Sentence examples for binding pose prediction from inspiring English sources

In addition, we confirmed that MIRS performed well on binding pose prediction.

Accurate ligand binding pose prediction was possible but difficult to achieve using homology models, even with the use of induced fit docking.

Our results reveal that it is indispensable to incorporate unbound ligand conformations in both binding affinity prediction and binding pose prediction.

Model quality was assessed relative to the crystal structure in terms of structural accuracy as well as performance in two typical structure-based drug design applications: ligand binding pose prediction and docking enrichment in virtual screening.

Our results indicate that while homology models that are reasonably accurate structurally can be constructed, without significant refinement homology models will be outperformed by crystal structures in ligand binding pose prediction and docking enrichment regardless of the template used, primarily due to the extremely high level of structural accuracy needed for such applications.

Two examples of these features demonstrated their usefulness in binding pose prediction and virtual screening.

Low RMSD values and the high fractions of contacts indicate better ligand binding pose predictions.

For the binding pose predictions, the recently reported X-ray crystal structure of mPGES-1 with the co-crystallized ligand (PDB code: LVJ; PDB accession code: 4bpm) was utilized for the docking study.

(C) Ligand binding poses predicted by PharmDock for co-crystallized ligand in PDB structure 1MQ6.

Tests of PharmDock on ligand pose prediction, binding affinity estimation, compound ranking and virtual screening yielded comparable or better performance to existing and widely used docking programs.

In our previous study, we have presented pose prediction and ranking results using pharmacophore models without any local optimization of the binding poses or use of an atomistic scoring function.