Sir Tom Blundell: "Proteins have been my life"
Sir Tom Blundell: "Proteins have been my life"

My strategy arose in the first research I did. In this paper we analyzed insulin in the 1960s. The amino acid sequence of insulin was already well analyzed. I discovered the three-dimensional structure of this protein, with Dorothy Hodgkin and his team. So he was one of the first to compare the amino acid sequences with the protein architecture. I came to the question What sequences can form a concrete architecture?
So, in the challenge of predicting how proteins bend I was interested in the reverse approach, that is, I wanted to see if sequences that have a certain way of bending the protein chain can be identified and then look for the corresponding genes.
I think predicting three-dimensional structures from the amino acid sequence is a problem with no solution. It is not only necessary to predict the shape of this structure but also the intermediate steps. On the contrary, the reverse route has been the most successful strategy, which has served to obtain a lot of information.
The study of protein interactions is a much more interesting problem, since there are few proteins from genes, but many protein combinations. Many proteins have no separate activity, but are associated with other proteins.
There are many examples of this and there are several ways to do it. In some cases, both proteins are activated with the simple association. On other occasions, as a result of the binding, the conformation is modified, that is, the way to activate the proteins is modified.
It is not easy to explain how it happens. Receptors are found outside the cell. When joined, the dimer or trimer of the protein is formed.

It was surprising to discover what few genes exist in the human genome. Human physiology is very complex, but there are few genes. On the one hand, the complexity is due to the flexibility of these genes, that is, to the possibility of each of them generating different proteins; on the other, to the systems composed of a large number of proteins --the same group of proteins works with several components at different times and in different cell locations.
I think we are in the first steps. To advance in proteomics it is necessary to have a cellular functioning model, that is, to investigate the biology of the systems. To understand the functioning of proteins at all levels it is necessary to develop an appropriate model, an important challenge. Currently the information is not complete.
If you block any pathway of metabolism, the cell will advance another way. The knowledge between proteins is very varied and interconnected. Therefore, it is a very complex system, like a network of electrical cables, but very complex, with many switches at many points. Even if you've turned off a switch in one place, it's not sure you've turned off a point in the network.
There is the possibility of a reductionist approach, since it is also necessary to define all the components. But then you have to join all these components and then analyze what is happening in a certain cell, at a given time.
We are trying to develop new drugs from modern structural biology. We wonder how we can use information about the structure of proteins, not only to design new proteins, but also to find new drugs.
At Cambridge we have created companies to apply methods developed over the years in the design of anticancer drugs. That is the most interesting thing today in my research.

Many times we look for proteins that we know beforehand and that may present defects, enzymes and receptors in general. Errors are due to overexpression or mutations, which in some cases produce cancer. They are often a good starting point. If we understand the activity of these proteins in the cell (for example, if we understand interactions with other proteins), we can design new molecules to have a chemical link with them. We also collaborate with physicists, chemists and biologists.
In my company, at ASTEX, we selected important cell cycle proteins and designed anti-cellular molecules. We are already conducting clinical sessions with molecules, we have put in project 100 million dollars and we will get another 1,000 million collaborations with other companies. Therefore, there is an interesting relationship between basic science and its application in biotechnology.
Of course, I have always studied proteins. The problem is that we can combine all analyses of protein architecture with bioinformatics software to develop theoretical models. These resources are essential for the design of new medicines.
They use databases with data of many proteins, of approximately four thousand proteins. From there we can perform general searches through the computer. Comparing the active protein foci, we select some and use them as models. The truth is that it is not a very good method, it does not have a great theoretical basis, but it helps us to choose some compounds that can be associated with these proteins. Then we tested them in the laboratory, using crystallography and nuclear magnetic resonance imaging to see if they join or not. And in cases where the connection is generated, we can improve this relationship through chemical methods. It is the best way to get anticancer drugs. Currently most companies are working on this strategy.
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