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Computational analysis of EBNA1 “druggability” suggests novel insights for Epstein-Barr virus inhibitor design

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Abstract

The Epstein-Barr Nuclear Antigen 1 (EBNA1) is a critical protein encoded by the Epstein-Barr Virus (EBV). During latent infection, EBNA1 is essential for DNA replication and transcription initiation of viral and cellular genes and is necessary to immortalize primary B-lymphocytes. Nonetheless, the concept of EBNA1 as drug target is novel. Two EBNA1 crystal structures are publicly available and the first small-molecule EBNA1 inhibitors were recently discovered. However, no systematic studies have been reported on the structural details of EBNA1 “druggable” binding sites. We conducted computational identification and structural characterization of EBNA1 binding pockets, likely to accommodate ligand molecules (i.e. “druggable” binding sites). Then, we validated our predictions by docking against a set of compounds previously tested in vitro for EBNA1 inhibition (PubChem AID-2381). Finally, we supported assessments of pocket druggability by performing induced fit docking and molecular dynamics simulations paired with binding affinity predictions by Molecular Mechanics Generalized Born Surface Area calculations for a number of hits belonging to druggable binding sites. Our results establish EBNA1 as a target for drug discovery, and provide the computational evidence that active AID-2381 hits disrupt EBNA1:DNA binding upon interacting at individual sites. Lastly, structural properties of top scoring hits are proposed to support the rational design of the next generation of EBNA1 inhibitors.

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Abbreviations

CD:

Core domain

EBNA1:

Epstein-Barr nuclear antigen 1

EBV:

Epstein Barr virus

EC:

Extended chain

FBDD:

Fragment-based drug design

FD:

Flanking domain

FP:

Fluorescence polarization

HTS:

High-throughput screening

MLS:

Minimum ligand scaffold

PR:

Proline rich

SBDD:

Structure-based drug design

vHTS:

Virtual high-throughput screening

VS:

Virtual screening

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Acknowledgments

EG and RZ gratefully acknowledge The Wistar Institute (www.wistar.org) for providing funding in partial support of this work. Also, EG and RZ thank Dr. Elia Eschenazi, Dr. Preston B. Moore and Dr. Vojislava Pophristic at the University of the Sciences, Philadelphia for useful discussions. TEM and PML acknowledge support from the Wellcome Trust Seeding Drug Discovery program (096496/Z/11/Z). TEM acknowledges supports from American Cancer Society (ACS-IRG-96-153-10).

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Correspondence to Eleonora Gianti.

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10822_2016_9899_MOESM1_ESM.zip

Supporting Information SI-1: Comparison of apo versus DNA-bound EBNA1 Structures and Figure S1; SI-2 Site Identified by SiteMap and Table S1; SI-3: Molecular Probes used in Binding Sites Identification and Table S2; SI-4 Primary Site or DNA Binding Site and Figure S2; SI-5 Re-docking (3’-TGC-5’)113 against the Primary Site and Figure S3; SI-6 Secondary Site or Recognition Helix Site and Figure S4; SI-7 Simulation Quality Plots: Top AID Hits in Primary Site; SI-8 Simulation Quality Plots: Top AID Hits in Secondary Site; SI-9 Simulation Quality Plots: Fragment substructures in Secondary Site; SI-10 Hydrogen bond networks upon MD simulations of Primary Site hits; SI-11 Hydrogen bond networks upon MD simulations of Secondary Site hits; SI-12 Binding modes and interaction diagrams obtained by induced fit docking of hits against the Secondary Site. IFD scores are listed in Table 2; SI-13 Fragment substructures against the Secondary Site; SI-14 Ligand Efficiency; SI-15 MM-GBSA of Primary Site Hits; SI-16 and SI-17 Attribution of hit 3196499; SI-18 MM-GBSA of Secondary Site Hits. (ZIP 14440 kb)

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Gianti, E., Messick, T.E., Lieberman, P.M. et al. Computational analysis of EBNA1 “druggability” suggests novel insights for Epstein-Barr virus inhibitor design. J Comput Aided Mol Des 30, 285–303 (2016). https://doi.org/10.1007/s10822-016-9899-y

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