Zakhar Ostrovsky

Leveraging Large Language Models for Literature-Driven Prioritization of Protein Binding Pockets

This paper combines geometric pocket detection with large language models to prioritize protein binding pockets for drug discovery, using a curated dataset and automated pipeline.

Improving ADMET prediction with descriptor augmentation of Mol2Vec embeddings

This paper improves ADMET prediction by augmenting Mol2Vec embeddings with classical descriptors and feature selection, achieving top results on 10 of 16 TDC benchmarks.

Boosting performance of generative diffusion model for molecular docking by training on artificial binding pockets

This paper introduces a generative diffusion model for molecular docking trained on artificial binding pockets, showing improved performance over existing methods.