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引用次数: 0
摘要
计算化学在药物设计和开发中起着至关重要的作用,其中分子相互作用的准确建模对于合理的药物设计至关重要。在现有的方法中,MMFF94等力场被广泛用于计算分子势能,特别是有机小分子的势能。然而,MMFF94的当前实现主要以商业软件或闭源模块的形式提供。开源包通常提供有限的功能和缺乏可扩展性。本文介绍了JMolecular Energy (JME),这是一个新颖的开源Java库,旨在通过一个健壮的、可扩展的API(应用程序编程接口)实现MMFF94,该API允许访问单个能量组件。利用化学开发工具包(CDK), JME提供了一个用于势能计算的模块化框架,并促进了CDK中以前没有的功能,例如3D构象能量最小化。此外,JME建立了一个框架,用于定制各种应用的力场能量项,并促进了定制力场的集成。
Extending Chemoinformatics Techniques With JMolecular Energy: A Robust CDK-Based Force Field Library
Computational chemistry plays a crucial role in drug design and development, where accurate modeling of molecular interactions is vital in rational drug design. Among the available methods, force fields such as MMFF94 are extensively used to calculate molecular potential energies, especially for small organic molecules. However, current implementations of MMFF94 are primarily available in commercial software or as closed-source modules. Open-source packages often offer limited functionality and lack extensibility. This paper introduces JMolecular Energy (JME), a novel, open-source Java library designed to implement MMFF94 with a robust and extendable API (Application Programming Interface) that allows for access to individual energy components. Leveraging the Chemistry Development Kit (CDK), JME provides a modular framework for potential energy calculation and facilitates functionalities previously absent in CDK, such as 3D conformation energy minimization. Additionally, JME establishes a framework for tailoring force field energy terms for various applications and facilitates the integration of custom-built force fields.
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.