AutoRNC: An automated modeling program for building atomic models of ribosome-nascent chain complexes

Area of Science:

• Computational biology
• Structural biology
• Biochemistry

Background:

• Co-translational protein folding is crucial for cellular function.
• Interactions between the nascent chain and the ribosome influence folding pathways.
• Existing methods for modeling ribosome-nascent chain (RNC) constructs require significant expertise.

Purpose of the Study:

• To develop an automated computational method for generating 3D models of RNC constructs.
• To simplify and accelerate the process of RNC modeling for researchers.
• To provide a tool for exploring co-translational protein folding dynamics.

Main Methods:

• Developed AutoRNC, an automated modeling program.
• Input user-specified structural regions of the nascent chain.
• Sampled dipeptide conformations from the Protein Data Bank (RCSB).
• Built atomic models of RNCs considering ribosomal constraints.

Main Results:

• AutoRNC can construct numerous plausible atomic models of RNCs rapidly.
• The program successfully generated models for various RNC constructs.
• Plausible conformations were generated using modest computational resources.
• Models are compatible with experimental data for reported RNC constructs.

Conclusions:

• AutoRNC effectively automates the generation of RNC models.
• The tool facilitates the study of co-translational protein folding.
• AutoRNC provides a valuable resource for structural and computational biology research.