ProBiS-Dock

ProBiS-Dock performs flexible docking of small molecules and proteins using Protein Data Bank (PDB) structures to predict ligand–protein interactions while modeling conformational changes in both partners.


Key Features:

  • Hybrid Multitemplate Homology Flexible Docking Algorithm: Combines homology modeling with multitemplate flexible docking to accommodate variable protein templates and model conformational changes.
  • ProBiS-Score Functionality: Implements a two-component scoring function comprising a binding site-specific ProBiS-Score and a general statistical scoring term to evaluate docking poses.
  • Rapid Docking Capability: Optimized for rapid docking of small molecules to proteins to support high-throughput virtual screening.
  • Validation and Benchmarking: Validated against standard benchmarks and applied to identify new active ligands, including inhibitors of human indoleamine 2,3-dioxygenase 1 (IDO1).

Scientific Applications:

  • Drug discovery: Enables rapid identification of novel active ligands by searching and comparing structural data from the Protein Data Bank (PDB) for compatible binding sites.
  • IDO1 inhibitor discovery: Applied to discover inhibitors of human indoleamine 2,3-dioxygenase 1 (IDO1), an enzyme involved in l-tryptophan metabolism via the kynurenine pathway with relevance to cancer therapy.

Methodology:

Compares protein binding sites from PDB structures with ligands explicitly incorporated, applies a hybrid multitemplate homology flexible docking algorithm to model conformational changes, and evaluates poses using the binding site-specific ProBiS-Score combined with a general statistical scoring function.

Topics

Details

Cost:
Free of charge
Tool Type:
command-line tool
Operating Systems:
Mac, Linux, Windows
Added:
7/5/2022
Last Updated:
11/24/2024

Operations

Publications

Konc J, Lešnik S, Škrlj B, Sova M, Proj M, Knez D, Gobec S, Janežič D. ProBiS-Dock: A Hybrid Multitemplate Homology Flexible Docking Algorithm Enabled by Protein Binding Site Comparison. Journal of Chemical Information and Modeling. 2022;62(6):1573-1584. doi:10.1021/acs.jcim.1c01176. PMID:35289616.

PMID: 35289616
Funding: - Javna Agencija za Raziskovalno Dejavnost RS: J1-1715, J1-9186, L7-8269, N1-0142, N1-0209, P1-0208