Identification of protein–protein interaction bridges for multiple sclerosis

Author:

Yazıcı Gözde1ORCID,Kurt Vatandaslar Burcu23,Aydin Canturk Ilknur4,Aydinli Fatmagul I25,Arici Duz Ozge6,Karakoc Emre7,Kerman Bilal E28ORCID,Alkan Can1ORCID

Affiliation:

1. Department of Computer Engineering, Bilkent University , Ankara, Turkey

2. Research Institute for Health Sciences and Technologies (SABITA), Istanbul Medipol University , Istanbul, Turkey

3. Graduate School of Health Sciences, Department of Neuroscience, Istanbul Medipol University , Istanbul, Turkey

4. Goztepe Prof. Dr. Suleyman Yalcin City Hospital , Istanbul, Turkey

5. Department of Medical Biology, School of Medicine, Nisantasi University , Istanbul, Turkey

6. Faculty of Medicine, Department of Neurology, Istanbul Medipol University , Istanbul, Turkey

7. Wellcome Sanger Institute , Hinxton, United Kingdom

8. Department of Medicine, Keck School of Medicine, University of Southern California , Los Angeles, California, United States

Abstract

Abstract Motivation Identifying and prioritizing disease-related proteins is an important scientific problem to develop proper treatments. Network science has become an important discipline to prioritize such proteins. Multiple sclerosis, an autoimmune disease for which there is still no cure, is characterized by a damaging process called demyelination. Demyelination is the destruction of myelin, a structure facilitating fast transmission of neuron impulses, and oligodendrocytes, the cells producing myelin, by immune cells. Identifying the proteins that have special features on the network formed by the proteins of oligodendrocyte and immune cells can reveal useful information about the disease. Results We investigated the most significant protein pairs that we define as bridges among the proteins providing the interaction between the two cells in demyelination, in the networks formed by the oligodendrocyte and each type of two immune cells (i.e. macrophage and T-cell) using network analysis techniques and integer programming. The reason, we investigated these specialized hubs was that a problem related to these proteins might impose a bigger damage in the system. We showed that 61%–100% of the proteins our model detected, depending on parameterization, have already been associated with multiple sclerosis. We further observed the mRNA expression levels of several proteins we prioritized significantly decreased in human peripheral blood mononuclear cells of multiple sclerosis patients. We therefore present a model, BriFin, which can be used for analyzing processes where interactions of two cell types play an important role. Availability and implementation BriFin is available at https://github.com/BilkentCompGen/brifin.

Funder

Scientific and Technological Research Council of Turkey

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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