Computational Modeling of RNA Binding Domains of Nucleolin and MicroRNA to Elucidate Interaction Mechanisms and Functional Implications

Name: 

Avdar Temmuz San

Department:

Biochemistry

Project Title:

Computational Modeling of RNA Binding Domains of Nucleolin and MicroRNA to Elucidate Interaction Mechanisms and Functional Implications

Avdar studied Biotechnology at New York University, where he realized the value of understanding biological phenomena in-depth to develop medical devices and design drugs to save human lives. As a result, he decided to study Biochemistry at the Graduate Center to develop the skills that could allow him to understand molecular interactions between proteins and nucleic acids in cancer biology. After receiving training in wet lab skills to investigate protein function at a molecular level, he joined Dr. Singh’s bioinformatics lab at Brooklyn College to study protein modeling. After completing his PhD, he aims to pursue endeavors that extend his passion for drug development/design. He is an avid listener-of-music and a coffee enthusiast.

Project

RNA binding proteins (RBPs) have become the frontline in cancer research. Nucleolin (NCL) is an RBP and has four RNA binding domains (RBDs) that associate with different types of RNA species (non-coding and coding) to alter gene expression in tumorigenesis. In this study, I focus on utilizing computational tools to elaborate NCL-RNA interactions at the molecular level. I predicted several models in which the type of NCL RBD dictates preferential association with specific miRNA that have cited roles in breast carcinoma. Using structural databases available for NCL-RBDs and other RBPs, we corroborated the RNA-binding preferences in NCL. The available miRNA structural information was applied to deduce specific NCL amino acid residues that have the potential to drive NCL-miRNA interactions. Future work will validate that these RNA interacting residues are essential for NCL binding to specific RNA species in an experimental setting. This study of protein-RNA interactions is part of our long-term goal to study global RBP-RNA interactions using in silico approaches that can be translated into the functional drug design studies.

Bioinformatics holds immense value in translating structural data from the literature into meaningful predictions that can be utilized in cancer research. As a Biochemistry PhD candidate, I am currently pursing my thesis research in Dr. Shaneen Singh’s bioinformatics lab. My research goals are to investigate the structural and biochemical basis of Protein-RNA interactions using in silico approaches and nucleolin as a model protein. NCL, like many other RNA binding proteins, has elaborate roles in changing gene expression during many diseases, including Alzheimer’s, Parkinson’s, and a variety of cancers. Studying breast cancer progression from an in-silico perspective extends my previous wet lab experience in cancer biology and allows for looking at this scientific question from a different perspective. I predicted protein-RNA interaction motifs, validated them using several different approaches, and identified key residues in specific NCL RNA-binding domains that drive the interactions with these RNA species. I presented the scientific outcomes at various local and international meetings:

1) American Association of Cancer Research (AACR) 2019 Annual Meeting Mar 29-Apr3, 2019 in Atlanta, GA

2) Brooklyn College Science Day, May 3, 2019, NY

3) New York Structural Biology Discussion Group Summer 2019 Meeting, The Roy and Diana Vagelos Education Center at Columbia Medical School, August 1, 2019, NY

These networking opportunities are valuable to me as I develop my understanding of the broader spectrum of protein-RNA interactions in various diseases. After receiving feedback from my peers during poster presentations at these events, we verified the robustness of our preliminary findings by utilizing multiple new methods. Based on statistical data obtained from computational analysis, residues most likely to drive these interactions were narrowed down to a list of most probable residues that we predict to drive NCL-microRNA interactions. Using this information, we are designing experiments in collaboration with Dr Anjana Saxena (Brooklyn College). Based on the aforementioned analysis, we have identified specific residues to mutate that should impair the miRNA binding activities of NCL. These experiments can help us identify the miRNA binding mechanism of NCL and ultimately help in targeting NCL for drug design. NCL is a multifaceted protein with many enigmatic roles in numerous physiological as well as disease conditions. These bioinformatical approaches are valuable assets in teasing apart the domain and site-specific roles of NCL. This structural-functional-experimental approach has the potential to promote broader interests in future drug design.

I am grateful for the Provost’s Pre-Dissertation Research Fellowship in the sciences, which has generously provided this opportunity for me to design and develop an interdisciplinary biochemistry project. In future studies, I plan to extend this work to investigate NCL-mRNA interactions in breast cancer progression by using the same methodology.