CodonMutator: a python-based automated oligonucleotide design framework for deep mutational scanning library construction

Deep mutational scanning (DMS) enables systematic evaluation of protein sequence-function relationships, but its utility is often limited by the complexity of library construction. Existing mutagenesis strategies are either biased, labor-intensive, or prone to design errors, restricting their scalability for comprehensive variant generation. Here, we present a systematic cloning framework coupled with an automated Python-based pipeline for oligonucleotide design in DMS library construction. Our strategy employs restriction enzyme-guided tiling to partition coding sequences into manageable fragments, ensuring uniform coverage and compatibility with standard cloning workflows. The pipeline supports both strict and relaxed design modes, minimizes redundancy, and incorporates silent mutations to prevent restriction site conflicts. This platform optimizes library design efficiency, improves accuracy, and provides a flexible framework adaptable to diverse genes and experimental contexts. By integrating molecular cloning constraints with computational automation, our method offers a scalable and accessible solution to accelerate DMS library construction and functional genomics studies. [BMB Reports 2026; 59(2): 137-142].

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Publication Details

Journal
BMB Reports
Published
2026-02-26
DOI
https://doi.org/10.5483/bmbrep.2025-0161
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

CodonMutator: a python-based automated oligonucleotide design framework for deep mutational scanning library construction

S.K. Park, Byung Joon Hwang, Jeongha Lee, Murim Choi
BMB Reports
Genomics and Phylogenetic Studies
article

CodonMutator: a python-based automated oligonucleotide design framework for deep mutational scanning library construction

S.K. Park, Byung Joon Hwang, Jeongha Lee, Murim Choi
article en

Abstract

Deep mutational scanning (DMS) enables systematic evaluation of protein sequence-function relationships, but its utility is often limited by the complexity of library construction. Existing mutagenesis strategies are either biased, labor-intensive, or prone to design errors, restricting their scalability for comprehensive variant generation. Here, we present a systematic cloning framework coupled with an automated Python-based pipeline for oligonucleotide design in DMS library construction. Our strategy employs restriction enzyme-guided tiling to partition coding sequences into manageable fragments, ensuring uniform coverage and compatibility with standard cloning workflows. The pipeline supports both strict and relaxed design modes, minimizes redundancy, and incorporates silent mutations to prevent restriction site conflicts. This platform optimizes library design efficiency, improves accuracy, and provides a flexible framework adaptable to diverse genes and experimental contexts. By integrating molecular cloning constraints with computational automation, our method offers a scalable and accessible solution to accelerate DMS library construction and functional genomics studies. [BMB Reports 2026; 59(2): 137-142].

BMB ReportsVol. 59(2)
Seoul National University (KR), Kangwon National University (KR)
National Research Foundation, National Research Foundation of Korea, Ministry of Science and ICT, South Korea
Openalex Percentile: Top 100%
Genomics and Phylogenetic Studies
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CodonMutator: a python-based automated oligonucleotide design framework for deep mutational scanning library construction — S.K. Park, Byung Joon Hwang, et al. · BMB Reports (2026) | TGRS Research Map | TGRS