I think Moore's law can help to an extent with approach 1, especially the protein folding bottleneck. We also need better computational techniques, taking more

I think Moore's law can help to an extent with approach 1, especially the protein folding bottleneck. We also need better computational techniques, taking more from dynamical systems maths for example. I think approach 2 can also inform approach 1. Especially if grey and clearbox models are used - probabilistic graphical models, markov logic networks even genetic programming. So instead of using them for just prediction or a distance metric, we study the patterns in the models they produce. For example, instead of merely fitting a bunch of weights in some sum product model, one could use genetic programming where the primitives represented actual computations from a simplified model of cell dynamics. So while not guidance it still offers some way of embedding some intelligence in the search.