BACKGROUND: The generation of focused mutant libraries at hotspot residues is an important strategy in directed protein evolution. Existing methods, such as combinatorial active site testing and residual coupling analysis, depend primarily on the evolutionary conserved information to find the hotspot residues. Hardly any attention has been paid to another important functional and structural determinants, the functionally correlated variation information--coevolution. RESULTS: In this paper, we suggest a new method, named combinatorial coevolving-site saturation mutagenesis (CCSM), in which the functionally correlated variation sites of proteins are chosen as the hotspot sites to construct focused mutant libraries. The CCSM approach was used to improve the thermal stability of α-amylase from Bacillus subtilis CN7 (Amy7C). The results indicate that the CCSM can identify novel beneficial mutation sites, and enhance the thermal stability of wild-type Amy7C by 8°C ( T5030), which could not be achieved with the ordinarily rational introduction of single or a double point mutation. CONCLUSIONS: Our method is able to produce more thermostable mutant α-amylases with novel beneficial mutations at new sites. It is also verified that the coevolving sites can be used as the hotspots to construct focused mutant libraries in protein engineering. This study throws new light on the active researches of the molecular coevolution.

Process planning is a time-consuming and tedious operation that is necessary to manufacture products. In addition, process plans must be optimized to drive machines most productively. To accomplish this goal, the authors search for plans that satisfy production feasibility requirements and time constraints. Unfortunately, this search operates in an enormous search-space that is usually impossible to navigate. Therefore, the authors use features and their corresponding heuristics to guide the search. To make the search more tractable, the authors convert some features into corresponding constraints as a priori knowledge to prune the space. The applications of these features are presented in this paper. The authors also discuss the feature interaction problems in the process planning. In this paper, the authors focus on the production of bent sheet metal parts and the machine setup. The authors have designed over forty test parts with their "parallel design" system, and the features are automatically generated as the design progresses. After the design is complete, an automatic process planning system uses the features and generates new ones to aid the production of a near-minimum manufacturing cost plan. Finally, these plans are used to produce parts on an automatic bending system.