Departamento de Física Aplicada, Facultade de Física, Universidade de Santiago de Compostela, Campus Vida, Santiago de Compostela, E-15782, A Coruña, Spain; Organic Chemistry Department, Centro Singular de Investigación en Química Biolóxica e Materiais Moleculares (CiQUS), Universidade de Santiago de Compostela, Campus Vida, Santiago de Compostela, E-15782, A Coruña, Spain.
Galicia Supercomputing Center (CESGA), Avenida de Vigo, s/n, Santiago de Compostela, E-15782, A Coruña, Spain.
Comput Biol Med. 2024 Nov;182:109157. doi: 10.1016/j.compbiomed.2024.109157. Epub 2024 Sep 24.
Antimicrobial peptides (AMPs) are crucial in the fight against infections and play significant roles in various health contexts, including cancer, autoimmune diseases, and aging. A key aspect of AMP functionality is their selective interaction with pathogen membranes, which often exhibit altered lipid compositions. These interactions are thought to induce a conformational shift in AMPs from random coil to alpha-helical structures, essential for their lytic activity. Traditional computational approaches have faced challenges in accurately modeling these structural changes, especially in membrane environments, thereby opening and opportunity for more advanced approaches.
This study extends an existing quantum computing algorithm, initially designed for peptide folding simulations in homogeneous environments, to address the complexities of AMP interactions at interfaces. Our approach enables the prediction of the optimal conformation of peptides located in the transition region between hydrophilic and hydrophobic phases, resembling lipid membranes. The new method was tested on three 10-amino-acid-long peptides, each characterized by distinct hydrophobic, hydrophilic, or amphipathic properties, across different media and at interfaces between solvents of different polarity.
The developed method successfully modeled the structure of the peptides without increasing the number of qubits required compared to simulations in homogeneous media, making it more feasible with current quantum computing resources. Despite the current limitations in computational power and qubit availability, the findings demonstrate the significant potential of quantum computing in accurately characterizing complex biomolecular processes, particularly AMP folding at membrane models.
This research highlights the promising applications of quantum computing in biomolecular simulations, paving the way for future advancements in the development of novel therapeutic agents. We aim to offer a new perspective on enhancing the accuracy and applicability of biomolecular simulations in the context of AMP interactions with membrane models.
抗菌肽（AMPs）在抗感染方面起着至关重要的作用，在癌症、自身免疫性疾病和衰老等多种健康环境中都具有重要作用。AMPs 功能的一个关键方面是它们与病原体膜的选择性相互作用，而病原体膜的脂质组成往往发生改变。这些相互作用被认为会诱导 AMP 从无规卷曲到α-螺旋结构的构象转变，这对其溶细胞活性是必不可少的。传统的计算方法在准确模拟这些结构变化方面面临挑战，特别是在膜环境中，因此为更先进的方法提供了机会。
本研究扩展了一种现有的量子计算算法，该算法最初是为均匀环境中的肽折叠模拟而设计的，以解决 AMP 在界面处相互作用的复杂性。我们的方法能够预测位于亲水区和疏水区之间的过渡区域中肽的最佳构象，类似于脂质膜。新方法在三种长度为 10 个氨基酸的肽上进行了测试，每种肽都具有不同的疏水性、亲水性或两亲性特性，跨越不同的介质和不同极性溶剂之间的界面。
与在均匀介质中的模拟相比，该方法无需增加所需的量子比特数即可成功模拟肽的结构，因此在当前的量子计算资源下更具可行性。尽管目前在计算能力和量子比特可用性方面存在限制，但这些发现表明量子计算在准确描述复杂生物分子过程方面具有巨大的潜力，特别是在膜模型中 AMP 的折叠方面。
本研究强调了量子计算在生物分子模拟中的应用前景，为新型治疗剂的开发开辟了道路。我们旨在为在膜模型中 AMP 与膜模型相互作用的背景下增强生物分子模拟的准确性和适用性提供新的视角。
