LocPro: A deep learning-based prediction of protein subcellular localization for promoting multi-directional pharmaceutical research
Drug development encompasses multiple processes, wherein protein subcellular localization is essential. It promotes target identification, treatment development, and the design of drug delivery systems. In this research, a deep learning framework called LocPro is presented for predicting protein sub...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-08-01
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| Series: | Journal of Pharmaceutical Analysis |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2095177925000723 |
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| author | Yintao Zhang Lingyan Zheng Nanxin You Wei Hu Wanghao Jiang Mingkun Lu Hangwei Xu Haibin Dai Tingting Fu Ying Zhou |
| author_facet | Yintao Zhang Lingyan Zheng Nanxin You Wei Hu Wanghao Jiang Mingkun Lu Hangwei Xu Haibin Dai Tingting Fu Ying Zhou |
| author_sort | Yintao Zhang |
| collection | DOAJ |
| description | Drug development encompasses multiple processes, wherein protein subcellular localization is essential. It promotes target identification, treatment development, and the design of drug delivery systems. In this research, a deep learning framework called LocPro is presented for predicting protein subcellular localization. Specifically, LocPro is unique in (a) combining protein representations from the pre-trained large language model (LLM) ESM2 and the expert-driven tool PROFEAT, (b) implementing a hybrid deep neural network architecture that integrates convolutional neural network (CNN), fully connected (FC) layer, and bidirectional long short-term memory (BiLSTM) blocks, and (c) developing a multi-label framework for predicting protein subcellular localization at multiple granularity levels. Additionally, a dataset was curated and divided using a homology-based strategy for training and validation. Comparative analyses show that LocPro outperforms existing methods in sequence-based multi-label protein subcellular localization prediction. The practical utility of this framework is further demonstrated through case studies on drug target subcellular localization. All in all, LocPro serves as a valuable complement to existing protein localization prediction tools. The web server is freely accessible at https://idrblab.org/LocPro/. |
| format | Article |
| id | doaj-art-45f5f8ed76544afaa0a6c0455cda5f17 |
| institution | Kabale University |
| issn | 2095-1779 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Pharmaceutical Analysis |
| spelling | doaj-art-45f5f8ed76544afaa0a6c0455cda5f172025-08-20T03:41:40ZengElsevierJournal of Pharmaceutical Analysis2095-17792025-08-0115810125510.1016/j.jpha.2025.101255LocPro: A deep learning-based prediction of protein subcellular localization for promoting multi-directional pharmaceutical researchYintao Zhang0Lingyan Zheng1Nanxin You2Wei Hu3Wanghao Jiang4Mingkun Lu5Hangwei Xu6Haibin Dai7Tingting Fu8Ying Zhou9Department of Pharmacy, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China; College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, ChinaDepartment of Pharmacy, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China; College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, ChinaCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, ChinaDepartment of Pharmacy, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, ChinaCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, ChinaCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, ChinaCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, ChinaDepartment of Pharmacy, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China; Corresponding author.Department of Pharmacy, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China; Corresponding author.Department of Pharmacy, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, China; Corresponding author.Drug development encompasses multiple processes, wherein protein subcellular localization is essential. It promotes target identification, treatment development, and the design of drug delivery systems. In this research, a deep learning framework called LocPro is presented for predicting protein subcellular localization. Specifically, LocPro is unique in (a) combining protein representations from the pre-trained large language model (LLM) ESM2 and the expert-driven tool PROFEAT, (b) implementing a hybrid deep neural network architecture that integrates convolutional neural network (CNN), fully connected (FC) layer, and bidirectional long short-term memory (BiLSTM) blocks, and (c) developing a multi-label framework for predicting protein subcellular localization at multiple granularity levels. Additionally, a dataset was curated and divided using a homology-based strategy for training and validation. Comparative analyses show that LocPro outperforms existing methods in sequence-based multi-label protein subcellular localization prediction. The practical utility of this framework is further demonstrated through case studies on drug target subcellular localization. All in all, LocPro serves as a valuable complement to existing protein localization prediction tools. The web server is freely accessible at https://idrblab.org/LocPro/.http://www.sciencedirect.com/science/article/pii/S2095177925000723Protein subcellular locationPharmaceutical researchProtein large language modelMulti-label prediction |
| spellingShingle | Yintao Zhang Lingyan Zheng Nanxin You Wei Hu Wanghao Jiang Mingkun Lu Hangwei Xu Haibin Dai Tingting Fu Ying Zhou LocPro: A deep learning-based prediction of protein subcellular localization for promoting multi-directional pharmaceutical research Journal of Pharmaceutical Analysis Protein subcellular location Pharmaceutical research Protein large language model Multi-label prediction |
| title | LocPro: A deep learning-based prediction of protein subcellular localization for promoting multi-directional pharmaceutical research |
| title_full | LocPro: A deep learning-based prediction of protein subcellular localization for promoting multi-directional pharmaceutical research |
| title_fullStr | LocPro: A deep learning-based prediction of protein subcellular localization for promoting multi-directional pharmaceutical research |
| title_full_unstemmed | LocPro: A deep learning-based prediction of protein subcellular localization for promoting multi-directional pharmaceutical research |
| title_short | LocPro: A deep learning-based prediction of protein subcellular localization for promoting multi-directional pharmaceutical research |
| title_sort | locpro a deep learning based prediction of protein subcellular localization for promoting multi directional pharmaceutical research |
| topic | Protein subcellular location Pharmaceutical research Protein large language model Multi-label prediction |
| url | http://www.sciencedirect.com/science/article/pii/S2095177925000723 |
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