, and inhibition of MAPK14 kinase activity was confirmed in live glioblastoma cells. Consistent with biophysical data, molecular modeling suggested that mebendazole was able to bind to the catalytic site of MAPK14. Finally, gene silencing demonstrated that MAPK14 is involved in glioblastoma tumor spheroid growth and response to mebendazole treatment. This study thus highlighted the role of MAPK14 in the anticancer mechanism of action of mebendazole and provides further rationale for the pharmacological targeting of MAPK14 in brain tumors. It also opens new avenues for the development of novel MAPK14/p38α inhibitors to treat human diseases.

Synthesis and Evaluation of the Antibacterial Activities of 13-Substituted Berberine Derivatives.

The biological activities of berberine, a natural plant molecule, are known to be affected by structural modifications, mostly at position 9 and/or 13. A series of new 13-substituted berberine derivatives were synthesized and evaluated in term of antimicrobial activity using various microorganisms associated to human diseases. Contrarily to the original molecule berberine, several derivatives were found strongly active in microbial sensitivity tests against Mycobacterium, Candida albicans and Gram-positive bacteria, including naïve or resistant Bacillus cereus, Staphylococcus aureus and Streptococcus pyogenes with minimal inhibitory concentration (MIC) of 3.12 to 6.25 µM. Among the various Gram-negative strains tested, berberine's derivatives were only found active on Helicobacter pylori and Vibrio alginolyticus (MIC values of 1.5-3.12 µM). Cytotoxicity assays performed on human cells showed that the antimicrobial berberine derivatives caused low toxicity resulting in good therapeutic index values. In addition, a mechanistic approach demonstrated that, contrarily to already known berberine derivatives causing either membrane permeabilization, DNA fragmentation or interacting with FtsZ protein, active derivatives described in this study act through inhibition of the synthesis of peptidoglycan or RNA. Overall, this study shows that these new berberine derivatives can be considered as potent and safe anti-bacterial agents active on human pathogenic microorganisms, including ones resistant to conventional antibiotics.

Fr-PPIChem: An Academic Compound Library Dedicated to Protein-Protein Interactions.

Protein-protein interactions (PPIs) mediate nearly every cellular process and represent attractive targets for modulating disease states but are challenging to target with small molecules. Despite this, several PPI inhibitors (iPPIs) have entered clinical trials, and a growing number of PPIs have become validated drug targets. However, high-throughput screening efforts still endure low hit rates mainly because of the use of unsuitable screening libraries. Here, we describe the collective effort of a French consortium to build, select, and store in plates a unique chemical library dedicated to the inhibition of PPIs. Using two independent predictive models and two updated databases of experimentally confirmed PPI inhibitors developed by members of the consortium, we built models based on different training sets, molecular descriptors, and machine learning methods. Independent statistical models were used to select putative PPI inhibitors from large commercial compound collections showing great complementarity. Medicinal chemistry filters were applied to remove undesirable structures from this set (such as PAINS, frequent hitters, and toxic compounds) and to improve drug likeness. The remaining compounds were subjected to a clustering procedure to reduce the final size of the library while maintaining its chemical diversity. In practice, the library showed a 46-fold activity rate enhancement when compared to a non-iPPI-enriched diversity library in high-throughput screening against the CD47-SIRPα PPI. The Fr-PPIChem library is plated in 384-well plates and will be distributed on demand to the scientific community as a powerful tool for discovering new chemical probes and early hits for the development of potential therapeutic drugs.

CovaDOTS: In Silico Chemistry-Driven Tool to Design Covalent Inhibitors Using a Linking Strategy.

We recently reported an integrated fragment-based optimization strategy called DOTS (Diversity Oriented Target-focused Synthesis) that combines automated virtual screening (VS) with semirobotized organic synthesis coupled to in vitro evaluation. The molecular modeling part consists of hit-to-lead chemistry, based on the growing paradigm. Here, we have extended the applicability of the DOTS strategy by adding new functionalities, allowing a generic chemistry-driven linking approach with a particular emphasis on covalent drugs. Indeed, the covalent mode of action can be described as a specific case of linking, where suitable linkers are sought to fuse a bound organic compound with a nucleophilic protein side chain. The proof of concept is established using three retrospective study cases in which known noncovalent inhibitors have been converted to covalent inhibitors. Our method is able to automatically design reference covalent inhibitors (and/or analogs) from an initial activated substructure and predict their binding mode. More importantly, the reference compounds are ranked high among several hundred putative adducts, demonstrating the utility of the approach to design covalent inhibitors.

Optimization of a fragment linking hit toward Dengue and Zika virus NS5 methyltransferases inhibitors.

