Solving Exact Cover Instances with Molecular-Motor-Powered Network-Based Biocomputation

Research output: Contribution to journalResearch articleContributedpeer-review


  • Pradheebha Surendiran - , Lund University (Author)
  • Christoph Robert Meinecke - , Chemnitz University of Technology (Author)
  • Aseem Salhotra - , Linnaeus University (Author)
  • Georg Heldt - , Linnaeus University (Author)
  • Jingyuan Zhu - , Lund University (Author)
  • Alf Månsson - , Linnaeus University (Author)
  • Stefan Diez - , Chair of BioNano-Tools, Clusters of Excellence PoL: Physics of Life, Max Planck Institute of Molecular Cell Biology and Genetics (Author)
  • Danny Reuter - , Chemnitz University of Technology, Fraunhofer Institute for Electronic Nano Systems (Author)
  • Hillel Kugler - , Bar-Ilan University (Author)
  • Heiner Linke - , Lund University (Author)
  • Till Korten - , Chair of BioNano-Tools (Author)


Information processing by traditional, serial electronic processors consumes an ever-increasing part of the global electricity supply. An alternative, highly energy efficient, parallel computing paradigm is network-based biocomputation (NBC). In NBC a given combinatorial problem is encoded into a nanofabricated, modular network. Parallel exploration of the network by a very large number of independent molecular-motor-propelled protein filaments solves the encoded problem. Here we demonstrate a significant scale-up of this technology by solving four instances of Exact Cover, a nondeterministic polynomial time (NP) complete problem with applications in resource scheduling. The difficulty of the largest instances solved here is 128 times greater in comparison to the current state of the art for NBC.


Original languageEnglish
Pages (from-to)396-403
Number of pages8
Journal ACS nanoscience Au : an open access journal of the American Chemical Society
Issue number5
Publication statusPublished - 23 Jun 2022

External IDs

unpaywall 10.1021/acsnanoscienceau.2c00013
PubMed 36281252
ORCID /0000-0002-0750-8515/work/142235522


Research priority areas of TU Dresden


  • biocomputation, biofunctionalization, computational nanotechnology, molecular motors, nanobiotechnology, parallel computing