Alphapulldown

Match with AlphaPulldown version

- **Bug Fix**: Fixed a bug affecting the pairing of sequences from the same species, which prevented pairing altogether. This issue was present in AlphaPulldown versions released since August 2023 and may have reduced prediction accuracy.
- **Database Note**: The MSA features in our [database](https://alphapulldown.s3.embl.de/index.html) currently lack the pairing information needed to pair sequences from the same species. Using these features may also impact accuracy, please generate features yourself using the latest AlphaPulldown version. We are actively working on a fix.

🚀 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 the 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 for a smoother user experience.

🌐 Repository of Precomputed Features
Released a web-based [repository of precomputed input features](https://github.com/KosinskiLab/AlphaPulldown?tab=readme-ov-file#features-database) for multiple model organisms, reducing redundant computations and accelerating workflows.

🚀 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 the 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 for a smoother user experience.

🌐 Repository of Precomputed Features
Released a web-based [**repository of precomputed input features**](https://github.com/KosinskiLab/AlphaPulldown?tab=readme-ov-file#features-database) for multiple model organisms, reducing redundant computations and accelerating workflows.

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Release Notes

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**🚀 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](https://github.com/KosinskiLab/AlphaPulldown?tab=readme-ov-file#features-database) for multiple model organisms, reducing redundant computations and accelerating workflows.

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1) Update biopython to the latest version
2) Instructions on how to install cpp4 within the analysis container
3) Fix run_multimer_jobs.py relative paths
4) Remove run_alphafold.py and stereo_chemicsl_props.py from installation
5) Made compatible with python>3.10
6) Multiple minor code optimizations