AlphaPulldown v2.0.0 #451
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Nice Does "relax" work now? and what about all-vs-all does that work in this version, as in there are no redundancy in the tested protein pairs? |
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Yes, "relax" works and all_vs_all does not produce redundant complexes anymore. Please feel free to give it a try, and we are looking forward to your feedback, as usual |
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Sounds good! One random idea, what do you think about having a filter for the relax part? As in it only runs relax protocol on the best model (ranked 0) for a protein pair if the iptm is above a certain threshold, like 0,6 etc.? |
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Yes, that is an interesting idea. We will think about implementing that, thanks! |
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Good idea, could you start a new issue with this feature request so we don’t forget? |
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Release Notes
🚀 Automated Workflows with Snakemake
Introduced a streamlined pipeline for modeling tasks, leveraging Snakemake for automation, scalability, and reproducibility. Installation is now simplified with Docker/Singularity containers.
🔧 Unified Configuration Syntax
All AlphaPulldown modes now share a unified configuration syntax, simplifying input setup and enabling automatic sequence retrieval with UniProt IDs.
🛠️ Modular Backend Support
Reorganized codebase to support multiple modeling backends flexibly. UniFold and AlphaLink2 are now integrated, with the potential to add more in the future.
🔗 Cross-Link-Driven Modeling
AlphaLink2 integration supports modeling with cross-linking mass spectrometry (XL-MS) data, enhancing the accuracy of complex structural models.
💾 Significant Storage Optimization
Achieved more than 90% reduction in storage through input feature and output file compression, promoting sustainability in large-scale modeling.
📦 ModelCIF Format Support
Models can now be stored in ModelCIF format, aligning with FAIR principles for improved model accessibility and simpler model deposition in databases.
🧩 Extended Modeling Capabilities
Increased flexibility with customizable modeling parameters, multimeric template support, and options to control MSA and template impact on predictions.
📊 Enhanced Analysis Pipeline
Enriched the analysis toolkit with additional evaluation metrics like average pLDDT and PAE scores at protein interfaces for better assessment of model confidence..
🔄 Improved Codebase and Documentation
Refactored code, introduced CI/CD pipelines, automated testing, and expanded documentation.
🌐 Repository of Precomputed Features
Released a web-based repository of precomputed input features for multiple model organisms, reducing redundant computations and accelerating workflows.
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