How did you get interested in Medicinal Chemistry?

I would describe my interest in medicinal chemistry as a journey. I have always been curious about science, a passion stimulated by my father Demetrio, a naval engineer with a deep love for physics and mathematics.

However, after high school, I was not sure which direction to take, and I even considered programs as different as Biological Sciences, Veterinary Medicine, and Graphic Design. At the very last minute, I discovered the degree course in Pharmaceutical Chemistry and Technology and decided to give it a try. I realized right away that it was the right choice for me.

During my university studies and later throughout my PhD, I met inspiring professors who introduced me first to the potential of small molecules in fighting disease, and then to the fascinating world of computational medicinal chemistry. That is when I truly fell in love with the discipline.

The people we meet along the way can deeply influence our interests and the choices we make, and that has certainly been true in my case.

Where did you have your postdoc position?

I initially carried out a two-year postdoctoral fellowship between the University of Messina and the University of Bari, both based in Italy, working in the research groups of Professors Alba Chimirri and Angelo Carotti, respectively.

Subsequently, I completed a one-and-a-half-year experience at the University of Houston, Texas, under the supervision of Professor James M. Briggs. There, my research focused on using molecular dynamics simulations to investigate resistance-related mutations that affect the efficacy of HIV integrase inhibitors.

What are your current research interests?

I have many! I am naturally a curious and creative person, and these characteristics shape the work we do in my lab. Broadly speaking, our research falls into two main areas.

On one side, we focus on the rational discovery of small bioactive molecules targeting proteins involved in various human diseases, including cancer, neurodegenerative disorders, antimicrobial resistance, and rare diseases. For the latter, we are applying an innovative drug discovery strategy that leverages protein folding interference as a new therapeutic modality to address undruggable or difficult-to-drug targets by promoting their physiological degradation. This approach implements a drugging paradigm called PPI-FIT (Pharmacological Protein Inactivation by Folding Intermediate Targeting), currently exploited by Sibylla Biotech, a company I co-founded. Specifically, we are currently applying PPI-FIT to two different targets: the prion protein, originally studied in an academic context, and a mutant form of AKT1 (E17K), which is implicated not only in cancer but also in a rare pediatric condition called Proteus syndrome. In this latter case, the research is part of a joint effort with the company to explore new therapeutic opportunities. 

And given the curiosity I mentioned earlier, our interests have recently extended beyond human health, and we have opened a new research line in precision agrochemical discovery, applying similar rational strategies to target plant disease proteins.

On the other side, we are developing computational tools to improve chemical and biological datasets by enriching them with curated data and information automatically extracted from patents. This is crucial to ensure data quality and completeness, which are both key to reliable predictions and successful drug discovery efforts.

What do you like best about your work?

What I love most is its dynamism, which aligns perfectly with my enthusiastic and tireless nature. I constantly shift between different roles depending on the situation: I’m a researcher, a teacher, a mentor, a manager. That variety keeps things exciting and always gives me the chance to learn something new. 

I also really value the connection with students, both in my lab and through teaching. It is a two-way exchange that I find incredibly enriching. Watching former students grow, find their path, and stay passionate about what they do is one of the most rewarding parts of my job.

What kind of tasks does your work involve?

The tasks I handle are quite diverse and often shift throughout the same day.

I work closely with members of my lab to plan experiments and analyze data, teach, write articles, and interact with collaborators from other disciplines to coordinate our joint research. I am currently supervising two PhD students working on projects co-funded by companies, one by Innovatune Srl and the other by Sibylla Biotech SpA., so part of my responsibilities includes regular interaction with the industrial partners.

In addition to internal mentoring activities, I have been part of the EFMC-YSN Mentoring Programme since 2021, supporting my mentee through scheduled meetings or whenever they need guidance. 

How did you get interested in Computational Chemistry? 

I obtained a Bachelor's degree in Pharmacy in 2018 from the German University in Cairo, Egypt. Despite coming from a family with no scientific background, I was driven by my passion for science and this is why I decided to move to France to pursue a career in research. During my final year of pharmacy, I was exposed to the world of computational chemistry and in silico drug discovery. This field fascinated me because of its ability to use simulation and computer-based tools for the drug discovery process. This is why I was enrolled in a master program where I gained extensive knowledge in molecular modelling then pursued a PhD in the same field.  

Where and when did you obtain your PhD diploma?

