Optimization calculations are not too difficult. However, challenges can arise as can many different results. I did an optimization on three different conformations of tryptophan that I created by changing one of many dihedral angles in the molecule (Two C’s in pentagon across from N, the next Carbon in substituent chain, and the next Carbon which was bonded to NH2).
I used angles of 0, 135, and 180 degrees. Using the “broom”/”sweep” button on GaussView, I was able to return each configuration to a more energetically favorable conformation near those angles (21.99, -158.0, 41.5, respectively). However, they were not all the same since these angles are quite far from one another. When I performed an optimization calculation, each gave very similar energies (within 2 kJ/mol; in fact the first and third configuration were the same up to the fourth decimal place), but ranged in their change in energy from the “swept” conformation.
Here comes the issue. One calculation would not run (B3LYP/6-31G). It failed three times, each 15 minute long trials. The error message overall read “Error with lnk1e” followed by another line of error (which I do not remember). This suggested that the error arose because the “redundant internal coordinates” of this optimization were not working. So, one method to fix this issue would be to run the calculation starting from the current coordinates in the checkpoint file to redefine the internal coordinates and essentially bypass the error. Yet, in one of the output images, one C-C bond was essentially broken which shows that in its attempt to optimize the energy of tryptophan, GaussView felt that these two atoms needed to be further apart (about 1.75 Angstroms) than a normal C-C bond (1.54 A). This is not a scenario that should be repeated so the method of starting with new coordinates from the checkpoint file would not be effective. Therefore, instead we decided to use Cartesian coordinates which required adding “opt=cartesian” into the keywords of the route line.
Although a cartesian calculation takes much longer, I was able to find the proper energy of the optimized molecule.
Doing computational chemistry requires (1) the technical know-how to use special software and computers and (2) the knowledge to understand what the software is telling you.
On that second point, there’s a lot of math and physics behind the theories of chemistry—and its great stuff! But before you dive into studying a lot of formal math and physics, its good to know what you’re working towards. Chris Cramer (a professor at U. Minnesota) is a computational chemist who has written a computational chemistry textbook and put a bunch of free video lectures up on Youtube that explain the concepts behind computational chemistry at a level that most students can understand. If you’ve taken general chemistry, an organic chemistry course, and a couple semester of calculus (multivariable calculus is great, but not absolutely necessary), these videos are great background and inspiration. As you move through the video series (49 total — a full course!) the material gets rich, but if you follow along you should understand the spirit of it.
You tell comet to run your calculation by submitting it to a queue. Your calculation waits in line with all the other jobs scientists want to run on comet. The software that controls this queue is called slurm (that’s a really dumb name, but so it is).
The basics are that first you make (or edit) a bash script containing all the slurm settings and Linux commands you need. Let’s say you call that file calculation.sh Then you can submit your job to the queue by typing:
If it works, you should see a short message with the job’s ID number. Your job might not start right away if there are a lot of either jobs ahead of yours in line.
To view all the jobs in the queue, you can just type
To view only the jobs you’ve submitted, you can just type
squeue -u yourusername
If you realize — whoops! — you made a mistake and want to cancel the job you’ve just submitted, you can type
When your job is done, it will silently disappear from the queue and your output files should be in your directory. You can put a setting in your calculation.sh script to email you when your job finishes. If something went wrong with the calculation, your output files should contain error messages to help you figure out what went wrong so you can fix it and resubmit the job.
That’s it for the basics. There are some more useful slurm commands you can read about on the slurm official documentation page. In another blog post, I’ll show you a simple slurm script you can copy, paste, and edit to get your own jobs running smoothly.
Comet is accessed over the internet using a command-line interface on the server comet.sdsc.edu. The basic program we use to access comet is called “ssh” (which is an acronym for “secure shell”).
On Mac OSX, you can go to Applications -> Utilities -> Terminal to open the command-line Linux interface on your mac. To login to comet from your mac, in the Terminal program type: ssh firstname.lastname@example.org Of course, use your own comet username in place of mine!
On Windows, there is no command-line Linux interface, so you need to use a separate program to connect to comet using ssh. The classic program is called putty, and it is pre-installed on all Skidmore-owned Windows computers. You may prefer to get a program with more features, for example, the Bitvise ssh client . In either case, download and install a ssh program and tell it to access comet.sdsc.edu.
On either type of computer, after a few seconds, you will connect to comet and be prompted for your password. After you type in your password, you will be looking at a Linux command line (specifically, it is a bash prompt) on a computer 3000 miles away from Saratoga Springs. Cool, eh?
Now you can use comet for whatever calculation you need, using Linux commands, your input and output files (for gaussian or AMBER)
Our research group has a special folder on the Skidmore server “datastor” where we all keep things we’re working on and sharing.
On Mac, connect to the server smb://datastor.skidmore.edu
On Windows, connect to //datastor.skidmore.edu
If you’re on a Skidmore computer, there is likely a “Datastor” icon on your desktop that will connect you automatically.
After you connect to datastor, look for the “Netshare” directory and then the subdirectory “KennerlyResearch”.
If this is your first time doing this, you can follow these instructions at the link below for more details. Also, you will need to ask me to add your Skidmore username for permission to read and write files in KennerlyResearch.
If you are on-campus, it is quick and easy to get access to the folder.
If you are off-campus, you will need to install VPN software called “Cisco AnyConnect” to securely connect back to Skidmore’s intranet. The links above have instructions for doing that for both Windows and Mac.