BARNACLE

BARNACLE implements a probabilistic model, as a Python library, to predict RNA three-dimensional (3D) structures from coarse-grained base-pairing information.

Key Features:

• Probabilistic Sampling: Employs a continuous-space probabilistic model for unbiased sampling of RNA conformations instead of relying on discrete fragment assembly.
• Efficient Conformational Sampling: Samples plausible RNA conformations using coarse-grained base-pairing information while capturing rotameric nature and helix length distributions.
• Native-like Structure Generation: Generates native-like 3D structures for 9 out of 10 test cases using only coarse-grained data without finely-tuned or unphysical energy functions.
• Theoretical and Practical Advancements: Addresses the conformational sampling bottleneck and enables routine atomic-level RNA structure prediction and simulation while providing theoretical insights.

Scientific Applications:

• RNA Structure Prediction: Predicts 3D RNA structures to inform understanding of biological function and molecular interactions.
• Research in Non-Coding RNAs: Supports exploration of structural dynamics and potential therapeutic applications of non-coding RNAs.

Methodology:

Continuous-space probabilistic model with conformational sampling from coarse-grained base-pairing information that captures rotameric states and helix length distributions while avoiding discrete fragment assembly and finely-tuned or unphysical energy functions.