Abstract
CRISPR technology has demonstrated its potential as a valuable tool for future disease treatment, cellular modeling, and diverse biological and pharmaceutical applications. However, persistent concerns regarding its precision have arisen, primarily attributed to the off-target effects that impose constraints on the proficient applicability of CRISPR technology. To address this challenge, the conceptualization of an inducible CRISPR system has captured substantial interest. Building upon a previously proposed model, this study aims to provide criteria for the evaluation of photo caging groups which offer promise for the development of the aforementioned system. Furthermore, a thorough study is carried out on selected candidates using density functional theory (TD-DFT) computations. Among the compounds studied, 1-acetyl-5-bromo-7-nitroindoline stands out as a more promising alternative to the current photoactivatable protecting groups (PPGs) used to modify guide RNA (gRNA) and Cas-9 nuclease function. Notably, this molecule has significant absorbance capabilities within targeted wavelength ranges, which is critical for effective PPGs in the context of an inducible CRISPR-Cas-9 system. As work is made towards the refining of this model, the trajectory of CRISPR-Cas-9 moves closer to widespread acceptance in clinical gene editing applications.
Keywords:
CRISPR Technology, Photoremovable Protecting Groups, TD-DFT, Gene Editing, Quantum Chemistry, ORCA.
Introduction
Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) represents an emerging gene therapy approach, frequently harnessing the Cas9 DNA endonuclease derived from Streptococcus pyogenes to induce gene “knockout”1. Guided by a programmed gRNA strand, the Cas9 enzyme identifies its target—a defective gene sequence complementary to the RNA, and effectively removes the gene. This allows space for introducing a healthy gene copy or prompting DNA self-repair. The target of the Cas9 enzyme is a nuclease-specific protospacer sequence in the DNA to which the gRNA binds. Modifying the gRNA’s structure facilitates the targeting of different genes. Though the process is relatively simple, the severity of certain common errors is concerning. The off-target effect, for instance, can cause inadvertent point mutations, insertions, deletions, translocations, and inversions at untargeted loci due to their similarity to the target sequence2. By preventing these issues associated with the CRISPR Cas-9 technology, its use can be widened, lowering production costs and patient costs while sparing many people from debilitating genetic disorders3.Research has explored several systems, examining external control of CRISPR-Cas9 using magnetic fields4, molecules5, or light6. Light has proven to be the most effective of these choices, with minimum influence on treated cells, quick functionality, noninvasiveness, and higher spatial resolution when compared to alternatives7.Previous studies have used light to modulate various CRISPR functions beyond gene removal8, 9, 7, 10, 11. Modified CRISPR components are capable of regulating transcription. To repurpose CRISPR components for that function, the nuclease activity of the Cas-9 enzyme must be removed and the resulting enzyme (dCas-9) should be bound to a transcriptional activation domain creating a transactivator. When led by the Cas-9 enzymes gRNA to the target gene, the transactivator can influence transcription. Therefore, light-induced translocation of the transactivator into the nucleus emerges as a strategy for increased control of gene expression. One study proposed a model wherein the transactivator, coupled with a Ca2+-responsive NFAT fragment, responds to Ca2+ influx triggered by light-activated Ca2+ channels. This influx prompts the transactivator to relocate to the nucleus and locate its target gene10, a representation of the various systems targeting transcriptional control through light. However, recovery of Cas-9 abilities has never been fully possible following this procedure, many systems have seen activity even in the absence of light, and only after several hours of light exposure can the full effect of the system be seen10. Studies using light to control the Cas-9 enzyme’s nuclease function have been conducted as well. One prominent approach uses DNA oligonucleotides complementary to the gRNA9. These can temporarily block gRNA function until it is removed with light. The system is simple and addresses the previous necessity of prolonged light exposure with quick reaction times. However, the process is not halted in the absence of light and requires high levels of UV for photolysis of DNA oligonucleotides (4.0 J/cm2 or 498.79nm)9.This study will focus on a similar inducible CRISPR Cas-9 system. Such a system would allow for better spatiotemporal control of the gene editing process and analysis of where the Cas enzyme is bound before allowing it to cut the wrong nucleotides. Rather than using DNA oligonucleotides, this can be accomplished by binding photo-protecting groups (PPGs), also commonly referred