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arXiv Machine Learning By Richard Zhu, Darren Xu, Lee-Shin Chu, Jeffrey J. Gray

Improving scoring functions for protein-protein docking with LambdaLoss

Read the original on arXiv Machine Learning →

The paper introduces LambdaDockScore, a protein‑protein docking scoring function that leverages the LambdaLoss loss from Learning‑to‑Rank to improve pose ranking. By fine‑tuning the energy prediction head of DFMDock on 2.9 million decoy poses from the DIPS dataset, LambdaDockScore outperforms the state‑of‑the‑art EuDockScore on CAPRI benchmark targets, achieving higher accuracy in top‑1 and top‑5 predictions. It also enhances ranking for antibody‑antigen and protein‑protein complexes with extreme binding interface sizes.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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