Cheminformatics seminars

Liver toxicity can emerge late in drug development when early assays fail to capture human biology, exposure or injury mechanisms. This webinar introduces Axiom’s hepatic profiling approach, combining multicellular liver systems, high-content imaging, transcriptomics, proteomics and ADME measurements. Its reasoning agent integrates those results with partner assays, chemical-series context, exposure estimates and clinical evidence to assess mechanistic liver-safety risks. Rather than using a single cell-toxicity score, the approach develops interpretable, series-specific structure–toxicity hypotheses, compares analogues, ranks compounds and suggests follow-up experiments or structural changes. Performance on established liver-injury reference compounds and newer molecules is examined through case studies, showing how multimodal evidence can inform medicinal-chemistry decisions and predicted therapeutic index.

Organic multicomponent crystals can alter material properties without changing the covalent structures of their constituent molecules. René de Gelder examines how these crystals can be classified and how chirality affects the resulting classes and subclasses. Thousands of structures in resources such as the Cambridge Structural Database provide the basis for a network-science analysis of structural diversity. The approach seeks principles governing multicomponent crystal formation, ways to predict new combinations, and a map of the transition between cocrystals and salts.

This webinar uses research on Chagas disease to explain how predicted protein structures can support drug discovery when experimental structures are unavailable. In the example study, AlphaFold models of Trypanosoma cruzi proteins supported a virtual screen of roughly 30,000 compounds; subsequent experiments identified antiparasitic activity in two approved drugs. The session introduces AlphaFold confidence measures and ways to obtain models, then follows a screening workflow through binding-pocket prediction, chemical-library selection, docking, and interpretation of results. It discusses difficulties encountered when docking against predicted structures and considerations for adapting the workflow to other targets. The material is intended for doctoral students, early-career researchers, and other drug-discovery professionals.

Bowen Li explains how ionizable lipids are designed for lipid nanoparticles that deliver messenger RNA. The seminar covers combinatorial and machine-learning-guided design, four-component reactions for rapidly producing lipid libraries, and barcoded screening in living systems to identify formulations targeting organs and cells, including lungs, T cells and tumours. It then examines applications of AI-guided nanoparticle platforms to mRNA therapeutics. Li is an Associate Professor and Canada Research Chair at the University of Toronto's Leslie Dan Faculty of Pharmacy. Online via Zoom. Thursday 24 September 2026, 11:00–12:00 Eastern Daylight Time (America/New_York; UTC−4). Use Join via Zoom on Western University's event page. The stated audience includes researchers, students, alumni and the general public. Organized by Western University's Western Bioinformatics Research Seminar.

The question of the origin of homochirality of living matter, or the dominance of one handedness for all molecules of life across the entire biosphere, is a long-standing puzzle in the research on the Origin of Life. In the fifties, Frank proposed a mechanism to explain homochirality based on the properties of a simple autocatalytic network containing only a few chemical species. Following this work, chemists struggled to find experimental realizations of this model, possibly due to a lack of proper methods to identify autocatalysis [1]. In any case, a model based on a few chemical species seems rather limited, because prebiotic earth is likely to have consisted of complex ‘soups’ of chemicals. To include this aspect of the problem, we recently proposed a mechanism based on certain features of large out-of-equilibrium chemical networks [2]. We showed that a phase transition towards an homochiral state is likely to occur as the number of chiral species in the system becomes large or as the amount of free energy injected into the system increases. Through an analysis of large chemical databases, we showed that there is no need for very large molecules for chiral species to dominate over achiral ones; it already happens when molecules contain about 10 heavy atoms. We also analyzed the various conventions used to measure chirality and discussed the relative chiral signs adopted by different groups of molecules [3]. We then proposed a generalization of Frank’s model for large chemical networks, which we characterized using random matrix theory. This analysis includes sparse networks, suggesting that the emergence of homochirality is a robust and generic transition. References: [1] A. Blokhuis, D. Lacoste, and P. Nghe, PNAS (2020), 117, 25230. [2] G. Laurent, D. Lacoste, and P. Gaspard, PNAS (2021) 118 (3) e2012741118. [3] G. Laurent, D. Lacoste, and P. Gaspard, Proc. R. Soc. A 478:20210590 (2022).