Dan Davidi
Weizmann Institute of Science
32 Papers
55 Citations
Dan Davidi is an academic researcher from Weizmann Institute of Science. The author has contributed to research in topics: RuBisCO & Biology. The author has an hindex of 17, co-authored 30 publications. Previous affiliations of Dan Davidi include Harvard University & Tel Aviv University.
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Papers
The Moderately Efficient Enzyme: Evolutionary and Physicochemical Trends Shaping Enzyme Parameters
Arren Bar-Even,Elad Noor,Yonatan Savir,Wolfram Liebermeister,Dan Davidi,Dan S. Tawfik,Ron Milo +6 more
TL;DR: It appears that both evolutionary selection pressures and physicochemical constraints shape the kinetic parameters of enzymes, and it seems likely that the catalytic efficiency of some enzymes toward their natural substrates could be increased in many cases by natural or laboratory evolution.
1K
Visual account of protein investment in cellular functions
TL;DR: It is suggested that evaluating the way protein resources are allocated by various organisms and cell types in different conditions will sharpen the understanding of how and why cells regulate the composition of their proteomes.
375
Sugar Synthesis from CO2 in Escherichia coli
Niv Antonovsky,Shmuel Gleizer,Elad Noor,Yehudit Zohar,Elad Herz,Uri Barenholz,Lior Zelcbuch,Shira Amram,Aryeh Wides,Naama Tepper,Dan Davidi,Yinon M. Bar-On,Tasneem Bareia,David G. Wernick,Ido Shani,Sergey Malitsky,Ghil Jona,Arren Bar-Even,Ron Milo +18 more
TL;DR: The successful evolution of a non-native carbon fixation pathway, though not yet resulting in net carbon gain, strikingly demonstrates the capacity for rapid trophic-mode evolution of metabolism applicable to biotechnology.
342
Global characterization of in vivo enzyme catalytic rates and their correspondence to in vitro kcat measurements.
Dan Davidi,Elad Noor,Wolfram Liebermeister,Arren Bar-Even,Avi I. Flamholz,Katja Tummler,Uri Barenholz,Miki Goldenfeld,Tomer Shlomi,Ron Milo +9 more
TL;DR: The approach here characterizes the quantitative relationship between enzymatic catalysis in vitro and in vivo and offers a high-throughput method for extracting enzyme kinetic constants from omics data.
256
The Protein Cost of Metabolic Fluxes: Prediction from Enzymatic Rate Laws and Cost Minimization.
TL;DR: ECM provides a physically plausible and computationally tractable way to include enzyme kinetics into constraint-based metabolic models, where kinetics have usually been ignored or oversimplified, and establishes a direct connection between protein cost and thermodynamics.