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Protein-protein interactions are not only about how structures interact - the strength of the interaction matters. In a new blog post, Wei Lu shows how the structure-predicting AlphaFold3 can contribute to an ensemble of binding-affinity prediction models. Check it out here: https://lnkd.in/ecEW-FmR

✅ Today was the final day of the ML Summer School for Drug Discovery in Montreal, which I attended with my colleague Joseph Brown. It was a fantastic five days of intensive learning about the latest ML tools for drug discovery. 🎉 A big shoutout to the organizing team from Valence Labs and Mila - Quebec Artificial Intelligence Institute for making it an incredible experience. Honoured to be a part of the vibrant community of ML specialists on Portal. 🙏 Special thanks to all the professors, including Yoshua Bengio, Bharath Ramsundar, Anne Carpenter, Mario Geiger, Connor W. Coley, Michael Bronstein, Camille Bilodeau, Sebastien Lemieux, Dominique Beaini, Charlotte Bunne, Karmen Čondić-Jurkić for sharing their knowledge and expertise with us. Special thanks to the lab leaders for demonstrating the applications of these tools in a clear and simple format! 🚀🔬It was a great event to meet fellow ML enthusiasts and learn from world-recognized experts in the field. Thanks Acceleration Consortium and University of Toronto for supporting our trip. I'm excited to start implementing this new knowledge in our self-driving laboratory on Human Organ Mimicry at Acceleration Consortium at Donnelly Centre for Cellular and Biomolecular Research, University of Toronto. #MLSummerSchool #DrugDiscovery #MachineLearning #networking #ValenceLabs #MILA #AI #BiomedicalResearch #Innovation #HumanOrganMimicry #SelfDrivingLab #AccelerationConsortium

Had a fantastic time at the ML for Drug Discovery Summer School @ Center PHI, Montréal. https://lnkd.in/gvUG-848 Many great speakers including Bharath Ramsundar Emmanuel Noutahi, PhD Dominique Beaini Mario Geiger Gabriele Corso Pratyush Tiwary Camille Bilodeau Connor W. Coley Michael Bronstein Anne Carpenter Sebastien Lemieux Charlotte Bunne and others shared their views on the current developments of the field. Program included five days of talks and hands-on labs on how machine learning can address key scientific goals related to molecular modeling and therapeutic design, followed by MoML conference 2024. Overall lots of insights on state-of-the-art ML approaches used in drug design. A big shoutout to Valence Labs Portal and Mila - Quebec Artificial Intelligence Institute for organizing this incredible event. #ML4DD #machinelearning #drugdiscovery #AI #MLsummerschool #biotech #computationalchemistry

Thank you to the 180 people who came to discover 50 scientific posters at the 2024 Molecular Machine Learning Conference at Mila! Portal

180 people. 50 posters. The 2024 Molecular Machine Learning Conference was so much fun! Thank you to all our speakers who made their way to Mila - Quebec Artificial Intelligence Institute to present amazing talks. This conference would not have been possible without your support (Jian Tang, Cas Wognum, Jason Hartford, Raquel Rodríguez-Pérez, Max Jaderberg). We’ll aim to make the recordings of the talks available to everyone in a few weeks. Follow us to get the latest updates.

The hackathon portion of the summer school is underway! The Polaris team is here to show students how to access datasets and benchmarks for kinase selectivity and molecular property prediction tasks.

Tune in live to Max Jaderberg's talk at MoML 2024 on "Towards Rational Drug Design with AlphaFold 3". Happening now! https://lnkd.in/gF7cpG4j

Day 2 of the ML for Drug Discovery Summer School was focused on ML in Structured-Based Drug Discovery. We had a great series of lectures from Gabriele Corso, Gianni De Fabritiis, Pratyush Tiwary, and Jacopo Venturin that covered everything from how ML methods can help with binding affinity prediction to intermolecular interactions modeling to free energy computations to QM and MD simulations, predictive modeling, and more! To finish the day, Cristian Gabellini and Stephan Thaler led an interactive lab session on binding affinity prediction with ML-based docking. If you want to get access to the Google Colab, drop a comment! See you tomorrow for day 3.

Day 1 of the ML for Drug Discovery Summer School was awesome! 🏫 Over 150 people were in attendance to learn from speakers like Bharath Ramsundar, Emmanuel Noutahi, PhD, Dominique Beaini, and Mario Geiger. Topics covered included: GNNs, virtual screening, molecular representation and scoring, and more. Building on the concepts taught in the lectures, Cas Wognum and Lu Zhu finished the day with a hands-on lab on virtual screening. Students used datasets of 2D molecules to develop predictive models for assessing inhibitory activity against EGFR! 🧪 Day 2 starts tomorrow at 8:30 AM with a talk on ML in Structure-Based Drug Discovery by Gabriele Corso. See the full schedule for the Summer School here: https://lnkd.in/gvUG-848

Join us live in a few minutes! https://lnkd.in/gHTNG8kB