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Predicting protein secondary structure is a fundamental problem in protein structure prediction. Here we present a new supervised generative stochastic network (GSN) based method to predict local secondary structure with deep hierarchical…

Quantitative Methods · Quantitative Biology 2014-03-07 Jian Zhou , Olga G. Troyanskaya

A fundamental goal of research in molecular biology is to understand protein structure. Protein crystallography is currently the most successful method for determining the three-dimensional (3D) conformation of a protein, yet it remains…

Artificial Intelligence · Computer Science 2014-11-17 L. Leherte , J. Glasgow , K. Baxter , E. Steeg , S. Fortier

Protein quantification and analysis are well-accepted approaches for biomarker discovery but are limited to identification without structural information. High-throughput omics data (i.e., genomics, transcriptomics, and proteomics) have…

Quantitative Methods · Quantitative Biology 2025-06-13 Lucas Wilken , Nihjum Paul , Troy Timmerman , Sara A. Tolba , Amara Arshad , Di Wu , Wenjie Xia , Bakhtiyor Rasulev , Rick Jansen , Dali Sun

Recent advancements in protein structure prediction, particularly AlphaFold2, have revolutionized structural biology by achieving near-experimental accuracy ($\text{average RMSD} < 1.5\text{\AA}$). However, the computational demands of…

Biomolecules · Quantitative Biology 2025-06-09 Joongwon Chae , Zhenyu Wang , Ijaz Gul , Jiansong Ji , Zhenglin Chen , Peiwu Qin

Highly accurate biomolecular structure prediction is a key component of developing biomolecular foundation models, and one of the most critical aspects of building foundation models is identifying the recipes for scaling the model. In this…

Biomolecules · Quantitative Biology 2026-01-02 Yi Zhou , Chan Lu , Yiming Ma , Wei Qu , Fei Ye , Kexin Zhang , Lan Wang , Minrui Gui , Quanquan Gu

Protein structures and functions are determined by a contiguous arrangement of amino acid sequences. Designing novel protein sequences and structures with desired geometry and functions is a complex task with large state spaces. Here we…

Chemical Physics · Physics 2022-09-01 Xeerak Agha , Nihang Fu , Jianjun Hu

Predicting protein secondary structure using lattice model is one of the most studied computational problem in bioinformatics. Here secondary structure or three dimensional structure of protein is predicted from its amino acid sequence.…

Computational Engineering, Finance, and Science · Computer Science 2014-07-18 Dipan Lal Shaw , M. Sohel Rahman , A. S. M. Sohidull Islam , Shuvasish Karmaker

The biological functions of proteins often depend on dynamic structural ensembles. In this work, we develop a flow-based generative modeling approach for learning and sampling the conformational landscapes of proteins. We repurpose highly…

Biomolecules · Quantitative Biology 2024-09-04 Bowen Jing , Bonnie Berger , Tommi Jaakkola

Pocket representations play a vital role in various biomedical applications, such as druggability estimation, ligand affinity prediction, and de novo drug design. While existing geometric features and pretrained representations have…

Machine Learning · Computer Science 2024-03-08 Bowen Gao , Yinjun Jia , Yuanle Mo , Yuyan Ni , Weiying Ma , Zhiming Ma , Yanyan Lan

Proteins are biological polymers that underlie all cellular functions. The first high-resolution protein structures were determined by x-ray crystallography in the 1960s. Since then, there has been continued interest in understanding and…

Soft Condensed Matter · Physics 2017-06-20 Jennifer C. Gaines , Abram H. Clark , Lynne Regan , Corey S. O'Hern

MicroRNAs (miRNAs) are endogenous small non-coding RNAs that play an important role in post-transcriptional gene regulation. However, the experimental determination of miRNA sequence and structure is both expensive and time-consuming.…

Genomics · Quantitative Biology 2021-06-30 Shyaman Jayasundara , Sandali Lokuge , Puwasuru Ihalagedara , Damayanthi Herath

Protein-protein interactions (PPIs) are essentials for many biological processes where two or more proteins physically bind together to achieve their functions. Modeling PPIs is useful for many biomedical applications, such as vaccine…

Biomolecules · Quantitative Biology 2021-12-10 Yang Xue , Zijing Liu , Xiaomin Fang , Fan Wang

Although machine learning has transformed protein structure prediction of folded protein ground states with remarkable accuracy, intrinsically disordered proteins and regions (IDPs/IDRs) are defined by diverse and dynamical structural…

Biomolecules · Quantitative Biology 2025-04-01 Oufan Zhang , Zi Hao Liu , Julie D Forman-Kay , Teresa Head-Gordon

Protein folding cooperativity is defined by the nature of the finite-size thermodynamic transition exhibited upon folding: two-state transitions show a free energy barrier between the folded and unfolded ensembles, while downhill folding is…

Biomolecules · Quantitative Biology 2017-08-23 Tristan Bereau , Michael Bachmann , Markus Deserno

The computer artificial intelligence system AlphaFold has recently predicted previously unknown three-dimensional structures of thousands of proteins. Focusing on the subset with high-confidence scores, we algorithmically analyze these…

Biomolecules · Quantitative Biology 2022-07-18 Maarten A. Brems , Robert Runkel , Todd O. Yeates , Peter Virnau

The field of protein folding research has been greatly advanced by deep learning methods, with AlphaFold2 (AF2) demonstrating exceptional performance and atomic-level precision. As co-evolution is integral to protein structure prediction,…

Quantitative Methods · Quantitative Biology 2023-06-06 Le Zhang , Jiayang Chen , Tao Shen , Yu Li , Siqi Sun

Designing novel proteins with desired functions is crucial in biology and chemistry. However, most existing work focus on protein sequence design, leaving protein sequence and structure co-design underexplored. In this paper, we propose…

Machine Learning · Computer Science 2023-10-05 Zhenqiao Song , Yunlong Zhao , Yufei Song , Wenxian Shi , Yang Yang , Lei Li

Proteins, by virtue of their central role in most biological processes, represent one of the key subjects of the study of molecular evolution. Inherent to the indispensability of proteins for living cells is the fact that a given protein…

Biomolecules · Quantitative Biology 2007-05-23 Eric J. Deeds , Eugene I. Shakhnovich

Proteolysis targeting chimeras (PROTACs) are small molecules that trigger the breakdown of traditionally ``undruggable'' proteins by binding simultaneously to their targets and degradation-associated proteins. A key challenge in their…

Biomolecules · Quantitative Biology 2024-05-14 Bo Qiang , Wenxian Shi , Yuxuan Song , Menghua Wu

Achieving a comprehensive understanding of the behaviour of proteins is greatly facilitated by the knowledge of their structures, thermodynamics and dynamics. All this information can be provided in an effective manner in terms of…

Quantitative Methods · Quantitative Biology 2019-03-27 Massimiliano Bonomi , Michele Vendruscolo