Reddit mentions of Molecular Modelling: Principles and Applications (2nd Edition)

Well, it depends. Are you interested only in applications, only in method development, or both? You don't necessarily study "computational chemistry", so if you can be more specific, it would help a lot.

It sounds like you're more interested in applications, and biochemical simulations can require many different techniques. Leach is a good start for textbook reading. I'd also start reading the peer-reviewed literature, specifically for joint experimental/computational papers. Biochemistry and Inorganic Chemistry have quite a few. Just saying "try this software and do XYZ thing" isn't very helpful.

I like this book for C++ if you want to learn C++. Python is easier though and most people start with Python. I like the book Learn Python the Hard Way (it's actually a pretty easy book lol) but there are quite a lot of books that are good for Python. (and I'm like 99% certain there are free versions of these books available on the web)

That's probably a good way to see if you like coding. Personally I love it 'cause it's a lot of problem solving, and then forcing a computer to do your evil bidding work.

Then for the chemistry part. I think everybody on the planet and their brother loves this book (it's also free on google). That will help you learn about the theory behind the software.

I also think you should talk to a professor who does computational work to let you toy around with it. I've had two advisors now in comp chem, and I get the feeling if a student came to either of them and said they wanted to play around with the software and see what comp chem is like, both of those professors would probably have been happy to set them up with an account to a supercomputer and show them a few tricks to setting up jobs, running simulations/calculations, viewing data, etc.

Personally I make a distinction between scripting and programming that doesn't really exist but highlights the differences I guess. I consider myself to be scripting if I am connecting programs together by manipulating input and output data. There is lots of regular expression pain and trial-and-error involved in this and I have hated it since my first day of research when I had to write a perl script to extract the energies from thousands of gaussian runs. I appreciate it, but I despise it in equal measure. Programming I love, and I consider this to be implementing a solution to a physical problem in a stricter language and trying to optimise the solution. I've done a lot of this in fortran and java (I much prefer java after a steep learning curve from procedural to OOP). I love the initial math and understanding, the planning, the implementing and seeing the results. Debugging is as much of a pain as scripting, but I've found the more code I write the less stupid mistakes I make and I know what to look for given certain error messages. If I could just do scientific programming I would, but sadly that's not realistic. When you get to do it it's great though.

The maths for comp chem is very similar to the maths used by all the physical sciences and engineering. My go to reference is Arfken but there are others out there. The table of contents at least will give you a good idea of appropriate topics. Your university library will definitely have a selection of lower-level books with more detail that you can build from. I find for learning maths it's best to get every book available and decide which one suits you best. It can be very personal and when you find a book by someone who thinks about the concepts similarly to you it is so much easier.
For learning programming, there are usually tutorials online that will suffice. I have used O'Reilly books with good results. I'd recommend that you follow the tutorials as if you need all of the functionality, even when you know you won't. Otherwise you get holes in your knowledge that can be hard to close later on. It is good supplementary exercise to find a method in a comp chem book, then try to implement it (using google when you get stuck). My favourite algorithms book is Numerical Recipes - there are older fortran versions out there too. It contains a huge amount of detailed practical information and is geared directly at computational science. It has good explanations of math concepts too.

For the actual chemistry, I learned a lot from Jensen's book and Leach's book. I have heard good things about this one too, but I think it's more advanced. For Quantum, there is always Szabo & Ostlund which has code you can refer to, as well as Levine. I am slightly divorced from the QM side of things so I don't have many other recommendations in that area. For statistical mechanics it starts and ends with McQuarrie for me. I have not had to understand much of it in my career so far though. I can also recommend the Oxford Primers series. They're cheap and make solid introductions/refreshers. I saw in another comment you are interested potentially in enzymology. If so, you could try Warshel's book which has more code and implementation exercises but is as difficult as the man himself.

Jensen comes closest to a detailed, general introduction from the books I've spent time with. Maybe focus on that first. I could go on for pages and pages about how I'd approach learning if I was back at undergrad so feel free to ask if you have any more questions.



Out of curiosity, is it DLPOLY that's irritating you so much?

I've read a couple books in the past and think [this one by Andrew Leach] (https://www.amazon.com/dp/0582382106/ref=pd_lpo_sbs_dp_ss_1?pf_rd_p=1944687722&pf_rd_s=lpo-top-stripe-1&pf_rd_t=201&pf_rd_i=0122673514&pf_rd_m=ATVPDKIKX0DER&pf_rd_r=RBQQJGVYTNCM7XBM7SF3) is the best one, for use as a good intro and also as a reference. It's actually a surprisingly engrossing read.