Classical studies show that for many proteins, the information required for specifying the tertiary structure is contained in the amino acid sequence. However, the potential complexity of this information is truly enormous, a problem that makes defining the rules for protein folding difficult through either computational or experimental methods. In the past few years, we have reported a new method (that we call the statistical coupling analysis or SCA) for estimating the conserved evolutionary constraints between sites on proteins through statistical analysis of large and diverse multiple sequence alignments1,2. Experiments in several protein systems demonstrate the functional importance of this evolution-based mapping of amino acid interactions1,3,4 and recently, the SCA information was shown to the necessary and sufficient to design functional artificial members of a small protein family in the absence of any structural or chemical information. These results support the hypothesis that in a purely statistical and mechanism-free way, the SCA captures the evolutionary rules for specifying natural-like proteins. In recent work, we have extended these results to the design of larger protein domains and are working on the physical mechanisms underlying the statistical coupling. The evolutionary constraints between residues are much more sparse and heterogeneous than traditional analyses of atomic structures would suggest, a finding that guides our thinking about potential general principles underlying the natural design of proteins. [1] S.W. Lockless, R. Ranganathan, Science, 286, 295-9 (1999). [2] G. Suel et al., Nature Struct. Biol., 10., 59-69 (2003). [3] M.E. Hatley, et al., PNAS, 100: 14445-14450 (2003). [4] A.I. Shulman et al., Cell, 116: 417-429 (2004). [5] Socolich et al., Nature, 437: 512-518 (2005). [6] Russ et al., Nature, 437: 579-583 (2005).