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

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2016-01-01
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Song, Jaekyun
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Guang Song
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Altmetrics
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Computer Science

Computer Science—the theory, representation, processing, communication and use of information—is fundamentally transforming every aspect of human endeavor. The Department of Computer Science at Iowa State University advances computational and information sciences through; 1. educational and research programs within and beyond the university; 2. active engagement to help define national and international research, and 3. educational agendas, and sustained commitment to graduating leaders for academia, industry and government.

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The Computer Science Department was officially established in 1969, with Robert Stewart serving as the founding Department Chair. Faculty were composed of joint appointments with Mathematics, Statistics, and Electrical Engineering. In 1969, the building which now houses the Computer Science department, then simply called the Computer Science building, was completed. Later it was named Atanasoff Hall. Throughout the 1980s to present, the department expanded and developed its teaching and research agendas to cover many areas of computing.

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1969-present

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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.

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Fri Jan 01 00:00:00 UTC 2016