返回
Modeling nucleic acids
DOI:10.1016/j.sbi.2012.03.012.png)
摘要
En 中文
Nucleic acids are an important class of biological macromolecules that carry out a variety of cellular roles. For many functions, naturally occurring DNA and RNA molecules need to fold into precise three-dimensional structures. Due to their self-assembling characteristics, nucleic acids have also been widely studied in the field of nanotechnology, and a diverse range of intricate three-dimensional nanostructures have been designed and synthesized. Different physical terms such as base-pairing and stacking interactions, tertiary contacts, electrostatic interactions and entropy all affect nucleic acid folding and structure. Here we review general computational approaches developed to model nucleic acid systems. We focus on four key areas of nucleic acid modeling: molecular representation, potential energy function, degrees of freedom and sampling algorithm. Appropriate choices in each of these key areas in nucleic acid modeling can effectively combine to aid interpretation of experimental data and facilitate prediction of nucleic acid structure.
Keyword:
DISCRETE MOLECULAR-DYNAMICS
KNOWLEDGE-BASED POTENTIALS
RNA TERTIARY STRUCTURES
DE-NOVO PREDICTION
FORCE-FIELD
DNA
MECHANICS
NANOTECHNOLOGY
SIMULATIONS
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7
论文数:
3.8K
被引数:
1.4W
机构
引用论文
Coarse-grained modeling of large RNA molecules with knowledge-based potentials and structural filters
RNA
IF5
Fully differentiable coarse-grained and all-atom knowledge-based potentials for RNA structure evaluation
RNA
IF5
Distribution Features of Skeletal Metastases: A Comparative Study between Pulmonary and Prostate Cancers
PLOS ONE
IF0

