Assessment of the CASP14 assembly predictions

Ozden B., Kryshtafovych A., KARACA EREK E.

PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, cilt.89, sa.12, ss.1787-1799, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 89 Sayı: 12
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1002/prot.26199
  • Dergi Adı: PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, BIOSIS, Biotechnology Research Abstracts, CAB Abstracts, Chemical Abstracts Core, EMBASE, Food Science & Technology Abstracts, INSPEC, MEDLINE, Veterinary Science Database
  • Sayfa Sayıları: ss.1787-1799
  • Anahtar Kelimeler: CASP, contact prediction, protein assembly, quaternary structure prediction, template-based modeling, CRYSTAL-STRUCTURE, PROTEIN DOCKING, CAPRI, COMPLEXES
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

In CASP14, 39 research groups submitted more than 2500 3D models on 22 protein complexes. In general, the community performed well in predicting the fold of the assemblies (for 80% of the targets), although it faced significant challenges in reproducing the native contacts. This is especially the case for the complexes without whole-assembly templates. The leading predictor, BAKER-experimental, used a methodology combining classical techniques (template-based modeling, protein docking) with deep learning-based contact predictions and a fold-and-dock approach. The Venclovas team achieved the runner-up position with template-based modeling and docking. By analyzing the target interfaces, we showed that the complexes with depleted charged contacts or dominating hydrophobic interactions were the most challenging ones to predict. We also demonstrated that if AlphaFold2 predictions were at hand, the interface prediction challenge could be alleviated for most of the targets. All in all, it is evident that new approaches are needed for the accurate prediction of assemblies, which undoubtedly will expand on the significant improvements in the tertiary structure prediction field.