Currently in my third year of PhD at the University Paris Cité and I will obtain my PhD by the end of 2024.

What was the topic of your PhD project?

Nanobodies targeting mGlu receptors as innovative agents for schizophrenia.

What are your current research interests?

Using in silico drug design and molecular modelling for the development of nanobodies to target metabotropic glutamate receptors. Including the protein structure prediction, epitope identification and nanbody re-design or re-epitoping. 

How would you explain what your research area is to non-scientists?

The main idea is to develop nanobodies (which are 10 times smaller than antibodies) to target certain receptors involved in schizophrenia. Using an analogy, one can think of nanobodies as Lego pieces that are already designed to bind to a specific target. The first step is to understand where the nanobody binds and how it interacts with the target receptor, and then try to redesign the nanobody so that it can bind to a different receptor for therapeutic purposes.

What do you like best about your work?

The field of my work is highly evolving, so every day presents a chance to learn something new and apply it to my research.

What kind of tasks does your work involve?

Mostly working on computers, I am focused on modelling the structures of nanobodies and receptors to understand how they bind together. I also conduct simulations to observe their movement and behaviour on a nanosecond scale.

What kind of skills does your work require?

A strong background in chemistry and biology is required to understand the principles of molecular interactions. As well as an expertise in programming and computational methods is crucial for designing and running simulations. But since it is an interdisciplinary field, I strongly believe that anyone who has the will to learn can acquire the necessary skills and knowledge to excel in this domain. 

What do you consider your greatest achievement in your scientific career? 

Still early since I am at the beginning of my career but the day the biology confirmed a hypothesis I suggested using molecular modelling was one of the best moments.

Can you describe why and where you studied chemistry, and your subsequent early career?

I always found chemistry fascinating, since my teens – micrograms of a substance can cure you, or they can kill you, it depends on the compound. That made chemistry really powerful in my mind, and I wanted to embark further into this direction, and learn more about it.

I did my diploma in Frankfurt, Germany, in 2002 in the bioinformatics area (predicting signalling peptides), and my PhD in Cambridge, UK, in the cheminformatics area in 2005, on molecular similarity. Both were excellent choices (not that I knew beforehand though, you often only know afterwards in life!), and I am still grateful to my supervisors, Gisbert Schneider who was then in Frankfurt (I was in fact his first student there), and Bobby Glen in Cambridge, who taught my lots about ‘real-world drug discovery’. 

For my postdoc I joined Novartis in Cambridge/MA, on a Presidential Postdoctoral Fellowship – this meant the ability to work on academic research, but with all resources available in a pharmaceutical company, which was another great experience. It also shaped my thinking about the practical relevance of research until this day, what I do should be applicable in practice, to improve drug discovery. Jeremy Jenkins, Meir Glick and John Davies were my mentors there, who provided a fantastic environment to learn more, about the analysis of high-throughput screening data, as well as high-content imaging data which became very popular around my time there, in 2006/2007. I can really recommend to keep the mind open about academia, big pharma, start-ups (and beyond) – they all have their advantages, and you learn something different everywhere.

Another aspect I find truly motivating in our area of research is its diversity – this can mean diversity from the scientific side (different data types, algorithms, and endpoints); but equally people from different countries, with very different backgrounds. I lived in multiple countries myself as well (at least count I realized I moved 23 times until that stage!), and this is what I always recommend to my students: In science it’s easy to see the world, so go to a new place on the planet, to different science, in your postdoc (or generally next stage in life).

Which of your papers are you most proud of and why?

There are indeed some papers that I quite like and which I am proud of – but for reasons that are maybe not so apparent from the outside. There is a story behind every paper – how the idea was developed, the people you have met and how you met them, and so on. 

The first paper I am quite proud of is from my postdoc times (https://www.nature.com/articles/nchembio.2007.53), on the integration of high-content screening data with target prediction. The reason why I quite like that is that the idea really came about during a postdoc seminar at Novartis, where both Daniel Young (the first author of the work) and myself were postdocs at the time. We met at this meeting where Daniel presented his work from the high-content screening side, I thought ‘hey, let’s add target prediction to this for the mode of action side’, and this is what led to a really nice Nature Chemical Biology publication, which combines a (then) relatively new readout type with a mechanistic angle from computational tools. 

