A Quick Q&A with Computational Biophysicists

In Quick Q&A, NLM staff share a bit about why they’re motivated and inspired. We also ask them to add something surprising about themselves.

For our second Quick Q&A, we reached four scientists in the National Center for Biotechnology Information (NCBI) who work in the Computational Biophysics group.

Meet Anna Panchenko and her team: Alexander Goncearenco, Alexey Shaytan, and Minghui Li.

Quick Q&A with Anna Panchenko and Alexander Goncearenco
Question Anna Panchenko, PhD Alexander Goncearenco, PhD
casual headshot of Anna Panchenko casual headshot of Alexander Goncearenco
What is the focus of your NLM research and why is it significant? I study how cellular processes are regulated, how disease mutations affect proteins, and how proteins can specifically recognize DNA and other molecules. The goal is to link genotype with the phenotype, find driving events in disease, and decipher relative roles of mutagenesis and selection in cancer. To do this, we need to discover key relationships between processes on gene, chromatin, and biochemical pathway levels.

We live during the exciting boom in sequencing techniques, a golden era for computational biologists. Yet we might forget to ask important questions if we are too data driven. Disease diagnostics have been improved, but the development of drugs is still lagging behind, mostly because our understanding of molecular mechanisms of disease is behind as well. Genetics and precision medicine can immensely benefit from modeling and complex problem solving of physics and biophysics.

I focus on molecular interactions, particularly in proteins, because their structures tell us a lot about their function and are helpful in interpreting the effects of mutations.

I work at trying to understand mutations and their connection to disease and cancers. I study how mutations appear and what exactly they change in the cells.

What or who inspired you to pursue your career? First of all my parents, who are both scientists. They continue to inspire me by their enduring enthusiasm. As a child I was captivated by the mystery of nature, especially the forest; this must have affected my decision to become a scientist. Throughout my career, I have met several scientists whom I consider my mentors. They encouraged me indirectly by example, with their dedication and wholesome motives. Life sciences always attracted me. I was curious about how things work in living creatures at the molecular level. Advances in genomics inspired me to try for a career change.
How did you get started in your career? I had the opportunity to study with many excellent professors, including my PhD advisor, Prof. Konstantin Shaitan at the Moscow State University in Russia. Their patience and time spent with us was impeccable. After I graduated from the biophysics department, where I studied protein dynamics by Mossbauer spectroscopy, I came to the physics department at the University of Illinois at Urbana-Champaign. In this small town, which is a paradise for scientists, I worked on the light-induced relaxation and kinetics of ligand binding to myoglobin and later on protein folding. Then I came to NCBI, NLM. I started my career as a software engineer and a systems analyst, but then decided to pursue a career in life sciences. I took a postgraduate course at Cologne University in Germany that immersed me into computational biology, and I never looked back.
What really gets you jazzed about science and research? The beauty and complexity of biological systems, and, of course, people. We are very lucky to have each other as colleagues. I think the scientific community is one of the most dedicated groups of people in the world, and mostly driven by our unsatisfied curiosity. What excites me most is being able to reveal simple rules behind complex biological phenomena and making sense of huge amounts of noisy data. I enjoy being around smart people, and NLM/NCBI is a unique place to be.
If you weren’t doing this work, what other profession might you have pursued? It would be nice to be a writer. I cherish the idea of writing more when I retire. I would be in computer science and engineering. Surprisingly, I write more computer code now than when I was writing it as a computer engineer.
Tell us something surprising about yourself. I am continuously surprised by the latest discoveries in biology, physics, and astronomy. These discoveries lead me to learn things about myself that I did not know. I am from a small country in Eastern Europe, the Republic of Moldova, and I speak five languages: Russian, Romanian, German, Norwegian, and English.
Quick Q&A with Alexey Shaytan and Minghui Li
Question Alexey Shaytan, PhD Minghui Li, PhD
casual headshot of Alexey Shaytan casual headshot of Minghui Li
What is the focus of your NLM research and why is it significant? My research revolves around nucleosomes—elementary structures that organize DNA inside living cells.

Apart from helping to compact DNA, they play a key role in all the cellular processes that aim to make use of genetic information encoded in DNA.

We use molecular modeling and bioinformatics methods to understand how nucleosomes function and how variations in its structure affect gene expression.

I focus my research on developing and applying computational biophysics-based and bioinformatics methods to explore the mechanisms of molecular recognition in biological systems.

To do this, I identify functionally important missense mutations (a genetic change that results in the substitution of one amino acid in a protein for another) and build the connection between genotype and phenotype.

Missense mutations can render proteins nonfunctional and may be responsible for many diseases. The analysis of the effect of missense mutations on proteins and their complexes can give us clues for identifying important missense mutations and understanding the molecular mechanisms of diseases that will facilitate their treatment and prevention.

There has been a rapid development of genome-wide techniques in the last decade along with a significant lowering of the cost of gene sequencing, which generated rich and widely available genomic data. However, the interpretation of such genomic data as well as predicting the association of genetic variations with diseases and phenotypes still needs significant improvement.

What or who inspired you to pursue your career? I come from a family of scientists, so a career in R&D [research and development] was on my priority list from early childhood. The love of mathematics, physics, and chemistry, and a high school teacher inspired me to pursue a career in science.
How did you get started in your career? I did my PhD studies in theoretical physics with a focus on modeling the structure and dynamics of synthetic and natural polymers. I decided to steer my career to research in computational biology by doing post-doc work at NCBI. I started with an undergraduate degree in chemistry and became interested in using computational methods to study protein structure and function during graduate school.
What really gets you jazzed about science and research? The collapse of boundaries between biology, engineering, and computer science open new opportunities in science. This excites me a lot. Science and research give me a way of understanding how the complex machine that is the human body works. Beautiful protein structures and complicated molecular interaction mechanisms always amaze me. How changes in DNA and protein make this complex machine nonfunctional inspire my greatest curiosity.
If you weren’t doing this work, what other profession might you have pursued? I might be doing experimental work in the field of synthetic biology. Film director.
Tell us something surprising about yourself. I’m fan of 3D printing, so as a side project I developed a plastic model of a nucleosome that I often present to collaborators. Check it out on YouTube. I lost 30 pounds after I came to the United States.

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