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相关论文: Biological Insights from Integrative Modeling of I…

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Protein design has the potential to revolutionize biotechnology and medicine. While most efforts have focused on proteins with well-defined structures, increased recognition of the functional significance of intrinsically disordered…

生物大分子 · 定量生物学 2025-09-17 Giulio Tesei , Francesco Pesce , Kresten Lindorff-Larsen

In 1999 Wright and Dyson highlighted the fact that large sections of the proteome of all organisms are comprised of protein sequences that lack globular folded structures under physiological conditions. Since then the biophysics community…

生物物理 · 物理学 2024-09-05 Zi Hao Liu , Maria Tsanai , Oufan Zhang , Julie Forman-Kay , Teresa Head-Gordon

Intrinsically disordered proteins (IDPs) constitute a broad set of proteins with few uniting and many diverging properties. IDPs-and intrinsically disordered regions (IDRs) interspersed between folded domains-are generally characterized as…

生物大分子 · 定量生物学 2021-06-03 Kresten Lindorff-Larsen , Birthe B. Kragelund

Disordered proteins play essential roles in myriad cellular processes, yet their structural characterization remains a major challenge due to their dynamic and heterogeneous nature. We here present a community-driven initiative to address…

Integrative modeling enables structure determination for large macromolecular assemblies by combining data from multiple sources of experiment data with theoretical and computational predictions. Recent advancements in AI-based structure…

生物大分子 · 定量生物学 2025-01-24 Kartik Majila , Shreyas Arvindekar , Muskaan Jindal , Shruthi Viswanath

We outline recent developments in artificial intelligence (AI) and machine learning (ML) techniques for integrative structural biology of intrinsically disordered proteins (IDP) ensembles. IDPs challenge the traditional protein…

生物大分子 · 定量生物学 2020-12-03 Arvind Ramanathan , Heng Ma , Akash Parvatikar , Chakra S. Chennubhotla

Characterizing structural and dynamic properties of proteins and large macromolecular assemblies is crucial to understand the molecular mechanisms underlying biological functions. In the field of Structural Biology, no single method…

定量方法 · 定量生物学 2023-10-04 Samuel Hoff , Maximilian Zinke , Nadia Izadi-Pruneyre , Massimiliano Bonomi

The human proteome is enriched in proteins that do not fold into a stable 3D structure. These intrinsically disordered proteins (IDPs) spontaneously fluctuate between a large number of configurations in their native form. Remarkably, the…

It is becoming clear that traditional, single-structure models of proteins are insufficient for understanding their biological function. Here, we outline one method for inferring, from experiments, not only the most common structure a…

生物物理 · 物理学 2014-08-04 Thomas J. Lane , Christian R. Schwantes , Kyle A. Beauchamp , Vijay S. Pande

Intrinsically disordered regions (IDRs) account for one-third of the human proteome and play essential biological roles. However, predicting the functions of IDRs remains a major challenge due to their lack of stable structures, rapid…

Intrinsically disordered proteins are fascinating the community of protein science since the last decade, at least. There is a well-established line of research that intends to reveal the crucial role played by intrinsically disordered…

生物大分子 · 定量生物学 2014-10-17 Antonio Deiana , Andrea Giansanti

In this paper we propose a straightforward operational definition of variants of disordered proteins, taking the human proteome as a case study. The focus is on a distinction between mostly unstructured proteins and proteins which contain…

生物大分子 · 定量生物学 2016-11-21 Antonio Deiana , Andrea Giansanti

Recent years have seen tremendous developments in the use of machine learning models to link amino acid sequence, structure and function of folded proteins. These methods are, however, rarely applicable to the wide range of proteins and…

生物大分子 · 定量生物学 2025-02-27 Sören von Bülow , Giulio Tesei , Kresten Lindorff-Larsen

Intrinsically disordered proteins (IDPs) and multidomain proteins with flexible linkers show a high level of structural heterogeneity and are best described by ensembles consisting of multiple conformations with associated thermodynamic…

生物大分子 · 定量生物学 2021-12-13 F. Emil Thomasen , Kresten Lindorff-Larsen

Numerous cellular functions rely on protein$\unicode{x2013}$protein interactions. Efforts to comprehensively characterize them remain challenged however by the diversity of molecular recognition mechanisms employed within the proteome. Deep…

生物大分子 · 定量生物学 2023-12-08 Julia R. Rogers , Gergő Nikolényi , Mohammed AlQuraishi

Biological networks provide insight into the complex organization of biological processes in a cell at the system level. They are an effective tool for understanding the comprehensive map of functional interactions, finding the functional…

分子网络 · 定量生物学 2017-09-14 Somaye Hashemifar

Deep learning is catalyzing a scientific revolution fueled by big data, accessible toolkits, and powerful computational resources, impacting many fields including protein structural modeling. Protein structural modeling, such as predicting…

生物大分子 · 定量生物学 2020-07-17 Wenhao Gao , Sai Pooja Mahajan , Jeremias Sulam , Jeffrey J. Gray

Intrinsically disordered proteins participate in many biological processes by folding upon binding with other proteins. However, coupled folding and binding processes are not well understood from an atomistic point of view. One of the main…

生物大分子 · 定量生物学 2023-02-22 Pablo Herrera-Nieto , Adrià Pérez , Gianni De Fabritiis

The term unfoldome has been recently used to indicate the universe of intrinsically disordered proteins. These proteins are characterized by an ensemble of high-flexible interchangeable conformations and therefore they can interact with…

基因组学 · 定量生物学 2010-12-30 Antonio Deiana , Andrea Giansanti

Intrinsically disordered protein regions (IDRs) are found across all domains of life and are characterized by a lack of stable 3D structure. Nevertheless, IDRs play critical roles in the most tightly regulated cellular processes, including…

生物大分子 · 定量生物学 2025-08-27 Emery T. Usher , Jacqueline F. Pelham
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