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. 2022:2517:229-240.
doi: 10.1007/978-1-0716-2417-3_18.

Bioinformatic Identification of ABC Transporters in Candida auris

Atanu Banerjee  1 , Poonam Vishwakarma  2   3 , Naveen Kumar Meena  2 , Andrew M Lynn  4 , Rajendra Prasad  5
Affiliations

Bioinformatic Identification of ABC Transporters in Candida auris

Atanu Banerjee et al. Methods Mol Biol. 2022.

Abstract

Antifungal resistance mediated by overexpression of ABC transporters is one of the primary roadblocks to effective therapy against Candida infections. Thus, identification and characterization of the ABC transporter repertoire in Candida species are of high relevance. The method described in the chapter is based on our previously developed bioinformatic pipeline for identification of ABC proteins in Candida species. The methodology essentially involves the utilization of a hidden Markov model (HMM) profile of the nucleotide-binding domain (NBD) of ABC proteins to mine these proteins from the proteome of Candida species. Further, a widely used tool to predict membrane protein topology is exploited to identify the true transporter candidates out of the ABC proteins. Even though the chapter specifically focuses on a method to identify ABC transporters in Candida auris , the same can also be applied to any other Candida species.

Keywords: ABC transporters; HMMER; Hidden Markov model; NBD-HMM profile; Pfam; TOPCONS.

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