聚乳酸的水合蓝图:预测生物降解的非共价相互作用的计算解码。

IF 4.8 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY
Rehin Sulay, Sneha Anna Sunny, S. Bushramol, A. N. Arshana, Abdullah Yahya Abdullah Alzahrani, Renjith Thomas
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引用次数: 0

摘要

聚乳酸(PLA)的生物降解基本上是由其与水的相互作用控制的,尽管对触发水解的分子水平机制知之甚少。这一限制阻碍了聚合物的合理设计与期望的降解动力学。在这项工作中,我们利用多层计算方法,结合DFT与M06-2X泛函和cc-pVDZ基集,以及溶剂化模型密度(SMD),自然键轨道(NBO)分析,非共价相互作用(NCI)指数和分子原子量子理论(QTAIM)估计溶剂效应,揭示了水化诱导的PLA降解。我们的研究结果表明,PLA的水稳定性是由相互作用力之间的微妙相互作用决定的:与水羰基的强定向氢键与广泛的范德华相互作用相辅相成,而这反过来又部分被聚合物内部的空间排斥力所抵消。AIM分析发现,所有氢键都被定量地归类为弱的闭壳相互作用,因此表现出水化网络的静电特征。此外,AIMD模拟提供了对水解链断裂早期过程的深入了解,揭示了水促进的质子转移和酯键断裂。在分子对接的支持下,鉴定出关键的微生物酶,并通过全面的氢键网络产生结合亲和力(高达-5.8 kcal mol-1)。这项工作提供了PLA的第一个电子级蓝图,为降解动力学的预测提供了机制基础,并有助于设计下一代环境友好的可降解聚合物。通过揭开水诱导聚乳酸降解的分子起源,本研究证明了聚合物稳定性和寿命的相干调谐。这些见解为工业和环境利益提供了具有可调节分解行为的下一代可生物降解聚合物的设计和开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The Hydration Blueprint of Polylactic Acid: Computational Decoding of Noncovalent Interactions for Predictive Biodegradation

The Hydration Blueprint of Polylactic Acid: Computational Decoding of Noncovalent Interactions for Predictive Biodegradation

The Hydration Blueprint of Polylactic Acid: Computational Decoding of Noncovalent Interactions for Predictive Biodegradation

The Hydration Blueprint of Polylactic Acid: Computational Decoding of Noncovalent Interactions for Predictive Biodegradation

The Hydration Blueprint of Polylactic Acid: Computational Decoding of Noncovalent Interactions for Predictive Biodegradation

The Hydration Blueprint of Polylactic Acid: Computational Decoding of Noncovalent Interactions for Predictive Biodegradation

The biodegradation of polylactic acid (PLA) is essentially controlled by its interaction with water although little is known about the molecular-level mechanisms that trigger hydrolysis. This limitation hinders the rational design of polymers with desired degradation kinetics. In this work, we unveil the hydration-induced degradation of PLA using a multilevel computational approach, combining DFT with M06-2X functional and cc-pVDZ basis set along with the estimation of solvent effect using solvation model density (SMD), natural bond orbital (NBO) analysis, noncovalent interaction (NCI) index and Quantum Theory of Atoms in Molecules (QTAIM). Our findings demonstrate that the aqueous stability of PLA is determined by a delicate interplay between opposing forces: strong, directional hydrogen bonds to water carbonyls complemented by widespread van der Waals interactions, which in turn are partly countered by intrinsic steric repulsion within the polymer. The AIM analysis finds that all hydrogen bonds are quantitatively classified as weak, closed-shell interactions and thus exhibit an electrostatic character of the hydration network. In addition, AIMD simulations provide insights into the early-stage process of hydrolytic chain scission, revealing a proton transfer facilitated by water and an ester bond cleavage. Supported by molecular docking, key microbial enzymes are identified and binding affinities (up to −5.8 kcal mol−1) transpire through comprehensive hydrogen bonding networks. The work offers a first-ever electronic-level blueprint of PLA, providing a mechanistic basis for predictions of degradation kinetics and aiding in the design of the next generation of environmentally benign degradable polymers. By unmasking the molecular inception of water-induced PLA degradation, this study demonstrates coherent tuning of polymer stability as well as lifetime. The insights provide the design and development of next-generation biodegradable polymers with regulated breakdown behavior for industrial and environmental interests.

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来源期刊
CiteScore
6.60
自引率
3.30%
发文量
247
审稿时长
1.7 months
期刊介绍: This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.
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