to as photocaging groups, to the gRNA. PPGs are molecules that can be used to cage a molecule, in this case, RNA, until they are removed by way of irradiation (Figure 1). In the revised CRISPR model proposed by Moroz-Omori et al., photocaged gRNA, obtained by solid-phase synthesis for greater yields, is used7. The PPG bound to the gRNA acts as an inhibitor, preventing it from binding to its target gene until the PPG (N-POM in the case of this study) is removed by UV light (100-400 nm)7. However, UV light exposure has negative effects on DNA and membranes that can cause cytotoxicity and mutations in cell signaling pathways12. Therefore, alternate, safer PPGs that can be used to modify CRISPR gRNA for use in humans must be identified. The gRNA used by the Cas-9 enzyme has two parts: crispr RNA (crRNA) and a tracrRNA13. The crRNA is typically 17-20 bases and is the component complementary to the target loci while the tracrRNA is where the Cas enzyme binds13. Problems with accuracy deal with the crRNA section of the gRNA so that is where PPGs will be placed14. Previous research has found that 2-3 photocaging groups evenly spaced in the crRNA are sufficient to temporarily restrict hybridization7. Once placed, the PPGs will prevent complementary base pairing until light-mediated deprotection occurs. This article will review the specific criterion which a PPG must meet in order to be considered for use in modifying the CRISPR Cas-9 system. It will then analyze some potential PPGs using the detailed criteria.
Methods
Identifying suitable molecules for gRNA modification.
The first step of this study involved identifying suitable PPGs for analysis. The selected PPGs were chosen from literature detailing their alternative uses, including the control of mRNA translation and light-controlled drug release15, 16, 17. Notably, nitrophenethyl and nitrobenzyl compounds, along with their dimethoxy variations, were frequently highlighted as effective photocaging groups in early studies16. For our analysis, we selected three specific 3-Nitrobenzaldehyde—based on their UV absorbance properties, which fall within the desired range for our experimental design, and smaller size. This was done to minimize computational costs and increase the accuracy of of the calculations. These molecules were also chosen due to their strong binding affinities with DNA, as demonstrated in previous research. For example, 3-Nitrobenzaldehyde has shown significant interaction with DNA. Specifically literature has pointed to the ability of Nitrobenzaldehyde derivatives to act as DNA intercalators, suggesting that 3-nitrobenzaldehyde has an affinity for DNA18. It has also been linked to inhibition of topoisomerase I, further suggesting affinity19. Selection based on these criteria of size, UV absorbance, and affinity for nucleic acids ensures that the molecules not only fit within the experimental requirements but are also supported by existing evidence to have strong potential for our study.
Analysis of the various molecules.
Once collected, the absorbance of the selected PPGs at various wavelengths was collected from literature20, 21. Only one had not been previously reported. The molecules were all reconstructed in the ChemDraw software and their cartesian coordinates were extracted. Then, using ORCA, time-dependent density functional theory (TD-DFT) calculations were run on all the molecules (Figure 2)22, 23, 24, 25–27, 28, 29. TD-DFT is a tractable ab initio way of calculating electronic excitation energies for molecules of all sizes. It has been shown to be quite accurate although its level of accuracy depends on several things and larger molecules tend to show less reliable results31. One prior study ran into issues while running TD-DFT calculations on large systems32. The molecules used in this study fall within a size range that has been relatively accurate in past studies33 so in theory, the results of the calculations described in this paper should not be significantly inaccurate. The accuracy of TD-DFT calculations is also being continuously improved. TD-DFT can model many electronic transitions, including singlet-singlet, singlet-triplet, as well as more complex excitations. It is also widely used in UV-Vis absorption and emission spectra calculations as it is able to determine the energy levels and transition strengths of excited states23.These calculations revealed the excited state energies and oscillator strengths of the molecules analyzed. When the oscillator strengths were plotted against the excitation energies the absorption spectrum of the molecules was generated, indicating where the molecule absorbs light most strongly. The software Multiwfn was used to create the absorption spectrum plot34. Note that the collected data can also be used to find quantum yield () using the corresponding equation35 as a way to investigate these molecules in a future study. Finally, to determine the viability of the spectra created based on TD DFT data, they were compared against previously.determined values using percent difference calculations.
