arXiv Machine Learning
Sep 29

Improving Molecular-Morphology Contrastive Pretraining using Deep-Learning-based Morphology Profiles

The paper presents MoCoP v2, an enhanced contrastive pretraining method that aligns small molecule embeddings with deep‑learning‑derived cell morphology profiles. By replacing CellProfiler fingerprints with richer image‑encoded features, the new embeddings better capture how molecules alter cell morphology, leading to improved QSAR, toxicity, ADME, and activity predictions. Performance scales log‑linearly with training data size, indicating further gains with larger datasets.

By Jie Li, Kathryn E. Kirchoff, Dante A. Pertusi, Zhizhuo Zhang
arXiv Machine Learning
Sep 29

Interpretable-by-Design Descriptor Portfolios Match a 2048-Dimensional Foundation Embedding on Low-Data Molecular Assays

The study evaluates whether a portfolio of compact, semantically named descriptor blocks can match the performance of a 2048‑dimensional CheMeleon embedding in low‑data molecular assays. Using a fixed 11‑dimensional physicochemical base and greedily adding provenance‑screened blocks, the portfolio achieves a mean test AUC of 0.762 across nine ADME/Tox assays, comparable to CheMeleon’s 0.764 and better than Mordred’s 0.756. The results meet a predeclared pooled parity threshold but not all per‑assay thresholds, and further analysis confirms the competitiveness of the auditable representation while highlighting unresolved assay‑level differences.

By Yiqi Yao, Miquel Duran-Frigola
arXiv AI
Jun 3

CP-Agent: Context-Aware Multimodal Reasoning for Cellular Morphological Profiling under Chemical Perturbations

arXiv:2606. 03435v1 Announce Type: new Abstract: Cell Painting combines multiplexed fluorescent staining, high-content imaging, and quantitative analysis to generate high-dimensional phenotypic readouts to support diverse downstream tasks such as mechanism-of-action (MoA) inference, toxicity prediction, and construction of drug-disease atlases.

By Yuxin Zhang, Yiyao Li, Ping Shu Ho, Simon See, Zhenqin Wu, Kevin Tsia