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Recent developments in the direction of target-class-specific scoring methods and machine-learning-based procedures reveal significant performance improvement in binding mode and affinity prediction.
For this purpose, a set of high-resolution holo crystallographic structures from CYP51 of human pathogen Trypanosoma cruzi were retrieved to statistically model the binding mode and affinity of fluconazole.
To obtain an accurate binding mode and affinity data, docking was conducted in the Geom mode of Surfelx-Dock.
The binding mode and affinity of biological substrates and inhibitors for caspase-1 were examined to compare these characteristics with those of RA.
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Structural studies of ZnF complexes reveal considerable diversity in terms of protein partners, binding modes and affinities, and highlight the often underestimated versatility of ZnF structure and function.
AutoDock clustering was performed based on similarities in binding modes and affinities in these cycles.
Furthermore, the developed template was applied to predict binding mode and binding affinity of thirty-six known Cdk5 inhibitors.
As such, future studies should be performed using molecular dynamics to analyze the binding mode and binding affinity of fenofibrate at both A*33 01 and B*57 01 variants.
In addition, recent studies show that polarization effects are important for both binding mode and binding affinity predictions (Cho et al. 2005; Xu and Lill 2013).
A molecular docking method is defined as the prediction of both the binding mode and binding affinity of a query ligand (such as a small-molecule drug) against a receptor (such as a target protein) (Brooijmans and Kuntz 2003; Sousa et al. 2006; Grinter and Zou 2014a, b).
In order to validate a fragment as an interesting starting point, its binding site, binding mode and binding affinity have to be characterized.
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CEO of Professional Science Editing for Scientists @ prosciediting.com