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Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
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PASTA sequence composition is a predictive tool for protein class identification.

Luisa Calvanese1, Lucia Falcigno1,2,3, Flavia Squeglia3

  • 1CIRPeB, University of Naples Federico II, via Mezzocannone 16, 80134, Naples, Italy.

Amino Acids
|July 23, 2018
PubMed
Summary

This study introduces a new method to classify bacterial PASTA domains, which are potential antibiotic targets. The approach uses sequence information to distinguish between PASTA domains found in penicillin-binding proteins and Ser/Thr protein kinases.

Keywords:
Amino acid compositionAnnotationBacterial proteinPASTA domain

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Area of Science:

  • Microbiology
  • Structural Biology
  • Drug Discovery

Background:

  • PASTA domains are bacterial protein modules found in penicillin-binding proteins (PBPs) and Ser/Thr protein kinases (STPKs).
  • These domains are potential targets for novel antibiotics and are thought to function as sensors, but their binding abilities differ between PBPs and STPKs.
  • Current methods cannot distinguish between PASTA domains from these two classes due to their conserved fold.

Purpose of the Study:

  • To develop a predictive tool for classifying bacterial PASTA domains based on their associated enzyme class (PBP or STPK).
  • To enable differentiation of PASTA domains, aiding in the development of targeted antibiotics.

Main Methods:

  • Analysis of amino acid compositions and total charges of PASTA domains from Actinobacteria, Firmicutes, and Bacteroidetes.
  • Screening of sequences from key bacterial phyla, including those containing human pathogens like Mycobacterium tuberculosis and Staphylococcus aureus.

Main Results:

  • Identification of distinct sequence-based parameters that differentiate PASTA domains linked to PBPs versus STPKs.
  • Development of a predictive method capable of assigning unknown PASTA domains to their respective enzyme classes using only sequence data.

Conclusions:

  • Sequence information alone is sufficient to predict the enzyme class of bacterial PASTA domains.
  • This predictive method can facilitate the identification of novel antibiotic targets by distinguishing between PBP- and STPK-associated PASTA domains.