Ligand binding with OBPRM and user input

O. B. Bayazit, G. Song, N. M. Amato

Research output: Contribution to journalConference articlepeer-review


In this paper, we present a framework for studying ligand binding which is based on techniques recently developed in the robotics motion planning community. We are interested in locating binding sites on the protein for a ligand molecule. Our work investigates the performance of a fully automated motion planner, as well as the effects of supplementary user input collected using a haptic device. Our results applying an obstacle-based probabilistic roadmap motion planning algorithm (OBPRM) to some protein-ligand complexes are encouraging. The framework successfully identified potential binding sites for all complexes studied. We find that user input helps the planner, and a haptic device helps the user to understand the protein structure by enabling them to feel the difficult-to-visualize forces.

Original languageEnglish (US)
Pages (from-to)954-959
Number of pages6
JournalProceedings - IEEE International Conference on Robotics and Automation
StatePublished - 2001
Externally publishedYes
Event2001IEEE International Conference on Robotics and Automation (ICRA) - Seoul, Korea, Republic of
Duration: May 21 2001May 26 2001

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering


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