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Fallah A, Havaei SA, Sedighian H, Kachuei R, Fooladi AAI. Prediction of aptamer affinity using an artificial intelligence approach. J Mater Chem B 2024; 12:8825-8842. [PMID: 39158322 DOI: 10.1039/d4tb00909f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/20/2024]
Abstract
Aptamers are oligonucleotide sequences that can connect to particular target molecules, similar to monoclonal antibodies. They can be chosen by systematic evolution of ligands by exponential enrichment (SELEX), and are modifiable and can be synthesized. Even if the SELEX approach has been improved a lot, it is frequently challenging and time-consuming to identify aptamers experimentally. In particular, structure-based methods are the most used in computer-aided design and development of aptamers. For this purpose, numerous web-based platforms have been suggested for the purpose of forecasting the secondary structure and 3D configurations of RNAs and DNAs. Also, molecular docking and molecular dynamics (MD), which are commonly utilized in protein compound selection by structural information, are suitable for aptamer selection. On the other hand, from a large number of sequences, artificial intelligence (AI) may be able to quickly discover the possible aptamer candidates. Conversely, sophisticated machine and deep-learning (DL) models have demonstrated efficacy in forecasting the binding properties between ligands and targets during drug discovery; as such, they may provide a reliable and precise method for forecasting the binding of aptamers to targets. This research looks at advancements in AI pipelines and strategies for aptamer binding ability prediction, such as machine and deep learning, as well as structure-based approaches, molecular dynamics and molecular docking simulation methods.
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Affiliation(s)
- Arezoo Fallah
- Department of Bacteriology and Virology, Faculty of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Seyed Asghar Havaei
- Department of Microbiology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
| | - Hamid Sedighian
- Applied Microbiology Research Center, Biomedicine Technologies Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.
| | - Reza Kachuei
- Molecular Biology Research Center, Biomedicine Technologies Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Abbas Ali Imani Fooladi
- Applied Microbiology Research Center, Biomedicine Technologies Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.
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2
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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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3
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Alfinito E. TBA for Sensing Toxic Cations: A Critical Analysis of Structural and Electrical Properties. Int J Mol Sci 2023; 24:14492. [PMID: 37833940 PMCID: PMC10572628 DOI: 10.3390/ijms241914492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 09/19/2023] [Accepted: 09/21/2023] [Indexed: 10/15/2023] Open
Abstract
Food and drinks can be contaminated with pollutants such as lead and strontium, which poses a serious danger to human health. For this reason, a number of effective sensors have been developed for the rapid and highly selective detection of such contaminants. TBA, a well-known aptamer developed to selectively target and thereby inhibit the protein of clinical interest α-thrombin, is receiving increasing attention for sensing applications, particularly for the sensing of different cations. Indeed, TBA, in the presence of these cations, folds into the stable G-quadruplex structure. Furthermore, different cations produce small but significant changes in this structure that result in changes in the electrical responses that TBA can produce. In this article, we give an overview of the expected data regarding the use of TBA in the detection of lead and strontium, calculating the expected electrical response using different measurement techniques. Finally, we conclude that TBA should be able to detect strontium with a sensitivity approximately double that achievable for lead.
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Affiliation(s)
- Eleonora Alfinito
- Dipartimento di Matematica e Fisica 'Ennio De Giorgi', Università del Salento, I-73100 Lecce, Italy
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4
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Lee SJ, Cho J, Lee BH, Hwang D, Park JW. Design and Prediction of Aptamers Assisted by In Silico Methods. Biomedicines 2023; 11:356. [PMID: 36830893 PMCID: PMC9953197 DOI: 10.3390/biomedicines11020356] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 01/21/2023] [Accepted: 01/23/2023] [Indexed: 01/28/2023] Open
Abstract
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.
