PyVADesign: a python-based cloning tool for one-step generation of large mutant libraries.

{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40888753", "kind": "science-record", "revision": 2, "content_hash": "sha256:97c8f944bedf7758e9982eaf246313c5a853ff3c97f1b8358273abcdd3952c34", "created_at": "2026-11-01T20:30:59Z", "updated_at": "2026-11-01T21:35:43Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "PyVADesign: a python-based cloning tool for one-step generation of large mutant libraries.", "doi": "10.1093/bioinformatics/btaf433", "pmid": "40888753", "authors": ["R C M Kuin", "M H Lamers", "G J P van Westen"], "journal": "Bioinformatics (Oxford, England)", "year": 2025, "abstract": "MOTIVATION: The generation and analysis of diverse mutants of a protein is a powerful tool for understanding protein function. However, generating such mutants can be time-consuming, while the commercial option of buying a series of mutant plasmids can be expensive. In contrast, the insertion of a synthesized double-stranded DNA (dsDNA) fragment into a plasmid is a fast and low-cost method to generate a large library of mutants with one or more point mutations, insertions, or deletions.\nRESULTS: To aid in the design of these DNA fragments, we have developed PyVADesign: a Python package that makes the design and ordering of dsDNA fragments straightforward and cost-effective. In PyVADesign, the mutations of interest are clustered in different cloning groups for efficient exchange into the target plasmid. Additionally, primers that prepare the target plasmid for insertion of the dsDNA fragment, as well as primers for sequencing, are automatically designed within the same program.\nAVAILABILITY AND IMPLEMENTATION: PyVADesign is open source and available at https://github.com/CDDLeiden/PyVADesign and archived via Zenodo (https://doi.org/10.5281/zenodo.15057525).", "claims": [{"id": "claim-method", "statement": "First, the desired mutations are grouped together into clusters using K-medoids clustering (Kaufman and Rousseau, 1990) in scikit-learn-extra (The scikit-learn-extra development team, 2020).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40888753", "locator": "sections[3] \"2.1 dsDNA fragment design process\" paragraph 2", "quote": "First, the desired mutations are grouped together into clusters using K-medoids clustering (Kaufman and Rousseau, 1990) in scikit-learn-extra (The scikit-learn-extra development team, 2020)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The source code is available at https://github.com/CDDLeiden/PyVADesign. All code and data are archived via Zenodo (https://doi.org/10.5281/zenodo.15057525).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40888753", "locator": "sections[19] \"Data availability\" paragraph 2", "quote": "The source code is available at https://github.com/CDDLeiden/PyVADesign. All code and data are archived via Zenodo (https://doi.org/10.5281/zenodo.15057525)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "PyVADesign automates the design of dsDNA fragments and associated primers for generating large libraries of protein mutants.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40888753", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "To aid in the design of these DNA fragments, we have developed PyVADesign: a Python package that makes the design and ordering of dsDNA fragments straightforward and cost-effective."}, {"asset": "source:pmid:40888753", "locator": "sections[12] \"3.4 Experimental validation\" paragraph 2", "quote": "The 24 mutations were distributed over three fragment regions."}, {"asset": "source:pmid:40888753", "locator": "sections[12] \"3.4 Experimental validation\" paragraph 2", "quote": "Using this approach, all 24 mutant plasmids were generated within a span of two weeks."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "PyVADesign automates the design of dsDNA fragments and associated primers for generating large libraries of protein mutants.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:40888753"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "blocked", "blocked_on": "data:accession_absent", "description": "The GEO series accession resolves and its sample accessions are listed. 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