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Protein-Ligand ANT System
O. Korb, T. Stützle, T.E. Exner
In the drug development process, predicting the complex structure of a small ligand with a protein, the so-called protein-ligand-docking-problem, is extensively used in virtual screening of large databases and in lead optimization. Given a protein structure, a ligand structure and a scoring function, the goal is to find a low energy ligand conformation in the protein's binding site that corresponds to the global minimum of the scoring function. The docking algorithm PLANTS is based on a class of stochastic optimization algorithms called ant colony optimization (ACO). ACO is inspired by the behavior of real ants finding a shortest path between their nest and a food source. The ants use indirect communication in the form of pheromone trails which mark paths between the nest and a food source. In the case of protein-ligand docking, an artificial ant colony is employed to find a minimum energy conformation of the ligand in the binding site. These ants are used to mimic the behavior of real ants and mark low energy ligand conformations with pheromone trails. The artificial pheromone trail information is modified in subsequent iterations to generate low energy conformations with a higher probability.
PLANTS Features
• ACO-based search engine
• two scoring functions (PLANTSCHEMPLP and PLANTSPLP)
• flexible protein side-chains
• rigid-body docking of multiconformer libraries into rigid and flexible receptors
• constraint system
• docking with selected explicit, displaceable water molecules
• fully automatic ligand setup (rotatable bond identification, atom typing ...)
• virtual screening
• rescoring capability
License Information
Versions for LINUX, Win32, and OSX are available here under a free academic license.
For a commercial copy please contact thomas.exner@uni-konstanz.de.
To run the basic docking example, download a PLANTS version, unzip simple_dock.zip and run:
./PLANTS --mode screen plantsconfig
The docking output will be stored in the directory results
Structure Preparation
It is recommended to preprocess the protein and ligand input structures used for docking with SPORES
User Interface
A graphical user interface able to generate PLANTS input scripts is available in Zodiac
Collaborators:

Thomas Stützle, IRIDIA, Université Libre de Bruxelles (ULB)
Nicola Zonta, Welsh School of Pharmacy, Cardiff University
Stefano Moro, Molecular Modeling Section, Department of Pharmaceutical Sciences, University of Padova
Wolfgang Brandt, IPB Halle
Bruno Villoutreix, MTi, Université Paris Diderot
References:
1) Korb, O.; Stützle, T.; Exner, T. E. "PLANTS: Application of Ant Colony Optimization to Structure-Based Drug Design" Lecture Notes in Computer Science 4150, 247-258 (2006).
2) Korb, O.; Stützle, T.; Exner, T. E. "An ant colony optimization approach to flexible protein-ligand docking" Swarm Intell. 1, 115-134 (2007).
3) Korb, O.; Stützle, T.; Exner, T. E. "Empirical Scoring Functions for Advanced Protein-Ligand Docking with PLANTS" J.Chem.Inf.Model. 49, 84-96 (2009).
4) Korb, O.; Möller, H.; Exner, T. E. "NMR-guided Molecular Docking of a Protein-Peptide Complex Based on Ant Colony Optimization" ChemMedChem 5, 1001-1006 (2010).
Studies using PLANTS:
1) Migliore, Marco D., Zonta, Nicola, McGuigan, Christopher, Henson, Geoffrey, Andrei, Graciela, Snoeck, Robert, and Balzarini, Jan   Synthesis and Antiviral Activity of the Carbocyclic Analogue of the Highly Potent and Selective Anti-VZV Bicyclo Furano Pyrimidines.   J. Med. Chem., 50, 26, 6485 - 6492, 2007. linkout
2) Jakub Grzegorz Kopycki, Milton T. Stubbs, Wolfgang Brandt, Martin Hagemann, Andrea Porzel, Jürgen Schmidt, Willibald Schliemann, Meinhart H. Zenk, and Thomas Vogt   Functional and Structural Characterization of a Cation-dependent O-Methyltransferase from the Cyanobacterium Synechocystis sp. Strain PCC 6803.   J. Biol. Chem., 283(30), pp. 20888-20896, July 25, 2008. linkout
3) Francesco Piscitelli, Antonio Coluccia, Andrea Brancale, Giuseppe La Regina, Anna Sansone, Cesare Giordano, Jan Balzarini, Giovanni Maga, Samantha Zanoli, Alberta Samuele, Roberto Cirilli, Francesco La Torre, Antonio Lavecchia, Ettore Novellino and Romano Silvestri   Indolylarylsulfones Bearing Natural and Unnatural Amino Acids. Discovery of Potent Inhibitors of HIV-1 Non-Nucleoside Wild Type and Resistant Mutant Strains Reverse Transcriptase and Coxsackie B4 Virus.   J. Med. Chem., ASAP, 2009. linkout
Publications referencing PLANTS:
1) N. Moitessier, P. Englebienne, D. Lee, J. Lawandi and C. R. Corbeil   Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go.   British Journal of Pharmacology (2008) 153, S7-S26. linkout
2) Stefan Janson, Daniel Merkle and Martin Middendorf   Molecular docking with multi-objective Particle Swarm Optimization.   Applied Soft Computing, Volume 8, Issue 1, January 2008, Pages 666-675. linkout
3) Andrea Bortolato and Stefano Moro   Designing a ligand for pharmaceutical purposes.   Expert Opinion on Drug Discovery, May 2008, Vol. 3, No. 5, Pages 579-590. linkout
4) Bruno O. Villoutreix, Nicolas Renault, David Lagorce, Olivier Sperandio, Matthieu Montes and Maria A. Miteva   Free resources to assist structure-based virtual ligand screening experiments.   Current Protein and Peptide Science, 2007, Vol. 8, No. 4, Pages 381-411. linkout
5) Jorge Tavares, Alexandru-Adrian Tantar, Nouredine Melab and El-Ghazali Talbi   The Influence of Mutation on Protein-Ligand Docking Optimization: A Locality Analysis.   Lecture Notes in Computer Science, 2008, Vol. 5199, Pages 589-598. linkout
thomas.exner@uni-konstanz.de last update: Jan 15, 2016