While nature evolved polypeptides over billions of years, protein design by evolutionary mimicry is progressing at a far more rapid pace. The mutation, selection, and amplification steps of the evolutionary cycle may be imitated in the laboratory using existing proteins, or molecules created de novo from random sequence space, as starting templates. However, the astronomically large number of possible polypeptide sequences remains an obstacle to identifying and isolating functionally interesting variants. Intelligently designed libraries and improved search techniques are consequently important for future advances. In this regard, combining experimental and computational methods holds particular promise for the creation of tailored protein receptors and catalysts for tasks unimagined by nature.

Give and take: The influence of fluoro substitution of amino acid side chains on their interaction profile in a native polypeptide environment was studied systematically. The fluorination of alkyl groups has opposing electrostatic and steric consequences for the stability of hydrophobic protein cores.

The use of fluorine has become well established in the analysis of protein structure and function, e.g. in tools such as 19F NMR spectroscopy. The application of the unique electronic properties of this element for the structural and chemical modification of peptides and proteins emerged as a promising approach. However, the influences of amino acid fluorination on side‐chain interactions in proteins are still controversially discussed. The systematic investigation of the interaction properties of fluoroalkyl groups in a native polypeptide environment broadens the scope of fluorinated amino acids to the rational design of structural motifs and protein interfaces. (© Wiley‐VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2005)

Consensus design is an appealing strategy for the stabilization of proteins. It exploits amino acid conservation in sets of homologous proteins to identify likely beneficial mutations. Nevertheless, its success depends on the phylogenetic diversity of the sequence set available. Here we show that randomization of a single protein represents a reliable alternative source of sequence diversity essentially free of phylogenetic bias. A small number of functional protein sequences selected from binary-patterned libraries suffices as input for consensus design of active enzymes that are easier to produce and substantially more stable than individual members of the starting data set. Although catalytic activity correlates less consistently with sequence conservation in these extensively randomized proteins, less extreme mutagenesis strategies might be adopted in practice to augment stability while maintaining function. Keywordsprotein stabilization; multiple sequence alignments; consensus mutation; binary patterning; chorismate mutase Utilization of proteins outside of their normal biological context -for example in diagnostic, medical, or industrial applications or for the creation of novel receptors and catalysts1 ; 2 -often requires optimization of biophysical properties like stability.3 ; 4 For this purpose, engineering methods that exploit statistical amino acid frequencies from multiple sequence alignments (MSAs) are widely used.5 ; 6 Data-driven consensus design is based on the simple assumption that the frequency of a given residue in an MSA of homologous proteins correlates with that amino acid's contribution to protein stability.7 An artificial protein possessing the most frequent residue at each position should accordingly show maximum stability. Given the difficulty of predicting how individual residues contribute to overall stability,8 this approach to protein stabilization is often preferable to classical rational design, particularly as it does not depend on the availability of structural information.If an MSA were composed of fully independent protein sequences all selected for stable folding to the same structure, and if individual residues contributed additively to stability,

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