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Cold-start drug-target interaction (DTI) prediction focuses on interaction between novel drugs and proteins. Previous methods typically learn transferable interaction patterns between structures of drug and proteins to tackle it. However,…

Machine Learning · Computer Science 2025-10-07 Ziying Zhang , Yaqing Wang , Yuxuan Sun , Min Ye , Quanming Yao

The Automated Protein Structure Analysis (APSA) method is used for the classification of supersecondary structures. Basis for the classification is the encoding of three-dimensional (3D) residue conformations into a 16-letter code (3D-1D…

Quantitative Methods · Quantitative Biology 2008-11-24 Sushilee Ranganathan , Dmitry Izotov , Elfi Kraka , Dieter Cremer

Local protein structure analysis is informative to protein structure analysis and has been used successfully in protein structure prediction and others. Proteins have recurring structural features, such as helix caps and beta turns, which…

Combinatorics · Mathematics 2007-10-26 Naoto Morikawa

The rapid growth in the number of experimental and predicted protein structures and more complicated protein structures challenge users in computational biology for utilizing the structural information and protein surface property…

Quantitative Methods · Quantitative Biology 2023-08-08 Junkang Wei , Jin Xiao , Siyuan Chen , Licheng Zong , Xin Gao , Yu Li

The cornerstone of computational drug design is the calculation of binding affinity between two biological counterparts, especially a chemical compound, i.e., a ligand, and a protein. Predicting the strength of protein-ligand binding with…

Biomolecules · Quantitative Biology 2019-12-04 Yanjun Li , Mohammad A. Rezaei , Chenglong Li , Xiaolin Li , Dapeng Wu

The binding between proteins and ligands plays a crucial role in the realm of drug discovery. Previous deep learning approaches have shown promising results over traditional computationally intensive methods, but resulting in poor…

Biomolecules · Quantitative Biology 2023-11-29 Shikun Feng , Minghao Li , Yinjun Jia , Weiying Ma , Yanyan Lan

Predicting compound-protein affinity is critical for accelerating drug discovery. Recent progress made by machine learning focuses on accuracy but leaves much to be desired for interpretability. Through molecular contacts underlying…

Biomolecules · Quantitative Biology 2020-01-01 Mostafa Karimi , Di Wu , Zhangyang Wang , Yang Shen

Protein-Protein Interactions (PPIs) are fundamental in various biological processes and play a key role in life activities. The growing demand and cost of experimental PPI assays require computational methods for efficient PPI prediction.…

Machine Learning · Computer Science 2024-02-23 Lirong Wu , Yijun Tian , Yufei Huang , Siyuan Li , Haitao Lin , Nitesh V Chawla , Stan Z. Li

Proteins are the major building blocks of life, and actuators of almost all chemical and biophysical events in living organisms. Their native structures in turn enable their biological functions which have a fundamental role in drug design.…

We demonstrate that Protein-Protein Interaction (PPI) networks in several eucaryotic organisms contain significantly more self-interacting proteins than expected if such homodimers randomly appeared in the course of the evolution. We also…

Genomics · Quantitative Biology 2007-05-23 Iaroslav Ispolatov , Anton Yuryev , Ilya Mazo , Sergei Maslov

Complexes of physically interacting proteins constitute fundamental functional units responsible for driving biological processes within cells. A faithful reconstruction of the entire set of complexes is therefore essential to understand…

Molecular Networks · Quantitative Biology 2015-05-21 Sriganesh Srihari , Chern Han Yong , Ashwini Patil , Limsoon Wong

Protein-protein interaction (PPI) networks, providing a comprehensive landscape of protein interacting patterns, enable us to explore biological processes and cellular components at multiple resolutions. For a biological process, a number…

Molecular Networks · Quantitative Biology 2016-04-13 Xiuli Ma , Guangyu Zhou , Jingjing Wang , Jian Peng , Jiawei Han

Predicting protein structure from amino acid sequence is one of the most important unsolved problems of molecular biology and biophysics.Not only would a successful prediction algorithm be a tremendous advance in the understanding of the…

Computational Engineering, Finance, and Science · Computer Science 2010-06-15 K. K Senapati , G. Sahoo , D. Bhaumik

Accurate identification of protein nucleic-acid-binding residues poses a significant challenge with important implications for various biological processes and drug design. Many typical computational methods for protein analysis rely on a…

Biomolecules · Quantitative Biology 2023-12-21 Linglin Jing , Sheng Xu , Yifan Wang , Yuzhe Zhou , Tao Shen , Zhigang Ji , Hui Fang , Zhen Li , Siqi Sun

Protein-ligand interactions are one of the fundamental types of molecular interactions in living systems. Ligands are small molecules that interact with protein molecules at specific regions on their surfaces called binding sites. Tasks…

Biomolecules · Quantitative Biology 2020-08-11 Arnab Bhadra , Kalidas Y

The field of protein-ligand pose prediction has seen significant advances in recent years, with machine learning-based methods now being commonly used in lieu of classical docking methods or even to predict all-atom protein-ligand complex…

Biomolecules · Quantitative Biology 2024-10-01 David Errington , Constantin Schneider , Cédric Bouysset , Frédéric A. Dreyer

Targeted protein degradation (TPD) induced by small molecules has emerged as a rapidly evolving modality in drug discovery, targeting proteins traditionally considered "undruggable". Proteolysis-targeting chimeras (PROTACs) and molecular…

Biomolecules · Quantitative Biology 2025-02-27 Fanglei Xue , Meihan Zhang , Shuqi Li , Xinyu Gao , James A. Wohlschlegel , Wenbing Huang , Yi Yang , Weixian Deng

Determining the structure of a protein has been a decades-long open question. A protein's three-dimensional structure often poses nontrivial computation costs, when classical simulation algorithms are utilized. Advances in the transformer…

Machine Learning · Computer Science 2023-10-09 Chen Dun , Qiutai Pan , Shikai Jin , Ria Stevens , Mitchell D. Miller , George N. Phillips, , Anastasios Kyrillidis

Despite an explosion in the number of experimentally determined, atomically detailed structures of biomolecules, many critical tasks in structural biology remain data-limited. Whether performance in such tasks can be improved by using large…

Biomolecules · Quantitative Biology 2019-12-30 Raphael J. L. Townshend , Rishi Bedi , Patricia A. Suriana , Ron O. Dror

The worldwide surge of multiresistant microbial strains has propelled the search for alternative treatment options. The study of Protein-Protein Interactions (PPIs) has been a cornerstone in the clarification of complex physiological and…

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