StemP: A fast and deterministic Stem-graph approach for RNA and protein folding prediction

by   Mengyi Tang, et al.

We propose a new deterministic methodology to predict RNA sequence and protein folding. Is stem enough for structure prediction? The main idea is to consider all possible stem formation in the given sequence. With the stem loop energy and the strength of stem, we explore how to deterministically utilize stem information for RNA sequence and protein folding structure prediction. We use graph notation, where all possible stems are represented as vertices, and co-existence as edges. This full Stem-graph presents all possible folding structure, and we pick sub-graph(s) which give the best matching energy for folding structure prediction. We introduce a Stem-Loop score to add structure information and to speed up the computation. The proposed method can handle secondary structure prediction as well as protein folding with pseudo knots. Numerical experiments are done using a laptop and results take only a few minutes or seconds. One of the strengths of this approach is in the simplicity and flexibility of the algorithm, and it gives deterministic answer. We explore protein sequences from Protein Data Bank, rRNA 5S sequences, and tRNA sequences from the Gutell Lab. Various experiments and comparisons are included to validate the propose method.



There are no comments yet.


page 11

page 13

page 16

page 17

page 20


MCP: a Multi-Component learning machine to Predict protein secondary structure

The Gene or DNA sequence in every cell does not control genetic properti...

MAS2HP: A Multi Agent System to predict protein structure in 2D HP model

Protein Structure Prediction (PSP) is an unsolved problem in the field o...

MCP: a multi-component learning machine for prediction of protein secondary structure

Proteins biological function is tightly connected to its specific 3D str...

MUFold-SS: Protein Secondary Structure Prediction Using Deep Inception-Inside-Inception Networks

Motivation: Protein secondary structure prediction can provide important...

FoldingZero: Protein Folding from Scratch in Hydrophobic-Polar Model

De novo protein structure prediction from amino acid sequence is one of ...

Monte Carlo sampling of flexible protein structures: an application to the SARS-CoV-2 omicron variant

Proteins can exhibit dynamic structural flexibility as they carry out th...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.