No antiviral drugs to treat or prevent life-threatening flavivirus infections such as those caused by mosquito-borne Dengue (DENV) and more recently Zika (ZIKV) viruses are yet available. We aim to develop, through a structure-based drug design approach, novel inhibitors targeting the NS5 AdoMet-dependent mRNA methyltransferase (MTase), a viral protein involved in the RNA capping process essential for flaviviruses replication. Herein, we describe the optimization of a hit (5) identified using fragment-based and structure-guided linking techniques, which binds to a proximal site of the AdoMet binding pocket. X-ray crystallographic structures and computational docking were used to guide our optimization process and lead to compounds 30 and 33 (DENV IC50 = 26 µM and 23 µM; ZIKV IC50 = 28 µM and 19  µM, respectively), two representatives of novel non-nucleoside inhibitors of flavivirus MTases.

Chemistry-driven Hit-to-lead Optimization Guided by Structure-based Approaches.

For several decades, hit identification for drug discovery has been facilitated by developments in both fragment-based and high-throughput screening technologies. However, a major bottleneck in drug discovery projects continues to be the optimization of primary hits from screening campaigns in order to derive lead compounds. Computational chemistry or molecular modeling can play an important role during this hit-to-lead (H2L) stage by both suggesting putative optimizations and decreasing the number of compounds to be experimentally synthesized and evaluated. However, it is also crucial to consider the feasibility of organically synthesizing these virtually designed compounds. Furthermore, the generated molecules should have reasonable physicochemical properties and be medicinally relevant. This review focuses on chemistry-driven and structure-based computational methods that can be used to tackle the difficult problem of H2L optimization, with emphasis being placed on the strategy developed in our laboratory.

Integrated Strategy for Lead Optimization Based on Fragment Growing: The Diversity-Oriented-Target-Focused-Synthesis Approach.

Over the past few decades, hit identification has been greatly facilitated by advances in high-throughput and fragment-based screenings. One major hurdle remaining in drug discovery is process automation of hit-to-lead (H2L) optimization. Here, we report a time- and cost-efficient integrated strategy for H2L optimization as well as a partially automated design of potent chemical probes consisting of a focused-chemical-library design and virtual screening coupled with robotic diversity-oriented de novo synthesis and automated in vitro evaluation. The virtual library is generated by combining an activated fragment, corresponding to the substructure binding to the target, with a collection of functionalized building blocks using in silico encoded chemical reactions carefully chosen from a list of one-step organic transformations relevant in medicinal chemistry. The proof of concept was demonstrated using the optimization of bromodomain inhibitors as a test case, leading to the validation of several compounds with improved affinity by several orders of magnitude.

S4MPLE--Sampler for Multiple Protein-Ligand Entities: Methodology and Rigid-Site Docking Benchmarking.

This paper describes the development of the unified conformational sampling and docking tool called Sampler for Multiple Protein-Ligand Entities (S4MPLE). The main novelty in S4MPLE is the unified dealing with intra- and intermolecular degrees of freedom (DoF). While classically programs are either designed for folding or docking, S4MPLE transcends this artificial specialization. It supports folding, docking of a flexible ligand into a flexible site and simultaneous docking of several ligands. The trick behind it is the formal assimilation of inter-molecular to intra-molecular DoF associated to putative inter-molecular contact axes. This is implemented within the genetic operators powering a Lamarckian Genetic Algorithm (GA). Further novelty includes differentiable interaction fingerprints to control population diversity, and fitting a simple continuum solvent model and favorable contact bonus terms to the AMBER/GAFF force field. Novel applications-docking of fragment-like compounds, simultaneous docking of multiple ligands, including free crystallographic waters-were published elsewhere. This paper discusses: (a) methodology, (b) set-up of the force field energy functions and (c) their validation in classical redocking tests. More than 80% success in redocking was achieved (RMSD of top-ranked pose < 2.0 Å).

In silico fragment-based drug discovery: setup and validation of a fragment-to-lead computational protocol using S4MPLE.