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Affiliation(s)
- Su Jin Lee
- Drug Manufacturing Center, Daegu-Gyeongbuk Medical Innovation Foundation (K-MEDI Hub), Daegu 41061, Republic of Korea
| | - Junmin Cho
- Medical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation (K-MEDI Hub), Daegu 41061, Republic of Korea
| | - Byung-Hoon Lee
- Medical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation (K-MEDI Hub), Daegu 41061, Republic of Korea
| | - Donghwan Hwang
- Medical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation (K-MEDI Hub), Daegu 41061, Republic of Korea
| | - Jee-Woong Park
- Medical Device Development Center, Daegu-Gyeongbuk Medical Innovation Foundation (K-MEDI Hub), Daegu 41061, Republic of Korea
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Hasanzadeh A, Hamblin MR, Kiani J, Noori H, Hardie JM, Karimi M, Shafiee H. Could artificial intelligence revolutionize the development of nanovectors for gene therapy and mRNA vaccines? NANO TODAY 2022; 47:101665. [PMID: 37034382 PMCID: PMC10081506 DOI: 10.1016/j.nantod.2022.101665] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Gene therapy enables the introduction of nucleic acids like DNA and RNA into host cells, and is expected to revolutionize the treatment of a wide range of diseases. This growth has been further accelerated by the discovery of CRISPR/Cas technology, which allows accurate genomic editing in a broad range of cells and organisms in vitro and in vivo. Despite many advances in gene delivery and the development of various viral and non-viral gene delivery vectors, the lack of highly efficient non-viral systems with low cellular toxicity remains a challenge. The application of cutting-edge technologies such as artificial intelligence (AI) has great potential to find new paradigms to solve this issue. Herein, we review AI and its major subfields including machine learning (ML), neural networks (NNs), expert systems, deep learning (DL), computer vision and robotics. We discuss the potential of AI-based models and algorithms in the design of targeted gene delivery vehicles capable of crossing extracellular and intracellular barriers by viral mimicry strategies. We finally discuss the role of AI in improving the function of CRISPR/Cas systems, developing novel nanobots, and mRNA vaccine carriers.
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Affiliation(s)
- Akbar Hasanzadeh
- Cellular and Molecular Research Center, Iran University of Medical Sciences, Tehran 1449614535, Iran
- Department of Medical Nanotechnology, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran 1449614535, Iran
| | - Michael R Hamblin
- Laser Research Centre, Faculty of Health Science, University of Johannesburg, Doornfontein 2028, South Africa
- Radiation Biology Research Center, Iran University of Medical Sciences, Tehran, Iran
| | - Jafar Kiani
- Oncopathology Research Center, Iran University of Medical Sciences, Tehran 1449614535, Iran
- Department of Molecular Medicine, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Hamid Noori
- Cellular and Molecular Research Center, Iran University of Medical Sciences, Tehran 1449614535, Iran
- Department of Medical Nanotechnology, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran 1449614535, Iran
| | - Joseph M. Hardie
- Division of Engineering in Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, 02139 USA
| | - Mahdi Karimi
- Cellular and Molecular Research Center, Iran University of Medical Sciences, Tehran 1449614535, Iran
- Department of Medical Nanotechnology, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran 1449614535, Iran
- Oncopathology Research Center, Iran University of Medical Sciences, Tehran 1449614535, Iran
- Research Center for Science and Technology in Medicine, Tehran University of Medical Sciences, Tehran 141556559, Iran
- Applied Biotechnology Research Centre, Tehran Medical Science, Islamic Azad University, Tehran 1584743311, Iran
| | - Hadi Shafiee
- Division of Engineering in Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, 02139 USA
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6
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Cai R, Chen X, Zhang Y, Wang X, Zhou N. Systematic bio-fabrication of aptamers and their applications in engineering biology. SYSTEMS MICROBIOLOGY AND BIOMANUFACTURING 2022; 3:223-245. [PMID: 38013802 PMCID: PMC9550155 DOI: 10.1007/s43393-022-00140-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 09/27/2022] [Accepted: 09/28/2022] [Indexed: 10/27/2022]
