Computational Biology

For more information see Dr. Gursoy’s home page.

Computational Biology

For more information see Dr. Keskin’s homepage.

Proteins bind together via their interface. It is important to determine how proteins interact through interfaces to understand protein binding mechanisms and to predict new protein-protein interactions. My study is about the computationally efficient prediction of protein-protein interactions at the structural level on the proteome scale using deep learning approaches.

Ph.D. Koç University-Computer Science & Engineering

M.Sc. Koç University-Computational Science & Engineering

B.Sc. Koç University-Computer Engineering (Double Major)

B.Sc. Koç University-Molecular Biology & Genetics

Investigation of the association between type2 diabetes and human gut microbiota

Ph.D. Student Koç University-Computational Science and Engineering

B.Sc. Hacettepe University-Biology

Proteins bind together via their interface. Some residues on the interface regions, play more important role than other residues in terms of contribution to binding. We call those residues “hotspots”. Considering their roles in binding, hotspots might be very promising drug targets for inhibition of unwanted protein interactions. My aim is to accurately predict hotspot residues by enhancing current detection algorithms.

M.Sc. Student Koç University-Molecular Biology and Genetics

B.Sc. Istanbul Bilgi University-Genetics and Bio-engineering

 Protein Interfaces

M.Sc. Student Koç University-Computer Science & Engineering

B.Sc. Boğaziçi University-Molecular Biology &Genetics

M.Sc. Candidate Koç University-Computational Science and Engineering

B.Sc. Boğaziçi University-Chemistry

M.Sc. Student Koç University-Data Science

B.Sc. Boğaziçi University-Chemistry (Double Major)

B.Sc. Boğaziçi University-Molecular Biology and Genetics

M.Sc. Student Koç University-Data Science

B.Sc. Istanbul Technical University-Mathematical Engineering

Identification and Structural Modelling of the Protein Interactors of A Long Non-coding RNA Involved in Prostate Cancer

Prostate cancer affects 1 in 7 men. A long non-coding RNA acts as an enhancer and influences transcription of the Kallikrein gene family involved in prostate cancer.  My main project aims to identify the protein partners of this lncRNA and structurally model the complex they form.

Side Projects:

• Structural analysis of the oligomerization & interactions of the steroid hormone glucocorticoid receptor
• RNA-Sequencing Analysis of Cryptochrome mutation in a p53 knockout background

B.Sc. Bilkent University-Molecular Biology and Genetics
M.Sc. Bilkent University-Molecular Biology and Genetics
Ph.D. Koç University-Chemical and Biological Engineering

Protein-Protein Interaction Using Statistical and Deterministic Algorithms

Since proteins are pivotal for the most of the crucial activities that are happening in organisms and the proteins, most of the time, do not act alone, studying protein-protein interactions is very important. Predicting which proteins can interact with each other is a very valuable skill on which I am working by using both statistical and deterministic algorithms.

B.Sc. Istanbul Technical University-Computer Engineering
M.Sc. Koç University-Computer Science and Engineering

Molecular Dynamics Simulations and Computational Analysis of KRAS and c-Raf Interaction

Ras  protein is shown to interact with the proteins involved in crucial pathways such as MAPK and PI3K. Our group recently showed that specific mutations on Ras protein interfere with the p-ERK level within the cell. Using molecular dynamics simulation methods and computational analysis, we aim to have a deeper understanding how these mutations affects the interaction .Therefore, I am simulating the interactions of KRAS protein and Ras-Binding-Domain (RBD) of c-Raf protein.

M.Sc. Koç University-Molecular Biology and Genetics

B.Sc. İstanbul Technical University-Molecular Biology and Genetics

Unraveling the Molecular Mechanism of Cdc42 and Rac1 Interactions with IQGAP2

IQGAP2 is a scaffold protein which plays central roles in cell-cell adhesion, polarity and cell motility. Rho GTPases Cdc42 and Rac1, in their GTP-bound active forms, interact with all three human IQGAP isoforms. IQGAP-Cdc42 interaction promotes metastasis by enhancing actin polymerization. However, despite their high degree of sequence identity, Cdc42 and Ra1 intrections with IQGAP show differences. We aim to reveal the interaction mechanisms of these proteins.

Publications
Unraveling the molecular mechanism of interactions of the Rho GTPases Cdc42 and Rac1 with the scaffolding protein IQGAP2. Ozdemir ES, Jang H, Gursoy A, Keskin O, Li Z, Sacks DB, Nussinov R (2018) . The Journal of Biological Chemistry. doi:10.1074/jbc.RA117.001596

 

Relation between Protein Intrinsic Normal Mode Weights and Pre-Existing Conformer Populations. Ozgur B^*, Ozdemir ES^*, Gursoy A, Keskin O (2017) Journal of Physical Chemistry B 121 (15):3686-3700.doi:10.1021/acs.jpcb.6b10401 *These authors contributed equally to the work.

