Predicting the Specificity- Determining Positions of Receptor Tyrosine Kinase Axl

Tülay Karakulak; Ahmet Sureyya Rifaioglu; João P G L M Rodrigues; Ezgi Karaca

doi:10.3389/fmolb.2021.658906

Predicting the Specificity- Determining Positions of Receptor Tyrosine Kinase Axl

Front Mol Biosci. 2021 Jun 14:8:658906. doi: 10.3389/fmolb.2021.658906. eCollection 2021.

Authors

Tülay Karakulak^{1

2

3

4

5}, Ahmet Sureyya Rifaioglu⁶, João P G L M Rodrigues⁷, Ezgi Karaca^{1

2}

Affiliations

¹ Izmir Biomedicine and Genome Center, Izmir, Turkey.
² Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir, Turkey.
³ Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.
⁴ Department of Pathology and Molecular Pathology, University Hospital Zurich, Zurich, Switzerland.
⁵ Swiss Institute of Bioinformatics, Lausanne, Switzerland.
⁶ Department of Electrical - Electronics Engineering, İskenderun Technical University, Hatay, Turkey.
⁷ Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, United States.

Abstract

Owing to its clinical significance, modulation of functionally relevant amino acids in protein-protein complexes has attracted a great deal of attention. To this end, many approaches have been proposed to predict the partner-selecting amino acid positions in evolutionarily close complexes. These approaches can be grouped into sequence-based machine learning and structure-based energy-driven methods. In this work, we assessed these methods' ability to map the specificity-determining positions of Axl, a receptor tyrosine kinase involved in cancer progression and immune system diseases. For sequence-based predictions, we used SDPpred, Multi-RELIEF, and Sequence Harmony. For structure-based predictions, we utilized HADDOCK refinement and molecular dynamics simulations. As a result, we observed that (i) sequence-based methods overpredict partner-selecting residues of Axl and that (ii) combining Multi-RELIEF with HADDOCK-based predictions provides the key Axl residues, covered by the extensive molecular dynamics simulations. Expanding on these results, we propose that a sequence-structure-based approach is necessary to determine specificity-determining positions of Axl, which can guide the development of therapeutic molecules to combat Axl misregulation.

Keywords: Axl; HADDOCK; molecular dynamics; protein selectivity; sequence analysis.