Justification of Selected TD-DFT Protocol.
We employed the B3LYP functional, a widely recognized hybrid functional that combines Becke’s three-parameter exchange functional with the Lee-Yang-Parr correlation functional. This choice is justified by its established reliability in accurately describing electronic structures and excitation energies for a variety of systems. B3LYP is effective for predicting singlet-singlet transitions and is well-suited for the types of electronic interactions present in our molecules. The def2-TZVP basis set was selected due to its triple zeta quality, which provides a high level of accuracy in describing the electronic wavefunctions. This basis set is known for its ability to capture subtle electronic effects and improve the precision of calculated properties, making it appropriate for the detailed analysis required in our study. We specified tight Self-Consistent Field (SCF) convergence criteria. This ensures that the electronic structure calculations are performed with high accuracy, minimizing errors in the ground-state wavefunction that could impact the TD-DFT results. As for molecular charge and multiplicity, the input specifies a charge of 0 and a multiplicity of 1. This setup reflects the actual system under study, ensuring that the calculations are representative of the molecule’s true electronic state and behavior.
Constructing molecular criteria.
Analysis of the various molecules and the trends among commonly used PPGs revealed certain properties that must be met to be used. To be effective without causing any harm the PPGs must show strong absorption at a range of wavelengths greater than at least 300.0 nm16, but over 400.0 nm if possible., which is a value from 0-1 or 0% to 100%, should be on the higher end of the spectrum.
Results and Discussion
The molecules selected for analysis in this article are 1-acetyl-5-bromo-7-nitroindoline, 4-methoxy-7-nitro-indoline, and 3-Nitrobenzaldehyde (Figure 3). There are a few criteria under which these molecules were analyzed. For a compound to be suitable not all criteria need to be met. However, the more criteria a molecule meets, the closer it is to ideal. These criteria are for molecules to be used with the above-mentioned model, but they can be slightly modified to be used for other models and functions.
Molecular Criteria for Evaluation
I) Binding Affinity
In order to be used, the molecule must be able to bind to the gRNA whether it’s to the phosphate groups or the nitrogenous base itself. Without this, it cannot perform the intended function of caging gRNA. All the molecules used in this study have been previously proven to have an appropriate binding affinity.
II) Strong Absorption at Safe Wavelengths
To prevent absorption of irradiation by the organism being genetically modified, the PPG must have strong absorption at wavelengths above least 300.0 nm16. However, to avoid damage associated with UV light it is recommended that the PPG shows strong absorption at wavelengths above 400.0 nm.
III) High Quantum Yield
Quantum yield () is a good measure of a reaction’s efficiency. It can be determined by finding the quotient of the number of photons emitted/photons absorbed. To determine the efficiency of the PPG itself, multiply the quantum yield by its molar decadic absorption coefficient () at the irradiation wavelength (irr). This value can be represented as (irr) and directly corresponds to release at the irr35 *This calculation is not entirely possible with TD-DFT software. However, calculating this property is an avenue to further test the molecules listed in this study.
IV) Stability
An important prerequisite for new PPGs is stability and low intrinsic activity so that the PPG does nothing but act as an intermediate on/off switch. If the PPG interacts with the system in any other way it could cause unwanted and potentially dangerous effects within the organism. Most previously studied PPGs have already been proven to meet this criteria, and have therefore been approved for use. For new PPGs being proposed, however, this is incredibly important.
Absorption Results
The TD-DFT revealed the absorption spectrum for each of the molecules. The spectra for two of these molecules have also been recorded in other studies20, 21. At the pictured wavelengths photolysis of the molecules will occur. They differ slightly in the byproducts of that reaction (Figure 5). two of the molecules can be expected to release CO2 while the other releases an H+. These are not strange byproducts and are typically released by other cellular processes. Therefore, they can be expected not to cause any interference with the gene editing or cellular function.
