Reymond Research Group

The paper "A probabilistic molecular fingerprint for big data settings" has been published by the Journal of Cheminformatics.

Background
Among the various molecular fingerprints available to describe small organic molecules, extended connectivity fingerprint, up to four bonds (ECFP4) performs best in benchmarking drug analog recovery studies as it encodes substructures with a high level of detail. Unfortunately, ECFP4 requires high dimensional representations (≥ 1024D) to perform well, resulting in ECFP4 nearest neighbor searches in very large databases such as GDB, PubChem or ZINC to perform very slowly due to the curse of dimensionality.

Results
Herein we report a new fingerprint, called MinHash fingerprint, up to six bonds (MHFP6), which encodes detailed substructures using the extended connectivity principle of ECFP in a fundamentally different manner, increasing the performance of exact nearest neighbor searches in benchmarking studies and enabling the application of locality sensitive hashing (LSH) approximate nearest neighbor search algorithms. To describe a molecule, MHFP6 extracts the SMILES of all circular substructures around each atom up to a diameter of six bonds and applies the MinHash method to the resulting set. MHFP6 outperforms ECFP4 in benchmarking analog recovery studies. By leveraging locality sensitive hashing, LSH approximate nearest neighbor search methods perform as well on unfolded MHFP6 as comparable methods do on folded ECFP4 fingerprints in terms of speed and relative recovery rate, while operating in very sparse and high-dimensional binary chemical space.

Conclusion
MHFP6 is a new molecular fingerprint, encoding circular substructures, which outperforms ECFP4 for analog searches while allowing the direct application of locality sensitive hashing algorithms. It should be well suited for the analysis of large databases. The source code for MHFP6 is available on GitHub (https://github.com/reymond-group/mhfp).

https://jcheminf.biomedcentral.com/articles/10.1186/s13321-018-0321-8

Author(s): Daniel Probst and Jean-Louis Reymond

A probabilistic molecular fingerprint for big data settings Among the various molecular fingerprints available to describe small organic molecules, extended connectivity fingerprint, up to four bonds (ECFP4) performs best in benchmarking drug analog recovery studies as it encodes substructures with a high level of detail. Unfortunately, ECFP4 requires high d...

The paper "Identifying Lysophosphatidic Acid Acyltransferase β (LPAAT‐β) as the Target of a Nanomolar Angiogenesis Inhibitor from a Phenotypic Screen Using the Polypharmacology Browser PPB2" has been published by ChemMedChem.

By screening a focused library of kinase inhibitor analogues in a phenotypic co‐culture assay for angiogenesis inhibition, we identified an aminotriazine that acts as a cytostatic nanomolar inhibitor. However, this aminotriazine was found to be completely inactive in a whole‐kinome profiling assay. To decipher its mechanism of action, we used the online target prediction tool PPB2 (http://ppb2.gdb.tools), which suggested lysophosphatidic acid acyltransferase β (LPAAT‐β) as a possible target for this aminotriazine as well as several analogues identified by structure–activity relationship profiling. LPAAT‐β inhibition (IC50 ≈15 nm) was confirmed in a biochemical assay and by its effects on cell proliferation in comparison with a known LPAAT‐β inhibitor. These experiments illustrate the value of target‐prediction tools to guide target identification for phenotypic screening hits and significantly expand the rather limited pharmacology of LPAAT‐β inhibitors.

Author(s): Marion Poirier, Mahendra Awale, Matthias A. Roelli, Guy T. Giuffredi, Lars Ruddigkeit, Lasse Evensen, Amandine Stooss, Serafina Calarco, James B. Lorens, Roch‐Philippe Charles, Jean‐Louis Reymond

Identifying Lysophosphatidic Acid Acyltransferase β (LPAAT‐β) as the Target of a Nanomolar Angiogenesis Inhibitor from a Phenotypic Screen Using the Polypharmacology Browser PPB2 - Poirier - - ChemMedChem - Wiley Online Library Full Paper Identifying Lysophosphatidic Acid Acyltransferase β (LPAAT‐β) as the Target of a Nanomolar Angiogenesis Inhibitor from a Phenotypic Screen Using the Polypharmacology Browser PPB2 Marion Poirier Department of Chemistry and Biochemistry, National Center of Competence in Research NCCR ...

