Improving deep learning protein monomer and complex structure prediction using DeepMSA2 with huge metagenomics data

Leveraging iterative alignment search through genomic and metagenome sequence databases, we report the DeepMSA2 pipeline for uniform protein single- and multichain multiple-sequence alignment (MSA) construction. Large-scale benchmarks show that DeepMSA2 MSAs can remarkably increase the accuracy of protein tertiary and quaternary structure predictions compared with current state-of-the-art methods. An integrated pipeline with DeepMSA2 participated in the most recent CASP15 experiment and created complex structural models with considerably higher quality than the AlphaFold2-Multimer server (v.2.2.0). Detailed data analyses show that the major advantage of DeepMSA2 lies in its balanced alignment search and…

• NS
  National Science Foundation

  Awards: IIS1901191, ACI1548562, MTM2025426, S10OD026825, GM136422, DBI2030790, AI134678
• DO
  Division of Intramural Research, National Institute of Allergy and Infectious Diseases

  Award: AI134678
• NI
  National Institute of General Medical Sciences

  Awards: AI134678, ACI1548562, IIS1901191, S10OD026825, DBI2030790, MTM2025426, GM136422
• NI
  National Institute of Allergy and Infectious Diseases

  Awards: MTM2025426, IIS1901191, ACI1548562, DBI2030790, S10OD026825, GM136422, AI134678