SDMap: a comprehensive database of spatial drug perturbation maps

The arrangement patterns and spatial distribution features of cells within tissues are key regulators of drug actions and cellular responses; however, the specific spatial microenvironment that mediates drug actions and efficacy remains to be elucidated. Here, we introduce SDMap (http://bio-bigdata.hrbmu.edu.cn/SDMap/), a database to dissect the spatial distributions of drug-associated cells and spatial contexts that contribute to drug actions. SDMap establishes connections between 5 490 079 spatial locations (spots/cells) derived from 989 slices of 35 human tissues (including disease-state slices) and 538 419 instances across 33 149 drugs. It also offers 10 user-friendly tools for retrieving and analyzing: (i) associations between drug-associated instances and spatial spots/cells, niches, or cell types; (ii) the influence of spatial drug target activity on drug actions; (iii) drug-associated instances exhibiting highly variable spatial perturbation effects; (iv) the perturbation effects of drug dosage and duration on the spatial microenvironment; (v) spatial differentiation trajectories of drug-perturbed cells; (vi) the impact of spatial cellular functional activity on drug perturbation; (vii) spatial perturbation effect maps of drug combinations; and (viii) 3D maps of drug perturbation effects within spatial tissue contexts. SDMap is anticipated to yield critical insights into how spatial heterogeneity influences drug actions, and serve as a comprehensive database for identifying spatially resolved precision therapy targets and elucidating drug-associated mechanisms.

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Publication Details

Journal
Nucleic Acids Research
Published
2025-10-22
DOI
https://doi.org/10.1093/nar/gkaf1046
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00

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article

SDMap: a comprehensive database of spatial drug perturbation maps

Xinguo Ye, Yunpeng Zhang, Chunlong Zhang, Wenli Fan et al.
Nucleic Acids Research
Single-cell and spatial transcriptomics
article

SDMap: a comprehensive database of spatial drug perturbation maps

Xinguo Ye, Yunpeng Zhang, Chunlong Zhang, Wenli Fan, Liying Pei, Zheng Zha, Xinyu Song, Alex Kang, Zhe Chen, Yifang Zhang, Yanjun Xu, Wensong Liu, Feng Li, Qi Quan
article en

Abstract

The arrangement patterns and spatial distribution features of cells within tissues are key regulators of drug actions and cellular responses; however, the specific spatial microenvironment that mediates drug actions and efficacy remains to be elucidated. Here, we introduce SDMap (http://bio-bigdata.hrbmu.edu.cn/SDMap/), a database to dissect the spatial distributions of drug-associated cells and spatial contexts that contribute to drug actions. SDMap establishes connections between 5 490 079 spatial locations (spots/cells) derived from 989 slices of 35 human tissues (including disease-state slices) and 538 419 instances across 33 149 drugs. It also offers 10 user-friendly tools for retrieving and analyzing: (i) associations between drug-associated instances and spatial spots/cells, niches, or cell types; (ii) the influence of spatial drug target activity on drug actions; (iii) drug-associated instances exhibiting highly variable spatial perturbation effects; (iv) the perturbation effects of drug dosage and duration on the spatial microenvironment; (v) spatial differentiation trajectories of drug-perturbed cells; (vi) the impact of spatial cellular functional activity on drug perturbation; (vii) spatial perturbation effect maps of drug combinations; and (viii) 3D maps of drug perturbation effects within spatial tissue contexts. SDMap is anticipated to yield critical insights into how spatial heterogeneity influences drug actions, and serve as a comprehensive database for identifying spatially resolved precision therapy targets and elucidating drug-associated mechanisms.

Nucleic Acids ResearchVol. 54(D1)
Harbin Medical University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Heilongjiang Province
Openalex Percentile: Top 73%
Single-cell and spatial transcriptomics
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