ArticleProteins2026
Modeling Protein-Protein and Protein-Ligand Interactions by the ClusPro Team in CASP16.
Article in Proteins, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Docking-based virtual screening: Past, present, and future.Biophysical journal · 2026Review
- The X-Ray Crystal Structure of BorF, the Flavin Reductase Subunit of a Two-Component Flavin-Dependent Tryptophan Halogenase.Proteins · 2026Article
- Generation and immunological evaluation of SARS-CoV-2 membrane protein virus-like particles.Virology journal · 2026Article
- Benchmarking AlphaFold and related deep learning approaches for modeling antibody and TCR antigen recognition.bioRxiv : the preprint server for biology · 2026Article
- Open-Source Molecular Docking and AI-Augmented Structure-Based Drug Design: Current Workflows, Challenges, and Opportunities.International journal of molecular sciences · 2026Review
- AI-Assisted Computed Structure Models for Pre-Ubiquitylation Complexes Assembled by Respiratory Syncytial Viral Suppressors of Cellular Interferon Response.International journal of molecular sciences · 2026Article
- Immunoinformatics-guided design of a multi-epitope vaccine targeting the envelopment polyprotein of oropouche virus.Molecular genetics and genomics : MGG · 2026Article
- Progress and Bottlenecks for Deep Learning in Computational Structure Biology: CASP Round XVI.Proteins · 2026Article
- Gold Nanoparticle-Based Systems for Targeting the Ara h2 Allergen: A Molecular Modeling Approach.Computational and structural biotechnology journal · 2026Article
- Article
- Modeling Protein-Protein and Protein-Ligand Interactions by the ClusPro Team in CASP16.Proteins · 2026Article
- Large scale prospective evaluation of co-folding across 557 Mac1-ligand complexes and three virtual screens.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
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Authors and funding
27 authors.
Funding
Abstract
In the CASP16 experiment, our team employed hybrid computational strategies to predict both protein-protein and protein-ligand complex structures. For protein-protein docking, we combined physics-based sampling-using ClusPro FFT docking and molecular dynamics-with AlphaFold (AF)-based sampling, followed by AF-based refinement. Our method produced numerous high-accuracy complex models, including cases where AF alone failed, underscoring the critical role of physics-based sampling alongside deep learning-based refinement. For protein-ligand docking, we integrated the ClusPro LigTBM template-based approach with a machine learning-based confidence model for rescoring. The method preserves conserved interaction fragments derived from homologous complexes, followed by local resampling using physics-based sampling and a diffusion model. Our template-based strategy achieved a mean lDDT-PLI of 0.69 across 233 targets, which was highly competitive. These results demonstrate that combining physics-based modeling with AI-driven refinement can significantly enhance the accuracy of both protein-protein and protein-ligand structure predictions.
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