The other publication is much more recent, while I was a PI in Cambridge, on using small molecules for the targeted differentiation of stem cells into a desired cell type, in this case cardiomyocytes (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4979408/). This work was done by Dr Yasaman KalantarMotamedi as a first author, and it was really fascinating that the computer, using data and algorithms, was able to select small molecules that led to a beating cardiomyocyte under the microscope – so in this way we basically generated a small part of the working heart, using the power of algorithms, chemistry, and biology. I still find this study fascinating when I think about it again.

Apart from that science is really often very incremental – you find one answer, and you have five new questions, so I am not sure this really led to me being ‘proud’ of what I did in particular. In other words, “The more you know – the more you know what you don’t know!”. I think to keep the curiosity alive, like when you were young, or in your PhD, this is what keeps science going.

What are the features of a successful PhD student or postdoc?

I think the most important thing in science, but maybe even as a human being, is to keep your eyes, ears, and mind open to what you currently don’t understand, to what other people say, and how other people are – which helps you develop science, but also to understand the whole world better. For example, I started out as a chemist, but during my postdoc with Novartis I was dealing with High-Content Screening Data. I first found the data very difficult to analyse (and I still do!) – but this made me realize how important it is to look at drug discovery (and associated data) across its whole range, from chemistry, to biology and pharmacology, to physiology (etc.) All of those aspects are pieces of the big puzzle of drug discovery.

An open mindset helps in science, but also more generally to learn in life. I was for example quite influenced by my trips to India: I taught in Bangalore, at the Institute for Bioinformatics and Applied Biotechnology (IBAB) for about 10 years of my life, from my postdoc years until quite recently. This only happened since I replied to an email from Karthikeyan, from NCL Pune, a bit before, but it changed my life. If you are in India you notice for example what ‘go with the flow’ means – if 10,000 people want to exit Mumbai Central Station, then you just will be unable to enter. In life of course this means to not fight situations, but to deal with them as they come, to accept how things are. 

The pictures below illustrate those years a bit – during my birthday celebration at the institute (the local tradition is to smear chocolate cake into the face of the lucky boy), as well as on the night train from Chennai to Bangalore. You get actually very good food from the vendors at the train stations, so next time you are in India, plan in a trip on the night train as well.

What is the most embarrassing thing you have done in the lab while doing experiments, e.g. explosions?

I started chemistry actually at home in my late teens – building rockets, and doing other science in what were ‘probably not entirely controlled conditions’. One time a chemical supplier at the time sent me (to my home address!) the wrong delivery containing, among others, elementary sodium. It was too cumbersome, so apparently the supplier thought it a good idea to keep this delivery nonetheless, as a present. The label on the sodium, stored under liquid to protect from oxidation, said ‘do not bring in touch with water’, which… of course, as a teenage boy, is precisely what I did. Generation of sodium hydroxide, as well as hydrogen, and a decent explosion followed. I spent six weeks or so in hospital and nearly got blind as a result (bases cause much more serious damage to the cornea than acids), so I can confirm from empirical evidence: In case you find some elementary sodium at home, for whatever reason, do not bring into touch with water. I have realized that sometime it is just fine to believe what one reads, and not everything needs to be proven in experiment.

What are your recommendations for a book, podcast, website, blog, YouTube channel or film?

As for resources, I can recommend for example Tom Mitchells’ ‘Machine Learning’ for an easy-to-read and very understandable introduction to the field; the blog ‘In The Pipeline’ for developments in and around the pharma area (https://www.science.org/blogs/pipeline), and TeachOpenCADD (https://volkamerlab.org/projects/teachopencadd/) from the Volkamer Lab for an hands-on introduction to the Computer-Aided Drug Discovery Field. I am also editing the Cambridge Cheminformatics Newsletter (http://www.drugdiscovery.net) with jobs and resources in the field which everyone is welcome to subscribe to, and where we organize regular events (also online) for those who are interested in the computational drug discovery field. 

What do you think about the future of your field, AI in drug discovery, and how it applies to the advancement of medicinal chemistry as a whole?

We live in really exciting times currently, be it due to new therapeutic modalities, the amount of data being generated, or the computational and algorithmic power available. From the AI in Drug Discovery angle, I would like to bring some realism to the debate – do we actually have the data available so that the field can live up to its expectations? I think this will be the case in some areas more than in others – for those interested in more details, the Cambridge Crystallographic Data Centre (CCDC) put one of my recent talks online which can be found here, on the topic “Artificial Intelligence in Drug Discovery – Where Are We Today, What Do We Need to Advance Further?”, which may be of interest to the reader here: https://www.youtube.com/watch?v=PrYIChWuUFI. 

