AIMC Topic: Thiadiazoles

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Integrating Machine Learning and SHAP Analysis to Advance the Rational Design of Benzothiadiazole Derivatives with Tailored Photophysical Properties.

Journal of chemical information and modeling Apr 29, 2025
2,1,3-Benzothiadiazole (BTD) derivatives show promise in advanced photophysical applications, but designing molecules with optimal desired properties remains challenging due to complex structure-property relationships. Existing computational methods ...
Machine Learning Drug Design Thiadiazoles
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On the ability of machine learning methods to discover novel scaffolds.

Journal of molecular modeling Dec 27, 2022
The recent advances in the application of machine learning to drug discovery have made it a 'hot topic' for research, with hundreds of academic groups and companies integrating machine learning into their drug discovery projects. Nevertheless, there ...
Machine Learning Anti-Bacterial Agents Drug Discovery Thiadiazoles
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A Deep Learning Approach to Antibiotic Discovery.

Cell Feb 20, 2020
Due to the rapid emergence of antibiotic-resistant bacteria, there is a growing need to discover new antibiotics. To address this challenge, we trained a deep neural network capable of predicting molecules with antibacterial activity. We performed pr...
Machine Learning Anti-Bacterial Agents Animals Drug Discovery Mice Mice, Inbred BALB C Mice, Inbred C57BL Mycobacterium tuberculosis Acinetobacter baumannii Databases, Chemical Clostridioides difficile Small Molecule Libraries Cheminformatics Thiadiazoles
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