Abstract
Aptamers are single-stranded DNA or RNA molecules that have high affinity and selectivity to bind to specific targets. Compared to antibodies, aptamers are easy to in vitro synthesize with low cost, and exhibit excellent thermal stability and programmability. With these features, aptamers have been widely used in biology and medicine-related fields. In the meantime, a variety of systematic evolution of ligands by exponential enrichment (SELEX) technologies have been developed to screen aptamers for various targets. According to the characteristics of targets, customizing appropriate SELEX technology and post-SELEX optimization helps to obtain ideal aptamers with high affinity and specificity. In this review, we first summarize the latest research on the systematic bio-fabrication of aptamers, including various SELEX technologies, post-SELEX optimization, and aptamer modification technology. These procedures not only help to gain the aptamer sequences but also provide insights into the relationship between structure and function of the aptamers. The latter provides a new perspective for the systems bio-fabrication of aptamers. Furthermore, on this basis, we review the applications of aptamers, particularly in the fields of engineering biology, including industrial biotechnology, medical and health engineering, and environmental and food safety monitoring. And the encountered challenges and prospects are discussed, providing an outlook for the future development of aptamers.
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Affiliation(s)
- Rongfeng Cai
- The Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, 214122 China
| | - Xin Chen
- The Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, 214122 China
| | - Yuting Zhang
- The Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, 214122 China
| | - Xiaoli Wang
- The Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, 214122 China
| | - Nandi Zhou
- The Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, 214122 China
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Dzuvor CKO, Tettey EL, Danquah MK. Aptamers as promising nanotheranostic tools in the COVID-19 pandemic era. WILEY INTERDISCIPLINARY REVIEWS. NANOMEDICINE AND NANOBIOTECHNOLOGY 2022; 14:e1785. [PMID: 35238490 PMCID: PMC9111085 DOI: 10.1002/wnan.1785] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 02/02/2022] [Accepted: 02/07/2022] [Indexed: 12/13/2022]
Abstract
The emergence of SARS-COV-2, the causative agent of new coronavirus disease (COVID-19) has become a pandemic threat. Early and precise detection of the virus is vital for effective diagnosis and treatment. Various testing kits and assays, including nucleic acid detection methods, antigen tests, serological tests, and enzyme-linked immunosorbent assay (ELISA), have been implemented or are being explored to detect the virus and/or characterize cellular and antibody responses to the infection. However, these approaches have inherent drawbacks such as nonspecificity, high cost, are characterized by long turnaround times for test results, and can be labor-intensive. Also, the circulating SARS-COV-2 variant of concerns, reduced antibody sensitivity and/or neutralization, and possible antibody-dependent enhancement (ADE) have warranted the search for alternative potent therapeutics. Aptamers, which are single-stranded oligonucleotides, generated artificially by SELEX (Evolution of Ligands by Exponential Enrichment) may offer the capacity to generate high-affinity neutralizers and/or bioprobes for monitoring relevant SARS-COV-2 and COVID-19 biomarkers. This article reviews and discusses the prospects of implementing aptamers for rapid point-of-care detection and treatment of SARS-COV-2. We highlight other SARS-COV-2 targets (N protein, spike protein stem-helix), SELEX augmented with competition assays and in silico technologies for rapid discovery and isolation of theranostic aptamers against COVID-19 and future pandemics. It further provides an overview on site-specific bioconjugation approaches, customizable molecular scaffolding strategies, and nanotechnology platforms to engineer these aptamers into ultrapotent blockers, multivalent therapeutics, and vaccines to boost both humoral and cellular immunity against the virus. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies Diagnostic Tools > Biosensing Therapeutic Approaches and Drug Discovery > Nanomedicine for Infectious Disease Therapeutic Approaches and Drug Discovery > Nanomedicine for Respiratory Disease.
