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vina term values  (AUTODOCK GmbH)

 
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    Structured Review

    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
    https://www.bioz.com/product/vina+term+values/vina+term+values/pmc09739603-415-19-19
    Average 90 stars, based on 1 article reviews
    vina term values - by Bioz Stars, 2026-11
    90/100 stars

    Images

    1) Product Images from "Assessing How Residual Errors of Scoring Functions Correlate to Ligand Structural Features"

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

    Journal: International Journal of Molecular Sciences

    doi: 10.3390/ijms232315018

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

    Techniques Used:

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

    Techniques Used:

    The selected scoring functions.
    Figure Legend Snippet: The selected scoring functions.

    Techniques Used:

    Related Articles

    other:

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



    Similar Products

    vina term values  (AUTODOCK GmbH)
    90
    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
    https://www.bioz.com/product/vina+term+values/vina+term+values/pmc09739603-415-19-19
    Average 90 stars, based on 1 article reviews
    vina term values - by Bioz Stars, 2026-11
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    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: