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Volume 168, Issue 12

Structure prediction-based insights into the patatin family of Free

Abstract

Despite its genome sequencing more than two decades ago, the majority of the genes of remain functionally uncharacterized. Patatins are one such class of proteins that, despite undergoing an expansion in this pathogenic species compared to their non-pathogenic cousins, remain largely unstudied. Recent advances in protein structure prediction using machine learning tools such as AlphaFold2 have provided high-confidence predicted structures for all proteins. Here we present detailed analyses of the patatin family of using AlphaFold-predicted structures, providing insights into likely modes of regulation, membrane interaction and substrate binding. Regulatory domains within this family of proteins include cyclic nucleotide binding, lid-like domains and other helical domains. Using structural homologues, we identified the likely membrane localization mechanisms and substrate-binding sites. These analyses reveal diversity in their regulatory capacity, mechanisms of membrane binding and likely length of fatty acid substrates. Together, this analysis suggests unique roles for the eight predicted patatins of .

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): AlphaFold , lipase , lipid , mycobacteria , patatin and tuberculosis
Funding
This study was supported by the:
  • Department of Biotechnology, Ministry of Science and Technology, India (Award BT/PR30856/Med/29/1363/2018)
    • Principle Award Recipient: SheetalGandotra
© 2022 The Authors
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2022-12-13
2024-05-17
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Structure prediction-based insights into the patatin family of Mycobacterium tuberculosis
Microbiology 168, 001270 (2022); https://doi.org/10.1099/mic.0.001270
/content/journal/micro/10.1099/mic.0.001270
/content/journal/micro/10.1099/mic.0.001270
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