Here's a huge review that goes over most everything you may have wanted to know about what's called "rational drug design". The authors are especially addressing selectivity, but that's a broad enough topic to cover all the important features. (If you can't access the paper, here's a key graphic from it).
"Rational", it should be understood, generally tends to mean "computationally modeled" in the world of drug discovery. And that's certainly how this review is pitched. I'm of two minds - at least - about the whole area (a personal bias that has made for some lively discussions over the years). Some of those discussions have taken place between my own ears as well, because I'm still not sure that all my opinions about computational drug design are self-consistent.
On the one hand, drug potency is a physical act which is mediated by physical laws. Computing the change in free energy during such a process should be feasible. But it turns out to be rather difficult - proteins flex and bonds rotate, water molecules assist and interfere, electrostatic charges help and hinder, hydrogen bonds are vital (and hard to model), and a dozen other sorts of interactions between clouds of electrons weigh in as well. Never forget, too, that free energy changes have an entropy component, and that's not trivial to model, either. I keep wondering if the error bars of the various assumptions and approximations don't end up swamping out the small changes that we're interested in predicting.
But, on that other hand, there are certainly cases where modeling has helped out a great deal. A cynic would say that we've been sure to hear about those, while the cases where it had no impact at all (or did actual harm) don't make the journals very often. It can't be denied, though, that modeling really has been (at times) the tool for the job. It would be interesting to know if the frequency of that happening has been increasing over time, as our tools get better.
Because on the third hand, it's been a poor bet to go against the relentless computational tide over the last few decades. You'd have to think that sheer computing power will end up making molecular modeling ever more capable and useful, as we learn more about what we're doing. Mind you, there were people back in the mid-1980s who thought we'd already reached that point. I'm not saying that they were the best-informed people at that time, but they certainly did exist. I wonder sometimes what it would have been like, to show people in 1985 what the state of rational drug design would be like in 2012. Would they be excited, or vaguely disappointed?
And then there's that word "rational". I think that its adoption might have been the best advertising that the field's ever achieved, because it makes everything else seem irrational (or at least arational) by default. I mean, do you just wanna make compounds, or do you want to think about what you're doing? I also wonder what might have changed if that phrase had never been adopted - perhaps expectations wouldn't have gotten out of hand in the computational field's early days, but it might not have received the attention (and money) that it did, either. . .