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Int J Mol Sci. 2019 Jun 6;20(11). pii: E2779. doi: 10.3390/ijms20112779.

A Practical Perspective: The Effect of Ligand Conformers on the Negative Image-Based Screening.

Author information

1
Department of Biological and Environmental Science & Nanoscience Center, University of Jyvaskyla, P.O. Box 35, FI-40014 Jyvaskyla, Finland. mira.m.k.ahinko@jyu.fi.
2
Department of Biological and Environmental Science & Nanoscience Center, University of Jyvaskyla, P.O. Box 35, FI-40014 Jyvaskyla, Finland. sami.t.kurkinen@utu.fi.
3
Integrative Physiology and Pharmacy, Institute of Biomedicine, University of Turku, FI-20014 Turku, Finland. sami.t.kurkinen@utu.fi.
4
Department of Biological and Environmental Science & Nanoscience Center, University of Jyvaskyla, P.O. Box 35, FI-40014 Jyvaskyla, Finland. sanna.niinivehmas@utu.fi.
5
Integrative Physiology and Pharmacy, Institute of Biomedicine, University of Turku, FI-20014 Turku, Finland. sanna.niinivehmas@utu.fi.
6
Department of Biological and Environmental Science & Nanoscience Center, University of Jyvaskyla, P.O. Box 35, FI-40014 Jyvaskyla, Finland. olli.pentikainen@utu.fi.
7
Integrative Physiology and Pharmacy, Institute of Biomedicine, University of Turku, FI-20014 Turku, Finland. olli.pentikainen@utu.fi.
8
Aurlide Ltd., FI-21420 Lieto, Finland. olli.pentikainen@utu.fi.
9
Department of Biological and Environmental Science & Nanoscience Center, University of Jyvaskyla, P.O. Box 35, FI-40014 Jyvaskyla, Finland. postila@gmail.com.

Abstract

Negative image-based (NIB) screening is a rigid molecular docking methodology that can also be employed in docking rescoring. During the NIB screening, a negative image is generated based on the target protein's ligand-binding cavity by inverting its shape and electrostatics. The resulting NIB model is a drug-like entity or pseudo-ligand that is compared directly against ligand 3D conformers, as is done with a template compound in the ligand-based screening. This cavity-based rigid docking has been demonstrated to work with genuine drug targets in both benchmark testing and drug candidate/lead discovery. Firstly, the study explores in-depth the applicability of different ligand 3D conformer generation software for acquiring the best NIB screening results using cyclooxygenase-2 (COX-2) as the example system. Secondly, the entire NIB workflow from the protein structure preparation, model build-up, and ligand conformer generation to the similarity comparison is performed for COX-2. Accordingly, hands-on instructions are provided on how to employ the NIB methodology from start to finish, both with the rigid docking and docking rescoring using noncommercial software. The practical aspects of the NIB methodology, especially the effect of ligand conformers, are discussed thoroughly, thus, making the methodology accessible for new users.

KEYWORDS:

cyclooxygenase-2 (COX-2); docking rescoring; molecular docking; negative image-based (NIB) screening; negative image-based rescoring (R-NiB); rigid docking; structure-based drug discovery; virtual screening

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