Pushing the Limits of Evolution
An Introduction to Protein Engineering
Professional sports is a field which is exciting to many people. Each week, millions of fans turn on the television or go to stadiums around the world to support their team. Between different sports teams there are many intense rivalries: the Boston Red Sox and the New York Yankees in major league baseball, Liverpool and Manchester United in soccer, and a variety of other famous competitors.
Rivalries such as these have been going on since the beginning of time when the original rivalry first came to life: bacteria versus viruses. The two continue to face off against one another in a game with huge stakes: survival. Losing bacteria or viruses can undergo the continuous process of natural selection, one of the key principles of evolution. Strands of viruses or bacteria which are unable to survive other organisms or unsuited for their environments will go extinct and only the strongest organisms will continue to exist.
In the early 1980s, after billions of years of evolution and the development of complex organisms, prominent scientists Sir Alan Fersht and Sir Greg Winter had a brilliant idea. They could control how organisms evolved by editing their genetic material to create new variants of organisms which may not ever have been a product of natural evolution. This technique is known as protein engineering.
Table of Contents
- What is protein engineering?
- Popular methods such as mutagenesis, and how they’re executed using PCRs
- Concerns surrounding unpredictability and inaccuracy
- Game changing technologies developed to solve these problems
- How protein engineering has the potential to change the world
- Key takeaways
What is protein engineering?
Protein engineering is a field of biotechnology which enables scientists to create new proteins that don’t exist naturally with DNA recombination (rDNA) technology and molecular design. It currently has the most useful applications in the field of biopharmaceuticals, but it also has many helpful use cases in a variety of fields.
There are three main buckets of protein engineering: Indels, substitutions, and de novo enzyme engineering. Indels are insertions or deletions of bases from a protein’s genetic code, they work either to insert a new aspect into the protein that didn’t exist at all before or to eliminate an aspect of the protein without replacing it. Indels are used to change factors such as a protein’s function, biophysical properties, or substrate specificity (a protein’s ability to bind to specific ions or molecules).
Substitutions involve both taking genetic material out of a protein and then putting something new in its place, which is typically utilized when scientists hope to keep the general function of a protein but slightly change the details of its execution (i.e. editing a fluorescent protein to be a different color but not changing the fact that it’s fluorescent).
Finally, the third main type of protein engineering is de novo (translating to “from scratch”) enzyme engineering. Enzymes are proteins produced in the cells of plants, animals, and microorganisms which accelerate chemical reactions. De novo enzyme engineering is the most challenging protein engineering method. It essentially consists simply of synthesizing enzymes from scratch, and is used simply to attempt to make new proteins with a less strong sense of intended direction.
Protein engineering is very dependent on the natural folds of a protein. Proteins come in many different shapes, and often look like long 3 dimensional squiggles (think curly fries). A protein’s shape is generated naturally during a process called biosynthesis, where a series of reacting enzymes form the protein. The shape of a protein’s fold can be impacted by many external factors such as the temperature, pH (acidity), salt levels, and presence of other factors. Scientists have already been able to develop new proteins by performing the biosynthesis of a protein outside of a living organism.
One of the biggest challenges in protein engineering (largely in the case of indels and substitutions) is ensuring the protein doesn’t break as a result of the modified genetic material. If the execution is lacking or the difference is too drastic between the initial protein and the final product, the protein can break altogether. To prevent this, a lot of testing and very careful precision are required when editing the protein. Additionally, ensuring that the final product protein is fairly similar to the initial protein at a genetic level (not adding or removing too much in the case of indels, making sure the genetic material being edited in is relatively similar to what’s being removed in substitutions) decreases the likelihood of a protein breaking so scientists also aim to achieve this.
Popular methods such as mutagenesis, and how they’re executed using PCRs
As stated before, protein engineering is performed using rDNA technology, a term which encompasses technologies utilizing enzymes (proteins which accelerate chemical reactions) to engineer new proteins. There are a variety of different methods used to modify proteins, dependent on the goal and degree of the modification.