Red emitting, cucurbituril-capped, pH-responsive conjugated oligomer-based nanoparticles for drug delivery and cellular imaging. Pennakalathil J, Jahja E, Ozdemir ES, Konu O, Tuncel D (2014) Biomacromolecules 15 (9):3366-3374. doi:10.1021/bm500839j

B.Sc. Bilkent University-Molecular Biology and Genetics

M.Sc. Bilkent University-Molecular Biology and Genetics

Ph.D. Koç University-Chemical and Biological Engineering

Computational and experimental investigation of RAS homodimer and RAS-effector interactions

Ras proteins recruit and activate effectors, including Raf, that transmit receptor-initiated signals and regulates gene expression. Ras is believed to function as a monomer; however, since Raf dimerizes, it was suspected that Ras may also dimerize. Here we show that GTP-bound K-Ras4B forms stable homodimers using two interfaces.  We aim to confirm RAS dimerization in vivo and understand the effect of

 

Ph.D. Koç University-Chemical and Biological Engineering

B.Sc. Istanbul Technical University-Chemistry and Molecular Biology & Genetics

Critical Assessment of PRediction of Interactions with PRISM

Capri is community wide experiment to test protein-protein docking methods in blind predictions based on three-dimensional structures. Targets are selected from experimentally known but unpublished complex structures. Predictors can use any of the information in literature about the components for prediction.

B.Sc. Koç University-Molecular Biology and Genetics

M.Sc. Koç University-Biomedical Science and Engineering

Mutation Mapping on Protein-Protein Interaction Networks

Diseases are commonly the result of dysregulated complex interactions involving large sets of genes and proteins as products of these genes, and their cooperation with other cellular components. Interpreting protein-protein interactions at both network and molecular interaction levels with mutation knowledge requires a comprehensive research process that is fed from different sources. In this project, we developed a web-based tool, Gene2Phen, by integrating large-scale protein-protein interaction network, 3D protein structure information and interface mutation knowledge to aid researchers in exploring and comparing the molecular mechanism of different phenotypes. Gene2Phen works as an automatized pipeline tool to build, visualize and compare phenotype specific subnetworks, to examine protein- protein interactions associated with their structure and mutation data. Gene2Phen web tool prioritizes the human protein-protein network based on seed genes specific to a phenotype. From the prioritized-PPI network, users can generate a phenotype specific subnetwork. The phenotype-specific subnetworks can be visualized and compared interactively. Genome annotations and topological properties of each protein are shown in this interactive network representation. A unique feature of Gene2Phen is its ability to display 3D structural models of protein-protein interactions and their predicted protein-protein interfaces. Users can see the list of mutations which are mapped on predicted protein-protein interfaces. This allows users to study mutations altering protein-protein interfaces and their role in the phenotype-specific subnetworks. Gene2Phen, by automating the integration of protein-protein networks, protein structure, and disease – related mutations at large scale, will not only boost the productivity and efficiency, but it may be the leveraging step to the novel solutions/studies. 

M.Sc. Koç University-Biomedical Science and Engineering

B.Sc. Bilkent University-Computer Engineering

Physical interactions between proteins are mapped into a network called protein-protein interaction network (PPIN)  where nodes represent proteins and edges represent pairwise interactions between proteins in the network. Analysis of PPINs is important and essential to understanding biological functions and processes.  However, PPINs do not indicate structural and chemical features of interactions, therefore structural PPINs (SPPIN) should be constructed and analyzed in order to give better results and understanding of the problem. My research will focus on the analysis of SPPINs.

M.Sc. Koç University – Computer Science and Engineering

B.Sc. The University of Jordan – Electrical Engineering

Updating Non-redundant Unique Interface Structures as Templates for Modeling Protein Interactions

Classification of structures of protein-protein interactions may provide valuable insights for modeling and abstracting design principles. We aim to cluster protein-protein interactions by their interface structures, and to exploit these clusters to obtain and study shared and distinct protein binding sites and expand previously created interface datasets. The novelty in this work is in generating structurally non-redundant protein-protein interfaces which are sensitive to small perturbations in protein binding sites that have a significant impact in template-based docking.

M.Sc. Koç University-Molecular Biology and Genetics

B.Sc. Üsküdar University-Computer Engineering (Double Major)

B.Sc. Üsküdar University-Molecular Biology and Genetics

Efficient Algorithms for Enriching Traditional Protein-protein Interaction Networks with Proteins Alternative Conformations

The common practice in structural PPI networks is to consider just one specific conformation for each protein. Yet it is not a comprehensive representation as it neglects the conformational changes of proteins which may lead to different protein interactions, functions, and downstream signaling. We propose a new representation for structural PPI networks which inspects the different conformations of proteins.

Publications
Enriching Traditional Protein-protein Interaction Networks with Alternative Conformations of Proteins. Halakou F, Kilic ES, Cukuroglu E, Keskin O, Gursoy A.  Sci Rep. 2017 Aug 3;7(1):7180.

Topological, functional, and structural analyses of protein-protein interaction networks of breast cancer lung and brain metastases, Halakou F, Gursoy A., Kilic E. S. and Keskin O. 2017 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), Manchester, 2017, pp. 1-7.
doi: 10.1109/CIBCB.2017.8058539 ​

B.Sc. Mirdamad Institute of Higher Education-Computer Engineering

M.Sc. Kerman Graduate University of Technology-Information Technology Engineering