The comparison of aggregation and folding of enhanced green fluorescent protein (EGFP) by spectroscopic studies is a research paper published in Spectroscopy (2010). On theSindex it has a DataRank of 1.3. It has been cited 22 times, with 19 citing works in its 1-hop citation network.
GFP (Green Fluorescent Protein) is well known for its unique chromophore which is formed by autocatalytic cyclization of a polypeptide backbone of Ser65, Tyr66 and Gly67, and is able to emit green visible light. Due to unusual chromophore responsible for the fluorescence GFP and its mutants (e.g., EGFP) have become widely used reporter proteins in molecular biology and biotechnology. GFP can easily be fused to any protein of interest and co-expressed in cells; the GFP fluorescence is then used to visualize the distribution, transport and aggregation of the protein in the cell. However, GFP has a tendency to aggregate itself, and also formation of its chromophore critically depends on the presence of reducing agents. Therefore we have undertaken spectroscopic kinetic studies of EGFP folding and aggregation as a function of pH, and in the presence of various reducing agents, to study the competition between these two processes. The best conditions for folding of EGFP provides BME as a reducing agent. Aggregation of EGFP depends strongly on pH, and on the concentration of the protein. The careful control experiments must therefore be performed during investigations of proteins fused with EGFP, especially at pH lower than 7.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.470
From this paper's citation signal
Citation Network Contribution
0.855
From 18 citing papers with measurable signal
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 35% comes from its base citations and 65% from the citation network (18 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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