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Activity Number:
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300
- The Appeal of Quantum Computing in Statistical Science
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 5, 2020 : 10:00 AM to 11:50 AM
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Sponsor:
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Quantum Computing in Statistics and Machine Learning
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Abstract #313045
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Title:
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Designing Peptides on a Quantum Computer
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Author(s):
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Hans Melo*
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Companies:
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Menten Al, Inc
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Keywords:
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optimization; quantum computing; drug-discovery; pharmaceutical; chemical; biochemistry
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Abstract:
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We investigated the use of quantum hardware as a potential alternative for solving conformational search problems in protein design. We developed an algorithm, the qPacker, to frame the side-chain rotamer search as a constrained binary optimization problem and solve it on two types of quantum devices: quantum annealers (e.g. D-Wave), and gate-based quantum computers (e.g. Rigetti). The qPacker algorithm was successful in finding low energy solutions for side-chain conformational optimization problems of varying sizes, and in many cases yielding results superior to Rosetta’s Monte Carlo/simulated annealing methods. These promising results foreshadow an exciting new route for emerging quantum computing technologies in synthetic biology and biochemistry with a wide range of applications in the pharmaceutical and chemical industries.
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Authors who are presenting talks have a * after their name.
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