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Affiliation(s)
- Christian K. O. Dzuvor
- Bioengineering Laboratory, Department of Chemical and Biological EngineeringMonash UniversityClaytonVictoriaAustralia
| | | | - Michael K. Danquah
- Department of Chemical EngineeringUniversity of TennesseeChattanoogaTennesseeUSA
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Chen Z, Hu L, Zhang BT, Lu A, Wang Y, Yu Y, Zhang G. Artificial Intelligence in Aptamer-Target Binding Prediction. Int J Mol Sci 2021; 22:3605. [PMID: 33808496 PMCID: PMC8038094 DOI: 10.3390/ijms22073605] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 03/25/2021] [Accepted: 03/26/2021] [Indexed: 12/18/2022] Open
Abstract
Aptamers are short single-stranded DNA, RNA, or synthetic Xeno nucleic acids (XNA) molecules that can interact with corresponding targets with high affinity. Owing to their unique features, including low cost of production, easy chemical modification, high thermal stability, reproducibility, as well as low levels of immunogenicity and toxicity, aptamers can be used as an alternative to antibodies in diagnostics and therapeutics. Systematic evolution of ligands by exponential enrichment (SELEX), an experimental approach for aptamer screening, allows the selection and identification of in vitro aptamers with high affinity and specificity. However, the SELEX process is time consuming and characterization of the representative aptamer candidates from SELEX is rather laborious. Artificial intelligence (AI) could help to rapidly identify the potential aptamer candidates from a vast number of sequences. This review discusses the advancements of AI pipelines/methods, including structure-based and machine/deep learning-based methods, for predicting the binding ability of aptamers to targets. Structure-based methods are the most used in computer-aided drug design. For this part, we review the secondary and tertiary structure prediction methods for aptamers, molecular docking, as well as molecular dynamic simulation methods for aptamer-target binding. We also performed analysis to compare the accuracy of different secondary and tertiary structure prediction methods for aptamers. On the other hand, advanced machine-/deep-learning models have witnessed successes in predicting the binding abilities between targets and ligands in drug discovery and thus potentially offer a robust and accurate approach to predict the binding between aptamers and targets. The research utilizing machine-/deep-learning techniques for prediction of aptamer-target binding is limited currently. Therefore, perspectives for models, algorithms, and implementation strategies of machine/deep learning-based methods are discussed. This review could facilitate the development and application of high-throughput and less laborious in silico methods in aptamer selection and characterization.
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Affiliation(s)
- Zihao Chen
- School of Chinese Medicine, The Chinese University of Hong Kong, Hong Kong, China; (Z.C.); (B.-T.Z.)
| | - Long Hu
- Law Sau Fai Institute for Advancing Translational Medicine in Bone & Joint Diseases, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong, China;
| | - Bao-Ting Zhang
- School of Chinese Medicine, The Chinese University of Hong Kong, Hong Kong, China; (Z.C.); (B.-T.Z.)
