Quantum synergy in peptide folding: A comparative study of CVaR-variational quantum eigensolver and molecular dynamics simulation.
Int J Biol Macromol
; 273(Pt 1): 133033, 2024 Jul.
Article
em En
| MEDLINE
| ID: mdl-38862055
ABSTRACT
One of the technological fields that is developing the fastest is quantum computing in biology. One of the main problems is protein folding, which calls for precise, effective algorithms with fast computing times. Mapping the least energy conformation state of proteins with disordered areas requires enormous computing resources. The current study uses quantum algorithms, such as the Variational Quantum Eigensolver (VQE), to estimate the lowest energy value of 50 peptides, each consisting of seven amino acids. To determine the ground state energy value, Variational Quantum Optimisation (VQE) is first utilised to generate the energy values along with Conditional Value at Risk (CVaR) as an aggregation function is applied over 100 iterations of 500,000 shots each. This is contrasted with 50 millisecond molecular dynamics-based simulations to determine the energy levels and folding pattern. In comparison to MD-based simulations, the results point to CvaR-VQE producing more effective folding outcomes with respect to sampling and global optimization. Protein folding can be solved to get deep insights into biological processes and drug formulation with improving quantum technology and algorithms.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Peptídeos
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Teoria Quântica
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Algoritmos
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Dobramento de Proteína
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Simulação de Dinâmica Molecular
Idioma:
En
Revista:
Int J Biol Macromol
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Índia
País de publicação:
HOLANDA
/
HOLLAND
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NETHERLANDS
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NL
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PAISES BAJOS
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THE NETHERLANDS