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dc.contributor.authorKurkinen, Sami
dc.contributor.authorNiinivehmas, Sanna
dc.contributor.authorAhinko, Mira
dc.contributor.authorLätti, Sakari
dc.contributor.authorPentikäinen, Olli
dc.contributor.authorPostila, Pekka
dc.identifier.citationKurkinen, S., Niinivehmas, S., Ahinko, M., Lätti, S., Pentikäinen, O., & Postila, P. (2018). Improving Docking Performance Using Negative Image-Based Rescoring. <i>Frontiers in Pharmacology</i>, <i>9</i>(March), Article 260. <a href="" target="_blank"></a>
dc.description.abstractDespite the large computational costs of molecular docking, the default scoring functions are often unable to recognize the active hits from the inactive molecules in large-scale virtual screening experiments. Thus, even though a correct binding pose might be sampled during the docking, the active compound or its biologically relevant pose is not necessarily given high enough score to arouse the attention. Various rescoring and post-processing approaches have emerged for improving the docking performance. Here, it is shown that the very early enrichment (number of actives scored higher than 1% of the highest ranked decoys) can be improved on average 2.5-fold or even 8.7-fold by comparing the docking-based ligand conformers directly against the target protein's cavity shape and electrostatics. The similarity comparison of the conformers is performed without geometry optimization against the negative image of the target protein's ligand-binding cavity using the negative image-based (NIB) screening protocol. The viability of the NIB rescoring or the R-NiB, pioneered in this study, was tested with 11 target proteins using benchmark libraries. By focusing on the shape/electrostatics complementarity of the ligand-receptor association, the R-NiB is able to improve the early enrichment of docking essentially without adding to the computing cost. By implementing consensus scoring, in which the R-NiB and the original docking scoring are weighted for optimal outcome, the early enrichment is improved to a level that facilitates effective drug discovery. Moreover, the use of equal weight from the original docking scoring and the R-NiB scoring improves the yield in most cases.
dc.publisherFrontiers Research Foundation
dc.relation.ispartofseriesFrontiers in Pharmacology
dc.subject.othermolecular docking
dc.subject.otherdocking rescoring
dc.subject.othernegative image-based rescoring (R-NiB)
dc.subject.otherconsensus scoring
dc.titleImproving Docking Performance Using Negative Image-Based Rescoring
dc.contributor.laitosBio- ja ympäristötieteiden laitosfi
dc.contributor.laitosDepartment of Biological and Environmental Scienceen
dc.contributor.oppiaineSolu- ja molekyylibiologiafi
dc.contributor.oppiaineNanoscience Centerfi
dc.contributor.oppiaineCell and Molecular Biologyen
dc.contributor.oppiaineNanoscience Centeren
dc.rights.copyright© the Authors, 2018. This is an open access article distributed under the terms of the Creative Commons License.

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© the Authors, 2018. This is an open access article distributed under the terms of the Creative Commons License.
Except where otherwise noted, this item's license is described as © the Authors, 2018. This is an open access article distributed under the terms of the Creative Commons License.