ASD2023: towards the integrating landscapes of allosteric knowledgebase.

Jixiao He,Xinyi Liu,Chunhao Zhu,Jinyin Zha,Qian Li,Mingzhu Zhao,Jiacheng Wei,Mingyu Li,Chengwei Wu, Junyuan Wang, Yonglai Jiao,Shaobo Ning, Jiamin Zhou,Yue Hong, Yonghui Liu, Hongxi He,Mingyang Zhang, Feiying Chen, Yanxiu Li,Xinheng He,Jing Wu,Shaoyong Lu,Kun Song,Xuefeng Lu,Jian Zhang

Nucleic acids research(2023)

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摘要
Allosteric regulation, induced by perturbations at an allosteric site topographically distinct from the orthosteric site, is one of the most direct and efficient ways to fine-tune macromolecular function. The Allosteric Database (ASD; accessible online at http://mdl.shsmu.edu.cn/ASD) has been systematically developed since 2009 to provide comprehensive information on allosteric regulation. In recent years, allostery has seen sustained growth and wide-ranging applications in life sciences, from basic research to new therapeutics development, while also elucidating emerging obstacles across allosteric research stages. To overcome these challenges and maintain high-quality data center services, novel features were curated in the ASD2023 update: (i) 66 589 potential allosteric sites, covering > 80% of the human proteome and constituting the human allosteric pocketome; (ii) 748 allosteric protein-protein interaction (PPI) modulators with clear mechanisms, aiding protein machine studies and PPI-targeted drug discovery; (iii) 'Allosteric Hit-to-Lead,' a pioneering dataset providing panoramic views from 87 well-defined allosteric hits to 6565 leads and (iv) 456 dualsteric modulators for exploring the simultaneous regulation of allosteric and orthosteric sites. Meanwhile, ASD2023 maintains a significant growth of foundational allosteric data. Based on these efforts, the allosteric knowledgebase is progressively evolving towards an integrated landscape, facilitating advancements in allosteric target identification, mechanistic exploration and drug discovery.
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