CHEMISTRY FOR TRANSLATIONAL MEDICINE
Translational medicine, chemical biology, chemo-genomics, chemo-proteomics, target fishing and validation, click chemistry, cellular imaging, macromolecular interactions, virtual screening, structure based drug design, biomarkers, polypharmacology, pathway analysis, site-specific protein labelling, protein engineering, bio-orthogonal reactions, antibody drug conjugates.
Laurent SCHIO (Sanofi, Paris, FR)
Stefan LAUFER (Eberhard-Karls-Universität Tübingen, DE)
Laurent MICOUIN (Université Paris Descartes, Paris, FR)
We have divided this symposium 1.2 dedicated to chemistry for Translational Medicine into three sessions: Chemical reactivity, innovation in drug design and “from chemical biology to therapeutic innovation”
The number of new NMEs per year delivered by pharmaceutical R&D has remained constant over the last decades despite exploding investment. This is largely explained by attrition, especially in clinical development and essentially due to efficacy and safety issues; the first being related mainly to poorly validated targets or non-optimal dosing in humans and the second to compounds that are not selective enough. Translational research aims to decrease this attrition through better analysis, validation and prediction of molecular mechanisms and properties that a candidate for development should exhibit to elicit expected efficacy in clinical trials. Chemical biology, chemo-genomics and chemo-proteomics elaborate selective tools, clickable or activable fluorescent probes for imaging in cells and in healthy and diseased tissues to provide dynamic information about cellular communication, signal transduction pathways, the role of macromolecules and their interactions in order to discover and validate new targets. They design chemical tools to help deconvolution of phenotypic screening hits to identify their targets and off-targets, cellular and in vivo markers to investigate drug efficacy and selectivity/toxicity or label-free techniques to directly analyze small molecule binding to proteins or other macromolecules. They help investigating target engagement and derisking, or tracking single molecules through cells and tissues. Synthetic chemistry designs and synthesizes more relevant compound libraries to identify better quality chemical tools and lead compounds, new types of molecules to modulate highly validated but “non druggable” targets (by revisiting macromolecular interactions, stabilizing rather that inhibiting interactions, activating rather than inhibiting enzymes), new types of allosteric modulators to reach higher selectivity or different biological response (by inhibiting protein transport rather than function, or by addressing poorly druggable macromolecular interactions, enzymes like phosphatases, nucleic acid polymers, stem cells, chromatins or the epigenome). This is becoming possible through the discovery of new chemistry, e.g. macrocycles, stabilized peptides and mimetics, irreversible inhibitors, degraders, peptide or nucleic acid based polymers, natural product based scaffolds etc. Specificity and efficacy can be increased by tagging 5 active small molecules and macromolecules to deliver them into cells, cellular compartments, specific tissues or diseased organs. Predictive mathematical models are used in systems biology for target identification and validation, druggability assessment and de risking. In silico approaches investigate the behavior of molecules on a systems level in cells, organs and whole organisms to predict mechanism of action, selectivity and side effects and potential for drug repurposing. Computational methods help identify targets or off-targets of phenotypic screening results through similarity based target fishing and deconvolution. Statistical and structure based methods are used to generate more efficient and drug-like small and macromolecular target modulators and probes through (i) fragment based design, (ii) new virtual screening strategies including covalent docking, (iii) design of cell penetrable small molecules interfering with nucleic acid polymers from sequence information or by comprehensive analysis of loops at protein-protein interfaces for macrocycle design. Analytical and biophysical tools are used to identify biomarkers that can translate observations in cells through animal models into humans, understand cellular networks and communications, track molecules to understand and predict polypharmacology and select the right patient population for personalized medicine. Structural biological methods may allow determining macromolecular structures and interactions to help rationally design modulators. It is becoming clear that many drugs may derive their therapeutic benefit or liability from interactions with multiple proteins rather than a single target. Chemistry needs to meet the challenge of designing compounds for multiple targets but still being selective enough to meet the requirements of polypharmacology i.e. maximizing efficacy while minimizing side effects. The symposiums will cover new tools, methods and approaches to select more relevant targets and design high quality molecules able to target the “non-druggable” genome together with tools helping a better translation of research findings to clinical success.