Title

Investigating Rigidity Properties and Atomic Content of Proteins

Presenter Information

Christian Walling

Document Type

Oral Presentation

Location

SURC 137B

Start Date

21-5-2015

End Date

21-5-2015

Keywords

Proteins, Rigidity, Scripts

Abstract

Proteins are three-dimensional molecules that bend and flex to perform a multitude of functions, ranging from cellular repair, to mediating the immune response, to aiding in neuronal signal propagation. Drugs are designed to regulate protein functions and their interactions, which they do by closely associating with cavities or other structurally important features on a protein’s surface. Because the properties of protein cavities have not been analyzed in a dataset large enough, it is unclear how, or to what extent, the geometric properties and atomic content of a cavity play in facilitating a protein’s interaction with other molecules. Analyzing the rigidity properties and atomic content of protein cavities from a large database would allow development toward a deeper understanding of how proteins interact with other molecules. Preliminary results from a dataset of about 20,000 cavities have already indicated a dominant region for cavity size and the number of rigid clusters within. For our work, we are trying to determine if the molecular content of rigid bodies within cavities can be used to distinguish them from other proteins by using metrics gathered on the size of cavity, the number of atoms in the cavity, and the types of those atoms. To accomplish this, we have created a series of custom BASH scripts to calculate metrics based on information gathered from calculated cavity data and the biological data of the protein.

Faculty Mentor(s)

Filip Jagodzinski

Department/Program

Computer Science

Additional Mentoring Department

Computer Science

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May 21st, 12:20 PM May 21st, 12:40 PM

Investigating Rigidity Properties and Atomic Content of Proteins

SURC 137B

Proteins are three-dimensional molecules that bend and flex to perform a multitude of functions, ranging from cellular repair, to mediating the immune response, to aiding in neuronal signal propagation. Drugs are designed to regulate protein functions and their interactions, which they do by closely associating with cavities or other structurally important features on a protein’s surface. Because the properties of protein cavities have not been analyzed in a dataset large enough, it is unclear how, or to what extent, the geometric properties and atomic content of a cavity play in facilitating a protein’s interaction with other molecules. Analyzing the rigidity properties and atomic content of protein cavities from a large database would allow development toward a deeper understanding of how proteins interact with other molecules. Preliminary results from a dataset of about 20,000 cavities have already indicated a dominant region for cavity size and the number of rigid clusters within. For our work, we are trying to determine if the molecular content of rigid bodies within cavities can be used to distinguish them from other proteins by using metrics gathered on the size of cavity, the number of atoms in the cavity, and the types of those atoms. To accomplish this, we have created a series of custom BASH scripts to calculate metrics based on information gathered from calculated cavity data and the biological data of the protein.