Computation chemistry has been going on for decades. Attempts at modeling how molecules behave is still quite primitive. We're talking about modelling the behavior of a object that is comprised of a few dozen atoms. That's it, pretty simple right? We'll the models aren't that good at predicting molecular behavior.
Let's move up a step now. Computation chemistry is used heavily by the drug industry. Get an x-ray structure of a protein (maybe a few hundred to a few thousand atoms) and see if it binds to a drug. Wow, now it's getting complicated. How successful is it? Not very. I can remember a computational chemist saying "oh hey, the model say if you replace X with Y, you'll increase binding by 10x". So we try and guess what? The binding was worse.
Now we move up to a biological system. Now we have hundreds (if not thousands) of proteins floating in a matrix of water and ions. We have a DNA strands of millions of base pairs, of which maybe 10% we actually know what they do. We also have small signalling molecules that do something we understand, but probably also do 10 other things we have no idea about.
It is very impressive how far biological "design" (genomics) has come so far, but right now the tools are incredibly blunt and the analysis is incredibly crude. I have no doubt our understanding will improve immensely over the coming decades, but I would guess we understand less than 1% of what's going on inside of complex living organisms.
You see, my feeling is that trying to guess the progress of genetics by extrapolating the complexity and insecurity of the computation chemistry is wrong. As far as I understood, genetics today is a lot about (but not only) identifying which genes (portions of DNA) are responsible of which phenotype (en.wikipedia.org/wiki/Phenotype).Therefore a lot of resources are and were allocated to create a dictionary with genes as keys and phenotype as values. This dictionary is being populated at a quite fast pace and this combined with the possibility to take genes from some organisms and implant them in the DNA of a cell of other organisms and see the resulting phenotype is already a great achievement (imagine undergrads cutting and pasting DNA daily). They are not inventing new proteins and worry that they will not "bind" enough. They just take the DNA known to produce proteins in some organisms and place it in other organisms and suddenly proteins which have a known effect in different organisms, appear in a new organism. Yes, there is a long way from here to engineering genes that will produce and deliver a medicine inside an organism but I wouldn't call this primitive at all. Sorry for the simplification and possible errors.
OK, I see your perspective now. I agree that our understanding of how genes encode for proteins is well developed, as are our techniques for "transplanting" a gene from one organism to another.
What we have very little handle on is gene regulation. All those "non-coding" genes that scientists used to think were junk? They are actually used to control gene transcription.
Controlling this is infinitely easier in a simple organism like a hookworm, but the complexities of in human borders on obscene.
Computation chemistry has been going on for decades. Attempts at modeling how molecules behave is still quite primitive. We're talking about modelling the behavior of a object that is comprised of a few dozen atoms. That's it, pretty simple right? We'll the models aren't that good at predicting molecular behavior.
Let's move up a step now. Computation chemistry is used heavily by the drug industry. Get an x-ray structure of a protein (maybe a few hundred to a few thousand atoms) and see if it binds to a drug. Wow, now it's getting complicated. How successful is it? Not very. I can remember a computational chemist saying "oh hey, the model say if you replace X with Y, you'll increase binding by 10x". So we try and guess what? The binding was worse.
Now we move up to a biological system. Now we have hundreds (if not thousands) of proteins floating in a matrix of water and ions. We have a DNA strands of millions of base pairs, of which maybe 10% we actually know what they do. We also have small signalling molecules that do something we understand, but probably also do 10 other things we have no idea about.
It is very impressive how far biological "design" (genomics) has come so far, but right now the tools are incredibly blunt and the analysis is incredibly crude. I have no doubt our understanding will improve immensely over the coming decades, but I would guess we understand less than 1% of what's going on inside of complex living organisms.