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Micromechanical studies of mitotic chromosomes have revealed them to be remarkably extensible objects and informed early models of mitotic chromosome organization. We use a data-driven, coarsegrained polymer modeling approach, capable of generating ensembles of chromosome structures that are quantitatively consistent with experiments, to explore the relationship between the spatial organization of individual chromosomes and their emergent mechanical properties. In particular, we investigate the mechanical properties of our model chromosomes by axially stretching them. Simulated stretching led to a linear force-extension curve for small strain, with mitotic chromosomes behaving about ten-fold stiffer than interphase chromosomes. Studying the relaxation dynamics we found that chromosomes are viscoelastic solids, with a highly liquid-like, viscous behavior in interphase that becomes solid-like in mitosis. This emergent mechanical stiffness in our model originates from lengthwise compaction, an effective potential capturing the activity of loop-extruding SMC complexes. Chromosomes denature under large strains via unraveling, which is characterized by opening of large-scale folding patterns. By quantifying the effect of mechanical perturbations on the chromosome’s structural features, our model provides a nuanced understanding of in vivo mechanics of chromosomes.

Made available in DSpace on 2022-04-29T08:31:58Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-08-12 The human genome is organized within a nucleus where chromosomes fold into an ensemble of different conformations. Chromosome conformation capture techniques such as Hi-C provide information about the genome architecture by creating a 2D heat map. Initially, Hi-C map experiments were performed in human interphase cell lines. Recently, efforts were expanded to several different organisms, cell lines, tissues, and cell cycle phases where obtaining high-quality maps is challenging. Poor sampled Hi-C maps present high sparse matrices where compartments located far from the main diagonal are difficult to observe. Aided by recently developed models for chromatin folding and dynamics investigation, we introduce a framework to enhance the compartments' information far from the diagonal observed in experimental sparse matrices. The simulations were performed using the Open-MiChroM platform aided by new trained parameters in the minimal chromatin model (MiChroM) energy function. The simulations optimized on a downsampled experimental map (10% of the original data) allow the prediction of a contact frequency similar to that of the complete (100%) experimental Hi-C. The modeling results open a discussion on how simulations and modeling can increase the statistics and help fill in some Hi-C regions not captured by poor sampling experiments. Open-MiChroM simulations allow us to explore the 3D genome organization of different organisms, cell lines, and cell phases that often do not produce high-quality Hi-C maps. Center for Theoretical Biological Physics Department of Physics & Astronomy Rice University Instituto de Biociências Letras e Ciências Exatas UNESP Univ. Estadual Paulista Departamento de Física The Center for Genome Architecture Department of Molecular and Human Genetics Baylor College of Medicine Instituto de Biociências Letras e Ciências Exatas UNESP Univ. Estadual Paulista Departamento de Física

Made available in DSpace on 2021-06-25T10:59:11Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-01-01 Intrinsically disordered proteins (IDPs) lack a rigid three-dimensional structure and populate a polymorphic ensemble of conformations. Because of the lack of a reference conformation, their energy landscape representation in terms of reaction coordinates presents a daunting challenge. Here, our newly developed energy landscape visualization method (ELViM), a reaction coordinate-free approach, shows its prime application to explore frustrated energy landscapes of an intrinsically disordered protein, prostate-associated gene 4 (PAGE4). PAGE4 is a transcriptional coactivator that potentiates the oncogene c-Jun. Two kinases, namely, HIPK1 and CLK2, phosphorylate PAGE4, generating variants phosphorylated at different serine/threonine residues (HIPK1-PAGE4 and CLK2-PAGE4, respectively) with opposing functions. While HIPK1-PAGE4 predominantly phosphorylates Thr51 and potentiates c-Jun, CLK2-PAGE4 hyperphosphorylates PAGE4 and attenuates transactivation. To understand the underlying mechanisms of conformational diversity among different phosphoforms, we have analyzed their atomistic trajectories simulated using AWSEM forcefield, and the energy landscapes were elucidated using ELViM. This method allows us to identify and compare the population distributions of different conformational ensembles of PAGE4 phosphoforms using the same effective phase space. The results reveal a predominant conformational ensemble with an extended C-terminal segment of WT PAGE4, which exposes a functional residue Thr51, implying its potential of undertaking a fly-casting mechanism while binding to its cognate partner. In contrast, for HIPK1-PAGE4, a compact conformational ensemble enhances its population sequestering phosphorylated-Thr51. This clearly explains the experimentally observed weaker affinity of HIPK1-PAGE4 for c-Jun. ELViM appears as a powerful tool, especially to analyze the highly frustrated energy landscape representation of IDPs where appropriate reaction coordinates are hard to apprehend. Center for Theoretical Biological Physics Rice University Department of Chemistry Massachusetts Institute of Technology Department of Medical Oncology and Therapeutics Research City of Hope National Medical Center Department of Chemical Sciences Indian Institute of Science Education and Research Kolkata Departamento de Física Instituto de Biociências Letras e Ciências Exatas Universidade Estadual Paulista (UNESP) Departamento de Física Instituto de Biociências Letras e Ciências Exatas Universidade Estadual Paulista (UNESP)

