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In Silico Selection in relation to Aptamer, Based on Computational Docking

A Summary Analysis of In Silico Selection in relation to Aptamer, Based on Computational Docking

An important aspect of this topic ‘In Silico Selection in relation to Aptamer, Based on Computational Docking’ is the use of Aptamers. These are synthetic nucleic acid molecules that In Silico Selection in relation to Aptamer, Based on Computational Dockinghave the capability to bind any biological targets based on the quality of their three-dimensional and sequence structure. The selection of Aptamers is based on the use of Systematic Evolution of Ligands by EXponential enrichment, generally known as SELEX, this could be referred to as a method that employ Aptamer-target binding attractive force. (Caroli et al., 2015) In addition to this, the SELEX technique can be used with many other procedures, such as high-throughput sequencing (HT-SELEX) which in turn develops billions of random sequences that are able of binding together various epitopes on particular targets. (Caroli et al., 2015) Emphatically, Aptamers are usually in replacement of conventional antibodies since they are chemical-antibodies, as stated above, they are obtained from SELEX technology which involves multi-round choices and improvement. (Weigel & Dowsett, 2010)

Moreover, the human estrogen receptor, scientifically known as α (ERα) is also a 66 kDa ligand inducible transcription component that refers to a major mediator of 17β estradiol stimulator proliferation, distinction, and evolution of uterine and breast tissues. It is a very important biomarker which relates in the utilization in any breast cancer issues, diagnosis, and treatment. (Ali & Coombes, 2000) The effectiveness of the presence of ERα in close to two-thirds of any level of tumors and their consequent treatment relating to infantile fixation with hormonal therapy have developed ERα as an important and useful target for medical purposes. (Lippman & Alegra, 1980) In addition, the detection of any modified demonstration of ERα in cancer relating to the breast or any related diseases can be acted upon through with the use of ERα antibodies. Nevertheless, this antibody is based on applications regularly fraught with large complexity and cost of production, cross-reactivity, batch to batch variability, short shelf life, and contamination. (GomezFernandez et al., 2010)

The next generation attractive force molecules that subdue the restrictions of cost, specificity of target-binding, and stability can be replaced by conventional antibodies. According to Ellington & Szostak, (1990) Aptamers were able to gain appreciable importance as attractive force-binding molecules and selective based on the fact that there’s a need for animals which is eliminated in their production with an extra advantage of limited manufacture cost and time. Moreover, Aptamers are regarded as short oligonucleotides that can be developed against any kind of molecule. (Tuerk & Gold, 1990) This is so, because they provide benefits based on their large target affinity specificity, the normal non-immunogenic nature, and low molecular weights. Also, Aptamers are the majorly recognized with respect to an iterative process generally known as SELEX, just as stated above. It is a revolving process that takes into consideration various rounds of choice and amplification. (Tuerk & Gold, 1990) Studies have shown that this whole process is difficult, complex, time consuming, usually fails to increase the high affinity Aptamers, and tedious. (Osborne et al., 1997)

Another aspect is the requirement of the determined priming sites relating to the sequences of a library enforces a length standard on random region; thus, limit the multifariousness of the synthesized Aptamer library. In fact, the extended Aptamers, which is often ≥40 nt in length need prior shortening in order to achieve an efficient scale-up production. Lately, ER aiming at Aptamers have been recognized by the use of classical SELEX screening needed several rounds of protein-aptamer amplification, binding, enrichment, and selection. (Xu et al., 2014) However, many of these Aptamers were way too enlongated and they needed strict shortenings to achieve smaller Aptamers. Similarly, a study from He X. et al., (2015) was able to demonstrate the utilization of conditioned library for the choice of the ER-aptamer, nevertheless, they needed to still have conventional SELEX for the screening of the Aptamer. (He X. et al., 2015)

Fundamentally, Bioinformatics conceptualizations that have the capability to combine in vitro and even in silico procedures could offer greater solutions for screening of Aptamer and selection. (Collett et al., 2005) These procedures such as DA/RNA micro-array help in the provision of large throughput mean to set apart Aptamers, but simultaneously, are restricted by the criteria of the pre-chosen pool of minimal sequence numbers which is about ~104–105 for any kind of chip synthesis. (Chushak & Stone, 2009) In addition, the technique that bases on a particularly designed RNA pool for the selection of Aptamer against particular-analytes can be limited by the criterion of heavy time and computation. (Chushak & Stone, 2009)

The identification of ERα-aiming at Aptamer based on a non-SELEX rudiment, it is necessary that the estrogen response elements are hypothesized, which are extends of B-DNA in the booster region of the genes controlled by the estrogen receptors. (Driscol et al., 1998) These can be used to achieve a pool of Aptamer-alike sequences for those in silico screening. They have an inverted repeat nature which has potential to relate with ERα in vivo which thereby offers a way to imitate these features in the system of an in silico. Virtually, there are single strands of all the EREs which have inverted repeats have the capability to accommodate stable hairpins and have the probability to act as potential Aptamers. Studies have been able to prove this based on the development of a non-SELEX method which helps in the combination of the in vivo chemistry of the ERE structure and the relationships with the computational modeling and any other related molecular docking to carefully identify the existence of the ERα binding Aptamer. (Ahirwar et al., 2016)

Consequently, there is a selection requirement drawn to attain hairpin-forming the EREs and also their RNA analogs, these are then modeled to examine their binding alongside ERα with the use of AutoDock Vina, PatchDock, and HADDOCK docking. (Trott & Olson, 2010) Many of these in silico predictions are made to be further validated with respect to the in vitro affinity metric. Moreover, a candidate sequence is chosen as ER-aptamer and assessed for its aimed-specificity. Additionally, there exists solid-phase assays which are usually employed to show the antibody alternative action of the chosen ERα-aptamer.