The paper Structure of bacterial oligosaccharyltransferase PglB bound to a reactive LLO and an inhibitory peptide has been published by Scientific Reports.

Oligosaccharyltransferase (OST) is a key enzyme of the N-glycosylation pathway, where it catalyzes the transfer of a glycan from a lipid-linked oligosaccharide (LLO) to an acceptor asparagine within the conserved sequon N-X-T/S. A previous structure of a ternary complex of bacterial single subunit OST, PglB, bound to a non-hydrolyzable LLO analog and a wild type acceptor peptide showed how both substrates bind and how an external loop (EL5) of the enzyme provided specific substrate-binding contacts. However, there was a relatively large separation of the substrates at the active site. Here we present the X-ray structure of PglB bound to a reactive LLO analog and an inhibitory peptide, revealing previously unobserved interactions in the active site. We found that the atoms forming the N-glycosidic bond (C-1 of the GlcNAc moiety of LLO and the –NH2 group of the peptide) are closer than in the previous structure, suggesting that we have captured a conformation closer to the transition state of the reaction. We find that the distance between the divalent metal ion and the glycosidic oxygen of LLO is now 4 Å, suggesting that the metal stabilizes the leaving group of the nucleophilic substitution reaction. Further, the carboxylate group of a conserved aspartate of PglB mediates an interaction network between the reducing-end sugar of the LLO, the asparagine side chain of the acceptor peptide, and a bound divalent metal ion. The interactions identified in this novel state are likely to be relevant in the catalytic mechanisms of all OSTs.

Author(s): Maja Napiórkowska, Jérémy Boilevin, Tamis Darbre, Jean-Louis Reymond & Kaspar P. Locher

Structure of bacterial oligosaccharyltransferase PglB bound to a reactive LLO and an inhibitory peptide Article

https://pubs.acs.org/doi/10.1021/acs.jcim.8b00402

reymond-group/virtual-reality-chemical-space

The article Exploring DrugBank in Virtual Reality Chemical Space has been published by the Journal of Chemical Information and Modeling.

Abstract

The recent general availability of low-cost virtual reality headsets and accompanying three-dimensional (3D) engine support presents an opportunity to bring the concept of chemical space into virtual environments. While virtual reality applications represent a category of widespread tools in other fields, their use in the visualization and exploration of abstract data such as chemical spaces has been experimental. In our previous work, we established the concept of interactive two-dimensional (2D) maps of chemical spaces followed by interactive web-based 3D visualizations, culminating in the interactive web-based 3D visualization of extremely large chemical spaces. Virtual reality chemical spaces are a natural extension of these concepts. As 2D and 3D embeddings and projections of high-dimensional chemical fingerprint spaces have been shown to be valuable tools in chemical space visualization and exploration, existing pipelines of data mining and preparation can be extended to be used in virtual reality applications. Here we present an application based on the Unity engine and the Virtual Reality Toolkit, allowing for the interactive exploration of chemical space populated by DrugBank compounds in virtual reality. The source code of the application as well as the most recent build are available on GitHub (https://github.com/reymond-group/virtual-reality-chemical-space).

Author(s): Daniel Probst, Jean-Louis Reymond

reymond-group/virtual-reality-chemical-space

The review "Synthesis of Lipid-Linked Oligosaccharides (LLOs) and Their Phosphonate Analogues as Probes To Study Protein Glycosylation Enzymes" has been published by Synthesis.

Here we review chemical and chemoenzymatic methods for the synthesis of lipid-linked oligosaccharides (LLOs) and their phosphonate analogues, which serve as substrates and inhibitors to investigate the structure and mechanism of protein N-glycosylation enzymes. We emphasize how to overcome the challenges pertaining to the instability and difficult physicochemical properties of this class of compounds.

