Postdoc Enrique Marcos (Barcelona 1982) is a chemist, a theoretical chemist to be exact. He has just published his first paper in Science, in which he explains how to computationally design the pocket-like cavities of proteins—essential areas that allow many proteins to perform their functions. And he has just been awarded a second Marie Skłodowska-Curie Action Fellowship.
“During my PhD”, Enrique tells in vivo, “I used to model chemical reactions in enzymes. For my postdoc, I decided to focus on how to modify proteins to make them catalyse new chemical reactions—something that is very important for industry.” He soon realised that the best approach was not just to redesign natural proteins, but rather to find a method to create them artificially from scratch. “This gave us much more control,” he explains.
Enrique began working on this idea five years ago at David Baker’s Lab at the University of Washington in Seattle, where he obtained a prestigious Marie Skłodowska-Curie Action Fellowship.
“We devoted our efforts to learning how to computationally create new protein structures that had cavities or holes. These cavities are of great biomedical interest because we can design in them active sites for enzymes or recognition sites for small molecules useful for certain types of treatment. This approach might have a number of promising applications,” he adds.
In autumn 2015, he joined Modesto Orozco’s Molecular Modelling and Bioinformatics Lab, where he was able to complete the project he started in the US and begin a new one on designing a protein capable of recognising DNA in nucleosomes (structures that comprise DNA coiled around histones and that make up chromatin), and which could be an interesting pharmaceutical target. Marcos has just been awarded a second Marie Skłodowska-Curie Action Fellowship for this project.
“What you can do, for example, is design proteins blocking the action of pathogenic ones, like those overexpressed in cancer and other diseases. This could inhibit pathological processes,” he adds.
Segments of natural proteins present distinct 3D structures. Among the most common of these are β-sheets, formed by dozens of amino acids. “Nature uses these structures for many proteins,” says the young scientist, “so we thought it would be interesting to learn how to design and regulate them.” This had not been done previously for β-sheets.
The researchers began their work in silico by first constructing a 3D model of the structure they were looking for. Next, thanks to a program called Rosetta, they found a sequence of amino acids capable of stabilising the structure and reproducing the desired folded β-sheet.
“We performed a geometric study of the parameters with the potential to regulate the curvature of these sheets, and then we built computer models based on these parameters,” explains Marcos.
“You can obtain various combinations and evaluate many sequences. You will only use those that give you a better ‘score’,” says the postdoc. “You then go backwards: you test whether the classical calculation method can predict the structure you are looking for, starting from the selected sequence.” Once you succeed, then the in vivo part begins. “This is when you are ready to produce the most promising proteins in the lab.”
For Marcos, the best part of this research was to combine computational research and the ‘wet lab.’ “I came from a computational background and had to learn how to do experiments. Others had the opposite experience. It was a privilege to be able to see the whole process, from beginning to end,” he notes.
Like many researchers, when he was young, Marcos was drawn to science because he was curious, “I wanted to discover new things; and, if on top of that they could be useful to society, even better,” he summarises. But it wasn’t always a smooth ride. “At the beginning of my career, I worked on experiments in the lab, but I decided that it wasn't my cup of tea. I also found it was not easy to make precise predictions and understand the details of what was going on. So I moved into computation, but then realised that when we did make a prediction, we needed someone to validate it in the lab. In the end, I found a nice balance between computation and experimentation.”
The lesson he learnt from his experience is unequivocal: “Barriers in science are always very high. Obstacles appear every day, but if you have a dream, you can always overcome them. You have to be a fighter and work hard, that’s true. But with sufficient drive, enthusiasm and motivation, you will get through any hurdle. My advice is: find something that truly motivates you, everything else will come naturally.”