AUTHOR=Haddad Yazan , Heger Zbyněk , Adam Vojtech 

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

JOURNAL=Frontiers in Molecular Neuroscience

VOLUME=Volume 10 - 2017

YEAR=2017

URL=https://www.frontiersin.org/journals/molecular-neuroscience/articles/10.3389/fnmol.2017.00007

DOI=10.3389/fnmol.2017.00007

ISSN=1662-5099

ABSTRACT=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 have chosen three candidate cell surface proteins that are suitable for homology modeling: norepinephrine transporter (hNET), anaplastic lymphoma kinase (ALK), and neurotrophic tyrosine kinase receptor (TrkB). When choosing templates, both sequence identity and structure quality are important for homology modeling of the targeted protein and pose the first of many challenges in the modeling process. Homology modeling of hNET is improved using template models of dopamine and serotonin transporters instead of the leucine transporter. 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 and faced problems. 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 structural models for protein targets plays major role in development of targeting agents and understanding of chemical interactions at the molecular level.