This paper describes the use and validation of S4MPLE in Fragment-Based Drug Design (FBDD)--a strategy to build drug-like ligands starting from small compounds called fragments. S4MPLE is a conformational sampling tool based on a hybrid genetic algorithm that is able to simulate one (conformer enumeration) or more molecules (docking). The goal of the current paper is to show that due to the judicious design of genetic operators, S4MPLE may be used without any specific adaptation as an in silico FBDD tool. Such fragment-to-lead evolution involves either growing of one or linking of several fragment-like binder(s). The native ability to specifically "dock" a substructure that is covalently anchored to its target (here, some prepositioned fragment formally part of the binding site) enables it to act like dedicated de novo builders and differentiates it from most classical docking tools, which may only cope with non-covalent interactions. Besides, S4MPLE may address growing/linking scenarios involving protein site flexibility, and it might also suggest "growth" moves by bridging the ligand to the site via water-mediated interactions if H2O molecules are simply appended to the input files. Therefore, the only development overhead required to build a virtual fragment→ligand growing/linking strategy based on S4MPLE were two chemoinformatics programs meant to provide a minimalistic management of the linker library. The first creates a duplicate-free library by fragmenting a compound database, whereas the second builds new compounds, attaching chemically compatible linkers to the starting fragments. S4MPLE is subsequently used to probe the optimal placement of the linkers within the binding site, with initial restraints on atoms from initial fragments, followed by an optimization of all kept poses after restraint removal. Ranking is mainly based on two criteria: force-field potential energy and RMSD shifts of the original fragment moieties. This strategy was applied to several examples from the FBDD literature with good results over several monitored criteria: ability to generate the optimized ligand (or close analogs), good ranking of analogs among decoy compounds, and accurate predictions of expected binding modes of reference ligands. Simulations included "classical" covalent growing/linking, more challenging ones involving binding site conformational changes, and growth with optional recognition of putatively favorable water-mediated interactions.

S4MPLE--sampler for multiple protein-ligand entities: simultaneous docking of several entities.

S4MPLE is a conformational sampling tool, based on a hybrid genetic algorithm, simulating one (conformer enumeration) or more molecules (docking). Energy calculations are based on the AMBER force field [Cornell et al. J. Am. Chem. Soc. 1995, 117, 5179.] for biological macromolecules and its generalized version GAFF [Wang et al. J. Comput. Chem. 2004 , 25, 1157.] for ligands. This paper describes more advanced, specific applications of S4MPLE to problems more complex than classical redocking of drug-like compounds [Hoffer et al. J. Mol. Graphics Modell. 2012, submitted for publication.]. Here, simultaneous docking of multiple entities is addressed in two different important contexts. First, simultaneous docking of two fragment-like ligands was attempted, as such ternary complexes are the basis of fragment-based drug design by linkage of the independent binders. As a preliminary, the capacity of S4MPLE to dock fragment-like compounds has been assessed, since this class of small probes used in fragment-based drug design covers a different chemical space than drug-like molecules. Herein reported success rates from fragments redocking are as good as classical benchmarking results on drug-like compounds (Astex Diverse Set [Hartshorn et al. J. Med. Chem. 2007, 50, 726.]). Then, S4MPLE is successfully challenged to predict locations of fragments involved in ternary complexes by means of multientity docking. Second, the key problem of predicting water-mediated interaction is addressed by considering explicit water molecules as additional entities to be docked in the presence of the "main" ligand. Blind prediction of solvent molecule positions, reproducing relevant ligand-water-site mediated interactions, is achieved in 76% cases over saved poses. S4MPLE was also successful to predict crystallographic water displacement by a therefore tailored functional group in the optimized ligand. However, water localization is an extremely delicate issue in terms of weighing of electrostatic and desolvation terms and also introduces a significant increase of required sampling efforts. Yet, the herein reported results - not making use of massively parallel deployment of the software - are very encouraging.

Fragment-based drug design: computational & experimental state of the art.

Fragment-based screening is an emerging technology which is used as an alternative to high-throughput screening (HTS), and often in parallel. Fragment screening focuses on very small compounds. Because of their small size and simplicity, fragments exhibit a low to medium binding affinity (mM to µM) and must therefore be screened at high concentration in order to detect binding events. Since some issues are associated with high-concentration screening in biochemical assays, biophysical methods are generally employed in fragment screening campaigns. Moreover, these techniques are very sensitive and some of them can give precise information about the binding mode of fragments, which facilitates the mandatory hit-to-lead optimization. One of the main advantages of fragment-based screening is that fragment hits generally exhibit a strong binding with respect to their size, and their subsequent optimization should lead to compounds with better pharmacokinetic properties compared to molecules evolved from HTS hits. In other words, fragments are interesting starting points for drug discovery projects. Besides, the chemical space of low-complexity compounds is very limited in comparison to that of drug-like molecules, and thus easier to explore with a screening library of limited size. Furthermore, the "combinatorial explosion" effect ensures that the resulting combinations of interlinked binding fragments may cover a significant part of "drug-like" chemical space. In parallel to experimental screening, virtual screening techniques, dedicated to fragments or wider compounds, are gaining momentum in order to further reduce the number of compounds to test. This article is a review of the latest news in both experimental and in silico virtual screening in the fragment-based discovery field. Given the specificity of this journal, special attention will be given to fragment library design.