# Proteins with alternative folds reveal blind spots in AlphaFold-based protein structure prediction

> In recent years, advances in artificial intelligence (AI) have transformed structural biology, particularly protein structure prediction. Though AI-based methods, such as AlphaFold (AF), often predict single conformations of proteins with high accuracy and confidence, predictions of alternative fold...

## Metadata
- Authors: Devlina Chakravarty, Myeongsang Lee, Lauren L. Porter
- Journal: Current Opinion in Structural Biology
- Published: 2025-01-05
- DOI: https://doi.org/10.1016/j.sbi.2024.102973
- Citations: 60
- Source: OpenAlex
- Access: Open Access

## Technology Hub
- Hub: Protein Structure Prediction
- Discipline: Biochemistry / AI
- Hub URL: https://science-database.com/technology/protein-structure
- Hub llms.txt: https://science-database.com/technology/protein-structure/llms.txt

## Abstract
In recent years, advances in artificial intelligence (AI) have transformed structural biology, particularly protein structure prediction. Though AI-based methods, such as AlphaFold (AF), often predict single conformations of proteins with high accuracy and confidence, predictions of alternative folds are often inaccurate, low-confidence, or simply not predicted at all. Here, we review three blind spots that alternative conformations reveal about AF-based protein structure prediction. First, proteins that assume conformations distinct from their training-set homologs can be mispredicted. Second, AF overrelies on its training set to predict alternative conformations. Third, degeneracies in pairwise representations can lead to high-confidence predictions inconsistent with experiment. These weaknesses suggest approaches to predict alternative folds more reliably.

## Links
- DOI: https://doi.org/10.1016/j.sbi.2024.102973
- OpenAlex: https://openalex.org/W4406063185
- PDF: https://doi.org/10.1016/j.sbi.2024.102973
- JSON API: https://science-database.com/api/v1/technology/protein-structure

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Paper ID: oa-W4406063185 | Hub: protein-structure