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Peer-reviewedCC BY 4.0Nucleic Acids Research

The MODNAP benchmark set for modeling ribose-based modified nucleic acid and nucleic acid–protein complexes: a case study with AlphaFold 3

  • Jiemin Fu1
  • Valeria Tohver Milam2
  • Andrew C McShan1
  1. 1School of Chemistry and Biochemistry, Georgia Institute of Technology , Atlanta, GA 30332 ,
  2. 2School of Materials Science and Engineering, Georgia Institute of Technology , Atlanta, GA 30332 ,
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Abstract

Modified nucleic acids play important roles in biology and biotechnology. However, their chemical and structural diversity as well as effects on nucleic acid structure and intermolecular interactions remain incompletely characterized. The performance of structure prediction and co-folding algorithms for modeling modified nucleic acids and nucleic acid–protein complexes has also not been evaluated. Here, we systematically analyze ribose-based modified nucleotides present in structures deposited in the Protein Data Bank. Modified nucleotides are primarily localized to the nucleobase, where they exhibit chemical and structural diversity shaped by molecular size, topological shape descriptors, and polarity-related properties. We develop MODNAP, the first curated dataset of experimentally determined structures containing modified nucleotides. Using MODNAP, we benchmark AlphaFold 3 on 1039 nucleic acid and nucleic acid–protein complex structures spanning a range of nucleotide modifications, tertiary folds, and biological functions. AlphaFold 3 achieves success rates exceeding 80% at an RMSD threshold of 2.5 Å. However, its accuracy in positioning modified nucleotides is variable and decreases for structures not explicitly represented in training. PoseBusters analysis reveals frequent intramolecular validity failures, primarily due to non-ideal ribose ring geometries. Together, these results establish MODNAP as a resource for evaluating and improving structure prediction methods for modified nucleic acids.

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Cite

BibTeXRIS
BibTeX
@article{fu2026modnap,
  title = {{The MODNAP benchmark set for modeling ribose-based modified nucleic acid and nucleic acid–protein complexes: a case study with AlphaFold 3}},
  author = {Jiemin Fu and Valeria Tohver Milam and Andrew C McShan},
  journal = {Nucleic Acids Research},
  year = {2026},
  month = oct,
  doi = {10.1093/nar/gkag999},
  url = {https://academic.oup.com/nar/article/doi/10.1093/nar/gkag999/8916839},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - The MODNAP benchmark set for modeling ribose-based modified nucleic acid and nucleic acid–protein complexes: a case study with AlphaFold 3
AU  - Jiemin Fu
AU  - Valeria Tohver Milam
AU  - Andrew C McShan
PY  - 2026
DA  - 2026/10/15
JO  - Nucleic Acids Research
DO  - 10.1093/nar/gkag999
UR  - https://academic.oup.com/nar/article/doi/10.1093/nar/gkag999/8916839
AB  - Modified nucleic acids play important roles in biology and biotechnology. However, their chemical and structural diversity as well as effects on nucleic acid structure and intermolecular interactions remain incompletely characterized. The performance of structure prediction and co-folding algorithms for modeling modified nucleic acids and nucleic acid–protein complexes has also not been evaluated. Here, we systematically analyze ribose-based modified nucleotides present in structures deposited in the Protein Data Bank. Modified nucleotides are primarily localized to the nucleobase, where they exhibit chemical and structural diversity shaped by molecular size, topological shape descriptors, and polarity-related properties. We develop MODNAP, the first curated dataset of experimentally determined structures containing modified nucleotides. Using MODNAP, we benchmark AlphaFold 3 on 1039 nucleic acid and nucleic acid–protein complex structures spanning a range of nucleotide modifications, tertiary folds, and biological functions. AlphaFold 3 achieves success rates exceeding 80% at an RMSD threshold of 2.5 Å. However, its accuracy in positioning modified nucleotides is variable and decreases for structures not explicitly represented in training. PoseBusters analysis reveals frequent intramolecular validity failures, primarily due to non-ideal ribose ring geometries. Together, these results establish MODNAP as a resource for evaluating and improving structure prediction methods for modified nucleic acids.
SN  - 0305-1048
SN  - 1362-4962
ER  -