Computational tools for aptamer identification and optimization
Aptamers are single-stranded DNA or RNA oligonucleotides that can selectively bind to a specific target. They are generally obtained by SELEX, but the procedure is challenging and time-consuming. Moreover, the identified aptamers tend to be insufficient in stability, specificity, and affinity. Thus,...
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| Published in | TrAC, Trends in analytical chemistry (Regular ed.) Vol. 157; p. 116767 |
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| Main Authors | , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
01.12.2022
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| Online Access | Get full text |
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| Abstract | Aptamers are single-stranded DNA or RNA oligonucleotides that can selectively bind to a specific target. They are generally obtained by SELEX, but the procedure is challenging and time-consuming. Moreover, the identified aptamers tend to be insufficient in stability, specificity, and affinity. Thus, only a handful of aptamers have entered the practical use stage. Recently, computational approaches have demonstrated a significant capacity to assist in the discovery of high-performance aptamers. This review discusses the advances achieved in several aspects of computational tools in this field, as well as the new progress in machine learning and deep learning, which are used in aptamer identification and optimization. To illustrate these computationally aided processes, aptamer selections against SARS-CoV-2 are discussed in detail as a case study. We hope that this review will aid and motivate researchers to develop and utilize more computational techniques to discover ideal aptamers effectively.
•A comprehensive summary was provided on computational approaches for obtaining high-performance aptamers.•The supervised machine learning-based algorithms for identification and optimization of aptamers are well detailed.•The practical studies of structure modeling and binding surface inference for aptamers against SARS-CoV-2 were presented. |
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| AbstractList | Aptamers are single-stranded DNA or RNA oligonucleotides that can selectively bind to a specific target. They are generally obtained by SELEX, but the procedure is challenging and time-consuming. Moreover, the identified aptamers tend to be insufficient in stability, specificity, and affinity. Thus, only a handful of aptamers have entered the practical use stage. Recently, computational approaches have demonstrated a significant capacity to assist in the discovery of high-performance aptamers. This review discusses the advances achieved in several aspects of computational tools in this field, as well as the new progress in machine learning and deep learning, which are used in aptamer identification and optimization. To illustrate these computationally aided processes, aptamer selections against SARS-CoV-2 are discussed in detail as a case study. We hope that this review will aid and motivate researchers to develop and utilize more computational techniques to discover ideal aptamers effectively. Aptamers are single-stranded DNA or RNA oligonucleotides that can selectively bind to a specific target. They are generally obtained by SELEX, but the procedure is challenging and time-consuming. Moreover, the identified aptamers tend to be insufficient in stability, specificity, and affinity. Thus, only a handful of aptamers have entered the practical use stage. Recently, computational approaches have demonstrated a significant capacity to assist in the discovery of high-performance aptamers. This review discusses the advances achieved in several aspects of computational tools in this field, as well as the new progress in machine learning and deep learning, which are used in aptamer identification and optimization. To illustrate these computationally aided processes, aptamer selections against SARS-CoV-2 are discussed in detail as a case study. We hope that this review will aid and motivate researchers to develop and utilize more computational techniques to discover ideal aptamers effectively. •A comprehensive summary was provided on computational approaches for obtaining high-performance aptamers.•The supervised machine learning-based algorithms for identification and optimization of aptamers are well detailed.•The practical studies of structure modeling and binding surface inference for aptamers against SARS-CoV-2 were presented. |
| ArticleNumber | 116767 |
| Author | Lin, Xin Lin, Fanghe Zhang, Peng Zhang, Yinkun Song, Jia Sun, Miao Zhang, Jialu Sun, Di Yang, Chaoyong |
| Author_xml | – sequence: 1 givenname: Di surname: Sun fullname: Sun, Di organization: Institute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China – sequence: 2 givenname: Miao surname: Sun fullname: Sun, Miao organization: State Key Laboratory for Physical Chemistry of Solid Surfaces, Key Laboratory for Chemical Biology of Fujian Province, Key Laboratory of Analytical Chemistry, And Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, People's Republic of China – sequence: 3 givenname: Jialu surname: Zhang fullname: Zhang, Jialu organization: State Key Laboratory for Physical Chemistry of Solid Surfaces, Key Laboratory for Chemical Biology of Fujian Province, Key Laboratory of Analytical Chemistry, And Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, People's Republic of China – sequence: 4 givenname: Xin surname: Lin fullname: Lin, Xin organization: Institute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China – sequence: 5 givenname: Yinkun surname: Zhang fullname: Zhang, Yinkun organization: State Key Laboratory for Physical Chemistry of Solid Surfaces, Key Laboratory for Chemical Biology of Fujian Province, Key Laboratory of Analytical Chemistry, And Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, People's Republic of China – sequence: 6 givenname: Fanghe surname: Lin fullname: Lin, Fanghe organization: State Key Laboratory for Physical Chemistry of Solid Surfaces, Key Laboratory for Chemical Biology of Fujian Province, Key Laboratory of Analytical Chemistry, And Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, 361005, People's Republic of China – sequence: 7 givenname: Peng surname: Zhang fullname: Zhang, Peng organization: Institute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China – sequence: 8 givenname: Chaoyong surname: Yang fullname: Yang, Chaoyong organization: Institute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China – sequence: 9 givenname: Jia surname: Song fullname: Song, Jia email: songjiajia2010@shsmu.edu.cn organization: Institute of Molecular Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China |
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| Keywords | AI DL SVM Aptamer optimization MFE Deep learning COVID-19 HT-SELEX NLP RF Aptamer identification Machine learning MD Bioinformatics MDS SELEX ML |
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| Snippet | Aptamers are single-stranded DNA or RNA oligonucleotides that can selectively bind to a specific target. They are generally obtained by SELEX, but the... |
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| SubjectTerms | analytical chemistry Aptamer identification Aptamer optimization Bioinformatics case studies COVID-19 Deep learning Machine learning oligonucleotides RNA Severe acute respiratory syndrome coronavirus 2 single-stranded DNA systematic evolution of ligands by exponential enrichment |
| Title | Computational tools for aptamer identification and optimization |
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