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## Gaussian 量子化學計算軟體 | |

Gaussian是量子化學軟體。

Gaussian 09 is the latest version of the Gaussian® series of electronic structure programs, used by chemists, chemical engineers, biochemists, physicists and other scientists worldwide. Starting from the fundamental laws of quantum mechanics, Gaussian 09 predicts the energies, molecular structures, vibrational frequencies and molecular properties of molecules and reactions in a wide variety of chemical environments. Gaussian 09’s models can be applied to both stable species and compounds which are difficult or impossible to observe experimentally (e.g., short-lived intermediates and transition structures).

Gaussian 09 provides the most advanced modeling capabilities available today, and it includes many new features and enhancements which significantly expand the range of problems and systems which can be studied. With Gaussian 09, you can model larger systems and more complex problems than ever before, even on modest computer hardware.

What Sets Gaussian 09 Apart from Other Programs?

- Gaussian 09 produces accurate, reliable and complete models without cutting corners.
- A wide variety of methods makes Gaussian 09 applicable to the full range of chemical conditions and problem sizes and across the entire periodic table.
- Gaussian 09 provides state-of-the-art performance in single CPU, multiprocessor/multicore and cluster/network computing environments.
- Setting up calculations is simple and straightforward, and even complex techniques are fully automated. The flexible, easy-to-use options give you complete control over calculation details when needed.
- Results from all calculation types are presented in natural and intuitive graphical form by GaussView 5.

With Gaussian 09, you can thoroughly investigate the chemical problems that interest you. For example, not only can you minimize molecular structures rapidly and reliably, you can also predict the structures of transition states, and verify that the located stationary points are in fact minima and transition states. You can go on to compute the reaction path by following the intrinsic reaction coordinate (IRC) and determine which reactants and products are connected by a given transition structure. Once you have a complete picture of the potential energy surface, reaction energies and barriers can be accurately predicted.

Researchers have used these fundamental capabilities of Gaussian 09 to study isopenicillin N synthase (IPNS), a member of a family of mononuclear nonheme iron enzymes (illustrated at the bottom right of the next image). Transition metal enzymes catalyze some of the most important biochemical processes, and they can also serve as inspiration for novel biomimetic catalysis. In the latter context, these researchers wanted to determine how the metal center and the protein matrix separately contribute to the enzyme system’s catalytic activity. They analyzed the catalytic mechanism of IPNS, exploring the potential energy surface for the transformation of the tripeptide substrate δ-(l-α-aminoadipoyl)-l-cysteinyl-d-valine (ACV) to isopenicillin N (IPN). The ONIOM facility in Gaussian 09 enables the transition structures and reaction paths to be computed for the reactions involving large proteins like this system.

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