Virtual screening (VS), as a computational technique, is being used widely by pharmacologists and medicinal chemists in drug discovery research. By using computers, it deals with the quick search of large libraries of chemical structures, to identify those structures, which are most likely to bind to a drug target, typically a protein receptor or enzyme (
1-
3).
The VS is defined as “automatically evaluating very large libraries of compounds using computer programs” (
4). As this definition suggests, VS has been largely focusing on questions like how can the enormous chemical space of 10
60 conceivable compounds (
5) be filtered to a manageable number that can be synthesized, purchased and tested. Although filtering the entire chemical universe might be a fascinating question, more practical VS scenarios focus on designing and optimizing targeted combinatorial libraries and enriching libraries of available compounds, from in-house compound repositories or vendor offerings.
Two major strategies are used in VS: 1) structure based VS method ,which is employed when three dimensional (3D) structures of the targets are available and 2) ligand based VS that is used where 3D target structures are unknown (
6). Structure based VS is dependent on the knowledge of target structure. A ligand collection is tested on the target by “docking” and a quantified interaction score is used to identify candidate lead compounds. Therefore, structure based VS is independent on the existence of known active lead compounds (
7). Another approach to ligand-based VS is to use two-dimensional (2D) chemical similarity analysis methods (
8) to scan a database of molecules against one or more active ligand structures. Another method of ligand-based VS is based on searching molecules with shapes similar to those of known active sites, as such molecules will fit the target’s binding site and, hence, will be likely to bind the target. A number of prospective applications of this class of techniques have been identified in the literature (
9,
10).
Docking is a method which predicts the preferred orientation of one molecule to a second, when bound to each other to form a stable complex (
11). Knowledge of the preferred orientation in turn may be used to predict the strength of association or binding affinity between two molecules, using, for example, scoring functions. Docking is frequently used to predict the binding orientation of small molecule drug candidates to their protein targets to, in turn, predict the affinity and activity of the small molecule. Therefore, docking plays an important role in the rational drug design (
7).
Various docking software have been developed for virtual screening, since the initiation of University of California, San Francisco dock (
12,
13), such as GOLD (
14), GLIDE (
15) or AutoDock Vina (
16). Multiple researchers have reported successful identification of lead compounds, using docking based VS methods (
17). Ligand based VS is based on the assumption that structurally similar compounds are likely to exhibit similar activities. Structural, physiochemical and energetic properties are used when screening large databases for related or novel chemical compounds (
18). The pharmacophore-based database searching technique is a widely used VS strategy (
19), which relies on knowledge of the biological activity of multiple hits, when identifying key features, during a search. A pharmacophore is a spatial arrangement of features that allows a compound to interact with a target receptor and generate a response. In research,, both methods can be used together or separately.
A very widely used data base for virtual screening is “ZINC” (it is not commercial) (
20). It is a curate collection of commercially available chemical compounds, prepared especially for VS. ZINC differs from other chemical databases, because it aims to represent the biologically relevant, 3D structure of the molecule. This database is updated regularly and may be downloaded and used, free of charge. The latest release of the website interface is “ZINC 12” (2012). The database contents are continuously updated, while static subsets are generated regularly and are dated.
Visual screening tools in hand are usually command-line oriented and lack an intuitive graphic user interface (GUI) and this has prevented the main audience of such software, which are medicinal chemists, pharmacologists and other pharmaceutical scientists, with mainly novice computer skills to actively engage.
Because there is a growing need for easy to use software, in this field, in this study, we have developed a VS piece of software: IranVScreen, which is an easily operable tool for medicinal chemists and pharmacologists, to carry out multiple practical virtual screening tasks, while also providing the facility to extract the results. IranVScreen integrates several static subsets of ZINC database, which further facilitates the task for the researcher and allows for very fast reclamation of results. IranVScreen provides a very intuitive all-in-one GUI to carry out multiple virtual screen tasks, with several mouse clicks, with minimal requirement of skill.