HitPick is a web server that facilitates the analysis of chemical screenings by identifying hits and predicting their molecular targets. The target prediction functionality can also be used in a stand-alone fashion.
For hit identification, the widely used B-score method (1) is applied.
For target prediction, HitPick applies a new approach that combines two 2D molecular similarity based methods, namely, simple 1-Nearest-Neighbour (1NN) similarity searching (2) and a machine learning method based on Laplacian-modified naive Bayesian models (3). Baca lebih lanjut
In the last decade, a growing number of drug discovery researchers have replaced robots and reagents in their high-throughput screens with computer modeling, relying on software to identify compounds that will bind to a protein target of interest.
Researchers often combine virtual screening with other computational tools that make predictions about the activity of individual compounds, such as how they will interact with proteins. Together, these tools help narrow down large libraries of compounds into a subset to test experimentally. The biggest compound libraries boast several million molecules, an unrealistic load for the best-equipped lab to screen the old-fashioned way. Experimentally testing more modest libraries of thousands of molecules would still strain the resources of academic researchers, who are increasingly tackling drug discovery. “As an academic lab, I can’t afford to buy thousands of compounds to do a high-throughput screen, but I could afford to buy 10 or 20,” says Werner Geldenhuys, an associate professor of pharmaceutical sciences at Northeast Ohio Medical University.
Computational tools have their own challenges, however. Depending on the type of predictions the program makes and the size of your library, these screens could take hours to days to run. Some programs require users to perform basic coding. And of course, virtual hits have to be validated in the lab for their ability to actually bind to the target and modulate its activity. Baca lebih lanjut
PyRx is a Virtual Screening software for Computational Drug Discovery that can be used to screen libraries of compounds against potential drug targets. PyRx enables Medicinal Chemists to run Virtual Screening from any platform and helps users in every step of this process – from data preparation to job submission and analysis of the results. While it is true that there is no magic button in the drug discovery process, PyRx includes docking wizard with easy-to-use user interface which makes it a valuable tool for Computer-Aided Drug Design. PyRx also includes chemical spreadsheet-like functionality and powerful visualization engine that are essential for Rational Drug Design.Visit Videos page for Getting Started Screencasts. See also Starting Virtual Screening and Getting Started with PyRx tutorials.
PyRx is using large body of established open source software such as: Baca lebih lanjut