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Motivation: Protein folding is a dynamic process during which a protein's amino acid sequence undergoes a series of 3-dimensional (3D) conformational changes en route to reaching a native 3D structure; the resulting 3D structural…

生物大分子 · 定量生物学 2026-04-09 Aydin Wells , Khalique Newaz , Jennifer Morones , Jianlin Cheng , Tijana Milenković

Protein one-dimensional (1D) structures such as secondary structure and contact number provide intuitive pictures to understand how the native three-dimensional (3D) structure of a protein is encoded in the amino acid sequence. However, it…

生物大分子 · 定量生物学 2007-05-23 Akira R. Kinjo , Ken Nishikawa

Cellular patterns formed by self-organization of dislocations are a most conspicuous feature of dislocation microstructure evolution during plastic deformation. To elucidate the physical mechanisms underlying dislocation cell structure…

材料科学 · 物理学 2020-07-20 Ronghai Wu , Michael Zaiser

The ability to computationally generate novel yet physically foldable protein structures could lead to new biological discoveries and new treatments targeting yet incurable diseases. Despite recent advances in protein structure prediction,…

生物大分子 · 定量生物学 2022-11-28 Kevin E. Wu , Kevin K. Yang , Rianne van den Berg , James Y. Zou , Alex X. Lu , Ava P. Amini

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…

We model the spatiotemporal dynamics of cellular protein concentrations near membranes composed of different lipids using a three-variable continuum model for membrane-bound protein, cytosolic protein, and the local composition of a binary…

软凝聚态物质 · 物理学 2026-03-26 Benjamin Winkler , Sergio Alonso , Markus Bär

Theory of multi-dimensional representation of free energy surface of protein folding is developed by adopting structural order parameters of multiple regions in protein as multiple coordinates. Various scenarios of folding are classified in…

生物大分子 · 定量生物学 2009-11-13 Kazuhito Itoh , Masaki Sasai

Protein folding, peptide aggregation and crystallization, as well as adsorption of molecules on soft or solid substrates have an essential feature in common: In all these processes, structure formation is guided by a collective, cooperative…

统计力学 · 物理学 2009-02-12 Michael Bachmann , Wolfhard Janke

From tumour invasion to cell sorting and animal territoriality, many biological systems rely on nonlocal interactions that drive complex spatial organisation. Partial differential equations (PDEs) with nonlocal advection are increasingly…

种群与进化 · 定量生物学 2025-06-03 Valeria Giunta , Thomas Hillen , Mark A. Lewis , Jonathan R. Potts

Motivation: Thanks to the recent advances in structural biology, nowadays three-dimensional structures of various proteins are solved on a routine basis. A large portion of these contain structural repetitions or internal symmetries. To…

定量方法 · 定量生物学 2018-10-30 Guillaume Pagès , Sergei Grudinin

Biological membranes are dynamic surfaces whose shape and function are critically influenced by protein inclusions (PIs). While membrane deformations induced by PIs have been extensively studied in the small-deformation regime, a variety of…

生物物理 · 物理学 2026-01-23 Gaetano Ferraro , Michele Castellana

Predicting the 3D conformation of small molecules within protein binding sites is a key challenge in drug design. When a crystallized reference ligand (template) is available, it provides geometric priors that can guide 3D pose prediction.…

生物大分子 · 定量生物学 2025-10-03 Noémie Bergues , Arthur Carré , Paul Join-Lambert , Brice Hoffmann , Arnaud Blondel , Hamza Tajmouati

A reduced model, which can fold both helix and sheet structures, is proposed to study the problem of protein folding. The goal of this model is to find an unbiased effective potential that has included the effects of water and at the same…

软凝聚态物质 · 物理学 2007-05-23 Nan-yow Chen

We model the self-organization of the MinE ring that is observed during subcellular oscillations of the proteins MinD and MinE within the rod-shaped bacterium {\it Escherichia coli}. With a steady-state approximation, we can study the…

亚细胞过程 · 定量生物学 2009-06-10 Julien Derr , Jason T. Hopper , Anirban Sain , Andrew D. Rutenberg

Despite significant progress in static protein structure collection and prediction, the dynamic behavior of proteins, one of their most vital characteristics, has been largely overlooked in prior research. This oversight can be attributed…

Protein structure prediction and folding are fundamental to understanding biology, with recent deep learning advances reshaping the field. Diffusion-based generative models have revolutionized protein design, enabling the creation of novel…

机器学习 · 计算机科学 2025-10-01 Yogesh Verma , Markus Heinonen , Vikas Garg

The paradigm that the primary amino acid sequence prescribes structure and thus function has for a long time been central to the understanding of protein science. Though the theory is supported by the behaviour of most structured proteins,…

生物物理 · 物理学 2022-12-19 Rickie Xian , Sarah Rauscher

We consider the hydrodynamics of lipid bilayers containing transmembrane proteins of arbitrary shape. This biologically-motivated problem is relevant to the cell membrane, whose fluctuating dynamics play a key role in phenomena ranging from…

软凝聚态物质 · 物理学 2016-10-10 Andrew Callan-Jones , Marc Durand , Jean-Baptiste Fournier

Deep generative models have been applied with increasing success to the generation of two dimensional molecules as SMILES strings and molecular graphs. In this work we describe for the first time a deep generative model that can generate 3D…

化学物理 · 物理学 2020-11-24 Tomohide Masuda , Matthew Ragoza , David Ryan Koes

Generating molecules that bind to specific proteins is an important but challenging task in drug discovery. Previous works usually generate atoms in an auto-regressive way, where element types and 3D coordinates of atoms are generated one…

生物大分子 · 定量生物学 2024-07-16 Haitao Lin , Yufei Huang , Odin Zhang , Siqi Ma , Meng Liu , Xuanjing Li , Lirong Wu , Jishui Wang , Tingjun Hou , Stan Z. Li