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3dDNAscoreA: A scoring function for evaluation of DNA 3D structures.
Zhang, Yi; Yang, Chenxi; Xiong, Yiduo; Xiao, Yi.
Afiliação
  • Zhang Y; Institute of Biophysics, School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei, China.
  • Yang C; Institute of Biophysics, School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei, China.
  • Xiong Y; Institute of Biophysics, School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei, China.
  • Xiao Y; Institute of Biophysics, School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei, China. Electronic address: yxiao@mail.hust.edu.cn.
Biophys J ; 2024 Feb 26.
Article em En | MEDLINE | ID: mdl-38409781
ABSTRACT
DNA molecules are vital macromolecules that play a fundamental role in many cellular processes and have broad applications in medicine. For example, DNA aptamers have been rapidly developed for diagnosis, biosensors, and clinical therapy. Recently, we proposed a computational method of predicting DNA 3D structures, called 3dDNA. However, it lacks a scoring function to evaluate the predicted DNA 3D structures, and so they are not ranked for users. Here, we report a scoring function, 3dDNAscoreA, for evaluation of DNA 3D structures based on a deep learning model ARES for RNA 3D structure evaluation but using a new strategy for training. 3dDNAscoreA is benchmarked on two test sets to show its ability to rank DNA 3D structures and select the native and near-native structures.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article