MOTIVATION: The structural characterization of protein-protein interactions is a key step in understanding the functions of living cells. Here, I show that AlphaFold3 often fails to predict protein complexes that are either weak or dependent on the presence of a cofactor that is not included in a prediction. RESULTS: To address this problem, I developed gapTrick, an AlphaFold2-based approach that uses multimeric templates to improve prediction reliability. I demonstrate that gapTrick improves predictions of weak and incomplete complexes based on low-accuracy templates, such as individual protein models that have been rigid-body fitted into cryo-EM reconstructions. I also show that gapTrick identifies residue-residue interactions with high precision. These interaction predictions are a very strong indicator of model correctness. The approach can aid in the interpretation of challenging experimental structures and the computational identification of protein-protein interactions. AVAILABILITY AND IMPLEMENTATION: The gapTrick source code is available at https://github.com/gchojnowski/gapTrick and requires only a standard AlphaFold2 installation to run. The repository also provides a Colab notebook that can be used to run gapTrick without installing it on the user's computer.

SUMMARY: AlphaPulldown2 streamlines protein structural modeling by automating workflows, improving code adaptability, and optimizing data management for large-scale applications. It introduces an automated Snakemake pipeline, compressed data storage, support for additional modeling backends like UniFold and AlphaLink2, and a range of other improvements. These upgrades make AlphaPulldown2 a versatile platform for predicting both binary interactions and complex multi-unit assemblies. AVAILABILITY AND IMPLEMENTATION: AlphaPulldown2 is freely available at https://github.com/KosinskiLab/AlphaPulldown.

SUMMARY: Structure determination is a key step in the functional characterization of many non-coding RNA molecules. High-resolution RNA 3D structure determination efforts, however, are not keeping up with the pace of discovery of new non-coding RNA sequences. This increases the importance of computational approaches and low-resolution experimental data, such as from the small-angle X-ray scattering experiments. We present RNA Masonry, a computer program and a web service for a fully automated modeling of RNA 3D structures. It assemblies RNA fragments into geometrically plausible models that meet user-provided secondary structure constraints, restraints on tertiary contacts, and small-angle X-ray scattering data. We illustrate the method description with detailed benchmarks and its application to structural studies of viral RNAs with SAXS restraints. AVAILABILITY AND IMPLEMENTATION: The program web server is available at http://iimcb.genesilico.pl/rnamasonry. The source code is available at https://gitlab.com/gchojnowski/rnamasonry.

SUMMARY: The artificial intelligence-based structure prediction program AlphaFold-Multimer enabled structural modelling of protein complexes with unprecedented accuracy. Increasingly, AlphaFold-Multimer is also used to discover new protein-protein interactions (PPIs). Here, we present AlphaPulldown, a Python package that streamlines PPI screens and high-throughput modelling of higher-order oligomers using AlphaFold-Multimer. It provides a convenient command-line interface, a variety of confidence scores and a graphical analysis tool. AVAILABILITY AND IMPLEMENTATION: AlphaPulldown is freely available at https://www.embl-hamburg.de/AlphaPulldown. SUPPLEMENTARY INFORMATION: Supplementary note is available at Bioinformatics online.

Abstract Summary: Co-crystallization experiments of proteins with nucleic acids do not guarantee that both components are present in the crystal. We have previously developed DIBER to predict crystal content when protein and DNA are present in the crystallization mix. Here, we present RIBER, which should be used when protein and RNA are in the crystallization drop. The combined RIBER/DIBER suite builds on machine learning techniques to make reliable, quantitative predictions of crystal content for non-expert users and high-throughput crystallography. Availability: The program source code, Linux binaries and a web server are available at http://diber.iimcb.gov.pl/ RIBER/DIBER requires diffraction data to at least 3.0 Å resolution in MTZ or CIF (web server only) format. The RIBER/DIBER code is subject to the GNU Public License. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.