Leif Axel Eriksson

MolAI: A Deep Learning Framework for Data-driven Molecular Descriptor Generation and Advanced Drug Discovery Applications

This paper introduces MolAI, a deep learning model for generating molecular descriptors, which improves drug discovery tasks like ADMET prediction and virtual screening.

FMO4 drives lung adenocarcinoma by stabilizing the MAT2A/MAT2B complex and hindering ferroptosis

This study identifies FMO4 as a driver of lung adenocarcinoma by stabilizing the MAT2A/MAT2B complex and inhibiting ferroptosis.

Proximity Interactome analyses unveil novel regulators of IRE1a canonical signaling

The paper identifies novel IRE1 interactors that regulate its RNase activity and stability, revealing new functions in the unfolded protein response.

iScore: A ML-Based Scoring Function for de novo Drug Discovery

iScore is a machine learning-based scoring function for predicting protein-ligand binding affinity, outperforming existing methods in accuracy and efficiency for drug discovery.

An experimental target-based platform in yeast for screening Plasmodium vivax deoxyhypusine synthase inhibitors

The paper develops a yeast-based platform to identify Plasmodium vivax DHS inhibitors, finding two compounds that selectively inhibit parasite DHS over human DHS.

Gene editing is suitable to treat GM1 Gangliosidosis: a proof-of-concept study

This study shows that adenine base editors can correct 41% of GLB1 pathogenic SNVs in patient-derived fibroblasts, restoring β-gal activity without significant off-target effects.