| | - Aiping Lu
- Institute of Integrated Bioinformedicine and Translational Science, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong, China;
- Guangdong-Hong Kong Macao Greater Bay Area International Research Platform for Aptamer-Based Translational Medicine and Drug Discovery, Hong Kong, China
| | - Yaofeng Wang
- Centre for Regenerative Medicine and Health, Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, Hong Kong, China
| | - Yuanyuan Yu
- Law Sau Fai Institute for Advancing Translational Medicine in Bone & Joint Diseases, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong, China;
- Guangdong-Hong Kong Macao Greater Bay Area International Research Platform for Aptamer-Based Translational Medicine and Drug Discovery, Hong Kong, China
| | - Ge Zhang
- Law Sau Fai Institute for Advancing Translational Medicine in Bone & Joint Diseases, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong, China;
- Guangdong-Hong Kong Macao Greater Bay Area International Research Platform for Aptamer-Based Translational Medicine and Drug Discovery, Hong Kong, China
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Buglak AA, Samokhvalov AV, Zherdev AV, Dzantiev BB. Methods and Applications of In Silico Aptamer Design and Modeling. Int J Mol Sci 2020; 21:E8420. [PMID: 33182550 PMCID: PMC7698023 DOI: 10.3390/ijms21228420] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 11/04/2020] [Accepted: 11/08/2020] [Indexed: 02/07/2023] Open
Abstract
Aptamers are nucleic acid analogues of antibodies with high affinity to different targets, such as cells, viruses, proteins, inorganic materials, and coenzymes. Empirical approaches allow the design of in vitro aptamers that bind particularly to a target molecule with high affinity and selectivity. Theoretical methods allow significant expansion of the possibilities of aptamer design. In this study, we review theoretical and joint theoretical-experimental studies dedicated to aptamer design and modeling. We consider aptamers with different targets, such as proteins, antibiotics, organophosphates, nucleobases, amino acids, and drugs. During nucleic acid modeling and in silico design, a full set of in silico methods can be applied, such as docking, molecular dynamics (MD), and statistical analysis. The typical modeling workflow starts with structure prediction. Then, docking of target and aptamer is performed. Next, MD simulations are performed, which allows for an evaluation of the stability of aptamer/ligand complexes and determination of the binding energies with higher accuracy. Then, aptamer/ligand interactions are analyzed, and mutations of studied aptamers made. Subsequently, the whole procedure of molecular modeling can be reiterated. Thus, the interactions between aptamers and their ligands are complex and difficult to understand using only experimental approaches. Docking and MD are irreplaceable when aptamers are studied in silico.
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Affiliation(s)
- Andrey A. Buglak
- A. N. Bach Institute of Biochemistry, Research Center of Biotechnology, Russian Academy of Sciences, Leninsky prospect 33, 119071 Moscow, Russia; (A.V.S.); (A.V.Z.); (B.B.D.)
- Physical Faculty, St. Petersburg State University, 7/9 Universitetskaya naberezhnaya, 199034 St. Petersburg, Russia
| | - Alexey V. Samokhvalov
- A. N. Bach Institute of Biochemistry, Research Center of Biotechnology, Russian Academy of Sciences, Leninsky prospect 33, 119071 Moscow, Russia; (A.V.S.); (A.V.Z.); (B.B.D.)
| | - Anatoly V. Zherdev
- A. N. Bach Institute of Biochemistry, Research Center of Biotechnology, Russian Academy of Sciences, Leninsky prospect 33, 119071 Moscow, Russia; (A.V.S.); (A.V.Z.); (B.B.D.)
| | - Boris B. Dzantiev
- A. N. Bach Institute of Biochemistry, Research Center of Biotechnology, Russian Academy of Sciences, Leninsky prospect 33, 119071 Moscow, Russia; (A.V.S.); (A.V.Z.); (B.B.D.)
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Cataldo R, De Nunzio G, Millithaler JF, Alfinito E. Aptamers Which Target Proteins: What Proteotronics Suggests to Pharmaceutics. Curr Pharm Des 2020; 26:363-371. [PMID: 31942851 DOI: 10.2174/1381612826666200114095027] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2019] [Accepted: 01/08/2020] [Indexed: 01/01/2023]
Abstract
Aptamers represent a challenging field of research, relevant for diagnosis in macular degeneration, cancer, thrombosis and many inflammatory diseases, and promising in drug discovery and development. Their selection is currently performed by a stable in vitro technology, namely, SELEX. Furthermore, computationalstatistical tools have been developed to complement the SELEX selection; they work both in the preliminary stage of selection, by designing high affinity aptamers for the assigned target, and also in the final stage, analyzing the features of the best performers to implement the selection technique further. A massive use of the in silico approach is, at present, only restricted by the limited knowledge of the specific aptamer-target topology. Actually, only about fifty X-ray structures of aptamer-protein complexes have been experimentally resolved, highlighting how this knowledge has to be improved. The structure of biomolecules like aptamer-protein complexes can be represented by networks, from which several parameters can be extracted. This work briefly reviews the literature, discussing if and how general network parameters in the framework of Proteotronics and graph theory (such as electrical features, link number, free energy change, and assortativity), are important in characterizing the complexes, anticipating some features of the biomolecules. To better explain this topic, a case-study is proposed, constituted by a set of anti-angiopoietin (Ang2) aptamers, whose performances are known from the experiments, and for which two different types of conformers were predicted. A topological indicator is proposed, named Möbius (M), which combines local and global information, and seems able to discriminate between the two possible types of conformers, so that it can be considered as a useful complement to the in vitro screening for pharmaceutical aims.
