Targeting neuroblastoma cell surface proteins: Recommendations for homology modeling of hNET, ALK, and TrkB

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43210%2F17%3A43911479" target="_blank" >RIV/62156489:43210/17:43911479 - isvavai.cz</a>

Alternative codes found

RIV/00216305:26620/17:PU123080

Result on the web

<a href="https://doi.org/10.3389/fnmol.2017.00007" target="_blank" >https://doi.org/10.3389/fnmol.2017.00007</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3389/fnmol.2017.00007" target="_blank" >10.3389/fnmol.2017.00007</a>

Result language

angličtina

Original language name

Targeting neuroblastoma cell surface proteins: Recommendations for homology modeling of hNET, ALK, and TrkB

Original language 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 &quot;good modeling practice&quot; 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.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

30204 - Oncology

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Frontiers in Molecular Neuroscience

ISSN

1662-5099

e-ISSN

—

Volume of the periodical

10

Issue of the periodical within the volume

20 January

Country of publishing house

CH - SWITZERLAND

Number of pages

7

Pages from-to

—

UT code for WoS article

000392250800001

EID of the result in the Scopus database

2-s2.0-85011003017