CavDetect: A DBSCAN Algorithm based Novel Cavity Detection Model on Protein Structure

Autor:	Adhikari, Swati, Roy, Parthajit
Rok vydání:	2024
Předmět:	Computer Science - Machine Learning Quantitative Biology - Biomolecules Quantitative Biology - Quantitative Methods 92-xx (Primary) 92-04
Druh dokumentu:	Working Paper
Popis:	Cavities on the structures of proteins are formed due to interaction between proteins and some small molecules, known as ligands. These are basically the locations where ligands bind with proteins. Actual detection of such locations is all-important to succeed in the entire drug design process. This study proposes a Voronoi Tessellation based novel cavity detection model that is used to detect cavities on the structure of proteins. As the atom space of protein structure is dense and of large volumes and the DBSCAN (Density Based Spatial Clustering of Applications with Noise) algorithm can handle such type of data very well as well as it is not mandatory to have knowledge about the numbers of clusters (cavities) in data as priori in this algorithm, this study proposes to implement the proposed algorithm with the DBSCAN algorithm. Comment: 14 pages, 9 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2407.18317 Zobrazit plný text záznamu View this record from Arxiv