Skip to main content

Color Coding for the Fragment-Based Docking, Design and Equilibrium Statistics of Protein-Binding ssRNAs

  • Conference paper
  • First Online:
Research in Computational Molecular Biology (RECOMB 2024)

Abstract

We revisit the fragment-based docking and design of single-stranded RNA aptamers (ssRNAs), consisting of k nucleotides, onto a rigid protein. Fragments, representing short sequences of (modified) nucleotides, are individually docked as poses onto the protein surface using a force field. Compatible poses are then assembled while optimizing for an additive notion of energy, to obtain stable conformations that can either be constrained to represent an input ssRNA sequence (docking) or left unconstrained (design). However, a brute-force enumeration of clash-free conformations quickly becomes prohibitive due to their superexponential (\(\varTheta (n^k)\) worst-case) combinatorial explosion, hindering the potential of fragment-based methods towards docking and design.

In this work, we adapt the color-coding technique, introduced by Alon, Yuster and Zwick, to optimize over self-avoiding fragment assemblies in time/space linear on n the number of poses, and in time only exponential on k the number of fragments. The dynamic programming algorithm at the core of our method is surprisingly simple, and can be extended to produce suboptimal candidates, or modified to perform Boltzmann sampling of candidates assemblies. Using a rejection principle, and further optimized by a clique decomposition of clashing poses, these algorithms can be leveraged into efficient algorithms optimizing over clash-free complexes. The resulting sampling procedure can further be adapted into statistically-consistent estimators for any computable feature of interest.

We showcase some of the capabilities of this new framework by reanalyzing a set of 7 documented ssRNA-protein complexes, demonstrating its practical relevance and versatility.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

Download references

Acknowledgments

This work was supported by a 2020 PhD Grant from the Fondation Vaincre Alzheimer (#FR-19059) and by the PaRNAssus project funded by Agence Nationale de la Recherche (ANR-19-CE45-0023). The authors are greatly indebted to Laurent Bulteau for suggesting well-colored paths as a memory-efficient alternative to colorful paths, and to Sebastian Will for debunking an earlier, but ultimately erroneous, epiphany.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yann Ponty .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Yacoub, T., González-Alemán, R., Leclerc, F., de Beauchêne, I.C., Ponty, Y. (2024). Color Coding for the Fragment-Based Docking, Design and Equilibrium Statistics of Protein-Binding ssRNAs. In: Ma, J. (eds) Research in Computational Molecular Biology. RECOMB 2024. Lecture Notes in Computer Science, vol 14758. Springer, Cham. https://doi.org/10.1007/978-1-0716-3989-4_10

Download citation

  • DOI: https://doi.org/10.1007/978-1-0716-3989-4_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-1-0716-3988-7

  • Online ISBN: 978-1-0716-3989-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics