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iLOV is a flavin mononucleotide-binding fluorescent protein used for in vivo cellular imaging similar to the green fluorescent protein. To expand the range of applications of iLOV, spectrally tuned red-shifted variants are desirable to reduce phototoxicity and allow for better tissue penetration. In this report, we experimentally tested two iLOV mutants, iLOV L470T/Q489K and iLOV V392K/F410V/A426S , which were previously computationally proposed by ( Khrenova Khrenova 28992704 J. Phys. Chem. B 2017 121 10018 10025 ) to have red-shifted excitation and emission spectra. While iLOV L470T/Q489K is about 20% brighter compared to the WT in vitro , it exhibits a blue shift in contrast to quantum mechanics/molecular mechanics (QM/MM) predictions. Additional optical characterization of an iLOV V392K mutant revealed that V392 is essential for cofactor binding and, accordingly, variants with V392K mutation are unable to bind to FMN. iLOV L470T/Q489K and iLOV V392K/F410V/A426S are expressed at low levels and have no detectable fluorescence in living cells, preventing their utilization in imaging applications.

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In most expert systems for constructional tasks, the knowledge base consists of a set of facts or object definitions and a set of rules. These rules contain knowledge about correct or ideal solutions as well as knowledge on how to control the construction process. In this paper, we present an approach that avoids this type of rules and thus the disadvantages caused by them.We propose a static knowledge base consisting of a set of object definitions interconnected by is-a and part-of links. This conceptual hierarchy declaratively defines a taxonomy of domain objects and the aggregation of components to composite objects. Thus, the conceptual hierarchy describes the set of all admissible solutions to a constructional problem. Interdependencies between objects are represented by constraints. A solution is a syntactically complete and correct instantiation of the conceptual hierarchy.No control knowledge is included in the conceptual hierarchy. Instead, the control mechanism will use the conceptual hierarchy as a guideline. Thus it is possible to determine in which respects a current partial solution is incomplete simply by syntactical comparison with the conceptual hierarchy. The control architecture proposed here has the following characteristics: separation of control and object knowledge, declarative representation of control knowledge, and explicit control decisions in the problem solving process. Thus, a flexible control mechanism can be realized that supports interactive construction, integration of case-based approaches and simulation methods.This control method is part of an expert system kernel for planning and configuration tasks in technical domains. This kernel has been developed at the University of Hamburg and is currently applied to several domains.

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