Identifying vulnerabilities hidden on the surface of ‘indrugable’ proteins could transform disease treatment
The number of potential therapeutic targets on the surface of human proteins is far greater than previously thought, according to the results of a new study published in the journal Nature.
A groundbreaking new technique developed by researchers at the Center for Genomic Regulation (CRG) in Barcelona has revealed the existence of a multitude of previously secret gates that control protein function and which could, in theory, be targeted to radically alter the over the course of conditions as varied as dementia, cancer and infectious diseases.
The method, in which tens of thousands of experiments are performed at the same time, has been used to draw the first-ever map of these elusive targets, also known as allosteric sites, in two of the most common human proteins, revealing that they are abundant. and identifiable.
This approach could be a game-changer for drug discovery, leading to safer, smarter and more effective drugs. It enables research labs around the world to find and exploit vulnerabilities in any protein, including those previously thought to be “tamper-proof”.
“Not only are these potential therapeutic sites abundant, but there is evidence that they can be manipulated in different ways. Rather than simply turning them on or off, we could modulate their activity like a thermostat. gives us a lot of space to design “smart drugs” that target the bad and spare the good”, explains André Faure, postdoctoral researcher at the CRG and co-first author of the article.
Proteins play a central role in all living organisms and perform vital functions such as providing structure, speeding up reactions, acting as messengers or fighting disease. They are made up of amino acids, folding into countless different shapes in three-dimensional space. The shape of a protein is crucial to its function, with a single error in an amino acid sequence having potentially devastating consequences for human health.
Allostery is one of the great unsolved mysteries of protein function. Allosteric effects occur when a molecule binds to the surface of a protein, which in turn causes changes at a distant site of the same protein, regulating its function by remote control. Many pathogenic mutations, including many cancer factors, are pathological due to their allosteric effects.
Despite their fundamental importance, allosteric sites are incredibly difficult to find. Indeed, the rules governing the functioning of proteins at the atomic level are hidden. For example, a protein can change shape in the presence of an incoming molecule, revealing hidden pockets deep within its surface that are potentially allosteric but unidentifiable using conventional structure determination alone.
Drug hunters have traditionally designed treatments that target a protein’s active site, the small region where chemical reactions occur or targets are bound. The downside of these drugs, also known as orthosteric drugs, is that the active sites of many proteins look very similar and therefore the drugs tend to bind and inhibit many different proteins at once, which has potential side effects. In comparison, allosteric site specificity means that allosteric drugs are among the most effective types of drugs currently available. Many allosteric drugs, which treat various ailments ranging from cancer to AIDS to hormonal disorders, were discovered by accident.
The study authors addressed this challenge by developing a technique called deep double PCA (ddPCA), which they describe as a “brute force experiment”. “We deliberately break things down in thousands of different ways to build a complete picture of how something works,” says ICREA research professor Ben Lehner, coordinator of the systems biology program at CRG and author of the study. “It’s like suspecting a faulty spark plug, but instead of just checking that, the mechanic takes the whole car apart and checks it piece by piece. By testing ten thousand things at once, we identify all the parts that really matter. “
The method works by altering the amino acids that make up a protein, resulting in thousands of different versions of the protein with only one or two differences in sequence. The effects of the mutations are then tested all at the same time on living cells in the laboratory.
“Each cell is a tiny factory making a different version of the protein. In a single test tube, we have millions of different factories, so we can very quickly test how all the different versions of a protein work,” adds Dr. Lehner. Data collected from experiments is fed into neural networks, algorithms that analyze the data by mimicking the functioning of the human brain, resulting in comprehensive maps that identify the location of allosteric sites on the surface of proteins. .
One of the great advantages of the method is that it is an affordable technique accessible to any research laboratory in the world. “This greatly simplifies the process needed to find allosteric sites, with the technique performing at a better level of accuracy than several more expensive and time-consuming laboratory methods,” says Júlia Domingo, co-first author of the study. “Our hope is that other scientists will use the technique to quickly and comprehensively map the allosteric sites of human proteins one by one.”
One of the technique’s longer-term benefits is its potential to study protein function and evolution. The study authors believe that, if scaled up, the method could one day lead to advances that can accurately predict the properties of proteins from their amino acid sequences. If successful, the authors say it would usher in a new era of predictive molecular biology, allowing much faster development of new drugs and a clean, biology-based industry.
“While some tools can predict the structure of a protein by reading its sequence, our method takes it a step further by telling us how a protein works. This is part of a larger vision to make biology as ingenious as planes, bridges or computers.the same challenges for more than 70 years, but it turns out that they are easier to solve than we previously thought.If we succeed, it will open a new field with possibilities without precedent,” concludes Dr. Lehner.