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Structural and functional diversity calls for a new classification of ABC transporters.

Christoph ThomasStephen G AllerKonstantinos BeisElisabeth P CarpenterGeoffrey ChangLei ChenElie DassaMichael DeanFranck Duong Van HoaDamian EkiertRobert FordRachelle GaudetXin GongI Barry HollandYihua HuangDaniel K KahneHiroaki KatoVassilis KoronakisChristopher M KothYoungsook LeeOded LewinsonRoland LillEnrico MartinoiaSatoshi MurakamiHeather W PinkettBert PoolmanDaniel RosenbaumBalazs SarkadiLutz SchmittErwin SchneiderYigong ShiShow-Ling ShyngDirk Jan SlotboomEmad TajkhorshidD Peter TielemanKazumitsu UedaAndrás VáradiPo-Chao WenNieng YanPeng ZhangHongjin ZhengJochen ZimmerRobert Tampé
Published in: FEBS letters (2020)
Members of the ATP-binding cassette (ABC) transporter superfamily translocate a broad spectrum of chemically diverse substrates. While their eponymous ATP-binding cassette in the nucleotide-binding domains (NBDs) is highly conserved, their transmembrane domains (TMDs) forming the translocation pathway exhibit distinct folds and topologies, suggesting that during evolution the ancient motor domains were combined with different transmembrane mechanical systems to orchestrate a variety of cellular processes. In recent years, it has become increasingly evident that the distinct TMD folds are best suited to categorize the multitude of ABC transporters. We therefore propose a new ABC transporter classification that is based on structural homology in the TMDs.
Keyphrases
  • machine learning
  • deep learning
  • dna binding
  • binding protein