The Evaluation of Structural and Utilitarian Choice of EREs and their Three-Dimensional Modeling

The expression of the target genes is being executed by ERs possibly by just directly binding the EREs directly or by relating and engaging transcriptional machinery at the other end in which the promoter sites of the ER target genes are existing. (Sanchez et al., 2002) As a matter of fact, most of the genes present in humans have been detected to have ERE, especially in their promoter proximal regions, in which the ER complex binds and originates any transcription of the target genes. Researchers, such as (Ahirwar et al., 2016) have been able to employ many of these specialized ERE-ER interactions just as a model in order to develop ERα binding with the RNA Aptamers. It is important to note that the ERs relate closely to ERE based on its offering as model sequences directly similar to EREs. Additionally, studies carried out by Ahirwar et al., 2016 is able to demonstrate a target to preserve all inverted repeat structures of the exactly projected modeled sequence that is alike with the natural EREs.

Based on the deduction, these researchers were able to develop a selection requirement that is aimed at selecting human EREs which are designed with full length inverted repeats and making it involve in direct binding with the ER in vivo. In order to ensure that the selected sequences adopt the high stable hairpin loops, it was necessary for them to use the prerequisite of full-length. Thus, giving them a result of the fashioned selection requirement which include about eighteen EREs that correlate perfectly with the criteria they had on their table. Also, the larger parts of the modeled RNAs have the media number of developed tertiary structures that has the range of five and hundred. Ahirwar et al., (2016) studies showed that the quantity of developed tertiary structures was higher for sequences that formed moderately stable hairpins; meanwhile there were still a similar number that confined to some sequences that developed strong hairpins.

Assessing the Virtual Screening for the Identification of Presumptive Aptamers for ERα

The identification of the capability of any modeled RNA sequences to be able to appear as ERα Aptamer, it is necessary that an in silico technique is designed, in which utilized the RNAs as ligand for the prediction of their binding with the ERα. Based on this binding prediction, the major types of docking platforms may be used for the accessibility. Just as stated above. (Ahirwar et al., 2016)

In relation to existing literatures, the testing of the designed in silico technique has to be done first in a set of putative Atamer-protein composite to assess its target-particular predictions. (Long et al., 2008) Accordingly, thrombi-RNA Aptamer composite and also VEGF165 – RNA Aptamer composite have to be used to test these complexes. (Jellinek et al., 1994) Once the method testing has been achieved, then the predicted binding partners have to be the next stage for the ERα (1SJ0) with the use of the chosen RNA sequences as the ligands. To predict the most possible Aptamer in any collected set of sequences, it is reasonable to employ the eighteen docking requirements in experiments based on the use of the docking requirements stated above. Analyzing these assumptions, the role played by hydrogen bonds has to be analyzed typically alongside with hydrophobic interactions, which is in the predicted Aptaer-protein complexes. (Hermann & Patel, 2000)

In summary, the accessibility of the virtual screening for the identification of presumptive Aptamers for ERα follows some chemical formula such as for the calculation to obtain the docking scores from the available docking algorithms, obtaining other values such as for the total Z-score must be evaluated, and observation of the in silico approach must be considered to achieve a relative prediction and differentiation among the target-specific as well as other non-specific binding partners, which can be in any level of a DNA-protein complex. (Ahirwar et al., 2016) Once these are achieved, the next phase is to guarantee the method testing through predicting the binding partners majorly for ERα (1SJ0) with the use of the chosen RNA sequences that stands as ligands.

Detailed Analytic Report

When making use of the method of classic SELEX, it is important to bear in mind the inevitable conditions that serve as shortcomings, based on the fact that they limit the efficacy towards the production of advanced affinity and also the selective-aptamers in the required duration and with the shortest available resources. (Hu et al., 2015) Aside the SELEX, the priming regions that exist in the Aptamer library have the possibility to deter the Aptamer-target interactions, thus, resulting in the improvement of low affinity binders. Considering the constant regions that exist at the end of the each sequence, they restrict the diverseness of synthesized libraries or needs synthesis of lengthier libraries in order to attain an adequately different pool. (Cho et al., 2010)

Additionally, there are many other limitations this study had been able to overcome based on the report of a non-SELEX technique of ERα-aptamer choice. The application of the novel ideology with the use of selective single stranded EREs as a likely pool of ERα-specific Aptamers. Meanwhile, considering the in vivo binding relating to dimerized estrogen receptors that are at the double stranded ERE, it has been known for a very long time and various researches have shown that these interactions exist in an in vitro system too. (Driscoll, 1998)

Finally, this study is an experimental demonstration that explores the RNA Aptamer to the ERα, chosen based on a non-SELEX in silico technique of Aptamer selection. The use of the single stranded estrogen response elements were important as a pool of likely Aptamers as well as related Aptamer is based on prediction with the use of computational dockings. To achieve aptamer against any other nuclear receptors, it is necessary to use the in silico technique SELEX-free aptamer selection because of its cost effectiveness, simplicity, and its non-requirement of sophisticated instruments.

