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Machine learning aids design of light-activated cancer drugs

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a computational method to design photoactive PARP1 inhibitors for cancer treatment. By screening 5 million hypothetical ligands using machine learning and atomistic simulations, they identified promising candidates that show differential binding to PARP1 under light and dark conditions. Ten compounds were synthesized and tested, with one candidate demonstrating a 15-fold increase in PARP1 inhibition when exposed to green light. AI

IMPACT Advances computational drug discovery, potentially accelerating the development of targeted light-activated therapies.

RANK_REASON Academic paper detailing a new computational method for drug discovery.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Machine learning aids design of light-activated cancer drugs

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Academic paper detailing a new computational method for drug discovery.
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Simon Axelrod, Miroslav Ka\v{s}par, Krist\'yna Jel\'inkov\'a, Mark\'eta \v{S}m\'idkov\'a, Erika Bart\r{u}\v{n}kov\'a, Sille \v{S}t\v{e}p\'anov\'a, Eugene Shakhnovich, V\'aclav Ka\v{s}i\v{c}ka, Martin Dra\v{c}\'insk\'y, Zlatko Janeba, Rafael G\'omez-Bombar ·

    Computational Design and Experimental Validation of Photoactive PARP1 Inhibitors

    arXiv:2604.24634v1 Announce Type: cross Abstract: Light-activated drugs are a promising way to treat localized diseases for which existing treatments have severe side effects. However, their development is complicated by the set of photophysical and biological properties that mus…

  2. arXiv cs.LG TIER_1 English(EN) · Rafael Gómez-Bombarelli ·

    Computational Design and Experimental Validation of Photoactive PARP1 Inhibitors

    Light-activated drugs are a promising way to treat localized diseases for which existing treatments have severe side effects. However, their development is complicated by the set of photophysical and biological properties that must be simultaneously optimized. Here we used comput…

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