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As such, a variety of computational methods like molecular docking have been developed to predict the structures of protein peptide complexes [3, 10 13].
In the past decade, quantitative structure activity relationship (QSAR) approaches based on 2D and 3D descriptors, pharmacophore, and molecular docking have been developed to predict inhibition potency of a limited number of structurally similar aromatase inhibitors [12 14].
Computational studies, including MD simulations, Brownian dynamics and molecular docking, have become new tools to study the roles of various subtypes of Nav channels in pathophysiology at an atomistic level (Gordon et al., 2013).
26 In other cases, the scoring functions of molecular docking have been unable to explain observed ligand binding affinities.
Most notably, advances in the a priori prediction of complexes by molecular docking have been made as well as NMR methods, such as saturation transfer difference (STD) NMR (Mayer and Meyer 2001; Meyer and Peters 2003).
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Molecular docking has profound applications in drug discovery and development.
Virtual screening of small molecules using molecular docking has become an important tool in drug discovery.
Molecular docking has become a valuable technique for structure-based drug discovery, including fragment-based approaches.
Besides the ligand-based CoMFA models, an alignment molecular set constructed by flexible molecular docking has been also studied.
Molecular docking has predicted the plausible binding interactions of compounds 3f, 3g and 3j with α-glucosidase.
Particularly, molecular docking has been used as an effective virtual screening tool and successfully applied in a number of therapeutic programs at the lead discovery stage [1].
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