Author(s): Jérémy M. Boilevin (Jérémy Ah Bonn), Jean-Louis Reymond

Thieme E-Journals - Synthesis / Abstract Thieme E-Books & E-Journals

Paint my work: Check out and vote for the talented Clémence Delalande (chemist, model) and Joelle Zamolo (chemist, artist) at https://bit.ly/2tViN5f

EFMC Photo competition voting The European Federation for Medicinal Chemistry (EFMC) is an independent association representing medicinal chemistry societies in Europe. Its objective is to advance the science of medicinal chemistry by promoting cooperation and networking, by providing training and mentoring, by rewarding scienti...

The paper "Optimizing Antimicrobial Peptide Dendrimers in Chemical Space" has been published by Angewandte Chemie.

https://onlinelibrary.wiley.com/doi/abs/10.1002/anie.201802837

Abstract
Here we used nearest neighbor searches in chemical space to improve the activity of antimicrobial peptide dendrimer (AMPD) G3KL and identified dendrimer T7 with an expanded activity range against Gram‐negative pathogenic bacteria including Klebsiellae pneumoniae, increased serum stability and promising activity in an in vivo infection model against a multidrug resistant strain of Acinetobacter baumannii. Imaging, spectroscopic studies and a structural model from molecular dynamics simulations suggest that T7 acts by membrane disruption. These experiments provide the first example of using virtual screening in the field of dendrimers and show that dendrimer size does not limit the activity of AMPDs.

Author(s): Thissa Siriwardena, Alice Capecchi, Bee-Ha Gan, Xian Jin, Runze He, Dengwen Wei, Lan Ma, Thilo Köhler, Christian van Delden, Sacha Javor, Jean-Louis Reymond

Optimizing Antimicrobial Peptide Dendrimers in Chemical Space - Siriwardena - - Angewandte Chemie International Edition - Wiley Online Library Angewandte Chemie International Edition Volume 0, Issue ja Communication Optimizing Antimicrobial Peptide Dendrimers in Chemical Space Thissa Siriwardena E-mail address:[email protected] SWITZERLANDSearch for more papers by this author Alice Capecchi E-mail address:[email protected]...

The paper Identification of potent and selective small molecule inhibitors of the cation channel TRPM4 has been published by the British Journal of Pharmacology.

https://bpspubs.onlinelibrary.wiley.com/doi/abs/10.1111/bph.14220

Background and Purpose
TRPM4 is a calcium‐activated non‐selective cation channel expressed in many tissues and implicated in several diseases, and has not yet been validated as a therapeutic target due to the lack of potent and selective inhibitors. We sought to discover a novel series of small‐molecule inhibitors by combining in silico methods and cell‐based screening assay, with sub‐micromolar potency and improved selectivity from previously reported TRPM4 inhibitors.

Experimental Approach
Here, we developed a high throughput screening compatible assay to record TRPM4‐mediated Na+ influx in cells using a Na+‐sensitive dye and used this assay to screen a small set of compounds selected by ligand‐based virtual screening using previously known weakly active and non‐selective TRPM4 inhibitors as seed molecules. Conventional electrophysiological methods were used to validate the potency and selectivity of the hit compounds in HEK293 cells overexpressing TRPM4 and in endogenously expressing prostate cancer cell line LNCaP. Chemical chaperone property of compound 5 was studied using Western blots and electrophysiology experiments.

Key Results
A series of halogenated anthranilic amides were identified with TRPM4 inhibitory properties with sub‐micromolar potency and adequate selectivity. We also showed for the first time that a naturally occurring variant of TRPM4, which displays loss‐of‐expression and function, is rescued by the most promising compound 5 identified in this study.

Conclusions and Implications
The discovery of compound 5, a potent and selective inhibitor of TRPM4 with an additional chemical chaperone feature, revealed new opportunities for studying the role of TRPM4 in human diseases and developing clinical drug candidates.

Author(s): Lijo Cherian Ozhathil, Clémence Delalande, Beatrice Bianchi, Gabor Nemeth, Sven Kappel, Urs Thomet, Daniela Ross‐Kaschitza, Céline Simonin, Matthias Rubin, Jürg Gertsch Martin Lochner, Christine Peinelt, Jean‐Louis Reymond, and Hugues Abriel

Identification of potent and selective small molecule inhibitors of the cation channel TRPM4 - Ozhathil - - British Journal of Pharmacology - Wiley Online Library British Journal of Pharmacology Volume 0, Issue 0 RESEARCH PAPER Open Access Identification of potent and selective small molecule inhibitors of the cation channel TRPM4 Lijo Cherian Ozhathil http://orcid.org/0000-0002-4620-8507 Institute of Biochemistry and Molecular Medicine, National Center of Co...

