Hidden Structure in Disordered Proteins is Adaptive to Intracellular Changes

Moses, David; Guadalupe, Karina; Ye, Feng; Flores, Eduardo Furtado; Perez, Anthony; McAnelley, Ralph; Shamoon, Nora M.; Cuevas-Zepeda, Estefania; Merg, Andrea D.; Martin, Erik W.; Holehouse, Alex S.; Sukenik, Shahar

doi:10.2139/ssrn.4002760

Cited by 6 publications

(5 citation statements)

References 61 publications

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“…SOURSOP contains a range of additional routines not explored in this work but have been applied to various systems under a range of contexts, including local residual structure, intra-residue contacts, and the interaction between folded and disordered regions ( Fig. S1 ) 57,58,85–87 .…”

Section: Discussionmentioning

confidence: 99%

SOURSOP: A Python package for the analysis of simulations of intrinsically disordered proteins

Lalmansingh

Keeley

Ruff

et al. 2023

Preprint

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Conformational heterogeneity is a defining hallmark of intrinsically disordered proteins and protein regions (IDRs). The functions of IDRs and the emergent cellular phenotypes they control are associated with sequence-specific conformational ensembles. Simulations of conformational ensembles that are based on atomistic and coarse-grained models are routinely used to uncover the sequence-specific interactions that may contribute to IDR functions. These simulations are performed either independently or in conjunction with data from experiments. Functionally relevant features of IDRs can span a range of length scales. Extracting these features requires analysis routines that quantify a range of properties. Here, we describe a new analysis suite SOURSOP, an object-oriented and open-source toolkit designed for the analysis of simulated conformational ensembles of IDRs. SOURSOP implements several analysis routines motivated by principles in polymer physics, offering a unique collection of simple-to-use functions to characterize IDR ensembles. As an extendable framework, SOURSOP supports the development and implementation of new analysis routines that can be easily packaged and shared.

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Section: Discussionmentioning

confidence: 99%

SOURSOP: A Python package for the analysis of simulations of intrinsically disordered proteins

Lalmansingh

Keeley

Ruff

et al. 2023

Preprint

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“…SOURSOP contains a range of additional routines not explored in this work but have been applied to various systems under a range of contexts, including the local residual structure, intraresidue contacts, and the interaction between folded and disordered regions (Figure S1). ,,− …”

Section: Discussionmentioning

confidence: 99%

SOURSOP: A Python Package for the Analysis of Simulations of Intrinsically Disordered Proteins

Lalmansingh

Keeley

Ruff

et al. 2023

J. Chem. Theory Comput.

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Conformational heterogeneity is a defining hallmark of intrinsically disordered proteins and protein regions (IDRs). The functions of IDRs and the emergent cellular phenotypes they control are associated with sequence-specific conformational ensembles. Simulations of conformational ensembles that are based on atomistic and coarse-grained models are routinely used to uncover the sequence-specific interactions that may contribute to IDR functions. These simulations are performed either independently or in conjunction with data from experiments. Functionally relevant features of IDRs can span a range of length scales. Extracting these features requires analysis routines that quantify a range of properties. Here, we describe a new analysis suite simulation analysis of unfolded regions of proteins (SOURSOP), an object-oriented and open-source toolkit designed for the analysis of simulated conformational ensembles of IDRs. SOURSOP implements several analysis routines motivated by principles in polymer physics, offering a unique collection of simple-to-use functions to characterize IDR ensembles. As an extendable framework, SOURSOP supports the development and implementation of new analysis routines that can be easily packaged and shared.

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“…A confluence of trends and events has laid the groundwork for a productive reexamination of these assumptions. First, the maturation of structural and sequence databases has prompted increasingly critical looks at our understanding of LCRs [25] and IDRs [26]. In parallel, specific examples have accumulated of well-defined structure in sequences which would, by existing heuristics, be overwhelmingly predicted to be disordered: alpha-helices in myosin [27] and caldesmon [28], and a coiled-coil region in the mRNA export protein GLE1 [29].…”

Section: Introductionmentioning

confidence: 99%

Pervasive, conserved secondary structure in highly charged protein regions

Triandafillou

Pan

Dinner

et al. 2023

Preprint

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Understanding how protein sequences confer function remains a defining challenge in molecular biology. Two approaches have yielded enormous insight yet are often pursued separately: structure-based, where sequence-encoded structures mediate function, and disorder-based, where sequences dictate physicochemical and dynamical properties which determine function in the absence of stable structure. Here we study highly charged protein regions (>40% charged residues), which are routinely presumed to be disordered. Using recent advances in structure prediction and experimental structures, we show that roughly 40% of these regions form well-structured helices. Features often used to predict disorder—high charge density, low hydrophobicity, low sequence complexity, and evolutionarily varying length—are also compatible with solvated, variable-length helices. We show that a simple composition classifier predicts the existence of structure far better than well-established heuristics based on charge and hydropathy. We show that helical structure is more prevalent than previously appreciated in highly charged regions of diverse proteomes and characterize the conservation of highly charged regions. Our results underscore the importance of integrating, rather than choosing between, structure- and disorder-based approaches.

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Hidden Structure in Disordered Proteins is Adaptive to Intracellular Changes

Cited by 6 publications

References 61 publications

SOURSOP: A Python package for the analysis of simulations of intrinsically disordered proteins

SOURSOP: A Python package for the analysis of simulations of intrinsically disordered proteins

SOURSOP: A Python Package for the Analysis of Simulations of Intrinsically Disordered Proteins

Pervasive, conserved secondary structure in highly charged protein regions

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