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AUTODOCK GmbH vina term values
Statistical characteristics of linear correlation of the predicted pK SF values with the reference pK <t> values. </t>
Vina Term Values, supplied by AUTODOCK GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Statistical characteristics of linear correlation of the predicted pK SF values with the reference pK  values.

Journal: International Journal of Molecular Sciences

Article Title: Assessing How Residual Errors of Scoring Functions Correlate to Ligand Structural Features

doi: 10.3390/ijms232315018

Figure Lengend Snippet: Statistical characteristics of linear correlation of the predicted pK SF values with the reference pK values.

Article Snippet: NNScore 2.0 averages the prediction of an ensemble of 20 pre-trained neural networks that make their predictions based on AutoDock Vina term values (3) and BINANA descriptors [ ].

Techniques:

Difference between AutoDock Vina and AutoDock VinaXB estimated pK  values  for complexes with non-zero contribution of the halogen bonding (according to AutoDock VinaXB).

Journal: International Journal of Molecular Sciences

Article Title: Assessing How Residual Errors of Scoring Functions Correlate to Ligand Structural Features

doi: 10.3390/ijms232315018

Figure Lengend Snippet: Difference between AutoDock Vina and AutoDock VinaXB estimated pK values for complexes with non-zero contribution of the halogen bonding (according to AutoDock VinaXB).

Article Snippet: NNScore 2.0 averages the prediction of an ensemble of 20 pre-trained neural networks that make their predictions based on AutoDock Vina term values (3) and BINANA descriptors [ ].

Techniques:

The selected scoring functions.

Journal: International Journal of Molecular Sciences

Article Title: Assessing How Residual Errors of Scoring Functions Correlate to Ligand Structural Features

doi: 10.3390/ijms232315018

Figure Lengend Snippet: The selected scoring functions.

Article Snippet: NNScore 2.0 averages the prediction of an ensemble of 20 pre-trained neural networks that make their predictions based on AutoDock Vina term values (3) and BINANA descriptors [ ].

Techniques: