By Nicole Zatorski

Dr. Filizola is the recipient of an endowed chair, the Sharon & Frederick A.
Klingenstein-Nathan G. Kase, MD Professorship, and the Dean of the Graduate
School of Biomedical Sciences. She is a dedicated leader in computational
biophysics of membrane proteins with over 20 years of experience in the
application of methods of computational and theoretical chemistry to biochemical
and biomedical problems, as well as to rational drug design. Dr. Filizola’s
research program is mainly focused on G Protein-Coupled Receptors (GPCRs),
which are the targets for about half of all currently used drugs. 

Could you please share what inspired you to go into your field?

Mostly because of inspiration from teachers or mentors and the love for the topic.
I found it very interesting. It was fun to work on it. Since I was having fun I stuck
to it.

I can tell you about the love for chemistry first. It was because of my high school
teacher. She was a very tough woman and very knowledgeable about chemistry.
I loved the way she taught and I found what she was explaining very inspiring
and stimulating. This is the reason why I took chemistry in college. So I did an
undergrad in chemistry in Naples, in Italy, where I lived.

The reason I took computational chemistry is a little bit more convoluted. I started
as a crystallographer. I was interested in a lab in Naples that was very strong on
peptides. So I did my Master’s thesis there on elucidating the effect of solvation
on the conformation of peptides by X-ray crystallography. After this I started a
small internship in Barcelona, Spain. I was supposed to be there for 6 months to
do my crystallography training on proteins, but then I got to meet a faculty who
had been working on G-protein coupled receptors (GPCRs), using a variety of
computational methods. I found the topic fascinating, and I started working with
him. At the time there were no crystal structures of GPCRs. There was an
electron density map of rhodopsin obtained from electron microscopy studies of
2D crystals, not even a high-resolution map, literally a 2D projection of 7
transmembrane helices on a paper. So we used geometric measurements to
characterize the relative position of these helices and built an algorithm that
would produce a 3D atomic model of the 7 helices automatically. This was the
main topic of my PhD thesis.

It was slightly after I wrote my thesis that I joined a lab here in the United States.
They were also interested in GPCRs, in particular, opioid receptors. They were
using different computer-aided approaches, from ligand-based to structure-based
drug discovery approaches. I had been exposed to the structure-based
approaches through my PhD, but I had no idea about cheminformatics tools for
small molecules. I started to be very interested in this type of research and the
passion arose from this incredible female mentor I was working for. She was very
inspiring. She was a tough woman, incredibly energetic, and she could really
transmit the love for the discipline. So I became passionate about opioid receptors, and how to develop improved drugs at these receptors using ligand-
based and structure-based drug discovery approaches.

Do you see chemistry and computational chemistry as different fields?

I see them as different fields because when I talk about ‘chemistry’ I mostly mean
analytical chemistry, biochemistry, or any other experimental subdiscipline that
requires the use of pipets and things like that. In the moment that I became a
computational chemist I did not use any pipets at all. My lab is a completely dry
lab and we test our computational predictions through collaboration with various
experimentalists.

Do you think it is easy to jump between fields in science or do you think it
is very stratified and hard to make a transition?

I don’t think so. I think you have to follow your passions. And if there are things
that interest you, you have an obligation to explore. And maybe you explore a
field that seems cool from the exterior but then when you get involved you
become easily bored. To me, structural determination by crystallography was
cool when I started it, but I became immediately more interested in its
applications to proteins. Nowadays it is not even crystallography that excites me
the most.

What nascent technology or techniques do you think have potential for
future scientific research?

I definitely think cryo-EM has good potential. Don’t get me wrong, I don’t think
that any one technique in isolation does anything. Cryo-EM combined with
computational methods for instance or with functional assays or other biophysical
methods can actually be pretty powerful. You might have seen a new structure of
the mu-opioid receptor bound to the G protein and solved by cryo-EM. There are
new cryo-EM structures of this opioid receptor solved by Kobilka and Skiniotis
labs that show small molecules bound in the receptor. The atomic resolution in
these binding pockets, however, is still not very high to unambiguously
characterize the interactions of small-molecules with the receptor. But if you
combine this information with computational methods, for instance, some
molecular dynamics simulations, you can see if the predicted binding mode of the
small molecule based on electron density is a stable pose or not, and then, you
can really tell a story.

If you could find out the definitive answer to a scientific question, what
would be the question?
It all depends on what you are studying. I guess the problems that I am
interested in are so complex that it is difficult to find one single question and one single answer for it. I also don’t think you can have one simple answer or one
single way to address the same question. If you are trying to tackle a question
with one single technique you will see only one aspect of the whole thing. It is like
the parable of the ‘blind men and the elephant’, where each blind man, who has
never come across an elephant before, feels a different part of an elephant’s
body, and tries to conceptualize what the elephant is like based on the small
parts they have touched, like the nose or the tail. It all depends on perspective.
It’s the same thing with these techniques. For instance even for experimental 3D
structures of GPCRs you see a nice picture but then how do they really activate
other proteins in the signaling cascade? What is happening there? What are the
dynamics involved? You don’t know, and not even molecular dynamics, in
isolation, will tell you the entire story about that.

What advice do you have for scientists that are beginning on their research
journey?

Well, to follow their passion and have fun. I see more anxiety in the new
generation going into science and I wish that they would just try to enjoy what
they are doing. The joy of starting an MD/PhD or a PhD program comes from
what you see around, from the environment you are in. If it is as intellectually
vibrant as here at Sinai, then you can make the best out of your experience, and
even if an experiment goes wrong, you have learned a lot out of it. So just follow
your passion and complement it with life outside the lab, because it is good to
have a healthy, social life, in addition to your scientific passion.

Students nowadays are a little bit too anxious, you know. You would like all the
experiments to work, you don’t know what future holds, whether you are going to
find a respectable position, etc. When I started, I was perhaps naïve. I was not
thinking about what is going to happen five years from now; I was thinking: what
am I doing right now, and am I enjoying it or not. I think that takes off a little bit of
anxiety. I also think that it is wrong to define success by only certain parameters.
In my time, I was not even thinking of being successful as a goal. For me, it was
having fun with what I was doing.

And speaking of that sort of balance, outside of research what things
excite you or interest you?

I like to travel when I have the opportunity. I am starting to plan my trip for my 50 th
birthday, that is two years from now, and my family and I are considering Japan
so we’ll see. Japan or Australia we haven’t decided yet.

Also, what is your favorite place in NYC and why?

There is no specific place. Its just going around the city and benefiting from the
vibe that you get from this crazy but exciting place. I love New York: the fact that
it is always lively, that you always see people in the streets, that you just walk
around and see humanity in action. This already makes New York worth living in.
In terms of museums, I like the MOMA a lot, although there are many worth going to. If you are feeling a little tired or upset at work or in the lab, you can just
go across the street, to Central Park, and enjoy the surroundings. Try it; it’s
great!