Twenty First Century research is all about leveraging the advances in computational power and computer-assisted drug design (CADD) to create or mimic specific biological functions.
Suhasini Iyengar, our next pathbreaker, Final Year PhD Candidate at the Ondrechen Research Group at Northeastern University (Boston), uses Computational Chemistry to solve problems related to neurological disorders like Parkinson’s and Alzheimer’s.
Suhasini talks to Shyam Krishnamurthy from The Interview Portal about her team being selected in the top 20 teams based on computational results that screened potential drug compounds out of a billion compounds against the SARS-CoV-2 virus.
For students, embrace the reality that nothing might go exactly according to your plan. You will eventually get to where you envision yourself to be and appreciate every milestone that made it possible!
Suhasini, what were your growing up years like?
As a kid, I was captivated by the wonders of science. My family is full of scientists, so it’s no surprise that I too wanted to become one. My love for science was ingrained in me from the very beginning. Thanks to my parents who were physicists and biologists, chemistry seemed like an exciting adventure! I have always been fascinated by atoms and molecules. My father, a physicist, works as a Scientist with the Government of India at Bhabha Atomic Research Center (B.A.R.C), Mumbai and my mother, a chemist/biologist, is a passionate educator. Both served as excellent mentors and played a huge role in shaping my career in science. I never really went to any “tutoring” classes, which I am super grateful for, because I was taught by my parents well into high school. That gave me enough time to learn and have other hobbies.
The ideology was simple, they let me learn everything by myself until the 8th grade and from 8th to 12th , I was put to the test quite often! One thing my parents taught me early on was, no matter how many reference books, or notes we have, nothing beats the notes we make ourselves- and I mean putting pen-to-paper kind of notes. As a PhD candidate, even today I make my own notes when I have to research a complex topic. During one of my candidature exams, the Professor was impressed by how well my answer sheet was organized as if it were my own notes!
The advantages are multifold:
1) everything is in one place with references so you can go back and read it whenever I need to,
2) you understand and learn better when you write, and it gets engraved in your brain better than when you are just reading,
3) you learn to organize complex pieces of information into easier ways by using tables, figures or even charts and infographics.
I was naturally attracted towards science as a kid, but the decision to get a PhD wasn’t until later in my life, when I got my first taste of research during my master’s at the Institute of Chemical Technology (ICT). It was here that I discovered an interest and passion for Computational Chemistry which would later lead me down a path towards becoming a scientist while also opening up many other opportunities within science itself ! After my master’s, it was clear to me that I wanted to pursue a PhD in Computational Chemistry because I had a new-found passion and so much to learn about this field.
What did you do for graduation / post-graduation?
I obtained my bachelor’s degree in Chemistry from Mumbai University in 2014 and a master’s degree in Chemistry from the Institute of Chemical Technology, Mumbai (ICT) in 2016. It was a thesis-based master’s program, and we had the option to choose a lab based on our first two semester grades. Fortunately, I got to be a member of the Joshi Lab, which was my first choice and thus began my journey in the field of Computational Chemistry. Being a beginner in those topics with very little experience under my belt was intimidating. Though I initially stumbled in Computational Chemistry, it became one of the most exciting fields for me. Reading Albert Einstein’s words, “A person who has never made a mistake, has never tried anything new”, gave me the motivation to take on something that was outside of my comfort zone!
What were some of the influences that led you to such an offbeat, unconventional, and unusual career?
Here’s what led me into choosing something that was entirely new to me. I believed I could do it! In 2014, I was getting my thesis-based master’s degree in Chemistry from the Institute Of Chemical Technology, and that’s when I chose to step into a project in the field of Computational Chemistry to get my degree. It was nerve-racking because:
- I had no prior experience in the field whatsoever. There was a steep learning curve, from learning the basics of computational chemistry to submitting complex calculations and analyzing them to write a thesis!
- I barely had six months to a year to learn the basics, complete the project and thereby my degree.
But it taught me some of the greatest lessons in my life!
- I worked hard to learn the basics and failed a few times. But I was confident in my ability to overcome those failures and move forward. It made me resilient.
- I understood that it’s never too late to start learning something new. The best time to learn new skills is the moment you decide to try something outside the box.
- I recognized my comfort zone to be a limiting factor. The moment you step outside the so-called “comfort zone”, growth happens. You might succeed or you might fail, but either way, you end up learning something!
