Skip to content

Virtual high-throughput screening of molecular databases.

by Markus H J Seifert, Jürgen Kraus, Bernd Kramer
Current opinion in drug discovery & development ()


Virtual high-throughput screening (vHTS) is an efficient and widely applicable method used to identify initial hit compounds for pharmaceutical research. Despite its widespread use, several aspects of protein structure-based vHTS can still be optimized, particularly its accuracy and speed in generating results. Recent developments that address these issues include machine learning and implicit solvation methods. Various machine learning methods are available to improve vHTS accuracy, for example, target-specific optimization of scoring functions, the integration of essential protein-ligand interactions, and the application of negative training data. Implicit solvation methods are exemplified by the molecular mechanics Poisson-Boltzmann solvent accessible surface area approach. Furthermore, grid computing and intelligent database screening approaches are used to improve the speed of vHTS.

Cite this document (BETA)

Readership Statistics

16 Readers on Mendeley
by Discipline
44% Agricultural and Biological Sciences
38% Chemistry
13% Computer Science
by Academic Status
31% Researcher
31% Student > Master
13% Professor
by Country
6% Australia
6% Mexico
6% United States

Sign up today - FREE

Mendeley saves you time finding and organizing research. Learn more

  • All your research in one place
  • Add and import papers easily
  • Access it anywhere, anytime

Start using Mendeley in seconds!

Sign up & Download

Already have an account? Sign in