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Targeting Neuroblastoma Cell Surface Proteins: Recommendations for Homology Modeling of hNET, ALK, and TrkB
Y. Haddad, Z. Heger, V. Adam
Jazyk angličtina Země Švýcarsko
Typ dokumentu časopisecké články
Grantová podpora
NV15-28334A
MZ0
CEP - Centrální evidence projektů
Digitální knihovna NLK
Plný text - Článek
NLK
Directory of Open Access Journals
od 2008
Free Medical Journals
od 2008
PubMed Central
od 2008
Europe PubMed Central
od 2008
ProQuest Central
od 2008-03-28
Open Access Digital Library
od 2008-01-01
Open Access Digital Library
od 2008-01-01
ROAD: Directory of Open Access Scholarly Resources
od 2008
PubMed
28163672
DOI
10.3389/fnmol.2017.00007
Knihovny.cz E-zdroje
- Publikační typ
- časopisecké články MeSH
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.
Central European Institute of Technology Brno University of TechnologyBrno Czechia
Department of Chemistry and Biochemistry Mendel University in BrnoBrno Czechia
Citace poskytuje Crossref.org
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