Insights in Protein Bioinformatics

Proteins carry out most of the work in the cell, and predicting their structure, function and interactions remains one of the great challenges in biology. The Protein Bioinformatics section sits where structural biology, machine learning, biophysics and sequence analysis meet, decoding how sequence gives rise to structure and function. This collection celebrates that progress: it brings together leading voices to highlight state-of-the-art developments and to set the agenda for the questions that will define the field next.
This Research Topic aims to provide an overview of the most recent advances in protein bioinformatics. It seeks to show how structure prediction, design and function annotation can move from sequence to mechanism and from prediction to application. Without losing sight of past achievements, the goal is to explore the potential of future work, addressing the accuracy, interpretability and data challenges that remain at the forefront of this multidisciplinary area.
The scope is broadly defined yet focused on areas where significant innovative strides have been made. We welcome contributions that emphasize:
• Protein structure prediction and model quality assessment
• Protein design and engineering with generative models
• Function prediction and annotation from sequence and structure
• Protein-protein and protein-ligand interaction modeling
• Intrinsically disordered regions and conformational dynamics
• Language models and deep learning for protein sequences
• Open, reproducible tools and benchmarks for protein analysis

This collection welcomes contributions reflecting on current developments and plotting pathways for upcoming research, from Editorial Board Members of the section, from authors they refer, and, on invitation, from a small number of external researchers whose work is shaping the direction of the field. Authors are encouraged to engage critically with their fields, identify the current challenges and propose novel solutions that advance bioinformatics tools and their application to real biological problems.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Systematic Review
• Technology and Code

Keywords: protein bioinformatics, structure prediction, protein design, function annotation, protein interactions, deep learning, protein language models, structural biology, disordered proteins, molecular modeling

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.