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In addition to its value in the study of molecular evolution, ancestral sequence reconstruction (ASR) has emerged as a useful methodology for engineering proteins with enhanced properties. Proteins generated by ASR often exhibit unique or improved activity, stability, and/or promiscuity, all of which are properties that are valued by protein engineers. Comparison between extant proteins and evolutionary intermediates generated by ASR also allows protein engineers to identify substitutions that have contributed to functional innovation or diversification within protein families. As ASR becomes more widely adopted as a protein engineering approach, it is important to understand the applications, limitations, and recent developments of this technique. This review highlights recent exemplifications of ASR, as well as technical aspects of the reconstruction process that are relevant to protein engineering. [Display omitted] • Proteins produced by ancestral sequence reconstruction (ASR) often exhibit high activity, stability, and evolvability. • ASR studies guide engineering by highlighting function-shifting substitutions. • ASR emphasizes fundamental drivers of, and constraints to, functional innovation. • Recent developments in ASR are making it more accessible to protein engineers. [ABSTRACT FROM AUTHOR]

• Designing genetically encoded fluorescence-based analyte biosensors is not trivial. • Many current design efforts take a nature-inspired, modular approach. • Individual sensor components can be engineered separately for desired properties. • Screening of large variant libraries is often required to optimize biosensors. Biosensors that selectively report on the presence of specific small molecule analytes have applications in many fields of research, medicine and biotechnology. Here, we review recent advances and emerging approaches in the design and optimisation of genetically encoded fluorescence-based small molecule biosensors. We discuss how natural sensory proteins can be exploited to produce novel biosensors and the strategies for optimizing ligand specificity and fluorescence readout. Finally, we provide insight into high-throughput sensor optimisation and discuss the challenges that are faced when designing novel biosensors. [ABSTRACT FROM AUTHOR]