Search for: All records

High-resolution techniques capable of manipulating from single molecules to millions of cells are combined with three-dimensional modeling followed by simulation to comprehend the specific aspects of chromosomes. From the theoretical perspective, the energy landscape theory from protein folding inspired the development of the minimal chromatin model (MiChroM). In this work, two biologically relevant MiChroM energy terms were minimized under different conditions, revealing a competition between loci compartmentalization and motor-driven activity mechanisms in chromatin folding. Enhancing the motor activity energy baseline increased the lengthwise compaction and reduced the polymer entanglement. Concomitantly, decreasing compartmentalization-related interactions reduced the overall polymer collapse, although compartmentalization given by the microphase separation remained almost intact. For multiple chromosome simulations, increased motorization intensified the territory formation of the different chains and reduced compartmentalization strength lowered the probability of contact formation of different loci between multiple chains, approximating to the experimental inter-contacts of the human chromosomes. These findings have direct implications for experimental data-driven chromosome modeling, specially those involving multiple chromosomes. The interplay between phase-separation and territory formation mechanisms should be properly implemented in order to recover the genome architecture and dynamics, features that might play critical roles in regulating nuclear functions. 

Molecular dynamics (MD) simulations provide a powerful means of exploring the dynamic behavior of biomolecular systems at the atomic level. However, analyzing the vast data sets generated by MD simulations poses significant challenges. This article discusses the energy landscape visualization method (ELViM), a multidimensional reduction technique inspired by the energy landscape theory. ELViM transcends one-dimensional representations, offering a comprehensive analysis of the effective conformational phase space without the need for predefined reaction coordinates. We apply the ELViM to study the folding landscape of the antimicrobial peptide Polybia-MP1, showcasing its versatility in capturing complex biomolecular dynamics. Using dissimilarity matrices and a force-scheme approach, the ELViM provides intuitive visualizations, revealing structural correlations and local conformational signatures. The method is demonstrated to be adaptable, robust, and applicable to various biomolecular systems.