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Efficient screening of protein-ligand complexes in lipid bilayers using LoCoMock score

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Abstract

Membrane proteins are attractive targets for drug discovery due to their crucial roles in various biological processes. Studying the binding poses of amphipathic molecules to membrane proteins is essential for understanding the functions of membrane proteins and docking simulations can facilitate the screening of protein–ligand complexes at low computational costs. However, identifying docking poses for a ligand in non-aqueous environments such as lipid bilayers can be challenging. To address this issue, we propose a new docking score called logP-corrected membrane docking (LoCoMock) score. To screen putative protein–ligand complexes embedded in a membrane, the LoCoMock score considers the affinity between a target ligand and the membrane. It combines the docking score of the protein–ligand complex with the logP of the target ligand. In demonstrations using several model ligands, the LoCoMock score screened more putative complexes than the conventional docking score. As extended docking, the LoCoMock score makes it possible to screen membrane proteins more effectively as drug targets than the conventional docking.

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Data and software availability

Structural data of proteins used in all the demonstrations are available from the OPM database. An implementation of the LoCoMock score on Jupyter notebook in Python can be downloaded from GitHub (https://github.com/riquri/LoCoMock).

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Acknowledgements

RH acknowledges the support from the Japan Society for the Promotion of Science (JSPS) KAKENHI under Grant Number JP21K06094 and the grant for basic science research projects of the Sumitomo foundation, Japan. This research was partially supported by the Initiative on the Promotion of Supercomputing for Young or Women Researchers, Information Technology Center, University of Tokyo. This study used the computational resources of Cygnus provided by the Multidisciplinary Cooperative Research Program at the Center for Computational Sciences (Project Code: LSC and MOLBIO), University of Tsukuba.

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Authors and Affiliations

  1. Center for Computational Sciences, University of Tsukuba, 1-1-1 Tennodai, 305-8577, Tsukuba, Ibaraki, Japan

    Rikuri Morita, Yasuteru Shigeta & Ryuhei Harada

Authors
  1. Rikuri Morita
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  2. Yasuteru Shigeta
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  3. Ryuhei Harada
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Contributions

Conceptualization: RM; Data curation: RM; Formal Analysis: RM; Funding acquisition: YS, RH; Investigation: RM; Methodology: RM, YS, RH; Project administration: RM; Resources: RM, YS, RH; Software: RM; Supervision: YS, RH; Validation: RM, RH; Visualization: RM; Writing – original draft: RM; Writing – review & editing: YS, RH.

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Correspondence to Rikuri Morita or Ryuhei Harada.

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Morita, R., Shigeta, Y. & Harada, R. Efficient screening of protein-ligand complexes in lipid bilayers using LoCoMock score. J Comput Aided Mol Des 37, 217–225 (2023). https://doi.org/10.1007/s10822-023-00502-8

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  • DOI: https://doi.org/10.1007/s10822-023-00502-8

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