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Martin DR, Mutombwera AT, Madiehe AM, Onani MO, Meyer M, Cloete R. Molecular modeling and simulation studies of SELEX-derived high-affinity DNA aptamers to the Ebola virus nucleoprotein. J Biomol Struct Dyn 2024:1-18. [PMID: 38217874 DOI: 10.1080/07391102.2024.2302922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 01/03/2024] [Indexed: 01/15/2024]
Abstract
Ebola viral disease (EVD) is a highly infectious and potentially fatal illness with a case fatality rate ranging from 25% to 90%. To effectively control its spread, there is a need for rapid, reliable and lowcost point-of-care (P OC) diagnostic tests. While various EVD diagnostic tests exist, few are P OC tests, and many are not cost-effective. The use of antibodies in these tests has limitations, prompting the exploration of aptamers as potential alternatives. Various proteins from the Ebola virus (EBOV) proteome, including EBOV nucleoprotein (NP), are considered viable targets for diagnostic assays. A previous study identified three aptamers (Apt1. Apt2 and Apt3) with high affinity for EBOV NP using systemic evolution of ligands by exponential enrichment (SELEX). This study aimed to employ in silico methods, such as Phyre2, RNAfold, RNAComposer, HADDOCK and GROMACS, to model the structures of EBOV NP and the aptamers, and to investigate their binding. The in silico analysis revealed successful binding of all the three aptamers to EBOV NP, with a suggested ranking of Apt1 > Apt2 > Apt3 based on binding affinity. Microscale thermophoresis (MST) analysis confirmed the binding, providing dissociation constants of 25 ± 2.84, 56 ± 2.76 and 140 ±3.69 nM for Apt1, Apt2 and Apt3, respectively. The study shows that the findings of the in silico analysis was in agreement with the MST analysis. Inclusion of these in silico approaches in diagnostic assay development can expedite the selection of candidate aptamers, potentially overcoming challenges associated with aptamer application in diagnostics.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- D R Martin
- Department of Science and Innovation/Mintek Nanotechnology Innovation Centre, Biolabels Node, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute (SANBI), University of the Western Cape, Bellville, South Africa Cape Town, South Africa
| | - A T Mutombwera
- Department of Biochemistry and Microbiology, Nelson Mandela University, Port Elizabeth, South Africa
| | - A M Madiehe
- Department of Science and Innovation/Mintek Nanotechnology Innovation Centre, Biolabels Node, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
- Nanobiotechnology Research Group, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
| | - M O Onani
- Department of Chemistry, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
| | - M Meyer
- Department of Science and Innovation/Mintek Nanotechnology Innovation Centre, Biolabels Node, Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, South Africa
| | - R Cloete
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute (SANBI), University of the Western Cape, Bellville, South Africa Cape Town, South Africa
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Yu H, Zhu J, Shen G, Deng Y, Geng X, Wang L. Improving aptamer performance: key factors and strategies. Mikrochim Acta 2023; 190:255. [PMID: 37300603 DOI: 10.1007/s00604-023-05836-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 05/16/2023] [Indexed: 06/12/2023]
Abstract
Aptamers are functional single-stranded oligonucleotide fragments isolated from randomized libraries by Systematic Evolution of Ligands by Exponential Enrichment (SELEX), exhibiting excellent affinity and specificity toward targets. Compared with traditional antibody reagents, aptamers display many desirable properties, such as low variation and high flexibility, and they are suitable for artificial and large-scale synthesis. These advantages make aptamers have a broad application potential ranging from biosensors, bioimaging to therapeutics and other areas of application. However, the overall performance of aptamer pre-selected by SELEX screening is far from being satisfactory. To improve aptamer performance and applicability, various post-SELEX optimization methods have been developed in the last decade. In this review, we first discuss the key factors that influence the performance or properties of aptamers, and then we summarize the key strategies of post-SELEX optimization which have been successfully used to improve aptamer performance, such as truncation, extension, mutagenesis and modification, splitting, and multivalent integration. This review shall provide a comprehensive summary and discussion of post-SELEX optimization methods developed in recent years. Moreover, by discussing the mechanism of each approach, we highlight the importance of choosing the proper method to perform post-SELEX optimization.
