典型文献
cgRNASP-CN:a minimal coarse-grained representation-based statistical potential for RNA 3D structure evaluation
文献摘要：
Knowledge of RNA 3-dimensional(3D)structures is critical to understand the important biological functions of RNAs,and various models have been developed to predict RNA 3D structures in silico.However,there is still lack of a reliable and efficient statistical potential for RNA 3D structure evaluation.For this purpose,we developed a statistical potential based on a minimal coarse-grained representation and residue separation,where every nucleotide is represented by C4'atom for backbone and N1(or N9)atom for base.In analogy to the newly developed all-atom rsRNASP,cgRNASP-CN is composed of short-ranged and long-ranged potentials,and the short-ranged one was involved more subtly.The examination indicates that the performance of cgRNASP-CN is close to that of the all-atom rsRNASP and is superior to other top all-atom traditional statistical potentials and scoring functions trained from neural networks,for two realistic test datasets including the RNA-Puzzles dataset.Very importantly,cgRNASP-CN is about 100 times more efficient than existing all-atom statistical potentials/scoring functions including rsRNASP.cgRNASP-CN is available at website:.
文献关键词：
中图分类号：
作者姓名：
Ling Song;Shixiong Yu;Xunxun Wang;Ya-Lan Tan;Zhi-Jie Tan
作者机构：
Department of Physics and Key Laboratory of Artificial Micro&Nano-structures of Education,School of Physics and Technology,Wuhan University,Wuhan 430072,China;Research Center of Nonlinear Science,School of Mathematical and Physical Sciences,Wuhan Textile University,Wuhan 430073,China
文献出处：
引用格式：
[1]Ling Song;Shixiong Yu;Xunxun Wang;Ya-Lan Tan;Zhi-Jie Tan-.cgRNASP-CN:a minimal coarse-grained representation-based statistical potential for RNA 3D structure evaluation)[J].理论物理,2022(07):129-137
A类：
cgRNASP,rsRNASP
B类：
CN,minimal,coarse,grained,representation,statistical,evaluation,Knowledge,dimensional,structures,critical,understand,biological,functions,RNAs,various,models,have,been,developed,predict,silico,However,there,still,lack,reliable,efficient,For,this,purpose,residue,separation,where,every,nucleotide,represented,by,C4,atom,backbone,N1,N9,In,analogy,newly,all,composed,short,ranged,long,potentials,was,involved,more,subtly,examination,indicates,that,performance,close,superior,other,top,traditional,scoring,trained,from,neural,networks,realistic,test,datasets,including,Puzzles,Very,importantly,about,times,than,existing,available,website
AB值：
0.479115
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