Haptic-assisted interactive molecular docking incorporating receptor flexibility

Nick Matthews, Akio Kitao, Stephen Laycock, Steven Hayward

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)
22 Downloads (Pure)


Haptic-assisted interactive docking tools immerse the user in an environment where intuition and knowledge can be used to help guide the docking process. Here we present such a tool where the user “holds” a rigid ligand via a haptic device through which they feel interaction forces with a flexible receptor biomolecule. To ensure forces transmitted through the haptic device are smooth and stable, they must be updated at a rate greater than 500 Hz. Due to this time constraint, the majority of haptic docking tools do not attempt to model the conformational changes that would occur when molecules interact during binding. Our haptic-assisted docking tool, “Haptimol Flexidock”, models a receptor’s conformational response to forces of interaction with a ligand whilst maintaining the required haptic refresh rate. In order to model receptor flexibility we use the method of linear response for which we determine the variance-covariance matrix of atomic fluctuations from the trajectory of an explicit-solvent Molecular Dynamics simulation of the ligand-free receptor molecule. Key to satisfying the time constraint is an eigenvector decomposition of the variance-covariance matrix which enables a good approximation to the conformational response of the receptor to be calculated rapidly. This exploits a feature of protein dynamics whereby most fluctuation occurs within a relatively small subspace. The method is demonstrated on Glutamine Binding Protein in interaction with glutamine, and Maltose Binding Protein in interaction with maltose. For both proteins, the movement that occurs when the ligand is docked near to its binding site matches the experimentally determined movement well. It is thought that this tool will be particularly useful for structure-based drug design.
Original languageEnglish
Pages (from-to)2900-2912
Number of pages13
JournalJournal of Chemical Information and Modeling
Issue number6
Early online date10 Apr 2019
Publication statusPublished - 24 Jun 2019

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