Konrad Diwold
ABSTRACT
The identification of protein binding sites and the prediction of protein-ligand complexes play a key role in the pharmaceutical drug design process and many domains of life sciences. Computational approaches for protein-ligand docking (or molecular docking) have received increased attention over the last years as they allow inexpensive and fast prediction of protein-ligand complexes. Here we introduce the principle of Bee Nest-Site Selection Optimisation (BNSO), which solves optimisation problems using a novel scheme inspired by the nest-site selection behaviour found in honeybees. Moreover, the first BNSO algorithm -- Bee-Nest -- is proposed and applied to molecular docking. The performance of Bee-Nest is tested on 173 docking instances from the PDBbind core set and compared to the performance of three reference algorithms. The results show that Bee-Nest could find ligand poses with very small energy levels. Interestingly, the reference Particle Swarm Optimization (PSO) produces results that are qualitatively closer to wet-lab experimentally derived complexes but have higher energy levels than the results found by Bee-Nest. Our results highlight the superior performance of Bee-Nest in semi-local optimization for the molecular docking problem and suggests Bee-Nest's usefulness in a hybrid strategy.
- K. Diwold, M. Beekman, and M. Middendorf. Bee nest site selection as an optimization process. In Proceedings of the 12th International Conference on the Synthesis and Simulation of Living Systems (Alife XII), pages 626--633. The MIT Press, Cambridge, MA, 2010.Google Scholar
- K. Diwold, M. Beekman, and M. Middendorf. Handbook of Swarm Intelligence - Concepts, Principles and Applications, chapter Honeybee Optimisation. Springer, 2010.Google Scholar
- M. Farooq. Bee-Inspired Protocol Engineering: From Nature to Networks. Natural Computation Series. Springer, 2008. Google ScholarDigital Library
- I. Halperin, B. Ma, H. Wolfson, and R. Nussinov. Princliples of docking: an overview of search algorithms and a guide to scoring functions. Proteins: Structure, Function, and Genetics, 47:409--443, 2002.Google Scholar
- S. Janson, D. Merkle, and M. Middendorf. Molecular docking with multi-objective particle swarm optimization. Applied Soft Computing, 8:666--675, 2008. Google ScholarDigital Library
- S. Janson, M. Middendorf, and M. Beekman. Searching for a new home -- scouting behavior of honeybee swarms. Behavioral Ecology, 18:384--392, 2007.Google ScholarCross Ref
- G. Jones, P. Willett, and R. C. Glen. Molecular regcognition of receptor sites using a genetic algorithm with a description of desolvation. Journal of Molecular Biology, 245:43--53, 1995.Google ScholarCross Ref
- P. Kampstra. Beanplot: A boxplot alternative for visual comparison of distributions. Journal of Statistical Software, 28, 2008.Google Scholar
- D. Karaboga and B. Akay. A survey: algorithms simulating bee swarm intelligence. Artificial Intelligence Review, 31:61--85, 2009. Google ScholarDigital Library
- O. Korb, T. Stützle, and T. Exner. Plants: Application of ant colony optimization to structure-based drug design. In Proceedings of the 5th International Workshop on Ant Colony Optimization and Swarm Intelligence, ANTS 2006, volume 4150 of LNCS, pages 247--258. Springer, 2006. Google ScholarDigital Library
- B. Liu, H. Chen, H. Huang, S. Hwang, and S. Ho. Flexible protein-ligand docking using particle swarm optimization. In IEEE Congress on Evolutionary Computation CEC2005, volume 1, pages 251--258, 2005.Google Scholar
- M. Matsumoto and T. Nishimura. Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator. ACM Transactions on Modeling and Computer Simulation, 8:3--30, 1998. Google ScholarDigital Library
- R. Meier, M. Pippel, F. Brandt, W. Sippl, and C. Baldauf. PARADOCKS: A Framework for Molecular Docking with Population-Based Metaheuristics. Journal of Chemical Information and Modeling, 50:879--889, 2010.Google ScholarCross Ref
- I. Muegge. PMF scoring revisited. Journal of Medicinal Chemistry, 49(20):5895--5902, 2006.Google ScholarCross Ref
- M. R. Myerscough. Dancing for a decision: a matrix model for nest-site choice by honeybees. Proceedings of the Royal Society of London series B, 270:577--582, 2003.Google ScholarCross Ref
- T. Schmickl and K. Crailsheim. Trophallaxis within a robotic swarm: bio-inspired communication among robots in a swarm. Autonomous Robots, 25:171--188, 2008. Google ScholarDigital Library
- K. M. Schultz, K. M. Passino, and T. D. Seeley. The mechanism of flight guidance in honeybee swarms: subtle guides or streaker bees? Journal of Experimental Biology, 7:3287--3295, 2008.Google ScholarCross Ref
- T. D. Seeley. Honeybee Democracy. Princeton University Press, Princeton, NJ, 2010.Google Scholar
- T. D. Seeley and P. K. Visscher. Sensory coding of nest-site value in honeybee swarms. Journal of Experimental Biology, 211:3691--3697, 2008.Google ScholarCross Ref
- R. Wang, X. Fang, Y. Lu, and S. Wang. The PDBbind database: collection of binding affinities for protein-ligand complexes with known three-dimensional structures. Journal of Medicinal Chemistry, 47(12):2977--2980, 2004.Google ScholarCross Ref
Index Terms
- Bonding as a swarm: applying bee nest-site selection behaviour to protein docking
Recommendations
Antiviral potential of natural compounds against influenza virus hemagglutinin
The antiviral activity of natural compounds against the HA protein of different subtypes of Influenza virus has been investigated using binding free energy and hydrogen bonding interactions.Display Omitted The curucmin derivatives (CI, CII and CIII) ...
Unraveling the mechanism of l-gulonate-3-dehydrogenase inhibition by ascorbic acid: Insights from molecular modeling
Graphical abstractLegend: Ascorbic acid (white) has steric clashed with NADH (orange) and leads to gulonate-3-dehydrogenase inhibition.
Display Omitted
Highlights- Molecular dockings of ascorbate to gulonate-3-dehydrogenase indicated its binding near the co-factor binding site.
Abstractl-Gulonate dehydrogenase (GuDH) is a crucial enzyme in the non-phosphorylated sugar metabolism or glucuronate-xylulose (GX) pathway. Some naturally occurring compounds inhibit GuDH. Ascorbic acid is one of such ...
Disruption of redox catalytic functions of peroxiredoxin-thioredoxin complex in Mycobacterium tuberculosis H37Rv using small interface binding molecules
Display Omitted A suitable peroxiredoxin-thioredoxin complex model was generated using protein-protein docking approach.Statistics of interface region revealed transient interaction between peroxiredoxin and thioredoxin.MD simulation studies revealed ...
Comments