Computational Chemistry
Computational chemistry is a branch of chemistry that uses computer simulations to assist in solving chemical problems. It utilizes methods from theoretical chemistry incorporated into computer programs to calculate molecular structures, properties, and interactions.
Historical Evolution
The origins of computational chemistry can be traced back to the 1920s with the development of quantum mechanics. In the 1950s, computational capabilities advanced, leading to the first ab initio Hartree-Fock calculations on diatomic molecules. Semi-empirical methods, such as Hückel theory and later CNDO, emerged in the 1960s and 1970s.
Applications
Computational chemistry has applications in various fields such as:
- Catalysis: Analyzing and designing catalysts without experimentation.
- Drug Development: Modeling molecules for drug discovery and optimization.
- Materials Science: Simulating nanomaterials for drug delivery systems.
Computational Databases
Databases are used to store and access computational chemistry data, including experimental data for comparison and verification. They also contain calculated values and allow researchers to share information. Some examples include:
- BindingDB: Protein-small molecule interactions
- RCSB: Protein and nucleic acid structures
- ChEMBL: Drug development research data
Methods
Computational chemistry employs various methods for calculating molecular properties:
- Ab Initio Methods: Use equations directly derived from theory, without relying on experimental data. Examples include Hartree-Fock, post-Hartree-Fock, and quantum chemistry composite methods.
- Density Functional Theory: Uses electron density to calculate molecular properties, offering a balance between accuracy and computational cost.
- Semi-Empirical Methods: Approximate quantum chemical calculations based on some empirical data.
- Molecular Mechanics: Uses classical physics to model molecular behavior, focusing on geometry and energy.
Computational Costs and Complexity
The complexity of computational chemistry algorithms varies depending on the size and complexity of the chemical system. Algorithms for MD, QM/MM, Hartree-Fock, and DFT show different degrees of computational cost.
Accuracy
Computational chemistry is not an exact science, but it can provide valuable insights and approximations. The accuracy of calculations depends on the computational cost and method chosen.
Software Packages
Numerous computational chemistry software packages are available, offering various capabilities. Some examples include:
- Gaussian: Widely used general-purpose quantum chemistry package
- ADF: Focuses on DFT and time-dependent DFT calculations
- Turbomole: Efficient quantum chemistry calculations for large systems