How can AI and machine learning accelerate the discovery of novel secondary metabolites for drug development?
Artificial intelligence and machine learning can significantly accelerate the discovery of novel secondary metabolites for drug development by using large-scale data analysis, pattern recognition, and predictive modeling. These technologies can analyze large genomic, metabolomics, and proteomics datasets to identify potential biosynthetic gene clusters (BGCs) and predict the structures and functions of secondary metabolites. Machine learning algorithms can also optimize the screening process by prioritizing compounds with desirable pharmacological properties, reducing the need for extensive laboratory testing. In addition, AI-based tools can simulate and predict interactions between metabolites and biological targets, enabling the identification of promising drug candidates more efficiently. By automating and enhancing these processes, AI and machine learning streamline the discovery pipeline, reducing time and costs while increasing the likelihood of finding new therapeutic compounds.
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@ Hamidreza Zahedi
Can you recommend any AI tool for it? I am interested in this area. Thanks
AI/ML can accelerate the discovery of secondary metabolites by enabling rapid virtual screening and AI‑based lead prioritization. MedChemExpress (MCE) provides compound libraries and virtual‑screening services suitable for this workflow, including the 50K Diversity Library (HY‑L901), MegaUni 10M Virtual Diversity Library (HY‑L912V), MegaUni 50K Virtual Diversity Library (HY‑L910V), and an optimized Virtual Screening protocol. For an end‑to‑end option, MCE’s Virtual Screening service can reduce experimental time and cost by prioritizing the most promising candidates. For additional context, please see our research proposal, “AI Deep Learning Accelerates Drug Development.”
Research Proposal AI Deep Learning Accelerates Drug Development
(All offerings are for research use only.)
The answer to this question comes from MedChemExpress (MCE) Technical Support.
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