PDAI: A green pesticide molecule design technology platform driven by high-performance computing and artificial intelligence Article Swipe
Z. A. Zhu
,
Mengzhu Jia
,
Xiuli Hou
,
Fan Wang
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.aac.2025.01.004
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.aac.2025.01.004
Pesticides are integral to agricultural productivity and food security. Despite the notable advancements in Computer Aided Drug Design (CADD) and Artificial Intelligence Drug Discovery (AIDD) in pharmaceuticals, their application in the pesticide sector remains underutilized. The complexity and non-user-friendly interfaces of these technologies have impeded their adoption by non-specialists, reducing their influence on pesticide creation. To overcome these obstacles, the Pesticide Discovery Artificial Intelligence (PDAI), a pioneering platform specifically tailored for the molecular design of pesticides would be a very useful tool. PDAI streamlines the innovation process, from target identification to the generation of viable pesticide candidates, optimizing key steps and simplifying the overall design workflow. This user-friendly platform significantly reduces the barriers for non-specialists, making the pesticide design process more accessible and cost-effective. Its innovative strategy promotes interdisciplinary cooperation and accessibility, inviting a broader community to advance pesticide research. For more comprehensive information of PDAI, please click on the website https://digitalpesticide.com.
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All OpenAlex metadata
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https://doi.org/10.1016/j.aac.2025.01.004Digital Object Identifier
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PDAI: A green pesticide molecule design technology platform driven by high-performance computing and artificial intelligenceWork title
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2025Year of publication
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2025-02-14Full publication date if available
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Z. A. Zhu, Mengzhu Jia, Xiuli Hou, Fan WangList of authors in order
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https://doi.org/10.1016/j.aac.2025.01.004Publisher landing page
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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