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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
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An Integrated Method to Reconstruct Ancient Proteins.

Amanda K Garcia1, Evrim Fer1,2, Cathryn Sephus3

  • 1Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA.

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|September 9, 2022
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Summary
This summary is machine-generated.

Ancestral sequence reconstruction (ASR) revives ancient proteins to study their evolutionary history. This method helps overcome limitations in studying protein evolution across geologic time.

Keywords:
Ancestral sequence reconstructionAncestral sequence uncertaintyMaximum likelihoodMolecular paleobiologyPhylogenetic reconstruction

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Area of Science:

  • Evolutionary Biology
  • Molecular Biology
  • Biochemistry

Background:

  • Proteins are fundamental to life, but their ancient origins and early functions are difficult to study due to poor preservation over geologic time.
  • Understanding protein evolution is crucial for deciphering life's history.
  • Existing methods struggle to directly investigate the deep evolutionary past of proteins.

Purpose of the Study:

  • To provide a generalized protocol for Ancestral Sequence Reconstruction (ASR).
  • To detail key elements for designing robust ASR studies.
  • To identify and mitigate potential biases in reconstructing ancient protein sequences.

Main Methods:

  • Utilizes phylogenetic tools to infer ancestral amino acid sequences from extant organisms.
  • Involves experimental resurrection of deduced ancient protein sequences.
  • Employs a stepwise approach to guide ASR study design.

Main Results:

  • Presents a generalized protocol for ASR.
  • Highlights critical stages for successful protein evolution studies.
  • Identifies sources of reconstruction bias that can affect historical inferences.

Conclusions:

  • ASR is a powerful method for inferring and studying ancient protein sequences.
  • The proposed protocol aims to improve the reliability of evolutionary inferences.
  • This approach enables broader utilization for reconstructing protein evolutionary histories.