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AI drug discovery

topic3 events
papersTODAY 04:00 UTC

Autoregressive Fragment Model Generates Molecules at Specified Attachment Sites

A new arXiv preprint introduces Fraglingo, a generative approach that builds molecules by mimicking common medicinal-chemistry edits such as extending a scaffold or swapping a substituent. The method generates fragments conditioned on a chosen attachment point, letting users direct where a new piece is added while optimizing desired molecular properties. It falls under fragment-based molecular design research.

molecular-design/generative-models/chemistry/research
papersTODAY 04:00 UTC

Multi-View Molecular Pretraining Combines Hierarchical Graphs With Contextualized Fingerprints

A new arXiv paper proposes a molecular representation learning approach that combines multiple views rather than relying on a single one. It pairs hierarchical graph modeling of atom-bond topology with contextualized molecular fingerprints to improve property prediction. The goal is representations that generalize from limited labeled data to structurally novel compounds.

research/molecular-ml/graph-neural-networks/pretraining
papersSEP 9 10:58 UTC

AI-designed lung fibrosis drug linked to slower biological aging in trial

A drug candidate for lung fibrosis that was developed with the help of artificial intelligence produced effects in a study that point to a reduced pace of biological aging. The reported findings come from a single trial and indicate additional effects beyond the compound's intended antifibrotic action. Researchers have not yet established whether these observations translate into clinical benefits for patients.

drug-discovery/ai-biotech/clinical-trial/aging