References:
  • Ahirwar, R., Nahar, S., Aggarwal, S., Ramachandran, S., Maiti, S., & Nahar, P. (2016). In silico selection of an aptamer to estrogen receptor alpha using computational docking employing estrogen response elements as aptamer-alike molecules. Sci. Rep. Scientific Reports, 6, 21285. doi:10.1038/srep21285
  • Ali, S., & Coombes, R. C. (2000). Estrogen receptor alpha in human breast cancer: Occurrence and significance. J Mammary Gland Biol Neoplasia, 5, 271-281. Retrieved August 20, 2016.
  • Caroli, J., Taccioli, C., Fuente, A. D., Serafini, P., & Bicciato, S. (2015). APTANI: A computational tool to select aptamers through sequence-structure motif analysis of HT-SELEX data. Bioinformatics. doi:10.1093/bioinformatics/btv545
  • Cho, M., Xiao, Y., Nie, J., Stewart, R., Csordas, A. T., Oh, S. S., . . . Soh, H. T. (2010).
  • Quantitative selection of DNA aptamers through microfluidic selection and high-throughput sequencing. Proceedings of the National Academy of Sciences, 107(35), 15373-15378. doi:10.1073/pnas.1009331107
  • Chushak, Y., & Stone, M. O. (2009). In silico selection of RNA aptamers. Nucleic Acids Research, 37(12). doi:10.1093/nar/gkp408
  • Collett, J. R., Cho, E. J., Lee, J. F., Levy, M., Hood, A. J., Wan, C., & Ellington, A. D. (2005). Functional RNA microarrays for high-throughput screening of antiprotein aptamers. Analytical Biochemistry, 338(1), 113-123. doi:10.1016/j.ab.2004.11.027
  • Driscoll, M. D., Sathya, G., Muyan, M., Klinge, C. M., Hilf, R., & Bambara, R. A. (1998). Sequence Requirements for Estrogen Receptor Binding to Estrogen Response Elements. Journal of Biological Chemistry, 273(45), 29321-29330. doi:10.1074/jbc.273.45.29321
  • Ellington, A. D., & Szostak, J. W. (1990). In vitro selection of RNA molecules that bind specific ligands. (Ser. 346). Nature.
  • Gomez-Fernandez, C., Mejias, A., Walker, G., & Nadji, M. (2010). Immunohistochemical Expression of Estrogen Receptor in Adenocarcinomas of the Lung. Applied Immunohistochemistry & Molecular Morphology, 18(2), 137-141. doi:10.1097/pai.0b013e3181bec23b
  • He, X., Chen, J., Yie, S., Ye, S., Dong, D., & Li, K. (2015). Using a Sequence of Estrogen Response Elements as a DNA Aptamer for Estrogen Receptors In Vitro. Nucleic Acid Therapeutics, 25(3), 152-161. doi:10.1089/nat.2014.0521
  • Hermann, T. (2000). Adaptive Recognition by Nucleic Acid Aptamers. Science, 287(5454), 820-825. doi:10.1126/science.287.5454.820
  • Lippman, M. E., & Allegra, J. C. (1980). Quantitative estrogen receptor analyses: The response to endocrine and cytotoxic chemotherapy in human breast cancer and the disease-free interval. Cancer, 46(S12), 2829-2834. doi:10.1002/1097-0142(19801215)46:12 3.0.co;2-m
  • Long, S., & Sullenger, B. (2008). Crystal structure of an RNA aptamer bound to human thrombin. doi:10.2210/pdb3dd2/pdb
  • Trott, O., & Olson, A. J. (2009). AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J. Comput. Chem. Journal of Computational Chemistry. doi:10.1002/jcc.21334
  • Sanchez, R., Nguyen, D., Rocha, W., White, J. H., & Mader, S. (2002). Diversity in the mechanisms of gene regulation by estrogen receptors. Bioessays BioEssays, 24(3), 244-254. doi:10.1002/bies.10066
  • Tuerk, C., & Gold, L. (1990). Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase. Science, 249(4968), 505-510. doi:10.1126/science.2200121
  • Weigel, M. T., & Dowsett, M. (2010). Current and emerging biomarkers in breast cancer: Prognosis and prediction. Endocrine Related Cancer, 17(4). doi:10.1677/erc-10-0136
  • Xu, D., Chatakonda, V., Kourtidis, A., Conklin, D. S., & Shi, H. (2014). In Search of Novel Drug Target Sites on Estrogen Receptors Using RNA Aptamers. Nucleic Acid Therapeutics, 24(3), 226-238. doi:10.1089/nat.2013.0474