1-acetyl-5-bromo-7-nitroindoline
In another study, the absorbance of 1-acyl-7-nitroindolines, the group to which this PPG belongs, as determined through photolysis in 99% CH3CN–1% H2O, had 434 nm21. High values of absorbance (1.0-1.5) are consistently reported for all wavelengths between 400-475 nm. This makes 1-Acetyl-5-bromo-7-nitroindoline especially promising for use in an inducible CRISPR CAS-9 system. The range of wavelengths at which it seems to show strong absorbance is ideal for preventing harm that may otherwise be caused by UV irradiation. Worth investigating is what part of this molecule makes it a good PPG. Such information may be useful in designing new, more effective PPGs in the future. The TD-DFT calculations for this molecule were unable to be completed for this molecule. Self-consistent field (SCF) convergence was incredibly expensive due to the input settings designed for increased accuracy of results. Due to the time and memory consumed by this calculation, the software used crashed before the TD-DFT could finish running. Regardless, the information obtained via TD-DFT calculations is likely to resemble the absorption spectrum of 1-acetyl-5-bromo-7-nitroindoline that was previously reported. In a follow-up study, these calculations may be run for comparison and improved understanding of TD-DFT capabilities in experiments like the ones conducted in this article.
4-methoxy-7-nitro-indoline
As seen in the UV-Vis spectrum constructed using TD-DFT data, the oscillation strength of 4-methoxy-7-nitro-indoline never crosses 0.5. Even at lower wavelengths, it doesn’t seem to be very effective in terms of absorbance. Its for molar absorption coefficients is around 185.0 nm. For oscillator strengths, on the other hand, it has a of 284.8 nm with a corresponding oscillator strength of 0.329641112. This wavelength is not bad, however, it is no more effective than other molecules and the wavelength of light it requires has the potential to damage organelles and cell function. Usually, spectra show a correlation between molar absorption coefficients and oscillator strengths. The difference in the two lines on the spectra is interesting and worth further investigation. There may be another property of this molecule that remains unaccounted for, causing those uncommon trends. When zoomed in, as seen in the second image of Figure 5, the lines seem to follow each other exactly, unlike the first image. Whether this is an error on the part of the software or something else is unclear. However, the current lack of information on this molecule and the irregularities in the results are reasons to continue experimenting with this PPG before deciding whether or not it should be used.
Table 1
ABSORPTION SPECTRUM VIA TRANSITION ELECTRIC DIPOLE MOMENTS | |||||||
State | Energy (cm-1) | Wave length (nm) | fosc | State | Energy (cm-1) | Wave length(?)(nm) | fosc |
1 | 25681.7 | 389.4 | 0.075394992 | 16 | 54767.5 | 182.6 | 0.042991245 |
2 | 29292.0 | 341.4 | 0.000007138 | 17 | 55215.9 | 181.1 | 0.030271671 |
3 | 34738.0 | 287.9 | 0.018763177 | 18 | 55228.5 | 181.1 | 0.064411033 |
4 | 35118.3 | 284.8 | 0.329641112 | 19 | 55467.0 | 180.3 | 0.147804142 |
5 | 40390.2 | 247.6 | 0.048218228 | 20 | 55985.4 | 178.6 | 0.024128788 |
6 | 42848.0 | 233.4 | 0.044094521 | 21 | 56396.1 | 177.3 | 0.074810346 |
7 | 45897.5 | 217.9 | 0.173982484 | 22 | 56466.5 | 177.1 | 0.000368547 |
8 | 46726.6 | 214.0 | 0.023492830 | 23 | 57967.9 | 172.5 | 0.004546505 |
9 | 49285.8 | 202.9 | 0.001196122 | 24 | 58048.8 | 172.3 | 0.004247363 |
10 | 49851.7 | 200.6 | 0.033104242 | 25 | 58225.4 | 171.7 | 0.004327243 |
11 | 50504.0 | 198.0 | 0.001256104 | 26 | 58906.9 | 169.8 | 0.010656368 |
12 | 51014.4 | 196.0 | 0.001671460 | 27 | 59671.8 | 167.6 | 0.002022425 |
13 | 51638.9 | 193.7 | 0.171809742 | 28 | 60591.1 | 165.0 | 0.070169042 |
14 | 52081.5 | 192.0 | 0.200464300 | 29 | 61122.1 | 163.6 | 0.010584193 |
15 | 54446.2 | 183.7 | 0.017996706 | 30 | 61318.6 | 163.1 | 0.112408314 |
3-nitrobenzaldehyde.
