Multimeric protein interaction and complex prediction: Structure, dynamics and function
Understanding the structure, interactions, dynamics, and functions of multimeric protein complexes is essential for studying multimeric protein complexes, with broad implications for disease mechanisms and drug design, and other areas of biomedical research. Although remarkable achievements have bee...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Computational and Structural Biotechnology Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037025001722 |
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| _version_ | 1849387399546667008 |
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| author | Da Lu Shuhong Yu Yixiang Huang Xinqi Gong |
| author_facet | Da Lu Shuhong Yu Yixiang Huang Xinqi Gong |
| author_sort | Da Lu |
| collection | DOAJ |
| description | Understanding the structure, interactions, dynamics, and functions of multimeric protein complexes is essential for studying multimeric protein complexes, with broad implications for disease mechanisms and drug design, and other areas of biomedical research. Although remarkable achievements have been made in monomer prediction in recent years, protein multimers prediction remains a crucial yet challenging area due to their complex structures, diverse physicochemical properties, and limited experimental data. This review encompasses recent advancements in multimer research, providing an overview of classical concepts and methodologies and the key differences from monomer prediction methods. It further explores state-of-the-art advances in CASP16, including predictions of unknown stoichiometries, supercomplexes, conformational ensembles. This review also delves into the contributions of AlphaFold2 & 3 to multimer prediction, highlighting both the successes and limitations, particularly in handling functional protein-protein interactions and dynamical conformations. Recent deep learning methods and their applications in multimer interaction analysis and quality assessment are discussed, along with insights into future research directions, such as improving prediction accuracy, enabling functional interpretation of protein–protein interactions, and reconstructing protein mechanisms. |
| format | Article |
| id | doaj-art-a7e95b0dc3b04068b5f304aee6e74645 |
| institution | Kabale University |
| issn | 2001-0370 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computational and Structural Biotechnology Journal |
| spelling | doaj-art-a7e95b0dc3b04068b5f304aee6e746452025-08-20T03:53:51ZengElsevierComputational and Structural Biotechnology Journal2001-03702025-01-01271975199710.1016/j.csbj.2025.05.009Multimeric protein interaction and complex prediction: Structure, dynamics and functionDa Lu0Shuhong Yu1Yixiang Huang2Xinqi Gong3Mathematical Intelligence Application LAB, Institute for Mathematical Sciences, Renmin University of China, Beijing, China; Bigdata and Responsible Artificial Intelligence for National Governance, Renmin University of China, Beijing, ChinaMathematical Intelligence Application LAB, Institute for Mathematical Sciences, Renmin University of China, Beijing, China; Bigdata and Responsible Artificial Intelligence for National Governance, Renmin University of China, Beijing, ChinaMathematical Intelligence Application LAB, Institute for Mathematical Sciences, Renmin University of China, Beijing, China; Bigdata and Responsible Artificial Intelligence for National Governance, Renmin University of China, Beijing, ChinaMathematical Intelligence Application LAB, Institute for Mathematical Sciences, Renmin University of China, Beijing, China; Bigdata and Responsible Artificial Intelligence for National Governance, Renmin University of China, Beijing, China; Corresponding author.Understanding the structure, interactions, dynamics, and functions of multimeric protein complexes is essential for studying multimeric protein complexes, with broad implications for disease mechanisms and drug design, and other areas of biomedical research. Although remarkable achievements have been made in monomer prediction in recent years, protein multimers prediction remains a crucial yet challenging area due to their complex structures, diverse physicochemical properties, and limited experimental data. This review encompasses recent advancements in multimer research, providing an overview of classical concepts and methodologies and the key differences from monomer prediction methods. It further explores state-of-the-art advances in CASP16, including predictions of unknown stoichiometries, supercomplexes, conformational ensembles. This review also delves into the contributions of AlphaFold2 & 3 to multimer prediction, highlighting both the successes and limitations, particularly in handling functional protein-protein interactions and dynamical conformations. Recent deep learning methods and their applications in multimer interaction analysis and quality assessment are discussed, along with insights into future research directions, such as improving prediction accuracy, enabling functional interpretation of protein–protein interactions, and reconstructing protein mechanisms.http://www.sciencedirect.com/science/article/pii/S2001037025001722Protein multimer predictionProtein dynamicsProtein functionProtein-protein interactionQuality assessmentDeep learning |
| spellingShingle | Da Lu Shuhong Yu Yixiang Huang Xinqi Gong Multimeric protein interaction and complex prediction: Structure, dynamics and function Computational and Structural Biotechnology Journal Protein multimer prediction Protein dynamics Protein function Protein-protein interaction Quality assessment Deep learning |
| title | Multimeric protein interaction and complex prediction: Structure, dynamics and function |
| title_full | Multimeric protein interaction and complex prediction: Structure, dynamics and function |
| title_fullStr | Multimeric protein interaction and complex prediction: Structure, dynamics and function |
| title_full_unstemmed | Multimeric protein interaction and complex prediction: Structure, dynamics and function |
| title_short | Multimeric protein interaction and complex prediction: Structure, dynamics and function |
| title_sort | multimeric protein interaction and complex prediction structure dynamics and function |
| topic | Protein multimer prediction Protein dynamics Protein function Protein-protein interaction Quality assessment Deep learning |
| url | http://www.sciencedirect.com/science/article/pii/S2001037025001722 |
| work_keys_str_mv | AT dalu multimericproteininteractionandcomplexpredictionstructuredynamicsandfunction AT shuhongyu multimericproteininteractionandcomplexpredictionstructuredynamicsandfunction AT yixianghuang multimericproteininteractionandcomplexpredictionstructuredynamicsandfunction AT xinqigong multimericproteininteractionandcomplexpredictionstructuredynamicsandfunction |