Ideas for a project in computational chemistry?

In summary, potential projects in computational chemistry could include developing molecular dynamics simulations to study protein folding, utilizing quantum mechanics to investigate reaction mechanisms, creating algorithms for drug design using machine learning, modeling complex biochemical pathways, or exploring materials science by simulating the properties of novel compounds. Each project could contribute to advancements in understanding molecular interactions and enhancing the efficiency of chemical processes.
  • #1
yenK
1
0
Hi all,

I'm having a course on computational chemistry, as part of a bachelor curriculum. We have a project that is due to 4 weeks and I'm failing to find an interesting idea for this project that has to be done using Python. It can be anything, as long as it involves chemistry and coding.

Would you guys have any idea for a tool or research that I could try to make it happen?

Thank you!
 
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  • #2
What about modeling chemical reactions?

example

you could focus on using different methods to solve the pde and analyzing their convergence behavior. you could also determine a reaction rate given a set of data, etc.
 
  • #3
Simulation of oscillators (like Belousov–Zhabotinsky reaction) is always fun.
 
  • #4
Simple molecular dynamics can probably be done if everything is hardcoded.
 
  • #5
Two suggestions: How about implementing quantum chemistry algorithms in Python to perform calculations such as molecular orbital theory, electronic structure calculations, or molecular dynamics simulations. Libraries like Psi4 or PySCF can be used for quantum chemistry calculations.

Or you could create a Python program to simulate chemical kinetics experiments and analyze reaction rate data. You can implement numerical integration methods to solve rate equations and visualize the kinetics of different reactions.
 
  • #6
Topic's been up for a few days, and small number of responses - maybe some you could use.

How about making a titration curve for a polyprotic acid?
 
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FAQ: Ideas for a project in computational chemistry?

What are some beginner-friendly project ideas in computational chemistry?

Beginner-friendly project ideas include studying molecular geometries using quantum mechanics, simulating the interaction of small molecules with proteins, or exploring the effects of temperature on reaction kinetics using molecular dynamics simulations. These projects can help you familiarize yourself with software tools and basic computational techniques.

How can I use computational chemistry to study drug design?

Computational chemistry can be applied in drug design through techniques such as molecular docking, where you predict the preferred orientation of a drug candidate when bound to a target protein. You can also utilize quantitative structure-activity relationship (QSAR) models to relate chemical structure to biological activity and use molecular dynamics simulations to assess the stability of drug-protein complexes.

What software tools are commonly used in computational chemistry projects?

Common software tools include Gaussian for quantum chemistry calculations, GROMACS for molecular dynamics simulations, and AutoDock for molecular docking studies. Other popular options are VMD for visualization, Chem3D for molecular modeling, and Open Babel for file format conversion and cheminformatics tasks.

How can I validate my computational chemistry results?

Validation of computational chemistry results can be achieved by comparing them with experimental data, such as thermodynamic properties or reaction rates. Cross-validation with other computational methods or software can also help confirm your findings. Additionally, performing sensitivity analyses to assess how changes in parameters affect your results is essential for ensuring robustness.

What advanced topics in computational chemistry can I explore for a project?

Advanced topics include studying reaction mechanisms using transition state theory, performing free energy calculations to understand binding affinities, or exploring the electronic properties of materials using density functional theory (DFT). You could also investigate machine learning applications in predicting molecular properties or optimizing chemical reactions.

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