The paper An Antimicrobial Bicyclic Peptide from Chemical Space Against Multidrug Resistant Gram-Negative Bacteria has been accepted for publication by Chemical Communications.

We used the concept of chemical space to explore a virtual library of bicyclic peptides formed by double thioether cyclization of a precursor linear peptide, and identified an antimicrobial bicyclic peptide (AMBP) with remarkable activity against several MDR strains of Acinetobacter baumannii and Pseudomonas aeruginosa.

Author(s): Ivan Dibonaventura, Stéphane Baeriswyl, Alice Capecchi, Bee-Ha Gan, Xian Jin, Thissa Nuwan Siriwardena, Runze He, Thilo Kohler, Arianna Pompilio, Giovanni Di Bonaventura, Christian van Delden, Sacha Javor and Jean-Louis Reymond

http://pubs.rsc.org/en/content/articlelanding/2018/cc/c8cc02412j

The article Deep Learning Invades Drug Design and Synthesis (https://chimia.ch/index.php?option=com_phocadownload&view=category&download=2042:2018-070&id=234:2018-01&lang=en) has been published by Chimia.

Discovering a new drug goes asfollows: given a medical need, identify the underlying biological mechanism, and design a molecule acting via this mechanism to produce the desired effects. This sounds simple, but in truth it’s not easy at all. Leaving aside biology, an important part of the problem is the chemistry: there are just too many molecules to choose from, perhaps as many as 1060 for all drug-like small molecules. Even with the help of computers one cannot enumerate more than a few billions of them, let alone predict their possible biological activity or how to synthesize them. Of course, we don’t really need to look at all these molecules. We can rely on trained medicinal chemists to make educated guesses on which onesto make and test first, often aided by modeling and automated searches, and this works well enough that trial-and-error cycles eventually succeed. Here comes a disruptive idea: can we automate the process and take the chemist out of the equation? Recent papers suggest that this might become possible using deep learning. Deep learning is an umbrella term for machine learning methods based on artificial neural networks, by which a software first learns from training data, and then is able to perform complex tasks or predictions. Parallelization of computer calculations, graphic cards and software frameworks such as TensorFlow have made deep learning practical for writing music, translating languages, and even playing (and winning) Go.

Author(s): Josep Arús-Pous, Daniel Probst, and Jean-Louis Reymond

chimia.ch

The paper Structural basis of the molecular ruler mechanism of a bacterial glycosyltransferase (https://www.nature.com/articles/s41467-018-02880-2) has been published by Nature Communications.

The membrane-associated, processive and retaining glycosyltransferase PglH from Campylobacter jejuni is part of the biosynthetic pathway of the lipid-linked oligosaccharide (LLO) that serves as the glycan donor in bacterial protein N-glycosylation. Using an unknown counting mechanism, PglH catalyzes the transfer of exactly three α1,4 N-acetylgalactosamine (GalNAc) units to the growing LLO precursor, GalNAc-α1,4-GalNAc-α1,3-Bac-α1-PP-undecaprenyl. Here, we present crystal structures of PglH in three distinct states, including a binary complex with UDP-GalNAc and two ternary complexes containing a chemo-enzymatically generated LLO analog and either UDP or synthetic, nonhydrolyzable UDP-CH2-GalNAc. PglH contains an amphipathic helix (“ruler helix”) that has a dual role of facilitating membrane attachment and glycan counting. The ruler helix contains three positively charged side chains that can bind the pyrophosphate group of the LLO substrate and thus limit the addition of GalNAc units to three. These results, combined with molecular dynamics simulations, provide the mechanism of glycan counting by PglH.

Author(s): Ana S. Ramírez, Jérémy Boilevin, Ahmad Reza Mehdipour, Gerhard Hummer, Tamis Darbre, Jean-Louis Reymond & Kaspar P. Locher