ReviewBiophysical reviews2017
Searching for the Pareto frontier in multi-objective protein design.
Review in Biophysical reviews, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
5 citing papers in PubMed.
- Beyond affinity: AI-supported developability assessment and multi-objective optimization in antibody development.Antibody therapeutics · 2026Review
- Soluble protein analog selection engine (SPASE): An automated AI-powered server to improve protein engineering workflows.Protein science : a publication of the Protein Society · 2026Article
- Optimising DNA origami assembly by reducing off-target interactions.Nature communications · 2026Article
- How electrostatic networks modulate specificity and stability of collagen.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- ProLego: tool for extracting and visualizing topological modules in protein structures.BMC bioinformatics · 2018Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The goal of protein engineering and design is to identify sequences that adopt three-dimensional structures of desired function. Often, this is treated as a single-objective optimization problem, identifying the sequence-structure solution with the lowest computed free energy of folding. However, many design problems are multi-state, multi-specificity, or otherwise require concurrent optimization of multiple objectives. There may be tradeoffs among objectives, where improving one feature requires compromising another. The challenge lies in determining solutions that are part of the Pareto optimal set-designs where no further improvement can be achieved in any of the objectives without degrading one of the others. Pareto optimality problems are found in all areas of study, from economics to engineering to biology, and computational methods have been developed specifically to identify the Pareto frontier. We review progress in multi-objective protein design, the development of Pareto optimization methods, and present a specific case study using multi-objective optimization methods to model the tradeoff between three parameters, stability, specificity, and complexity, of a set of interacting synthetic collagen peptides.
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Registered trials
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