The article introduces the fifth release of STITCH (Search Tool for Interacting Chemicals), a comprehensive resource for protein–chemical interaction networks. The updated version integrates data from various sources, including high-throughput experiments, curated datasets, and prediction methods, to create a global network of over 9.6 million proteins and 430,000 chemicals. Key features of this release include: 1. **Network View with Binding Affinities**: Users can now view binding affinities of chemicals in the interaction network, providing insights into the potential effects of chemicals on their interaction partners. 2. **Tissue-Specific Filtering**: A new functionality allows users to filter the network to show only proteins and chemicals associated with a specific tissue, addressing the issue of spatial expression differences among proteins. 3. **Data Sources**: The network is built using data from manually curated datasets (e.g., DrugBank, GPCR-ligand database) and experimentally validated datasets (e.g., ChEMBL, PDSP K_i Database). Automated text mining and structure-based prediction methods also contribute to the network. 4. **Display of Binding Affinities**: The network view now includes the binding affinity (K_i) of protein–chemical interactions, which helps users understand the strength and confidence of these interactions. 5. **Tissue-Specific Data Integration**: Tissue-specific protein expression patterns from resources like TISSUES and the Expression Atlas are integrated to filter the network based on tissue expression. The article also highlights use cases where STITCH has been utilized for various purposes, including small- to medium-scale analyses, large-scale analyses, and the development of new web-based resources and prediction methods. The authors acknowledge the contributions of various individuals and institutions and provide funding details.The article introduces the fifth release of STITCH (Search Tool for Interacting Chemicals), a comprehensive resource for protein–chemical interaction networks. The updated version integrates data from various sources, including high-throughput experiments, curated datasets, and prediction methods, to create a global network of over 9.6 million proteins and 430,000 chemicals. Key features of this release include: 1. **Network View with Binding Affinities**: Users can now view binding affinities of chemicals in the interaction network, providing insights into the potential effects of chemicals on their interaction partners. 2. **Tissue-Specific Filtering**: A new functionality allows users to filter the network to show only proteins and chemicals associated with a specific tissue, addressing the issue of spatial expression differences among proteins. 3. **Data Sources**: The network is built using data from manually curated datasets (e.g., DrugBank, GPCR-ligand database) and experimentally validated datasets (e.g., ChEMBL, PDSP K_i Database). Automated text mining and structure-based prediction methods also contribute to the network. 4. **Display of Binding Affinities**: The network view now includes the binding affinity (K_i) of protein–chemical interactions, which helps users understand the strength and confidence of these interactions. 5. **Tissue-Specific Data Integration**: Tissue-specific protein expression patterns from resources like TISSUES and the Expression Atlas are integrated to filter the network based on tissue expression. The article also highlights use cases where STITCH has been utilized for various purposes, including small- to medium-scale analyses, large-scale analyses, and the development of new web-based resources and prediction methods. The authors acknowledge the contributions of various individuals and institutions and provide funding details.