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Knowledge-based prediction scoring functions

One major reason for the currently not satisfying performance of knowledge-based prediction methods is the obvious deficiency in the currently used empirical scoring functions. As has been demonstrated there are many methods to improve the capabilities of the potentials by calibrating parameters or weightings of the scoring system [149]. This hints to clear deficiencies of the available potentials. As more data become available the database-derived potential can be expected to become more accurate. [Pg.309]

Gohlke H, Hendlich M, Klebe G. Knowledge-based scoring function to predict protein-ligand interactions. J Mol Biol 2000 295 337-56. [Pg.416]

Predicting Binding Modes, Binding Affinities and Hot Spots for Protein-Ligand Complexes Using a Knowledge-Based Scoring Function. [Pg.81]

Pfeffer, P., Gohlke, H. DrugScoreRNA-knowledge-based scoring function to predict RNA-ligand interactions. J. Chem. Inf. Model 2007, 47(5), 1868. [Pg.164]

Table 1 Correlations of binding affinity prediction for seven published knowledge-based scoring functions for the PMF validation sets of 77 protein-ligand complexes (all) which consist of five classes [47] 16 serine protease (Ser), 15 metalloprotease (Met), 18 L-arabinose binding protein (L-ara), 11 endothiapepsin (End), and 17 diverse protein-ligand complexes (Oth)... [Pg.286]

Table 2 The success rates for binding mode prediction and the correlation coefficients (R) for binding affinity prediction with seven knowledge-based scoring functions on Wang et al. s test set of 100 diverse protein-ligand complexes... Table 2 The success rates for binding mode prediction and the correlation coefficients (R) for binding affinity prediction with seven knowledge-based scoring functions on Wang et al. s test set of 100 diverse protein-ligand complexes...
It can be seen from Eq. (18) that the improvement for the potentials Ujj(r) depends only on the difference between the predicted and experimentally observed pair distribution functions instead of any properties related to the reference state. Therefore, the iterative method does not face the reference state problem encountered by traditional mean-force/knowledge-based scoring functions. [Pg.292]

Velec, H.F.G., Gohlke, H., Klebe, G. DrugScoreCSD-knowledge-based scoring function derived from small molecule crystal data with superior recognition rate of near-native ligand poses and better affinity prediction. J. Med. Chem. 2005, 48, 6296-303. [Pg.295]


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See also in sourсe #XX -- [ Pg.200 , Pg.201 ]




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Base function

Function-based

Functional prediction

Knowledge bases

Knowledge-based

Knowledge-based prediction

Knowledge-based scoring functions

Predicting function

Scoring function

Scoring knowledge-based

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