How did you get interested in Medicinal Chemistry?

During my Bachelors, I became fascinated by the way in which molecules interact and how humans, using rational design, can purposely modulate their behaviour.

Where and when did you obtain your PhD diploma?

I did my PhD in the lab of Prof. Dr. Stefan Günther (Freiburg, Germany). I obtained my diploma in 2014.

What was the topic of your PhD project?

The research in my PhD focused on implementing and applying computational methods for the identification and characterisation of small molecules modulating protein–protein interactions, in particular bromodomains. As part of my PhD, I deepened my knowledge in virtual screening, cheminformatics, and structure-based drug design among others.

Where did you have your postdoc position?

I did my postdoc in the lab of Prof. Dr. Alessio Ciulli (Scotland), working on PROTACs and targeted protein degradation. I implemented and applied molecular dynamics and structure-based drug approaches to study and modulate the mode of action of small-molecule degraders.

Where are you currently working and what is your current position?

Since mid-2018 I work as a scientist in computational drug design at Roche (Switzerland). I support portfolio projects especially in pre-clinical stage, i.e. from early target assessment up to lead optimisation, covering diverse therapeutic areas.

What are your current research interests?

I am particularly interested in new therapeutic modalities that challenge undruggability, for example in the fields of targeted protein degradation, RNA-targeting, or protein–protein interaction modulators, and in investigating how computational methods such as machine learning, artificial intelligence, and molecular dynamics, can facilitate that.

How would you explain what your research area is to non-scientists?

I work in the early stages of drug development designing molecules with the help of computers. Hopefully, some of those molecules follow their path to clinical trials and, eventually, cure diseases.

What do you like best about your work?

The possibility to work with highly knowledgeable scientists and the constant challenge of innovating new medicines.

What kind of tasks does your work involve?

I use all sorts of computational methods with two goals: first, to study how proteins and small molecules interact and behave, and second, to identify and design new molecules with desired biological activities and appropriate physicochemical properties. For these tasks, I use machine learning, artificial intelligence, molecular dynamics, quantum chemistry, virtual screening, cheminformatics, Free-Wilson analysis, etc.

What kind of skills does your work require?

I believe a computational chemist can benefit the most from combining a wide range of technical and behavioural skills, including programming; a sound understanding of quantum mechanics and non-covalent interactions; machine learning methods, and capabilities for spatial vision and chemical pattern recognition, along with perseverance, curiosity, and a good amount of creativity.

What are the features of a successful PhD student or postdoc?

I would say that important features include not being afraid of failure, not getting obsessed with success, not avoiding challenges, and being always open to connecting with other scientists and learning new complementary skills.

What are your recommendations for a book, podcast, website, blog, YouTube channel or film?

I very strongly recommend Derek Lowe’s blog “In the pipeline”, in which he writes mostly about medicinal chemistry topics (https://www.science.org/blogs/pipeline). I also keep myself up to date about the biotech world and the pharmaceutical industry by checking regularly Fierce Pharma (https://www.fiercepharma.com/).

Which scientist do you admire the most and why?

I admire scientists with the ability to communicate science to non-specialised audiences in an accurate yet appealing manner.

Which field of medicinal chemistry do you consider the most promising for the future?

I think that in the next few years we will see drugs in the marked that exploit the targeted protein degradation concept, such as PROTACs and molecular glues, to treat diseases.

What would you expect to be the next major breakthrough in medicinal chemistry?

I expect a revolution in medicinal chemistry by further exploiting artificial intelligence, machine learning, and predictive structure-based drug design approaches.

Where and when did you obtain your PhD diploma?

I obtained my PhD in “Chemical and Pharmaceutical Sciences” at the University of Siena, Italy in the group of Professor Maurizio Botta. It was the beginning of 2017.

Where are you currently working and what is your current position?

I am currently working for the French company Discngine, in Paris. Discngine develops and provides state-of-the-art IT solutions, mainly for customers involved in life science R&D.

The title of my position is “Senior Consultant”, which, even if it does not seem to tell much, is a pretty good description of what my duties are- helping our customers with, well, a little bit of everything!

What do you like best about your work?

There are multiple aspects I love about my work. For starters, it is never boring! I have the possibility to help our customers in many different areas: from designing a custom solution to handling the administration of an application, to give training on various software, to provide scientific and technical support, to suggest and implement new ways for integration and automation… as I said – a bit of everything.

