Prediction of RNA pseudoknots by Monte Carlo simulations
G. Vernizzi, H. Orland, A. Zee
Abstract
In this paper we consider the problem of RNA folding with pseudoknots. We use a graphical representation in which the secondary structures are described by planar diagrams. Pseudoknots are identified as non-planar diagrams. We analyze the non-planar topologies of RNA structures and propose a classification of RNA pseudoknots according to the minimal genus of the surface on which the RNA structure can be embedded. This classification provides a simple and natural way to tackle the problem of RNA folding prediction in presence of pseudoknots. Based on that approach, we describe a Monte Carlo algorithm for the prediction of pseudoknots in an RNA molecule.
Create a lesson
Related papers
Discrete Backbone Elasticity and Curvature-Dependent Torsion Statistics in Proteins
Yiquan Wang, Mingyu Bian, Jiayuan Ma
Ablating Design Choices for Protein Ensemble Generators Across Structural Regimes
Eoin Quinn, Oliver Bent
Predicting protein structures at any folding stage from sequence
Lisheng Zhang, Qingsong Li, Zinan Xie et al.
Automatic Generation of Novel Highly-Functional Molecular Sequences
Vincent R. Ragusa, Chrisoph Adami
D2ML: Models for Direct-to-Biology Small Molecule Screening
AkshatKumar Nigam, Neri Amara, Hillary Dequina et al.
Contribution of chromosome-naïve transposon-seeded network of DNA templates to intracellular pools of protein dimers of liquid-liquid phase-separated condensate-forming proteins
Gennadi Glinsky