Written by TKS Boston Student, Alice Liu (email: email@example.com)
Gene editing is exactly how it sounds — literally cutting or modifying DNA within a genome. This is undoubtedly scary, especially if this powerful technology is taken advantage of in the hands of bad intentions (for example, the concept of designer babies), leading to many moral and ethical concerns.
However, there are many other incredibly impactful implications, including for cellular agriculture which could potentially solve world hunger, curing of genetic diseases, and even battling climate change.
A large majority of media interest has focused on curing diseases with a genetic basis, which is done by cutting disease-causing genes that alters gene’s protein product and reduces disease symptoms. But what if gene editing can be used for drug discovery leading to the development of new drugs and personalized medicine?
CRISPR-Cas9as a basis, is a tool enabling the use of physical cuts in DNA genetic material creating mutations. The CRISPR cas itself aims to identify target molecules and can easily create cellular and whole-animal model systems.
This in turn is able to precisely mimic diseases which can accurately verify a new drug’s safety and efficacy. This system is used to either activate or inhibit genes, where we can then determine the genes and proteins which either cause or prevent the disease, then identifying the targets for potential drugs.
Within the modeling, a short strand ofRNAis used to target a specific sequence ofDNA, which is linked to enzyme. That enzyme is then able to cut double-stranded DNA. With the RNA and enzyme delivered to cell nucleus, the RNA is able to bind to its complementary DNA. This sequences and acts as a guide for the enzyme, the enzyme cutting the DNA, where the DNA-repair enzymes are able to “fix” the break (caused by the enzyme) by eitherdisabling or modifyingthe targeted gene. As a result, the activity levels either increase or decrease which can be used to track new mutations and inverted sections.
To determine which proteins matter for formation of cancer/diseases, CRISPR Cas can switch off, orknock outspecific genes to test out their role in system and what they do, while avoiding unwanted effects on targets. Current developments have been made to knock out 20,000 protein-coding genes found in humans also known as agenomic-wide screen. By using knock out screening, we can identify the genes involved in drug resistance and ways of preventing it. The process is:
Genes that are resistant to specific drugs can be identified through cells becoming “more sensitive” to the compouds after the CRISPR-Cas treatment. Those genes they encode are targeted with other drugs in attempt to get around resistance.
For example, a recent study was held that investigated tumor formation in mice. By using CRISPR to remove all the genes in the cancer cells, we are able to understand which genes cause the growth of a specific cancer. This in turn allows us to identify the subset of genes which block tumor formation when removed using CRISPR. If the drug is designed to inactivate protein and is identified by CRISPR as necessary for tumor formation, then it represents an effective anti-cancer therapy.
Candidate drugs are able to bind to and interfere with proteins encoded by genes (as opposed to directly affecting the genes) while identifying the genes promoting disease. The steps are:
As opposed to the conventional way of making a “precise genome cut,” scanning allows the cutting of DNA, then “repairing” with fusing it back together, creating ascar. The scars are used as instructions to make the proteins. We are now able to determine which parts of the protein matter for a specific function, by observing if the mutant versions of a gene generated by CRISPR generate mutant versions of the corresponding protein.
CRISPR scanning allows the identifying of the exact region within the protein that the therapeutic drug can attach itself to inactivate the protein. We are able to observe the extent of cells that contain genetic scars thrive, despite the presence of the drug, with how a good drug = kills cancer cells. If a mutation by a scar prevents the drug from binding, the growth of the cancer cell can be rescued in a way. The cells containing the scars are also multiplied, and from this, we are able to know if a drug is cancer-resistant or not.
Problems begin to arise based on the complexity of proteins (their structure and relationships between other proteins) as well as the time it takes with sorting and identifying.
A quantum computer is able to assemble and sort through gene variants at same time leading to 1) faster sequencing and 2) biomarker discovery, finding disease-related mutations with better accuracy. With the use of quantum processes, we are able to have more accurate descriptions with the classical computational model of drug-protein interaction.
In recent studies, researchers were able to demonstrate how a quantum processor could be used as a predictive tool when assisting the binding of gene regulatory proteins to the genome.
During the process when the production ofTFor transcription factor proteins (controlling which genes are expressed), they have to find specific locations of the genome to attach themselves. Mutations in TFs and TF-binding sites are what cause many human diseases. How these TFs are able to identify the functional binding sites in the genome is still unknown, but with more comprehensive knowledge on protein formation, we will have a better understanding of the underlying causes of these diseases.
In this case, quantum computing is applied to machine learning when deriving models to predict if certain sequences of DNA represented strong or weak binding sites with a set of transcription factors. The quantum processor then learns the patterns and models which are used to estimate the strength of the proteins binding the sequences. As a result, the quantum mapping can predict the correct binding site for selected proteins.
On average, it takes over 10 years for a drug to be developed, from discovery, and clinical trials, to when it finally lands in the market. The process can be decreased significantly with the “discovery” part, through approaches with CRISPR, Quantum, and combining both CRISPR and Quantum. This will account for saving millions of lives each year, as well as the prevention of new diseases from developing.