Another aspect I really like about my job is that it gives me the possibility to interact with many smart and talented people, both co-workers and customers. This often results in producing enriching experiences, allowing me to continuously grow.

Finally, it is really rewarding when I see a customer heavily relying on a piece of work I have done, or helped with. It really shows how much important what we do is.

What kind of tasks does your work involve?

See the previous answer for some examples. More in general, the kind of tasks my work involves are all around the ideation, design, implementation, management, and maintenance of custom IT solutions deployed at customers’ sites. All of this without forgetting the “human factors” as engagement and support of the user community.

What kind of skills does your work require?

My work requires a broad range of competencies. Of course, there is the need for a solid scientific and technical base, but that’s not all. Particularly important skills are also in presentation, project management and people management. It is important to have the capability to quickly grasp - and keep in mind - the “big picture”, so that one can better proceed with all the steps I have mentioned in the previous answer. Mental elasticity is finally crucial; not only is the fundamental to understand the needs, but also what is required to adapt a project when it has already started. In a real-world scenario, we need to be prepared to navigate through an ever-changing landscape of possibilities. Be able to steer in time is the key between success and failure.

What are the features of a successful PhD student or postdoc?

That depends on what one intends with “successful”. Success and sense of achievement are strictly personal feelings. Therefore, my answer here is based purely on my personal idea of success – which, in the case of a PhD student or postdoc, is to put themselves in the best conditions to proceed towards what they would like to do with their next steps. Based on such premise, I would say that to be successful they should be able to not think only about science. They should be able to think about their career path, to create opportunities for themselves, to not waste any occasion to interact with other scientists as well as not-scientists. So, translated into feature, I think that I could say: “communicative planner”.

How would you describe yourself as a supervisor?

I think that many of the ex-students I supervised while working at the university would agree on these 3 words: “tough but fair”. I believe it fits.

Which field of medicinal chemistry do you consider the most promising for the future?

The usage of AI-assisted computational methods to reliably predict 3D protein structures.

How did you get interested in Medicinal Chemistry?

I have a MSc in Pharmaceutical Biotechnologies from the University of Bologna. When attending the final year in the program, thanks to some compelling lectures, I got interested in the subject of drug discovery. However, I have to say, It was computational molecular modelling that sold me the discipline.

How did you get interested in Medicinal Chemistry?

It was at the beginning of my scientific career, when I was just a PhD student. I became interested in the interface between chemistry and biology and more concretely and how the, at that time incipient, molecular modelling methods, might contribute to the understanding of the mechanism of action of drugs.

Where and when did you obtain your PhD diploma?

I obtained my PhD diploma in 1982 in the Autonomous University of Barcelona. The topic of my PhD was the study of differential molecular determinants of MAO-A and MAO-B inhibitors using computational approaches.

Where do you work at the moment and what is your current position?

I am currently director of a Research Program on Biomedical Informatics, which is a joint program of the Pompeu Fabra University and the Hospital del Mar Medical Research Institute, located in Barcelona. My current research is focused on the development of new computational strategies and tools serving the biomedical research.

What do you like most in your job? 

The most interesting aspect of my job is its multidisciplinary nature. The projects that we develop and the research team that I lead synergically integrate knowledge and professionals from several disciplines, such as medicine, biology, computer sciences, chemistry and pharmacy.

What kind of tasks your job includes?

As director of a program (a kind of academic department), constituted by more than sixty professionals including ten principal investigators and their groups, I have tasks related with the coordination and strategic guidance of the program, including bureaucratic duties that, as you can imagine, are the less attractive. In addition, I have some direct collaborators within the program, and I develop my own research projects in collaboration with them.

What kind of skills your job requires?

My job requires scientific and human experience and I think that have a lot of this taking into account my age.

What do you consider your biggest achievement in your scientific career?

I am particularly proud of the DisGeNET knowledge resource on gene-disease associations that we have been developing along the last ten years. It has become a worldwide recognized resource with more than 5000 users per month and more than 1000 bibliographic citations.

What is the most embarrassing thing you did in the lab while doing experiments?

Since I use to work in silico (computational) labs, explosions are not particularly usual, but we remember incidents related with floods in the room were our computer servers are located, which were particularly damaging.

Which scientist do you admire the most and why?

