Date of Award


Publication Type

Master Thesis

Degree Name



Computer Science

First Advisor

Asish Mukhopadhyay


Alpha Carbon Trace Problem, Molecular Distance Geometry Problem



Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.


To structural researchers, predicting protein structures currently remains a challenging task. During the past decades, different methodologies have been developed to address this issue. One such protein structure prediction problem is the Alpha Carbon Trace Problem. The Alpha Carbon trace problem is to determine the 3-D coordinates of the main chain atoms(C, N, and O) from just the CA carbon coordinates. This master's thesis presents a novel approach for solving the CA trace problem by using a molecular distance geometry approach. The current approach uses the algorithms which are used to solve the Molecular Distance Geometry Problem to nd the coordinates of the atoms in the peptide plane of a given protein. Once, the coordinates of the atoms(CA, C, N, and O) in the single peptide plane are computed, the two CA atoms are aligned with the first two CA atoms in the CA trace by finding the appropriate rotation and translation. The same rotation and translation are applied to all the other atoms in the peptide plane(C, N, and O). The process is then repeated for the entire trace, and the coordinates of all the atoms in the main chain of the protein are retrieved. In order to predict the side-chain atoms from the main Chain, SCWRL4.0 is used. The output generated by SCWRL4.0 is then subjected to LBFGS energy minimizer using a tool called MESHI. The key advantage of using our approach is that it eliminates the building and searching for a huge protein fragment library. Experiments show that our approach is highly comparable to other approaches such as BBQ, PD2Main, and PULCHRA for solving the CA trace problem.