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Affiliation(s)
- Hong Yu
- School of Agriculture and Biology, Key Laboratory of Urban Agriculture, Ministry of Agriculture, Bor S. Luh Food Safety Research Center, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China
- Shanghai Jiao Tong University YunNan (Dali) Research Institute, Dali, 671000, Yunnan, China
- Shanghai Yangtze River Delta Eco-Environmental Change and Management Observation and Research Station, Ministry of Science and Technology, Ministry of Education, 800 Dongchuan Rd, Shanghai, 200240, China
- Shanghai Urban Forest Ecosystem Research Station, National Forestry and Grassland Administration, 800 Dongchuan Rd, Shanghai, 200240, China
| | - Jiangxiong Zhu
- School of Agriculture and Biology, Key Laboratory of Urban Agriculture, Ministry of Agriculture, Bor S. Luh Food Safety Research Center, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China
- Shanghai Jiao Tong University YunNan (Dali) Research Institute, Dali, 671000, Yunnan, China
- Shanghai Yangtze River Delta Eco-Environmental Change and Management Observation and Research Station, Ministry of Science and Technology, Ministry of Education, 800 Dongchuan Rd, Shanghai, 200240, China
- Shanghai Urban Forest Ecosystem Research Station, National Forestry and Grassland Administration, 800 Dongchuan Rd, Shanghai, 200240, China
| | - Guoqing Shen
- School of Agriculture and Biology, Key Laboratory of Urban Agriculture, Ministry of Agriculture, Bor S. Luh Food Safety Research Center, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China
- Shanghai Jiao Tong University YunNan (Dali) Research Institute, Dali, 671000, Yunnan, China
- Shanghai Yangtze River Delta Eco-Environmental Change and Management Observation and Research Station, Ministry of Science and Technology, Ministry of Education, 800 Dongchuan Rd, Shanghai, 200240, China
- Shanghai Urban Forest Ecosystem Research Station, National Forestry and Grassland Administration, 800 Dongchuan Rd, Shanghai, 200240, China
| | - Yun Deng
- School of Agriculture and Biology, Key Laboratory of Urban Agriculture, Ministry of Agriculture, Bor S. Luh Food Safety Research Center, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China
- Shanghai Jiao Tong University YunNan (Dali) Research Institute, Dali, 671000, Yunnan, China
- Shanghai Yangtze River Delta Eco-Environmental Change and Management Observation and Research Station, Ministry of Science and Technology, Ministry of Education, 800 Dongchuan Rd, Shanghai, 200240, China
- Shanghai Urban Forest Ecosystem Research Station, National Forestry and Grassland Administration, 800 Dongchuan Rd, Shanghai, 200240, China
| | - Xueqing Geng
- School of Agriculture and Biology, Key Laboratory of Urban Agriculture, Ministry of Agriculture, Bor S. Luh Food Safety Research Center, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China
- Shanghai Jiao Tong University YunNan (Dali) Research Institute, Dali, 671000, Yunnan, China
- Shanghai Yangtze River Delta Eco-Environmental Change and Management Observation and Research Station, Ministry of Science and Technology, Ministry of Education, 800 Dongchuan Rd, Shanghai, 200240, China
- Shanghai Urban Forest Ecosystem Research Station, National Forestry and Grassland Administration, 800 Dongchuan Rd, Shanghai, 200240, China
| | - Lumei Wang
- School of Agriculture and Biology, Key Laboratory of Urban Agriculture, Ministry of Agriculture, Bor S. Luh Food Safety Research Center, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China.
- Shanghai Jiao Tong University YunNan (Dali) Research Institute, Dali, 671000, Yunnan, China.
- Shanghai Yangtze River Delta Eco-Environmental Change and Management Observation and Research Station, Ministry of Science and Technology, Ministry of Education, 800 Dongchuan Rd, Shanghai, 200240, China.
- Shanghai Urban Forest Ecosystem Research Station, National Forestry and Grassland Administration, 800 Dongchuan Rd, Shanghai, 200240, China.