I particularly appreciate the history of Paul Janssen and his ability for leading an international pharmaceutical company without abandoning his direct involvement in the successful discovery of new drugs.

Which paper of yours you are the proudest of and why?

The papers that we have published about the DisGeNET resource, for instance the last one recently published in Nucleic Acids Research. I am also proud of my paper in Nature Reviews in Drug Discovery in which we reported the results of the IMI eTOX project on data sharing in predictive toxicology.  

Which field of medicinal chemistry do you consider the most promising in the future?

I am probably biased in this respect, but I think that the computational methods and tools offer great opportunities to medicinal chemistry. In particular, the joint exploitation of the biological, chemical and medical big data is very promising for improving the drug discovery process.

What would you like to ask from other medicinal chemists?

I would ask my colleagues to keep them always open-minded, combining their deep experience in the field of their specialization with a global scientific perspective.

What would you guess to be the next major breakthrough in medicinal chemistry?

Given my current professional focus, I do not have a deep insight on all the facets of the medicinal chemistry. However, I think that the incorporation of the systems biology perspective in the design of new drugs offers interesting perspectives.

This week's #Iamamedicinalchemist is Ana Sofia Newton from Yale University. She enjoys working in a creative environment. Do you think drug design requires creativity?

Find her on Twitter! @AnaSofiaNewton

How did you get interested in Medicinal Chemistry?
I had an interest in Chemistry very early on. I did my undergrad studies at the Faculty of Science in Lisbon. At the time Martinho Simões, a distinguished Physical Chemistry Professor, and Amélia Pilar Rauter a pioneer in Carbohydrate Chemistry had a profound impact on me and my initial directions in research. I became more and more interested in Medicinal Chemistry and decided to do my graduate studies at the Faculty of Pharmacy and develop my knowledge in both Medicinal and Computational Chemistry under the supervision of Prof. Rui Moreira and Prof. Rita Guedes.

Where and when did you obtain your PhD diploma? What was the topic of your PhD project?
I obtained my PhD diploma at the University of Lisbon in 2013. “Design, Synthesis, and Evaluation of Peptidyl Inhibitors for Clan CA and Clan CD Cysteine Proteases.” A big title but basically I applied Medicinal and Computational skills for the development of anti-malaria and anti-neurodegenerative agents. It was pretty exciting and I learned tons.

Where did you have your postdoc position?
My interest in drug discovery and Medicinal Chemistry assisted by computer aided-methods lead me to William Jorgensen’s lab at Yale University. Throughout my doctoral and postdoctoral work, I was particularly interested in being able to apply both computational chemistry and organic synthesis in drug discovery. I knew that applying computational strategies to design small molecule inhibitors was important, but at the same time having a strong synthetic background would allow me to rapidly distinguish computational hits that could be feasibly synthesized from those that would represent a substantial synthetic challenge.

Where do you work at the moment and what is your current position? What are your current research interests?
Currently I work at Yale University as an Associate Research Scientist where I am leading two collaborative research projects to design potent, safe, easily administrated, and long-acting small molecule inhibitors that could reduce or eliminate blood cancer growth and skin cancer. The approach combines state-of-the-art technology for molecular design, synthetic organic chemistry, biological assaying, and crystallographic determination of structures of the designed molecules bound to their protein target.

What do you like most in your job? What kind of tasks and skills your job includes?’
I would say being surrounded by people with a lot of creativity. Also, attention to detail and enormous passion for drug discovery are good skills to have if you want to be a good scientist. Perseverance, working as a group and always pushing the projects forward because you will most likely find a breakthrough.

How many PhD and postdoc students do you have at the moment?
Are you currently looking for a new PhD and postdoc students?
We have 3 PhD students and 4 Postdocs. Currently we have two Medicinal Chemistry Postdoctoral positions open. They will work in close collaboration with experts in computer-aided drug design, biological assays, and protein crystallography.

What are the features of a successful PhD student or postdoc?
Strong organic and medicinal chemistry bench skills, good interpersonal skills, flexibility, and the ability to work well within an interdisciplinary team environment.

Which scientist do you admire the most and why?
I suspect the expected answer would be Sir Isaac Newton. The brilliant British mathematician and physicist is definitely among my top choices. For Newton, all there was in the world was matter moving. His equations are so effective we still use them today. However, Albert Einstein proved that time and space are shaped by matter. He could take a hard, physical problem and boil it down to a powerful visual image, a thought experiment. A creativity process that very few are able to achieve.