One of the biggest types of protein engineering techniques is mutagenesis, a technique used to mutate genes, proteins, and organisms. It’s a process which can occur spontaneously in nature, but is typically achieved using laboratory techniques. The three main types of mutagenesis are random (makes all sorts of protein variants but they may not be useful), focused/site-directed (does engineering at very specific sites but odds are lower of getting a functioning protein), and recombination based (finds variety in engineered proteins to see why they vary).
There are different methods which can be used to achieve mutagenesis, but the basis of each is that a short DNA primer (single stranded nucleic acid in DNA) from the initial protein is synthesized (undergoes a series of chemical reactions) to complement the DNA of the mutation so that it can hybridize with the DNA being outsourced from a different gene.
Oftentimes, whether or not a protein engineering technique is a type of mutagenesis, it is executed using polymerase chain reactions or PCRs for short. This term may sound familiar as it is a technique also utilized to make COVID tests. The way PCR works is that a small sequence of DNA is copied many times until it is exponentially amplified to make it more visible. This makes it easier to detect COVID because virus shedding molecules are easier to detect when found in large quantities, and this is useful in protein engineering because scientists are better able to study a protein’s genetic material and make the most precise plan of action for a higher probability of success in execution.
PCR does happen to have a lesser ability to work with highly complex structures in comparison to other DNA based methods, but with this it is also easier to execute which is part of why it’s so popular.
Additionally, there are many computational technologies which offer scientists the ability to execute protein engineering computationally. These technologies are fairly easy to use, and simulate the experience of engineering proteins in real life in a more convenient as well as efficient way.
After proteins have been engineered (or protein engineering has been attempted), it’s time to evaluate the results. The success rates of protein engineering can range from 1 in 1,000 to 1 in 10 million, so many different possibilities for execution (which part of genetic material is changed, in what quantity, which external material is being edited in during a substitution, etc.) must be tested.
Because of this, determining which products of the experiment were effective (if any) can be a lengthy process. First, the proteins are screened to see the results of each. Then, if any proteins have shown signs of possible success, they are selected out of the larger group for additional testing and/or observation.
Concerns surrounding unpredictability and inaccuracy
While protein engineering has incredible potential, there are certainly still concerns and barriers in the field which must be acknowledged to view the technique holistically.
First of all and perhaps most importantly, protein engineering is often wildly unpredictable. The probability of a successfully engineered protein which both doesn’t break during the process and obtains the desired function (when there is one) is highly unlikely, success rates range from 1 in 1000 to 1 in 10 million.
Many scientists dedicate their careers to the field with hopes of developing technologies that can engineer and screen proteins on a large level based on the abundantly low probability of a successfully engineered protein. Technologies have been developed (as will be outlined in the next section!), but the uncertain nature of protein engineering is still often a barrier.
Secondly, while computational protein engineering technologies can be far easier to use, they have been found to be lacking in accuracy and have no correlation to the success rates of in vivo protein engineering when performing the same tasks. The technology simply shows how certain tasks would be executed without consideration of realistic accuracy rates, which means this technology isn’t a very valuable tool when looking for insights on the likelihood of a protein engineering technique being successful.
Clearly, although protein engineering shows great promise and has been able to have a great impact in some cases, there are still large barriers which make its success inconsistent. That said, many people work to develop technologies that can address these barriers to make the process more efficient.
Game changing technologies developed to solve these problems
First up is a robotic model designed at MIT to accelerate the process of screening protein samples and selecting promising ones in the case of directed evolution (making many variants of a protein to see which are most effective/useful).
The model picked out mammalian cells identified under a microscope that expressed multiple specific properties the scientists were looking for, and screened over 100,000 protein samples in just a few hours by evaluating them using multiple different criteriums which would optimize the value of the protein in comparison to the initial protein.
This technology is incredibly useful specifically when performing directed evolution, because the use of robotic technology makes the process of screening hundreds of thousands of proteins far more efficient than humans are capable of, and its automated nature acts as a constant which eliminates the former potential factor of human error.
