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A novel approach for structure alignment is presented, where the key ingredients are: (1) An error function formulation of the problem simultaneously in terms of binary (Potts) assignment variables and real-valued atomic coordinates. (2)…

Biological Physics · Physics 2007-05-23 M. Ohlsson , C. Peterson , M. Ringner , R. Blankenbecler

The protein folding problem has attracted an increasing attention from physicists. The problem has a flavor of statistical mechanics, but possesses the most common feature of most biological problems -- the profound effects of evolution. I…

Statistical Mechanics · Physics 2009-10-31 Chao Tang

We present a sequence-based probabilistic formalism that directly addresses co-operative effects in networks of interacting positions in proteins, providing significantly improved contact prediction, as well as accurate quantitative…

Quantitative Methods · Quantitative Biology 2012-07-12 Alan Lapedes , Bertrand Giraud , Christopher Jarzynski

Proteins populate a manifold in the high-dimensional sequence space whose geometrical structure guides their natural evolution. Leveraging recently-developed structure prediction tools based on transformer models, we first examine the…

Biomolecules · Quantitative Biology 2023-11-13 A. Zambon , R. Zecchina , G. Tiana

Predicting protein secondary structures such as alpha helices, beta sheets, and coils from amino acid sequences is essential for understanding protein function. This work presents a transformer-based model that applies attention mechanisms…

Artificial Intelligence · Computer Science 2025-12-10 Manzi Kevin Maxime

We use a free energy functional theory to elucidate general properties of heterogeneously ordering, fast folding proteins, and we test our conclusions with lattice simulations. We find that both structural and energetic heterogeneity can…

Disordered Systems and Neural Networks · Physics 2009-10-31 Steven S. Plotkin , Jose N. Onuchic

How do protein structure prediction models fold proteins? We investigate this question by tracing how ESMFold folds a beta hairpin, a prevalent structural motif. Through counterfactual interventions on model latents, we identify two…

Machine Learning · Computer Science 2026-02-10 Kevin Lu , Jannik Brinkmann , Stefan Huber , Aaron Mueller , Yonatan Belinkov , David Bau , Chris Wendler

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…

Biomolecules · Quantitative Biology 2026-04-09 Aydin Wells , Khalique Newaz , Jennifer Morones , Jianlin Cheng , Tijana Milenković

Protein structure prediction is pivotal for understanding the structure-function relationship of proteins, advancing biological research, and facilitating pharmaceutical development and experimental design. While deep learning methods and…

Machine Learning · Computer Science 2024-12-30 Kaihui Cheng , Ce Liu , Qingkun Su , Jun Wang , Liwei Zhang , Yining Tang , Yao Yao , Siyu Zhu , Yuan Qi

We inquire to what extent protein peptide plane and side chain dynamics can be reconstructed from knowledge of C-alpha dynamics. Due to lack of experimental data we analyze all atom molecular dynamics trajectories from Anton supercomputer,…

Biomolecules · Quantitative Biology 2019-01-23 Jiaojiao Liu , Jin Dai , Jianfeng He , Xubiao Peng , Antti J. Niemi

Although, several factors have been attributed to thermostability, the stabilization strategies used by proteins are still enigmatic. Studies on recombinant xylanase which has the ubiquitous (\b{eta}/{\alpha})8 TIM (Triosephosphate…

Biomolecules · Quantitative Biology 2015-01-13 P. Mahanta , A. Bhardwaj , K. Kumar , V. S. Reddy , S. Ramakumar

Proteins are essential for almost all biological processes and derive their diverse functions from complex 3D structures, which are in turn determined by their amino acid sequences. In this paper, we exploit the rich biological inductive…

Protein structures are a very special class among all possible structures. It was suggested that a ``designability principle'' plays a crucial role in nature's selection of protein sequences and structures. Here we provide a theoretical…

Statistical Mechanics · Physics 2009-10-30 Hao Li , Chao Tang , Ned S. Wingreen

Protein folding is the intricate process by which a linear sequence of amino acids self-assembles into a unique three-dimensional structure. Protein folding kinetics is the study of pathways and time-dependent mechanisms a protein undergoes…

Machine Learning · Computer Science 2023-09-19 Vijay Arvind. R , Haribharathi Sivakumar , Brindha. R

Increasing evidence suggests that chromosome folding and genetic expression are intimately connected. For example, the co-expression of a large number of genes can benefit from their spatial co-localization in the cellular space.…

Soft Condensed Matter · Physics 2018-03-13 Guillaume Le Treut

Understanding how monomeric proteins fold under in vitro conditions is crucial to describing their functions in the cellular context. Significant advances both in theory and experiments have resulted in a conceptual framework for describing…

Soft Condensed Matter · Physics 2010-07-20 D. Thirumalai , Edward P. O'Brien , Greg Morrison , Changbong Hyeon

We study four citrate synthase homodimeric proteins within a structure-based coarse-grained model. Two of these proteins come from thermophilic bacteria, one from a cryophilic bacterium and one from a mesophilic organism; three are in the…

Biomolecules · Quantitative Biology 2015-02-26 Bartosz Rozycki , Marek Cieplak

Many unicellular organisms allocate their key proteins asymmetrically between the mother and daughter cells, especially in a stressed environment. A recent theoretical model is able to predict when the asymmetry in segregation of key…

Populations and Evolution · Quantitative Biology 2021-08-11 Jiseon Min , Ariel Amir

In the protein sequence space, natural proteins form clusters of families which are characterized by their unique native folds whereas the great majority of random polypeptides are neither clustered nor foldable to unique structures. Since…

Biomolecules · Quantitative Biology 2018-02-06 Akira R. Kinjo

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…

Machine Learning · Computer Science 2025-10-01 Yogesh Verma , Markus Heinonen , Vikas Garg