There is a tendency in the literature to be critical of scoring functions when docking programs perform poorly. The assumption is that existing scoring functions need to be enhanced or new ones developed in order to improve the performance of docking programs for tasks such as pose prediction and virtual screening. However, failures can result from either sampling or scoring (or a combination of the two), although less emphasis tends to be given to the former. In this work, we use the programs GOLD and Glide on a high-quality data set to explore whether failures in pose prediction and binding affinity estimation can be attributable more to sampling or scoring. We show that identification of the correct pose (docking power) can be improved b...
International audienceAbstractBackgroundPose generation error is usually quantified as the differenc...
Machine learning scoring functions for protein–ligand binding affinity have been found to consistent...
Molecular docking is the most frequently used computational method for studying the interactions bet...
There is a tendency in the literature to be critical of scoring functions when docking programs perf...
There is a tendency in the literature to be critical of scoring functions when docking programs perf...
There is a tendency in the literature to be critical of scoring functions when docking programs perf...
There is a tendency in the literature to be critical of scoring functions when docking programs perf...
Computational methods for docking ligands have been shown to be remarkably dependent on precise prot...
Background: Protein-protein docking, which aims to predict the structure of a protein-protein comple...
Abstract Background In drug design, an efficient structure-based optimization of a ligand needs the ...
In a previous self-docking study, we have shown that structure reproduction performance can be impro...
Molecular docking is a computational tool commonly applied in drug discovery projects and fundament...
Molecular docking is a computational tool commonly applied in drug discovery projects and fundament...
International audienceAbstractBackgroundPose generation error is usually quantified as the differenc...
International audienceAbstractBackgroundPose generation error is usually quantified as the differenc...
International audienceAbstractBackgroundPose generation error is usually quantified as the differenc...
Machine learning scoring functions for protein–ligand binding affinity have been found to consistent...
Molecular docking is the most frequently used computational method for studying the interactions bet...
There is a tendency in the literature to be critical of scoring functions when docking programs perf...
There is a tendency in the literature to be critical of scoring functions when docking programs perf...
There is a tendency in the literature to be critical of scoring functions when docking programs perf...
There is a tendency in the literature to be critical of scoring functions when docking programs perf...
Computational methods for docking ligands have been shown to be remarkably dependent on precise prot...
Background: Protein-protein docking, which aims to predict the structure of a protein-protein comple...
Abstract Background In drug design, an efficient structure-based optimization of a ligand needs the ...
In a previous self-docking study, we have shown that structure reproduction performance can be impro...
Molecular docking is a computational tool commonly applied in drug discovery projects and fundament...
Molecular docking is a computational tool commonly applied in drug discovery projects and fundament...
International audienceAbstractBackgroundPose generation error is usually quantified as the differenc...
International audienceAbstractBackgroundPose generation error is usually quantified as the differenc...
International audienceAbstractBackgroundPose generation error is usually quantified as the differenc...
Machine learning scoring functions for protein–ligand binding affinity have been found to consistent...
Molecular docking is the most frequently used computational method for studying the interactions bet...