In this work, we develop a computational tool for ranking ligand binding affinity that uniformly samples ligand conformations over the target protein's surface ...
Sep 9, 2015 · In this work, we develop a computational tool for ranking ligand binding affinity that uniformly samples ligand conformations over the target ...
In this work, we develop a computational tool for ranking ligand binding affinity that uniformly samples ligand conformations over the target protein's surface ...
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Uniform Obstacle-Based Probabilistic Roadmap shows promise as a potential technique with which to rank protein-ligand complexes based on their binding ...
In this paper, we present a novel approach to study the dynamics and kinetics of flexible ligand binding using robotic motion planning. Several algorithms ...
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Mar 5, 2024 · Abstract. Accurately predicting the binding affinity between proteins and ligands is crucial in drug screening and optimization, ...
May 11, 2022 · They evaluate different scoring functions for their performance on scoring, ranking, docking, and screening on a diverse and high-quality set of ...
Feb 2, 2024 · Employing a geometric deep learning model, we explore the usefulness of these bond-critical points to predict absolute binding affinities of ...
We have developed a novel approach to study the dynamics of protein-ligand interactions based on motion planning algorithms from the field of robotics. Our ...