The oscillator strength and molar absorption of this molecule reach near zero values after 325.0 nm. Absorption peaks at excitation states 22 and 11 respectively or wavelengths 170.6 nm and 218.1 nm (Figure 6). At those wavelengths, 3 Nitrobenzaldehyde reaches oscillator strengths of 0.293819444 and 0.519509981. Oscillator strengths of 0.5 and above are typically considered high, so absorbance is likely strongest at 218.1 nm. Oscillator strengths are measures of absorbance likelihood so it can be reasonably concluded from the absorbance spectrum that this molecule does not show strong absorption at wavelengths above 300.0 nm, let alone wavelengths above 400.0 nm. For that reason, 3 Nitrobenzaldehyde would not be a suitable molecule to use as a PPG to improve CRISPR accuracy. Worth looking into, however, is ortho-nitrobenzyl, which has a slightly different structure than 3-nitrobenzaldehyde. Its NO2 group is attached next to one of the carbon-carbon double bonds (ortho positions) on a benzene ring rather than the meta position, or the carbon atom three positions away. Previous research has found similar trends in absorbance with around 232 nm and absorbance nearing 0 after 325 nm20. The exact percent difference between the wavelengths at which the highest absorbance/oscillator strength/molar absorption coefficient is observed in the two graphs is only approximately 6.18%, indicating a very strong similarity between the TD-DFT and previously recorded values. Though conclusions cannot be drawn from this singular example, the accuracy of TD-DFT calculations is certainly worth consideration and has been subject of a few previous studies39.
Table 2
ABSORPTION SPECTRUM VIA TRANSITION ELECTRIC DIPOLE MOMENTS | |||||||
State | Energy (cm-1) | Wave length (nm) | fosc | State | Energy (cm-1) | Wave length(?)(nm) | fosc |
1 | 26484.0 | 377.6 | 0.000002925 | 16 | 53594.9 | 186.6 | 0.132976954 |
2 | 27453.3 | 364.3 | 0.000071102 | 17 | 53673.2 | 186.3 | 0.000494611 |
3 | 30717.7 | 325.5 | 0.000000011 | 18 | 55258.8 | 181.0 | 0.001100023 |
4 | 32746.2 | 305.4 | 0.000169211 | 19 | 55421.4 | 180.4 | 0.044553866 |
5 | 33958.2 | 294.5 | 0.012286835 | 20 | 56183.9 | 178.0 | 0.000027079 |
6 | 38720.8 | 258.3 | 0.212460770 | 21 | 57772.1 | 173.1 | 0.000404676 |
7 | 39677.1 | 252.0 | 0.000000875 | 22 | 58620.0 | 170.6 | 0.293819444 |
8 | 42245.6 | 236.7 | 0.047355747 | 23 | 59173.6 | 169.0 | 0.000027269 |
9 | 43304.0 | 230.9 | 0.081467227 | 24 | 60184.6 | 166.2 | 0.141959458 |
10 | 45107.0 | 221.7 | 0.000016261 | 25 | 61109.8 | 163.6 | 0.025323852 |
11 | 45849.8 | 218.1 | 0.519509981 | 26 | 63058.5 | 158.6 | 0.000000523 |
12 | 46534.2 | 214.9 | 0.000303678 | 27 | 63356.8 | 157.8 | 0.009955596 |
13 | 48698.6 | 205.3 | 0.083708253 | 28 | 64448.0 | 155.2 | 0.000624204 |
14 | 50769.2 | 197.0 | 0.000001151 | 29 | 65043.5 | 153.7 | 0.166532127 |
15 | 52095.5 | 192.0 | 0.000000107 | 30 | 65866.4 | 151.8 | 0.005311595 |
Considerations and Complications
- Our research was conducted at home rather than in a lab, which, while cost-effective, limited access to advanced computational resources and experimental validation. Some results could not be obtained due to the expensive nature of the calculations.
