1 citations · 2 across the 5 of their papers we have counts for
5 papers
AgenticPosesRanker: An Agentic AI Framework for Physically Grounded Ranking of Protein-Ligand Docking Poses
Sofiene Khiari, Amr H. Mahmoud, Markus A. Lill
Scoring functions remain the principal bottleneck in molecular docking: they routinely fail to rank near-native poses above decoys, and their composite single-score design obscures…
Synthetic Protein-Ligand Complex Generation for Deep Molecular Docking
Sofiene Khiari, Matthew R. Masters, Amr H. Mahmoud +1
The scarcity of experimental protein-ligand complexes poses a significant challenge for training robust deep learning models for molecular docking. Given the prohibitive cost and t…
Accelerated Hydration Site Localization and Thermodynamic Profiling
Florian B. Hinz, Matthew R. Masters, Julia N. Kieu +2
Water plays a fundamental role in the structure and function of proteins and other biomolecules. The thermodynamic profile of water molecules surrounding a protein are critical for…
Graph-convolution neural network-based flexible docking utilizing coarse-grained distance matrix
Amr H. Mahmoud, Jonas F. Lill, Markus A. Lill
Prediction of protein-ligand complexes for flexible proteins remains still a challenging problem in computational structural biology and drug design. Here we present two novel deep…
On-the-fly Prediction of Protein Hydration Densities and Free Energies using Deep Learning
Ahmadreza Ghanbarpour, Amr H. Mahmoud, Markus A. Lill
The calculation of thermodynamic properties of biochemical systems typically requires the use of resource-intensive molecular simulation methods. One example thereof is the thermod…