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- W4387563617 abstract "Developments in the field of computational structural biology and with increasing computing speeds have encouraged researchers in studying large compound libraries during the virtual screening. After performing molecular docking, the consideration of vina score in filtering the compounds without collecting the hydrogen bond or hydrophobic interaction between protein and ligand complex leads to missing multiple good lead molecules. The tools used for virtual screening in drug design and discovery studies were previously designed and developed for small datasets. LigPlots were used to generate 2-dimensional (2D) interaction maps of protein-ligand complexes. These maps depict diverse bonds like hydrogen and hydrophobic interactions in varied colors for all ligand conformations within the library. However, handling large numbers of protein-ligand complexes can make this process quite laborious. The development of a tool is strongly required or an implementation of automation to generate all the interaction details has a strong demand. This paper describes an implementation of an automation technique on the executable programs like ligplot.exe, hbplus.exe and hbadd.exe to obtain the 2D interaction map (LigPlots) of the protein and ligand complex (*.ps) and hydrogen bonds and hydrophobic interactions in *.csv format for molecules to be considered for virtual screening by using some sorting & searching algorithms and python's file handling functions, and it also mentions the program's limitations and availability of the program. The program can be found on github.Communicated by Ramaswamy H. Sarma." @default.
- W4387563617 created "2023-10-13" @default.
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- W4387563617 date "2023-10-11" @default.
- W4387563617 modified "2023-10-13" @default.
- W4387563617 title "VinaLigGen: a method to generate LigPlots and retrieval of hydrogen and hydrophobic interactions from protein-ligand complexes" @default.
- W4387563617 cites W2009831225 @default.
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- W4387563617 doi "https://doi.org/10.1080/07391102.2023.2266524" @default.
- W4387563617 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37822199" @default.
- W4387563617 hasPublicationYear "2023" @default.
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