<?xml version='1.0' encoding='utf-8'?> <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"> <dc:creator>Hozzova, Jana</dc:creator> <dc:creator>Krenek, Ales</dc:creator> <dc:creator>Simkova, Maria</dc:creator> <dc:creator>Spiwok, Vojtech</dc:creator> <dc:date>2019-05-17</dc:date> <dc:description>Biomolecular simulations are computationally expensive. This limits their application in protein folding simulations, protein engineering, drug design and related fields. Enhanced sampling techniques such as metadynamics accelerates slow events in molecular simulation. This and other method apply artificial forces in directions of collective degrees of freedom (aka collective variables). Path collective variables and Property Map collective variables are defined using a series of reference structures of the studied molecular system. They require a huge number of mean square deviation calculations along the simulation. Close Structure algorithm reduces the number of these operations.</dc:description> <dc:identifier>https://archive.materialscloud.org/record/2019.0021/v1</dc:identifier> <dc:identifier>doi:10.24435/materialscloud:2019.0021/v1</dc:identifier> <dc:identifier>mcid:2019.0021/v1</dc:identifier> <dc:identifier>oai:materialscloud.org:132</dc:identifier> <dc:language>en</dc:language> <dc:publisher>Materials Cloud</dc:publisher> <dc:rights>info:eu-repo/semantics/openAccess</dc:rights> <dc:rights>Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights> <dc:subject>metadynamics</dc:subject> <dc:subject>collective variable</dc:subject> <dc:subject>mean square deviation</dc:subject> <dc:title>Reducing the Number of Mean-Square Deviation Calculations with Floating Close Structure in Metadynamics</dc:title> <dc:type>Dataset</dc:type> </oai_dc:dc>