Another type of great technology being used to optimize protein engineering are biosensors. Biosensors are analytical devices used to detect biophysical properties which combine a biological component and a physicochemical detector. This makes them very useful for monitoring proteins. A group of scientists from the State Key Laboratory of Bioreactor Engineering in China designed an enzyme-based biosensor to monitor and engineer protein stability within proteins.
Protein stability is a highly desirable trait in proteins, which can be challenging to achieve in engineered proteins based on their unpredictable and unnatural nature. The way the scientists’ biosensor works is by inserting the protein of interest into their specially engineered enzyme based biosensor which forms stable fluorescent compounds and then couples their stability to the protein to therefore increase the protein stability as well.
This can be useful for all types of proteins, but is specifically useful for engineered proteins since they are often unstable and increasing their stability can help them stay in tact and function effectively.
Additionally, since computational models for protein engineering have proven to be ineffective in predicting the success rates of engineered protein samples, in the past year there have been groups working to incorporate machine learning into computational models which will have the ability to make such predictions.
A group of machine learning experts from the University of Florida designed ECNet (evolutionary context-integrated neural network), a tool which aims to predict the functionality of specific engineered proteins as opposed to simply demonstrating execution. This has incredible potential, as the greater efficiency and accessibility of computational methods combined with accurate predictions of successfully engineered proteins is a combination which would make protein exponentially more efficient and less risky.
How protein engineering has the potential to change the world
All in all, protein engineering is a technique with massive potential and a variety of opportunities to make great impact. It could help millions of patients receive more personalized and effective medical care, optimize products such as leather and paper, immensely help the environment by making more materials biodegradable, and expand the limits of evolution farther than was ever previously imaginable.
There are certainly challenges which prevent the technique currently from being utilized to its full potential, but as mass scale tests continue to be performed and assistive technologies are also developed, the boundaries continue to be pushed and the challenges in this field conquered. The fields of science and technology continue to flourish, and as they do protein engineering is on the front line of techniques changing the world as we know it for good.
Key Takeaways
- Protein engineering is a technique and form of biotechnology enabling scientists to create new proteins which don’t exist naturally with the help of recombinant DNA technology .
- The three main buckets of protein engineering functions are indels (insertions and deletions from pre existing proteins), substitutions (replacing pieces of genetic material from pre existing proteins), and de novo enzyme engineering (building brand new proteins from scratch).
- Protein engineering is based off of the natural folds of a protein which give it its shape. When looking for proteins which will make a good match in the instance of a substitution, other proteins with similar folds and amino acid patterns are more likely to be successfully edited in since they will differ less from the genetic material they’re replacing.
- Mutagenesis is a standard method in protein engineering often used as a basis. The three types of mutagenesis are random, site directed/focused, and recombination based.
- In terms of execution, polymerase chain reactions (PCRs) are a popular way to execute mutagenesis or other techniques. They make many copies of a piece of genetic material to exponentially increase its visibility. They have a lesser ability to achieve highly complex structures than DNA based methods, but are also easier to execute.
- Protein engineering has helpful applications in many fields such as biopharmaceuticals and healthcare, sustainability, food, cosmetics, and many more. Its nature of optimizing proteins makes it useful for optimizing all sorts of materials, and it is also great for precision medicine.
- Two of the big concerns in this field are the highly unpredictable nature of protein engineering and the lack of predictability of engineered proteins when using computational methods.
- With these concerns, there are also many scientists aiming to create technologies which conquer these challenges and maximize the efficiency of the protein engineering process with robotic models, biosensors, machine learning algorithms, and other cutting edge technological tools.
- Despite it being less than perfect due to some concerns, protein engineering has incredible potential and can have a huge positive impact in a variety of industries.
Thank you so much for reading my article, I hope you enjoyed it! My name is Raina Bornstein and I’m 15 years old. I’m passionate about branches of neuroscience and biotechnology, especially when they connect to treating neurological conditions. I’d love to connect on LinkedIn or Twitter, or you can reach out to me at rainabornstein@gmail.com to talk or collaborate. I can’t wait to hear from you!