Made available in DSpace on 2021-06-25T10:45:52Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-03-19 Significant efforts have been recently made to obtain the three-dimensional (3D) structure of the genome with the goal of understanding how structures may affect gene regulation and expression. Chromosome conformational capture techniques such as Hi-C, have been key in uncovering the quantitative information needed to determine chromatin organization. Complementing these experimental tools, co-polymers theoretical methods are necessary to determine the ensemble of three-dimensional structures associated to the experimental data provided by Hi-C maps. Going beyond just structural information, these theoretical advances also start to provide an understanding of the underlying mechanisms governing genome assembly and function. Recent theoretical work, however, has been focused on single chromosome structures, missing the fact that, in the full nucleus, interactions between chromosomes play a central role in their organization. To overcome this limitation, MiChroM (Minimal Chromatin Model) has been modified to become capable of performing these multi-chromosome simulations. It has been upgraded into a fast and scalable software version, which is able to perform chromosome simulations using GPUs via OpenMM Python API, called Open-MiChroM. To validate the efficiency of this new version, analyses for GM12878 individual autosomes were performed and compared to earlier studies. This validation was followed by multi-chain simulations including the four largest human chromosomes (C1-C4). These simulations demonstrated the full power of this new approach. Comparison to Hi-C data shows that these multiple chromosome interactions are essential for a more accurate agreement with experimental results. Without any changes to the original MiChroM potential, it is now possible to predict experimentally observed inter-chromosome contacts. This scalability of Open-MiChroM allow for more audacious investigations, looking at interactions of multiple chains as well as moving towards higher resolution chromosomes models. Center for Theoretical Biological Physics Rice University ICTP South American Institute for Fundamental Research Instituto de Física Teórica Instituto de Biociências Letras e Ciências Exatas UNESP - Univ. Estadual Paulista Departamento de Física São José do Rio Preto Chemical Engineering Department Military Institute of Engineering Instituto de Biociências Letras e Ciências Exatas UNESP - Univ. Estadual Paulista Departamento de Física São José do Rio Preto

Made available in DSpace on 2018-11-12T17:27:04Z (GMT). No. of bitstreams: 0 Previous issue date: 2018. Added 1 bitstream(s) on 2021-07-14T17:51:22Z : No. of bitstreams: 1 S1806-11172018000400407.pdf: 16053464 bytes, checksum: 05cd6507810278fc2f0b49b98b824b8e (MD5) Resumo Este trabalho tem como objetivo introduzir estudantes de física e áreas afins ao problema de enovelamento de proteína. A proteína é uma macromolécula biológica de grande importância para os seres vivos. Entender como esta macromolécula encontra uma configuração tridimensional e funcional, tomando como a priori a informação presente em uma sequência linear de diferentes aminoácidos, é uma questão relevante e envolve pesquisadores de diversas áreas do conhecimento. Neste trabalho, é apresentada uma introdução sobre a importância das proteínas e suas principais características, além de mostrar um breve histórico do estudo de enovelamento de proteínas e como esses trabalhos convergem na construção da teoria de Superfície de Energia. São descritos alguns modelos teóricos e computacionais, desde as primeiras abordagens em modelos analíticos até a construção de modelos baseados em estruturas para simulações. Também são apresentados e discutidos alguns resultados esperados em cada modelo utilizado. Abstract This work aims to introduce students of physics and related areas to the problem of protein folding. Proteins are biological macromolecules of great importance to living things. The understanding of how this macromolecule finds a three-dimensional and functional structure, using the information present in a linear sequence of different amino acids, is a relevant question which involves researchers from different areas of knowledge. This work discusses the importance and the main properties of proteins and presents a brief history of protein folding studies and how these works converge to the Energy Landscape theory. There are described some theoretical and computational models from analytical approaches to the development of the Structure-Based Models for simulations. Here it is also presented and discussed some expected results for each used model. Centro Nacional de Pesquisa em Energia e Materiais Laboratório Nacional de Ciência e Tecnologia do Bioetanol Universidade Estadual Paulista Instituto de Biociências Departamento de Física Rice University Center for Theoretical Biological Physics Universidade Federal do Triângulo Mineiro Instituto de Ciências Exatas Departamento de Física Universidade Estadual Paulista Instituto de Biociências Departamento de Física