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Targeting Neuroblastoma Cell Surface Proteins: Recommendations for Homology Modeling of hNET, ALK, and TrkB

Targeted therapy is a promising approach for treatment of neuroblastoma as evident from the large number of targeting agents employed in clinical practice today. In the absence of known crystal structures, researchers rely on homology modeling to construct template-based theoretical structures for d...

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Autores principales: Haddad, Yazan, Heger, Zbyněk, Adam, Vojtech
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5247432/
https://www.ncbi.nlm.nih.gov/pubmed/28163672
http://dx.doi.org/10.3389/fnmol.2017.00007
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author Haddad, Yazan
Heger, Zbyněk
Adam, Vojtech
author_facet Haddad, Yazan
Heger, Zbyněk
Adam, Vojtech
author_sort Haddad, Yazan
collection PubMed
description Targeted therapy is a promising approach for treatment of neuroblastoma as evident from the large number of targeting agents employed in clinical practice today. In the absence of known crystal structures, researchers rely on homology modeling to construct template-based theoretical structures for drug design and testing. Here, we discuss three candidate cell surface proteins that are suitable for homology modeling: human norepinephrine transporter (hNET), anaplastic lymphoma kinase (ALK), and neurotrophic tyrosine kinase receptor 2 (NTRK2 or TrkB). When choosing templates, both sequence identity and structure quality are important for homology modeling and pose the first of many challenges in the modeling process. Homology modeling of hNET can be improved using template models of dopamine and serotonin transporters instead of the leucine transporter (LeuT). The extracellular domains of ALK and TrkB are yet to be exploited by homology modeling. There are several idiosyncrasies that require direct attention throughout the process of model construction, evaluation and refinement. Shifts/gaps in the alignment between the template and target, backbone outliers and side-chain rotamer outliers are among the main sources of physical errors in the structures. Low-conserved regions can be refined with loop modeling method. Residue hydrophobicity, accessibility to bound metals or glycosylation can aid in model refinement. We recommend resolving these idiosyncrasies as part of “good modeling practice” to obtain highest quality model. Decreasing physical errors in protein structures plays major role in the development of targeting agents and understanding of chemical interactions at the molecular level.
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spelling pubmed-52474322017-02-03 Targeting Neuroblastoma Cell Surface Proteins: Recommendations for Homology Modeling of hNET, ALK, and TrkB Haddad, Yazan Heger, Zbyněk Adam, Vojtech Front Mol Neurosci Neuroscience Targeted therapy is a promising approach for treatment of neuroblastoma as evident from the large number of targeting agents employed in clinical practice today. In the absence of known crystal structures, researchers rely on homology modeling to construct template-based theoretical structures for drug design and testing. Here, we discuss three candidate cell surface proteins that are suitable for homology modeling: human norepinephrine transporter (hNET), anaplastic lymphoma kinase (ALK), and neurotrophic tyrosine kinase receptor 2 (NTRK2 or TrkB). When choosing templates, both sequence identity and structure quality are important for homology modeling and pose the first of many challenges in the modeling process. Homology modeling of hNET can be improved using template models of dopamine and serotonin transporters instead of the leucine transporter (LeuT). The extracellular domains of ALK and TrkB are yet to be exploited by homology modeling. There are several idiosyncrasies that require direct attention throughout the process of model construction, evaluation and refinement. Shifts/gaps in the alignment between the template and target, backbone outliers and side-chain rotamer outliers are among the main sources of physical errors in the structures. Low-conserved regions can be refined with loop modeling method. Residue hydrophobicity, accessibility to bound metals or glycosylation can aid in model refinement. We recommend resolving these idiosyncrasies as part of “good modeling practice” to obtain highest quality model. Decreasing physical errors in protein structures plays major role in the development of targeting agents and understanding of chemical interactions at the molecular level. Frontiers Media S.A. 2017-01-20 /pmc/articles/PMC5247432/ /pubmed/28163672 http://dx.doi.org/10.3389/fnmol.2017.00007 Text en Copyright © 2017 Haddad, Heger and Adam. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution and reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Haddad, Yazan
Heger, Zbyněk
Adam, Vojtech
Targeting Neuroblastoma Cell Surface Proteins: Recommendations for Homology Modeling of hNET, ALK, and TrkB
title Targeting Neuroblastoma Cell Surface Proteins: Recommendations for Homology Modeling of hNET, ALK, and TrkB
title_full Targeting Neuroblastoma Cell Surface Proteins: Recommendations for Homology Modeling of hNET, ALK, and TrkB
title_fullStr Targeting Neuroblastoma Cell Surface Proteins: Recommendations for Homology Modeling of hNET, ALK, and TrkB
title_full_unstemmed Targeting Neuroblastoma Cell Surface Proteins: Recommendations for Homology Modeling of hNET, ALK, and TrkB
title_short Targeting Neuroblastoma Cell Surface Proteins: Recommendations for Homology Modeling of hNET, ALK, and TrkB
title_sort targeting neuroblastoma cell surface proteins: recommendations for homology modeling of hnet, alk, and trkb
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5247432/
https://www.ncbi.nlm.nih.gov/pubmed/28163672
http://dx.doi.org/10.3389/fnmol.2017.00007
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