Teppei Hayama, Rin Sugawara, Ryo Kamata, Masakazu Sekijima, Kazuki Takeda
{"title":"基于alphafold预测的蛋白质结构蛋白质组的综合分子对接:鉴定青春期少女酸的候选靶蛋白。","authors":"Teppei Hayama, Rin Sugawara, Ryo Kamata, Masakazu Sekijima, Kazuki Takeda","doi":"10.2131/jts.50.309","DOIUrl":null,"url":null,"abstract":"<p><p>Identifying the molecular targets of toxic compounds remains a major challenge in toxicology, particularly when adverse effects occur in off-target organs and the mechanism of action is unknown. To address this issue, a comprehensive computational pipeline was developed to perform high-throughput molecular docking across the entire AlphaFold2-predicted structural proteome of representative organisms such as human and mouse, followed by enrichment analysis to estimate biological processes potentially affected by ligand binding. The pipeline was first evaluated using six known drug-target pairs. In several cases, the known targets were ranked between the top 2 and 250 proteins (top 0.009-1.15%) among more than 21,000 proteins, and displayed docking poses consistent with experimentally observed binding conformations. However, performance was limited for certain targets, such as carbonic anhydrase II with acetazolamide, where the binding pocket was broad, leading to inaccurate docking results. The pipeline was subsequently applied to puberulic acid, a compound suspected of causing severe nephrotoxicity. Screening identified sodium/myo-inositol cotransporter 2 (SLC5A11) as a high-affinity target in both human and mouse, suggesting a mechanism involving disruption of renal osmoregulation. Although docking scores represent only theoretical binding estimates and do not directly imply physiological effects, their distribution was independent of protein length and AlphaFold2 confidence scores (pLDDT), supporting the methodological robustness. This in silico framework enables hypothesis-driven identification of potential target proteins for toxicants or therapeutics and offers a useful tool for predictive toxicology, particularly when experimental data are limited. The pipeline is available at: https://github.com/toxtoxcat/reAlldock.</p>","PeriodicalId":17654,"journal":{"name":"Journal of Toxicological Sciences","volume":"50 7","pages":"309-324"},"PeriodicalIF":1.8000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comprehensive molecular docking on the AlphaFold-predicted protein structure proteome: identifying target protein candidates for puberulic acid.\",\"authors\":\"Teppei Hayama, Rin Sugawara, Ryo Kamata, Masakazu Sekijima, Kazuki Takeda\",\"doi\":\"10.2131/jts.50.309\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Identifying the molecular targets of toxic compounds remains a major challenge in toxicology, particularly when adverse effects occur in off-target organs and the mechanism of action is unknown. 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Screening identified sodium/myo-inositol cotransporter 2 (SLC5A11) as a high-affinity target in both human and mouse, suggesting a mechanism involving disruption of renal osmoregulation. Although docking scores represent only theoretical binding estimates and do not directly imply physiological effects, their distribution was independent of protein length and AlphaFold2 confidence scores (pLDDT), supporting the methodological robustness. This in silico framework enables hypothesis-driven identification of potential target proteins for toxicants or therapeutics and offers a useful tool for predictive toxicology, particularly when experimental data are limited. 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Comprehensive molecular docking on the AlphaFold-predicted protein structure proteome: identifying target protein candidates for puberulic acid.
Identifying the molecular targets of toxic compounds remains a major challenge in toxicology, particularly when adverse effects occur in off-target organs and the mechanism of action is unknown. To address this issue, a comprehensive computational pipeline was developed to perform high-throughput molecular docking across the entire AlphaFold2-predicted structural proteome of representative organisms such as human and mouse, followed by enrichment analysis to estimate biological processes potentially affected by ligand binding. The pipeline was first evaluated using six known drug-target pairs. In several cases, the known targets were ranked between the top 2 and 250 proteins (top 0.009-1.15%) among more than 21,000 proteins, and displayed docking poses consistent with experimentally observed binding conformations. However, performance was limited for certain targets, such as carbonic anhydrase II with acetazolamide, where the binding pocket was broad, leading to inaccurate docking results. The pipeline was subsequently applied to puberulic acid, a compound suspected of causing severe nephrotoxicity. Screening identified sodium/myo-inositol cotransporter 2 (SLC5A11) as a high-affinity target in both human and mouse, suggesting a mechanism involving disruption of renal osmoregulation. Although docking scores represent only theoretical binding estimates and do not directly imply physiological effects, their distribution was independent of protein length and AlphaFold2 confidence scores (pLDDT), supporting the methodological robustness. This in silico framework enables hypothesis-driven identification of potential target proteins for toxicants or therapeutics and offers a useful tool for predictive toxicology, particularly when experimental data are limited. The pipeline is available at: https://github.com/toxtoxcat/reAlldock.
期刊介绍:
The Journal of Toxicological Sciences (J. Toxicol. Sci.) is a scientific journal that publishes research about the mechanisms and significance of the toxicity of substances, such as drugs, food additives, food contaminants and environmental pollutants. Papers on the toxicities and effects of extracts and mixtures containing unidentified compounds cannot be accepted as a general rule.