- The conditions under which the simulations were run, such as temperature, pH, and concentration levels, were based on theoretical models. These conditions might not perfectly replicate real-world scenarios, potentially impacting the accuracy of our findings. Assumptions regarding the stability and behavior of the compounds could also affect the results, as real-world conditions might differ from those modeled.
- As mentioned earlier in the article, another way to assess these molecules is to calculate the (irr). This calculation is beyond the capabilities of TD-DFT software and requires further modeling and was therefore out of the scope for this study. As this hasn’t been accounted for, calculations of this nature should be performed before assuming the efficacy of 1-acetyl-5-bromo-7-nitroindoline for future studies.
- Unexpected trends observed in the data may be attributed to unaccounted properties of the molecules that were not captured by our computational models. These results were obtained on the assumption that the relatively small size of the molecules would increase accuracy. However, it isn’t entirely clear at what point results may be impacted by size as larger molecules often exhibit different behaviors, leading to inconsistencies.
- Working with photosensitive protecting groups (PPGs) that absorb in the UV range may also present challenges in a biological context. UV light can induce phototoxicity, leading to cell death, DNA damage, and other detrimental effects. When PPGs absorb UV light, they can generate reactive oxygen species (ROS) that further contribute to phototoxicity. UV light also has limited penetration depth in biological tissues, posing limitations to its ability to reach deeper tissues or cells.
- a) To minimize phototoxicity, it is essential to carefully control the intensity and duration of UV exposure. The molecules selected in this study were chosen for their strong absorption at safe wavelengths. Also worth exploring is protective agents or antioxidants to scavenge ROS and reduce oxidative damage.
- b) Advanced techniques such as pulsed UV light or localized irradiation can also confine the UV exposure to specific areas and times, thereby reducing overall cellular damage.
Future Avenues
Future research could significantly benefit from in vivo studies to validate the findings obtained from computational models. These studies would provide a more accurate understanding of how these compounds behave in biological systems, addressing some of the limitations inherent in theoretical studies. Additionally, exploring a broader range of PPGs could offer valuable insights into their effectiveness and potential applications. Other PPGs may be selected by investigating the structural or functional aspects of 1-acetyl-7-nitroindoline that contribute to its better performance. Further, employing quantum yield measurements could provide a more direct assessment of PPG efficiency.(irr), offers a quantitative measure of the release at the irradiation wavelength (irr), that may offer more insight into the efficacy of selected PPGs. Investigating other unaccounted properties of the molecules might also explain unusual trends and contribute to a more comprehensive understanding of their behavior. As the field progresses, refining both computational models and experimental techniques will be essential for improving the accuracy and reliability of predictions regarding molecular interactions and efficiencies.
Conclusion
A noticeable inference may be derived from the completed TD-DFT calculations involving 1-Acetyl-5-bromo-7-nitroindoline, 4-Methoxy-7-nitroindoline, and 3-Nitrobenzaldehyde. Only one of the compounds examined shows potential compatibility with the inducible CRISPR-Cas-9 model described in the introduction: 1-Acetyl-5-bromo-7-nitroindoline. The incorporation of this approach, in conjunction with effective chemicals such as the aforementioned, has the prospect of increasing the viability of CRISPR as a clinical route for treating genetic illnesses. This is especially important in minimizing the existing off-target impact, which is a substantial barrier to wider CRISPR implementation. Furthermore, the similarity between previously published absorption spectra and those generated by TD-DFT calculations supports the use of these calculations to evaluate photoactivatable protecting groups (PPGs) using the proposed criteria. Prospective research directions include the design and characterization of novel PPGs that meet requirements, as well as extensive computational analysis of these compounds to improve cost-effectiveness and efficacy in this specific application.
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