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Moussa S, Kilgour M, Jans C, Hernandez-Garcia A, Cuperlovic-Culf M, Bengio Y, Simine L. Diversifying Design of Nucleic Acid Aptamers Using Unsupervised Machine Learning. J Phys Chem B 2023; 127:62-68. [PMID: 36574492 DOI: 10.1021/acs.jpcb.2c05660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Inverse design of short single-stranded RNA and DNA sequences (aptamers) is the task of finding sequences that satisfy a set of desired criteria. Relevant criteria may be, for example, the presence of specific folding motifs, binding to molecular ligands, sensing properties, and so on. Most practical approaches to aptamer design identify a small set of promising candidate sequences using high-throughput experiments (e.g., SELEX) and then optimize performance by introducing only minor modifications to the empirically found candidates. Sequences that possess the desired properties but differ drastically in chemical composition will add diversity to the search space and facilitate the discovery of useful nucleic acid aptamers. Systematic diversification protocols are needed. Here we propose to use an unsupervised machine learning model known as the Potts model to discover new, useful sequences with controllable sequence diversity. We start by training a Potts model using the maximum entropy principle on a small set of empirically identified sequences unified by a common feature. To generate new candidate sequences with a controllable degree of diversity, we take advantage of the model's spectral feature: an "energy" bandgap separating sequences that are similar to the training set from those that are distinct. By controlling the Potts energy range that is sampled, we generate sequences that are distinct from the training set yet still likely to have the encoded features. To demonstrate performance, we apply our approach to design diverse pools of sequences with specified secondary structure motifs in 30-mer RNA and DNA aptamers.
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Affiliation(s)
- Siba Moussa
- Department of Chemistry, McGill University, 801 Sherbrooke Street West, Montreal, QuebecH3A 0B8, Canada
| | - Michael Kilgour
- Department of Chemistry, McGill University, 801 Sherbrooke Street West, Montreal, QuebecH3A 0B8, Canada
| | - Clara Jans
- Department of Chemistry, McGill University, 801 Sherbrooke Street West, Montreal, QuebecH3A 0B8, Canada
| | - Alex Hernandez-Garcia
- Montreal Institute for Learning Algorithms, 6666 St. Urbain, #200, Montreal, QuebecH2S 3H1, Canada
| | - Miroslava Cuperlovic-Culf
- Digital Technologies Research Centre, National Research Council of Canada, 1200 Montreal Road, Ottawa, OntarioK1A 0R6, Canada
| | - Yoshua Bengio
- Montreal Institute for Learning Algorithms, 6666 St. Urbain, #200, Montreal, QuebecH2S 3H1, Canada
| | - Lena Simine
- Department of Chemistry, McGill University, 801 Sherbrooke Street West, Montreal, QuebecH3A 0B8, Canada
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Rodríguez Serrano AF, Hsing IM. Prediction of Aptamer-Small-Molecule Interactions Using Metastable States from Multiple Independent Molecular Dynamics Simulations. J Chem Inf Model 2022; 62:4799-4809. [PMID: 36134737 DOI: 10.1021/acs.jcim.2c00734] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Understanding aptamer-ligand interactions is necessary to rationally design aptamer-based systems. Commonly used in silico tools have proven to be accurate to predict RNA and DNA oligonucleotide tertiary structures. However, given the complexity of nucleic acids, the most thermodynamically stable conformation is not necessarily the one with the highest affinity for a specific ligand. Because many metastable states may coexist, it remains challenging to predict binding sites through molecular docking simulations using available computational pipelines. In this study, we used independent simulations to broaden the conformational diversity sampled from DNA initial models of distinct stability and assessed the binding affinity of selected metastable representative structures. In our results, utilizing multiple metastable conformations for molecular docking analysis helped identify structures favorable for ligand binding and accurately predict the binding sites. Our workflow was able to correctly identify the binding sites of the characterized adenosine monophosphate and l-argininamide aptamers. Additionally, we demonstrated that our pipeline can be used to aid the design of competition assays that are conducive to aptasensing strategies using an uncharacterized aflatoxin B1 aptamer. We foresee that this approach may help rationally design effective and truncated aptamer sequences interacting with protein biomarkers or small molecules of interest for drug design and sensor applications.
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Affiliation(s)
- Alan Fernando Rodríguez Serrano
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR 999077, China
| | - I-Ming Hsing
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR 999077, China
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