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A Computational Modeling of the Structure, Frontier Molecular Orbital (FMO) Analysis, and Global and Local Reactive Descriptors of a Phytochemical ‘Coumestrol’
Published in Nazmul Islam, Satya Bir Singh, Prabhat Ranjan, A. K. Haghi, Mathematics Applied to Engineering in Action, 2021
P. Vinduja, Vijisha K. Rajan, Swathi Krishna, K. Muraleedharan
Computational chemistry is a technique used for the investigation of chemical processes by using a computer. The applications of computers in chemistry are manifold. It is mainly used in the expanse of molecular geometry, energies of molecules and transition state, chemical reactivity, IR, UV, and nuclear magnetic resonance (NMR) spectra, interaction of substrate with an enzyme, physical properties of the substance, multi-poles, polarizability, atomic charges, electrostatic potential, magnetic properties, vibrational frequencies, etc. One may think for the necessity of clubbing an experiment with theory. Computational/theoretical methods can be used for interpretation of ambiguous or conflicting results. If there requires a real-time analysis of the progress of experimental process, computational method can be used for optimizing the data. Not all process can be experimentally carried forward, but with computational methods, it can be made easier.
Advancing Computational Methods in Chemical Engineering and Chemoinformatics
Published in Francisco Torrens, A. K. Haghi, Tanmoy Chakraborty, Chemical Nanoscience and Nanotechnology, 2019
Drug discovery has become a significant element supplementing classical medicinal chemistry and high-throughput screening these results to many computational chemistry methods were developed to aid them in learning capable drug candidates. ODDT open-source player in the drug discovery field which aims to fulfill the need for comprehensive and open-source drug discovery software because there has been enormous progress in the open cheminformatics field in both methods and software development. Sadly, there has only been little effort to combine them in only one package.
Computation Chemistry and Engineering
Published in Shintaro Furusaki, John Garside, L.S. Fan, The Expanding World of Chemical Engineering, 2019
Jennifer Sinclair, Gavin Sinclair
For example, let’s say you want a drug to inhibit a certain enzyme involved in a disease, such as the HIV protease involved in AIDS. If the enzyme isn’t well characterized yet, such as the HIV protease, it is difficult to find a drug molecule that will interact with the drug target receptor. A structuring-focusing program can be used to analyze the active site of the HIV protease and then to search virtual molecular libraries for candidate drugs that might bind to the active site. Hence, computational chemistry, which allows for high throughput screening, is an integral part of drug discovery.
Speeding up density fitting Hartree–Fock calculations with multipole approximations
Published in Molecular Physics, 2020
The Hartree–Fock (HF) method is one of the most important approaches in quantum chemistry. Currently, it is rarely used as a standalone method, but it is usually employed for generating molecular orbitals (MOs) for a subsequent correlation calculation. Though the formal scaling of its computation time with the system size is better than that for conventional correlation methods, due to the rapid development of reduced-scaling correlation approaches [1–3], the HF calculation has become the bottleneck for large molecules. The other core approximation in quantum chemistry is Kohn–Sham (KS) density functional theory (DFT) [4], which is the most widely used method in computational chemistry these days. If the KS approach is employed in conjunction with a hybrid functional [5], the complexity of the resulting equations is very similar to that of the HF method. Consequently, considerable effort has been invested into the improvement of HF algorithms.
Theoretical and experimental investigation on the electrochemical properties, structural and spectroscopic parameters of 6,7-dihydroxy-9-thia-1,4a-diaza fluoren-2-one (DTDFO)
Published in Journal of Sulfur Chemistry, 2019
Hassan Goodarzi, Alireza Asghari, Davood Nematollahi, Maryam Rajabi
It is a great advantage to theoretically obtain redox potentials, especially when a complicated chemical equilibrium causes difficult empirical analyses, and when the aim of research is to design new molecules with desirable electrochemical properties [15,16]. Computational chemistry and molecular modeling play an essential role in characterizing the novel drug substances. Thanks to the developments in quantum chemistry and computer sciences, the description of physical and chemical properties of relatively small molecules is accurately possible via density functional theory (DFT) calculations within a reasonable time [17–21]. Accordingly, in some publications, the effects of electron donation and acceptance on the electrochemical potentials have been investigated using the substitution of different groups [22].
Theoretical design of azaacene-based non-fullerene electron transport material used in inverted perovskite solar cells
Published in Molecular Physics, 2019
Keke Wen, Xiao Pan, Songyan Feng, Wenpeng Wu, Xugeng Guo, Jinglai Zhang
On the basis of our previous studies [24], enlarging the conjugation of discotic molecule hexaazatrinaphthylene can not only decrease the LUMO level, but also can decrease electron reorganisation energy and increase electron mobility. So in this paper, we designed a new azaacene 3 (see Figure 1) by adding the benzopyrazine group to the conjugation structure of compound 1. Electronic structure method is a convenient way to predict the electronic properties of various systems. In the past 30 years, Kohn–Sham density functional theory (DFT) has emerged as the most popular electronic structure method in computational chemistry [25-27]. As a result, DFT calculations have been performed and it is found that compound 3 has better performance than compound 1. At the same time, we substituted i-Pr groups in compound 1 with H atoms to form compound 2, and discussed the effect of i-Pr groups on the performance of ETL.