1st International and 10th National Iranian Conference on Bioinformatics

Protein structure assessment using knowledge-based statistical potential function based on Ramachandran plots

Paper ID : 1427-ICB10

Authors:

Maryam Hojati *, Seyed Shahriar Arab

Tarbiat Modares University

Abstract:

Protein structural data is of prime importance for researchers in various biological fields, and the accuracy of the data can impact the significance of analysis results. However, native protein structures are not always available, so predicted protein models are widely used in many cases. Generally, in predicting protein structures, knowledge-based scoring methods based on statistical potential are used to select the most stable and native-like structure from the predicted models. For instance, the Modeller simulation tool uses "dope-score" to rank protein structures.[1] According to a study by Anfinsen et al., the native structures have the least amount of free energy in a set of simulated models.[2] Methods based on statistical potential do not have the certainty and accuracy for calculating molecular mechanics force field; in contrast, statistical potential functions are computationally possible. For example, out of 55 decoy sets created by QUARK and I-TASSER algorithms for CASP11 targets,[3], [4] dope-score allocates only 15 minimum energy to native structures. Therefore, the need for research to achieve better evaluation criteria remains essential.
This project intends to design a new knowledge-based scoring function based on PDB database information. Ramachandran diagrams are created for amino acid windows with 2 to 7 residues. The probability of any angle occurring in each window using statistical potential and the Boltzmann function is converted into energy. The protein with the least energy is considered as the best model. Our method could successfully rank more native protein structures as the top 5% among all modeled proteins in CASP11 than dope-score function.

Keywords:

Validation of structure, protein structure, Ramachandran, statistical potential, protein quality

Status : Paper Accepted (Poster Presentation)