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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

In this paper we address the problem of protein classification starting from a multi-view 2D representation of proteins. From each 3D protein structure, a large set of 2D projections is generated using the protein visualization software…

Computer Vision and Pattern Recognition · Computer Science 2019-10-30 Loris Nanni , Alessandra Lumini , Federica Pasquali , Sheryl Brahnam

Proteins are essential for maintaining life. For example, knowing the structure of a protein, cell regulatory mechanisms of organisms can be modeled, supporting the development of disease treatments or the understanding of relationships…

Biomolecules · Quantitative Biology 2019-01-07 Daniel Bonetti , Alexandre Delbem , Dorival Leão , Jochen Einbeck

Analyzing the structure of proteins is a key part of understanding their functions and thus their role in biology at the molecular level. In addition, design new proteins in a methodical way is a major engineering challenge. In this work,…

Computer Vision and Pattern Recognition · Computer Science 2021-06-23 Hao Huang , Boulbaba Ben Amor , Xichan Lin , Fan Zhu , Yi Fang

Artificial intelligence for scientific discovery has recently generated significant interest within the machine learning and scientific communities, particularly in the domains of chemistry, biology, and material discovery. For these…

Improving the ability to predict protein function can potentially facilitate research in the fields of drug discovery and precision medicine. Technically, the properties of proteins are directly or indirectly reflected in their sequence and…

Biomolecules · Quantitative Biology 2024-11-19 Runze Ma , Chengxin He , Huiru Zheng , Xinye Wang , Haiying Wang , Yidan Zhang , Lei Duan

We propose a model that explains the hierarchical organization of proteins in fold families. The model, which is based on the evolutionary selection of proteins by their native state stability, reproduces patterns of amino acids conserved…

Statistical Mechanics · Physics 2007-05-23 Nikolay V. Dokholyan , Eugene I. Shakhnovich

Predicting interactions between proteins is one of the most important yet challenging problems in structural bioinformatics. Intrinsically, potential function sites in protein surfaces are determined by both geometric and chemical features.…

Biomolecules · Quantitative Biology 2024-01-19 Yiqun Lin , Liang Pan , Yi Li , Ziwei Liu , Xiaomeng Li

Protein structure prediction has reached revolutionary levels of accuracy on single structures, yet distributional modeling paradigms are needed to capture the conformational ensembles and flexibility that underlie biological function.…

Biomolecules · Quantitative Biology 2023-04-06 Bowen Jing , Ezra Erives , Peter Pao-Huang , Gabriele Corso , Bonnie Berger , Tommi Jaakkola

The analysis of the three-dimensional structure of proteins is an important topic in molecular biochemistry. Structure plays a critical role in defining the function of proteins and is more strongly conserved than amino acid sequence over…

Applications · Statistics 2015-01-19 Abel Rodriguez , Scott C. Schmidler

Protein is linked to almost every life process. Therefore, analyzing the biological structure and property of protein sequences is critical to the exploration of life, as well as disease detection and drug discovery. Traditional protein…

Machine Learning · Computer Science 2021-12-08 Yijia Xiao , Jiezhong Qiu , Ziang Li , Chang-Yu Hsieh , Jie Tang

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

Developing accurate and efficient coarse-grained representations of proteins is crucial for understanding their folding, function, and interactions over extended timescales. Our methodology involves simulating proteins with molecular…

Biomolecules · Quantitative Biology 2023-10-11 Carles Navarro , Maciej Majewski , Gianni de Fabritiis

Protein language models often take into consideration the alignment between a protein sequence and its textual description. However, they do not take structural information into consideration. Traditional methods treat sequence and…

Machine Learning · Computer Science 2026-03-10 Aditya Ranganath , Hasin Us Sami , Kowshik Thopalli , Bhavya Kailkhura , Wesam Sakla

We present a novel dual-head deep learning architecture for protein-protein interaction modeling that enables simultaneous prediction of binding affinity ($\Delta G$) and mutation-induced affinity changes ($\Delta\Delta G$) using only…

Quantitative Methods · Quantitative Biology 2025-09-30 Supantha Dey , Ratul Chowdhury

Rapid progress in deep learning has spurred its application to bioinformatics problems including protein structure prediction and design. In classic machine learning problems like computer vision, progress has been driven by standardized…

Biomolecules · Quantitative Biology 2019-02-04 Mohammed AlQuraishi

Amino acid sequence portrays most intrinsic form of a protein and expresses primary structure of protein. The order of amino acids in a sequence enables a protein to acquire a particular stable conformation that is responsible for the…

Machine Learning · Computer Science 2022-08-29 Ashish Ranjan , Md Shah Fahad , David Fernandez-Baca , Akshay Deepak , Sudhakar Tripathi

Protein-Protein Interactions (PPIs) perform essential roles in biological functions. Although some experimental techniques have been developed to detect PPIs, they suffer from high false positive and high false negative rates. Consequently,…

Quantitative Methods · Quantitative Biology 2017-12-29 Samaneh Aghajanbaglo , Sobhan Moosavi , Maseud Rahgozar , Amir Rahimi

How proteins fold remains a central unsolved problem in biology. While the idea of a folding code embedded in the amino acid sequence was introduced more than 6 decades ago, this code remains undefined. While we now have powerful predictive…

Biomolecules · Quantitative Biology 2025-11-04 Carlos Bustamante , Christian Kaiser , Erik Lindahl , Robert Sosa , Giovanni Volpe

Protein interactions are important in a broad range of biological processes. Traditionally, computational methods have been developed to automatically predict protein interface from hand-crafted features. Recent approaches employ deep…

Machine Learning · Computer Science 2020-07-21 Yi Liu , Hao Yuan , Lei Cai , Shuiwang Ji
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