Biology, Chemistry and Physics are core subjects that all have a combination of experiment and theory that are required to truly start to understand topics in these areas of science. Historically, much of the focus has been on hands-on experiments for observations and then analytical theories (based on mathematics) to relate and understand these observations at a more fundamental level, with the ultimate goal of developing theories that allow predictions about nature and the universe. In modern times, computers are playing a much larger role in both sides of experiment and theory. Most theorists rely heavily on computers for numerical and iterative mathematics that are only possible because of the processing power of computers. Also, experimentals often do ‘virtual experiments’ on computers either instead of doing real-world experiments or as a way of texting variables and idea systems out on a computer before doing the real-world experiment in the lab. The rapid development of AI, Machine Learning algorithms, quantum computation, etc. indicate that computers and computational methods will continue to grow in significance for all practical and fundamental science, especially in the core areas of Biology, Chemistry and Physics.
The field of computational biophysical chemistry is so large that entire courses don’t even do it justice. However, it would be a huge omission not to at least introduce a few of the more important and practically used computational methods in biophysical chemistry. Lets start with the books Prof. Yarger recommends most for developing an understanding of molecular level computational modeling:
- Schrier, Introduction to Computational Physical Chemistry.
- Cramer, Essentials of Computational Chemistry.
- Leach, Molecular Modelling: Principles and Applications.
- Frenkel & Smit, Understanding Molecular Simulations.
- Forescman & Frisch, Exploring Chemistry with Electronic Structure Methods
There are a lot of computational chemistry online resources, tutorials, and both commercial and open-source software. There are way too many different methods for molecular modelling and associated software and computer programs/code for each type of molecular modelling to provide a thorough list here. Listed below are a few specific links to software and programs that are directly useful for BCH 341 students.
- MolCalc (and the associated J. Chemical Education paper: molcalc_JCE2013)
- GAMESS (open-source molecular electronic structure system)
- ORCA (Electronic Structure program)
- Gaussian (commercial electronic structure software – ASU has Linux/MacOS Site License)
- Spartan (commercial molecular modeling software)
- Cresset (Software for molecular design, Prof. Yarger has a teaching license for Torch, Forge and Spark that can be used for BCH 341)
- NAMD (Scalable Molecular Dynamics, open-source)
- MS2 (Molecular Simulation Program for Thermodynamic Properties)
- eQuilibrator (open source web interface for thermodynamic analysis of biochemical systems)