Computational and Structural Biotechnology Journal

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Computational and Structural Biotechnology Journal

Computational and Structural Biotechnology Journal (ISSN 2001-0370) is an online journal publishing research articles and reviews after full peer review.

Computational and Structural Biotechnology Journal (CSBJ) is an open access journal (Impact Factor 4.5) and is composed of four specialty sections:
• General • Smart Hospital • Nanoscience and Advanced Materials • Quantum Biology and Biophotonics. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic

understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to:

• Structure and function of proteins, nucleic acids and other macromolecules
• Structure and function of multi-component complexes
• Protein folding, processing and degradation
• Enzymology
• Computational and structural studies of plant systems
• Microbial Informatics
• Genomics
• Proteomics
• Metabolomics
• Algorithms and Hypothesis in Bioinformatics
• Computational Chemistry & Drug Discovery
• Microscopy and Molecular Imaging
• Nanotechnology

While all general topics related to Computational and Structural Biology are welcomed, the editors reserve the right to pre-screen submissions based on the suitability of the topic of a submission and, therefore, the right as whether a manuscript will be processed/reviewed or not. Even though experimental validation is not required for publication, reliability and significance of biological discovery are validated and enriched by experimental studies. The journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence, and enables the rapid publication of papers under the following categories:

• Research articles
• Review articles
• Mini Reviews
• Highlights
• Communications
• Software/Web server articles
• Methods articles
• Database articles
• Book Reviews
• Meeting Reviews

06/07/2025

🔬 Can AI help decode how antibodies recognize cancer-related proteins like HER2?

This study presents an in silico docking-based strategy to investigate where novel monoclonal antibodies bind to HER2, a key receptor in many aggressive cancers. Using LightDock and AlphaFold, the researchers explored potential binding interfaces—offering crucial insights for diagnostic and therapeutic innovation in oncology.

📝 Emil Stefańczyk, Agata Mitura, Marta Utratna, Magdalena Staniszewska.

🔗 Investigating and evaluating potential antigen binding sites for monoclonal anti-HER2 antibodies: The LightDock approach. Computational and Structural Biotechnology Journal, DOI: https://doi.org/10.1016/j.csbj.2025.06.001

📚 CSBJ: https://www.csbj.org/

06/07/2025

🤖 How can artificial intelligence help us outsmart rapidly evolving viruses like H5N1?

This study introduces Frankies – an AI-driven pipeline that automates the discovery of antibodies targeting recent H5N1 avian influenza strains. Amid rising zoonotic threats, this breakthrough offers a fast, scalable method to generate therapeutic antibody candidates—marking a major leap in pandemic preparedness.

📝 Nicholas Santolla, Colby T. Ford.

🔗 AI-based antibody design targeting recent H5N1 avian influenza strains. Computational and Structural Biotechnology Journal, DOI: https://doi.org/10.1016/j.csbj.2025.06.026

📚 CSBJ: https://www.csbj.org/

03/07/2025

🧬 Are we ready to let algorithms decide which human samples are worth saving for science?

This study introduces an AI-driven two-step workflow for automated annotation of residual samples from hospitalized patients with diabetes mellitus—a game-changer for healthcare-integrated biobanking. By leveraging machine learning (ML) and natural language processing (NLP), the system improves accuracy, efficiency, and scalability of biosample curation.

📝 Johannes Stolp, Christoph Weber, Danny Ammon, André Scherag, Claudia Fischer, Christof Kloos, Gunter Wolf, P. Christian Schulze, Utz Settmacher, Michael Bauer, Andreas Stallmach, Michael Kiehntopf, Boris Betz.

🔗 Automated sample annotation for diabetes mellitus in healthcare integrated biobanking. Computational and Structural Biotechnology Journal, DOI: https://doi.org/10.1016/j.csbj.2024.10.033

📚 CSBJ Smart Hospital: https://www.csbj.org/smarthospital

01/07/2025

Combining long-read DNA and RNA sequencing to enhance molecular understanding of structural variations leading to copy gains.
Read the article here: https://doi.org/10.1016/j.csbj.2025.04.031

01/07/2025

Transfer learning towards predicting viral missense mutations: A case study on SARS-CoV-2.
Read the article here: https://doi.org/10.1016/j.csbj.2025.04.029

30/06/2025

🧬 Could the way a virus “writes” its genes reveal how—and when—it jumps hosts?

This study introduces a codon usage-based approach for stratifying Influenza A viruses (IAVs), offering a scalable, data-driven method for genomic surveillance—especially during viral spillovers. By analyzing codon preferences in the HA segment, the study reveals evolutionary patterns that clade-based naming systems often miss.

📝 Tommaso Alfonsi, Matteo Chiara, Anna Bernasconi.

🔗 A codon usage-based approach for the stratification of Influenza A across recent spillovers. Computational and Structural Biotechnology Journal, DOI: https://doi.org/10.1016/j.csbj.2025.06.030

📚 CSBJ: https://www.csbj.org/

30/06/2025

Flavivirus NS4B proteins do not form homodimers: discrepancies with an AlphaFold-based oligomeric model.
Read the article here: https://doi.org/10.1016/j.csbj.2025.04.026

30/06/2025

MitoEdit: A pipeline for optimizing mtDNA base editing and predicting bystander effects.
Read the article here: https://doi.org/10.1016/j.csbj.2025.04.027

30/06/2025

Identification and functional analysis of growth rate associated long non-coding RNAs in Komagataella phaffii.
Read the article here: https://doi.org/10.1016/j.csbj.2025.04.028

30/06/2025

Mathematical proof of the Fisher-Escolà Q statistical distribution in quantum consciousness modeling.
Read the article here: https://doi.org/10.1016/j.csbj.2025.04.025

30/06/2025

Prediction and validation of nanowire proteins in Oleidesulfovibrio alaskensis G20 using machine learning and feature engineering.
Read the article here: https://doi.org/10.1016/j.csbj.2025.04.022

29/06/2025

Graph-based process models as basis for efficient data-driven surrogates – expediting the material development process.
Read the article here: https://doi.org/10.1016/j.csbj.2025.04.018

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