Investigating the effects of different force fields on spring-based normal mode analysis

<p>Classical normal mode analysis (CNMA) has been widely acknowledged as one of the most useful simulation tools for studying protein dynamics. CNMA uses a fine-grained all-atom model of proteins and a complex empirical potential. In addition, CNMA requires a structure that must be energetically minimized, which makes the method cumbersome to use, especially for large proteins. In contrast, elastic network models (ENM) use coarse-grained protein models and adopt a simplified potential function. ENM is much faster than CNMA but is less accurate. To take the advantages of both CNMA and ENM, the spring-based normal mode analysis (sbNMA) was developed. It uses a fine-grained all-atom model for proteins and an all-atom empirical force field to maintain accuracy while reducing the computing complexity by eliminating the minimization step. In the previous work on sbNMA, only the CHARMM force field was explored. In this work, we extend the analyses to AMBER, another widely-used force field. We investigate the dependence of sbNMA's performance on force fields. This work provides also insightful understandings of the differences between CHARMM and AMBER.</p>

Name thesis:degree_name

Master of Science

Level thesis:degree_level

thesis

Discipline thesis:degree_discipline

Computer Science

Department dc:contributor.department

Department of Computer Science

Year dc:date.issued

2016

Author dc:creator

• Song, Jaekyun

Advisor dc:contributor.advisor

• Guang Song

Language dc:language.iso

en

DOI

https://doi.org/10.31274/etd-180810-5440

Identifier

archive/lib.dr.iastate.edu/etd/15812/

OAI identifier oai:identifier

oai:dr.lib.iastate.edu:20.500.12876/29995