open access publication

Article, 2024

Chromatin image-driven modelling

Methods, ISSN 1046-2023, Volume 226, Pages 54-60, 10.1016/j.ymeth.2024.04.006

Contributors

Kadlof M. 0000-0002-4293-4456 [1] Banecki K. [1] [2] Chilinski M. 0000-0001-6641-8504 [1] [2] [3] Plewczynski D. 0000-0002-3840-7610 [1] [2]

Affiliations

  1. [1] Warsaw University of Technology
  2. [NORA names: Poland; Europe, EU; OECD];
  3. [2] University of Warsaw
  4. [NORA names: Poland; Europe, EU; OECD];
  5. [3] University of Copenhagen
  6. [NORA names: KU University of Copenhagen; University; Denmark; Europe, EU; Nordic; OECD]

Abstract

The challenge of modelling the spatial conformation of chromatin remains an open problem. While multiple data-driven approaches have been proposed, each has limitations. This work introduces two image-driven modelling methods based on the Molecular Dynamics Flexible Fitting (MDFF) approach: the force method and the correlational method. Both methods have already been used successfully in protein modelling. We propose a novel way to employ them for building chromatin models directly from 3D images. This approach is termed image-driven modelling. Additionally, we introduce the initial structure generator, a tool designed to generate optimal starting structures for the proposed algorithms. The methods are versatile and can be applied to various data types, with minor modifications to accommodate new generation imaging techniques.

Funders

  • Narodowe Centrum Nauki
  • Narodowa Agencja Wymiany Akademickiej
  • European Commission
  • Ministerstwo Edukacji i Nauki
  • Politechnika Warszawska
  • Research University
  • H2020 Marie SkÅ‚odowska-Curie Actions
  • National Institutes of Health
  • IDUB

Data Provider: Elsevier