Hydrogen Bond Energy Estimation in Large Molecular Clusters via the Method of Synergistic Cyclic Cooperativity: A Software Update H-BEE 2.0

IF 2.9 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY
Ayush Shivhare, Mini Bharati Ahirwar, Subodh S. Khire, Shridhar R. Gadre, Milind M. Deshmukh
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Abstract

Our earlier developed software utility, H-BEE, for estimating the energies of individual hydrogen bonds (HB) in molecular clusters was implemented with three methods. These methods are: the molecular tailoring approach based (MTA-based) one, the first spherical shell (SS1), and the Fragments-in-Fragments. These methods work quite well but are still time-consuming and have certain shortcomings. Herein, our recently proposed method of synergistic cyclic cooperativity (SCC) is implemented as an update (called H-BEE 2.0) to H-BEE. The three-dimensional (3D) molecular cluster is usually made up of small cyclic structures which result from the interconnected network of HBs. Within the SCC method, the energy of a referenced HB is estimated as the sum of the cooperativity contributions (CCs) of these small cyclic structures and its energy in an isolated dimeric species. The SCC is an effective and swift method. The H-BEE 2.0 identifies all possible cyclic structures in an automatic manner and evaluates the CCs of these cycles. The H-BEE 2.0 utility has been extensively tested on a variety of molecular clusters and the results are compared with the earlier implemented methods. It also brings out the finer aspects of the strength of HBs in terms of the nature of cooperativity of small cyclic networks.

基于协同循环协同性方法的大分子团簇氢键能估算:H-BEE 2.0软件更新
我们早期开发的软件实用程序H-BEE,用于估计分子簇中单个氢键(HB)的能量,通过三种方法实现。这些方法是:基于分子裁剪方法(MTA-based),第一球壳(SS1)和片段中的片段(Fragments-in-Fragments)。这些方法效果很好,但仍然很耗时,并且有一定的缺点。在此,我们最近提出的协同循环协同(SCC)方法作为H-BEE的更新(称为H-BEE 2.0)实现。三维(3D)分子簇通常由小的环状结构组成,这些环状结构是由HBs相互连接的网络形成的。在SCC方法中,参考HB的能量被估计为这些小环结构的协同贡献(cc)及其在孤立二聚体中的能量的总和。SCC是一种快速有效的方法。H-BEE 2.0自动识别所有可能的循环结构,并评估这些循环的CCs。H-BEE 2.0实用程序已经在各种分子簇上进行了广泛的测试,并将结果与早期实现的方法进行了比较。从小循环网络的协同性的本质来看,它还揭示了HBs的优点。
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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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