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Affiliation(s)
- Rosella Cataldo
- Department of Mathematics and Physics "Ennio De Giorgi", University of Salento, Lecce, Italy.,Laboratory of Interdisciplinary Research Applied to Medicine (DReAM), University of Salento and ASL (Local Health Authority), Lecce, Italy
| | - Giorgio De Nunzio
- Department of Mathematics and Physics "Ennio De Giorgi", University of Salento, Lecce, Italy.,Laboratory of Interdisciplinary Research Applied to Medicine (DReAM), University of Salento and ASL (Local Health Authority), Lecce, Italy
| | - Jean-Francois Millithaler
- Electrical and Computer Engineering, University of Massachusetts Lowell, Lowell, MA, 01854, United States
| | - Eleonora Alfinito
- Department of Innovation Engineering, University of Salento, Lecce, Italy
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Yasmeen F, Seo H, Javaid N, Kim MS, Choi S. Therapeutic Interventions into Innate Immune Diseases by Means of Aptamers. Pharmaceutics 2020; 12:pharmaceutics12100955. [PMID: 33050544 PMCID: PMC7600108 DOI: 10.3390/pharmaceutics12100955] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 10/03/2020] [Accepted: 10/04/2020] [Indexed: 12/25/2022] Open
Abstract
The immune system plays a crucial role in the body's defense system against various pathogens, such as bacteria, viruses, and parasites, as well as recognizes non-self- and self-molecules. The innate immune system is composed of special receptors known as pattern recognition receptors, which play a crucial role in the identification of pathogen-associated molecular patterns from diverse microorganisms. Any disequilibrium in the activation of a particular pattern recognition receptor leads to various inflammatory, autoimmune, or immunodeficiency diseases. Aptamers are short single-stranded deoxyribonucleic acid or ribonucleic acid molecules, also termed "chemical antibodies," which have tremendous specificity and affinity for their target molecules. Their features, such as stability, low immunogenicity, ease of manufacturing, and facile screening against a target, make them preferable as therapeutics. Immune-system-targeting aptamers have a great potential as a targeted therapeutic strategy against immune diseases. This review summarizes components of the innate immune system, aptamer production, pharmacokinetic characteristics of aptamers, and aptamers related to innate-immune-system diseases.
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12
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Biosensing Cytokine IL-6: A Comparative Analysis of Natural and Synthetic Receptors. BIOSENSORS-BASEL 2020; 10:bios10090106. [PMID: 32847008 PMCID: PMC7557795 DOI: 10.3390/bios10090106] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Revised: 08/15/2020] [Accepted: 08/21/2020] [Indexed: 12/18/2022]
Abstract
Cytokines are a family of proteins which play a major role in the regulation of the immune system and the development of several diseases, from rheumatoid arthritis to cancer and, more recently, COVID-19. Therefore, many efforts are currently being developed to improve therapy and diagnosis, as well as to produce inhibitory drugs and biosensors for a rapid, minimally invasive, and effective detection. In this regard, even more efficient cytokine receptors are under investigation. In this paper we analyze a set of IL-6 cytokine receptors, investigating their topological features by means of a theoretical approach. Our results suggest a topological indicator that may help in the identification of those receptors having the highest complementarity with the protein, a feature expected to ensure a stable binding. Furthermore, we propose and discuss the use of these receptors in an idealized experimental setup.
