4 papers · 1 filter
Zatom-1: Towards a Multimodal Foundation Model for 3D Molecules and Materials
Alex Morehead, Miruna Cretu, Antonia Panescu +14
General-purpose 3D modeling in chemistry encompasses molecules and materials, requiring both generative and predictive capabilities. However, most existing AI approaches are optimi…
Learning Inter-Atomic Potentials without Explicit Equivariance
Ahmed A. Elhag, Arun Raja, Alex Morehead +6
Accurate and scalable machine-learned inter-atomic potentials (MLIPs) are essential for molecular simulations ranging from drug discovery to new material design. Current state-of-t…
Topotein: Topological Deep Learning for Protein Representation Learning
Zhiyu Wang, Arian Jamasb, Mustafa Hajij +3
Protein representation learning (PRL) is crucial for understanding structure-function relationships, yet current sequence- and graph-based methods fail to capture the hierarchical…
Assessing the potential of deep learning for protein-ligand docking
Alex Morehead, Nabin Giri, Jian Liu +2
The effects of ligand binding on protein structures and their in vivo functions carry numerous implications for modern biomedical research and biotechnology development efforts suc…