id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-278456-gsv6dh36	Qureshi, Abid	AVCpred: an integrated web server for prediction and design of antiviral compounds	2016-09-09		.txt	text/plain	3465	211	49	In this study, we have developed quantitative structure–activity relationship (QSAR)‐based models for predicting antiviral compounds (AVCs) against deadly viruses like human immunodeficiency virus (HIV), hepatitis C virus (HCV), hepatitis B virus (HBV), human herpesvirus (HHV) and 26 others using publicly available experimental data from the ChEMBL bioactivity database. We have integrated these models in the AVCpred web server, which will be helpful for virtual screening of AVCs and designing new compounds to target the viruses. The QSAR models have been integrated into a freely available and easy to use web server, 'AVCpred', where users can predict the antiviral potential of their query molecules against the different viruses in terms of percent inhibition value. In this study, we developed virus specific as well as general prediction models to identify the likelihood of a compound being antiviral using selected chemical attributes of experimentally validated AVCs. PaDEL, an open-source software, was used to calculate molecular descriptors and fingerprints.	./cache/cord-278456-gsv6dh36.txt	./txt/cord-278456-gsv6dh36.txt