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<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/"><rdf:Description rdf:about="https://repozitorij.uni-lj.si/IzpisGradiva.php?id=155379"><dc:title>Enhanced molecular docking</dc:title><dc:creator>Rozman,	Kati	(Avtor)
	</dc:creator><dc:creator>Ghysels,	An	(Avtor)
	</dc:creator><dc:creator>Zavalnij,	Bogdan	(Avtor)
	</dc:creator><dc:creator>Kunej,	Tanja	(Avtor)
	</dc:creator><dc:creator>Bren,	Urban	(Avtor)
	</dc:creator><dc:creator>Janežič,	Dušanka	(Avtor)
	</dc:creator><dc:creator>Konc,	Janez	(Avtor)
	</dc:creator><dc:subject>highest weight k-cliques algorithm</dc:subject><dc:subject>weighted graphs</dc:subject><dc:subject>graph coloring</dc:subject><dc:subject>graph theory</dc:subject><dc:subject>molecular docking</dc:subject><dc:subject>ProBiS-Dock algorithm</dc:subject><dc:description>Molecular docking, a key process in drug discovery, is often used in the discovery of new bioactive compounds. In this technique, small molecules are systematically placed at a protein binding site to identify the ligands with the highest binding affinity. Here we have developed a new graph-theoretical algorithm called K-CliqueWeight. This algorithm efficiently identifies the top N highest weight k-cliques in different types of vertex-weighted graphs and can serve as a building block for various algorithms addressing different problems, including molecular docking. K-CliqueWeight and its variant K-CliqueDynWeight are extensions of our established and widely used maximum clique algorithm. Our new algorithm uses a novel approach to approximate graph coloring and provides efficient upper bounds on the size and weight of a k-clique within the branch-and-bound algorithm. It outperforms alternative methods and often shows a speedup of several orders of magnitude. Rigorous tests with general random graphs and those specifically designed for docking confirm its exceptional performance. K-CliqueWeight has been integrated into the existing ProBiS-Dock algorithm for molecular docking. The algorithm is freely available to the academic community at http://insilab.org/kcliqueweight.</dc:description><dc:date>2024</dc:date><dc:date>2024-03-28 10:04:27</dc:date><dc:type>Članek v reviji</dc:type><dc:identifier>155379</dc:identifier><dc:language>sl</dc:language></rdf:Description></rdf:RDF>