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Emami N, Pakchin PS, Ferdousi R. Computational predictive approaches for interaction and structure of aptamers. J Theor Biol 2020; 497:110268. [PMID: 32311376 DOI: 10.1016/j.jtbi.2020.110268] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 03/27/2020] [Accepted: 04/02/2020] [Indexed: 02/07/2023]
Abstract
Aptamers are short single-strand sequences that can bind to their specific targets with high affinity and specificity. Usually, aptamers are selected experimentally via systematic evolution of ligands by exponential enrichment (SELEX), an evolutionary process that consists of multiple cycles of selection and amplification. The SELEX process is expensive, time-consuming, and its success rates are relatively low. To overcome these difficulties, in recent years, several computational techniques have been developed in aptamer sciences that bring together different disciplines and branches of technologies. In this paper, a complementary review on computational predictive approaches of the aptamer has been organized. Generally, the computational prediction approaches of aptamer have been proposed to carry out in two main categories: interaction-based prediction and structure-based predictions. Furthermore, the available software packages and toolkits in this scope were reviewed. The aim of describing computational methods and tools in aptamer science is that aptamer scientists might take advantage of these computational techniques to develop more accurate and more sensitive aptamers.
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Affiliation(s)
- Neda Emami
- Department of Health Information Technology, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Parvin Samadi Pakchin
- Research Center for Pharmaceutical Nanotechnology, Biomedicine Institute, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Reza Ferdousi
- Department of Health Information Technology, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran; Research Center for Pharmaceutical Nanotechnology, Biomedicine Institute, Tabriz University of Medical Sciences, Tabriz, Iran.
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Cataldo R, Giotta L, Guascito MR, Alfinito E. Assessing the Quality of in Silico Produced Biomolecules: The Discovery of a New Conformer. J Phys Chem B 2019; 123:1265-1273. [PMID: 30642170 DOI: 10.1021/acs.jpcb.8b11456] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The computational procedures for predicting the 3D structure of aptamers interacting with different biological molecules have gained increasing attention in recent years. The information acquired through these methods represents a crucial input for research, especially when relevant crystallographic data are not available. A number of software programs able to perform macromolecular docking are currently accessible, leading to the prediction of the quaternary structure of complexes formed by two or more interacting biological macromolecules. Nevertheless, the scoring protocols employed for ranking the candidate structures do not always produce satisfactory results, making difficult the identification of structures that are most likely to occur in nature. In this paper, we propose a novel procedure to improve the predictive performances of computational scoring protocols, using a maximum likelihood estimate based on topological and electrical properties of interacting biomolecules. The reliability of the new computational approach, enabling the ranking of aptamer-protein configurations produced by an open source docking program, has been assessed by its successful application to a set of antiangiopoietin aptamers, for which experimental data highlighting the sequence-dependent affinity toward the target protein are available. The procedure led to the identification of two main types of aptamer conformers involved in angiopoietin binding. Interestingly, one of these reproduces the arrangement of angiopoietin with its natural target, tyrosine kinase, while the other one is completely unexpected. The possible scenarios related to these results have been discussed. The methodology here described can be used to refine the outcomes of different computational procedures and can be applied to a wide range of biological molecules, thus representing a new tool for guiding the design of bioinspired sensors with enhanced selectivity.
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Affiliation(s)
- R Cataldo
- Department of Mathematics and Physics, "Ennio De Giorgi" , University of Salento , Via Monteroni , I-73100 Lecce , Italy
| | - L Giotta
- Department of Biological and Environmental Sciences and Technologies , University of Salento , Via Monteroni , I-73100 Lecce , Italy
| | - M R Guascito
- Department of Biological and Environmental Sciences and Technologies , University of Salento , Via Monteroni , I-73100 Lecce , Italy
| | - E Alfinito
- Department of Innovation Engineering , University of Salento , Via Monteroni , I-73100 Lecce , Italy
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