Design and Prediction of Aptamers Assisted by In Silico Methods
An aptamer is a single-stranded DNA or RNA that binds to a specific target with high binding affinity. Aptamers are developed through the process of systematic evolution of ligands by exponential enrichment (SELEX), which is repeated to increase the binding power and specificity. However, the SELEX...
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| Format: | Article |
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MDPI AG
2023-01-01
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| Series: | Biomedicines |
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| Online Access: | https://www.mdpi.com/2227-9059/11/2/356 |
| _version_ | 1797622183324811264 |
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| author | Su Jin Lee Junmin Cho Byung-Hoon Lee Donghwan Hwang Jee-Woong Park |
| author_facet | Su Jin Lee Junmin Cho Byung-Hoon Lee Donghwan Hwang Jee-Woong Park |
| author_sort | Su Jin Lee |
| collection | DOAJ |
| description | An aptamer is a single-stranded DNA or RNA that binds to a specific target with high binding affinity. Aptamers are developed through the process of systematic evolution of ligands by exponential enrichment (SELEX), which is repeated to increase the binding power and specificity. However, the SELEX process is time-consuming, and the characterization of aptamer candidates selected through it requires additional effort. Here, we describe in silico methods in order to suggest the most efficient way to develop aptamers and minimize the laborious effort required to screen and optimise aptamers. We investigated several methods for the estimation of aptamer-target molecule binding through conformational structure prediction, molecular docking, and molecular dynamic simulation. In addition, examples of machine learning and deep learning technologies used to predict the binding of targets and ligands in the development of new drugs are introduced. This review will be helpful in the development and application of in silico aptamer screening and characterization. |
| first_indexed | 2024-03-11T09:06:42Z |
| format | Article |
| id | doaj.art-2639bdce5b3a4520b543dcac9039d232 |
| institution | Directory Open Access Journal |
| issn | 2227-9059 |
| language | English |
| last_indexed | 2024-03-11T09:06:42Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biomedicines |
| spelling | doaj.art-2639bdce5b3a4520b543dcac9039d2322023-11-16T19:17:00ZengMDPI AGBiomedicines2227-90592023-01-0111235610.3390/biomedicines11020356Design and Prediction of Aptamers Assisted by In Silico MethodsSu Jin Lee0Junmin Cho1Byung-Hoon Lee2Donghwan Hwang3Jee-Woong Park4Drug Manufacturing Center, Daegu-Gyeongbuk Medical Innovation Foundation (K-MEDI Hub), Daegu 41061, Republic of KoreaMedical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation (K-MEDI Hub), Daegu 41061, Republic of KoreaMedical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation (K-MEDI Hub), Daegu 41061, Republic of KoreaMedical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation (K-MEDI Hub), Daegu 41061, Republic of KoreaMedical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation (K-MEDI Hub), Daegu 41061, Republic of KoreaAn aptamer is a single-stranded DNA or RNA that binds to a specific target with high binding affinity. Aptamers are developed through the process of systematic evolution of ligands by exponential enrichment (SELEX), which is repeated to increase the binding power and specificity. However, the SELEX process is time-consuming, and the characterization of aptamer candidates selected through it requires additional effort. Here, we describe in silico methods in order to suggest the most efficient way to develop aptamers and minimize the laborious effort required to screen and optimise aptamers. We investigated several methods for the estimation of aptamer-target molecule binding through conformational structure prediction, molecular docking, and molecular dynamic simulation. In addition, examples of machine learning and deep learning technologies used to predict the binding of targets and ligands in the development of new drugs are introduced. This review will be helpful in the development and application of in silico aptamer screening and characterization.https://www.mdpi.com/2227-9059/11/2/356in silicoaptamerSELEX |
| spellingShingle | Su Jin Lee Junmin Cho Byung-Hoon Lee Donghwan Hwang Jee-Woong Park Design and Prediction of Aptamers Assisted by In Silico Methods Biomedicines in silico aptamer SELEX |
| title | Design and Prediction of Aptamers Assisted by In Silico Methods |
| title_full | Design and Prediction of Aptamers Assisted by In Silico Methods |
| title_fullStr | Design and Prediction of Aptamers Assisted by In Silico Methods |
| title_full_unstemmed | Design and Prediction of Aptamers Assisted by In Silico Methods |
| title_short | Design and Prediction of Aptamers Assisted by In Silico Methods |
| title_sort | design and prediction of aptamers assisted by in silico methods |
| topic | in silico aptamer SELEX |
| url | https://www.mdpi.com/2227-9059/11/2/356 |
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