I often get messages on LinkedIn from undergrad/ master’s students asking me how I knew computational chemistry was the right way to go? My answer? I didn’t. All I knew going in was that I had a genuine curiosity to do something different compared to what everyone else was doing at the time. Personally, I knew that I didn’t want to be in the lab all day doing experiments, I wanted to solve the same problems, just using a different approach. And I was okay with facing a few failures. (And I sure did, a bunch of times!). But that gave me the courage to pursue a PhD in the same field. Had I not been willing to take that risk, I would’ve never found out my passion for Computational Chemistry! Did everything work out the way I wanted to? Absolutely not! Science rarely does. That’s the beauty of science. But it made me a better scientist for sure. My two cents for someone interested in getting started in this field is to try it for yourself. Take it one step at a time, you don’t have to have it all figured out!
Do an internship or a summer project. Worst case, you’ll end up making mistakes or realize you love being in the lab! Either way you’ll learn something new.
Looking back, that has to be one of the best (and easiest) decisions I’ve ever made in my life! And a huge part of this was my advisor, Dr. Kaustubh Joshi who had faith in me that I could succeed, sometimes even when I didn’t!
How did you plan the steps to get into the career you wanted? Or how did you make a transition to a new career? Tell us about your career path
In high school, I bid goodbye to biology and took computer science instead. This was one of the earliest decisions, I would say, that shaped my career as a computational chemist. At the time, I didn’t even know such a field existed. I would say my career path was pretty straight forward up to this point, though I have been creative with my choices. After I finished my bachelor’s with distinction, I was admitted into three different colleges for Masters in Mumbai, Ramnarain Ruia College and Institute of Science where I was planning on pursuing Masters in Analytical Chemistry, and Institute of Chemical Technology where I was planning on pursuing master’s in General Chemistry but with a thesis-based master’s program. I decided to go to the Institute of Chemical Technology, for a thesis-based master’s program. This was the second decision that helped shape my career.
Institute of Chemical Technology (ICT) in Mumbai, is accredited by the Royal Society of Chemistry and is known for its excellent research facilities. The coursework at ICT is very meticulous and unique, as it is revised regularly to keep pace with current research . This led me to utilize the library and refer to scientific publications on a systematic basis. To learn more about the fundamentals, I opted for an elective course on Computational Chemistry, which consisted of theoretical knowledge of the subject as well as hands-on experience of carrying out molecular simulation-based problems. This course also introduced me to programming in Python. Working on various group projects helped to develop my skills in teamwork and leadership. We were also required to prepare presentations as a part of internal assessments, which enhanced my communication and oratory skills. Moreover, during the program, I attended various international symposia conducted by the American Chemical Society and the Royal Society of Chemistry. The didactic curriculum, industrial visits and endowment lectures provided by the Institute gave me an opportunity to interact with experts from different fields, which helped me to develop a broader mindset. This experience opened my eyes towards scientific research as a career and around this time, I decided that I would get a PhD in the United States.
In the second year at ICT, I had the opportunity to complete a major part of the program, the research project, under the guidance of Dr. Kaustubh Joshi. The project titled “Mechanistic and Docking studies of Heterocyclic sulfones and exploring them as potential non-nucleoside reverse transcriptase inhibitors (NNRTIs)” was a Computational Chemistry based research project, which deepened my interest in this field. It explored the mechanistic pathways for the synthesis of heterocyclic sulfones based on quantum chemical approach using density functional theory and their subsequent use as potential non-nucleosidic reverse transcriptase inhibitors by means of molecular docking approach. The project also dealt with understanding of solvent effect on the involved SNAr mechanistic pathway, variation of nucleophilic and electrophilic nature of the reactants in different reaction conditions, studied through global reactivity descriptors and theoretically calculated 13C NMR spectra data analysis. Molecular docking study helped to reveal heterocyclic sulfones as an important pharmacophore in search of potential NNRTIs. One of the main challenges that I faced during this project was to locate the transition state structures, important to determine and confirm the mechanistic pathways. Exhaustive work with the scan function helped in resolving this issue. This research project taught me the process of planning and constructively interpreting both positive and negative results obtained from the simulations.
I graduated from ICT in 2016 and continued to work as a Research student in the lab while working on my GRE prep and application for my Graduate school admission in the US. Keeping in mind that I would be an international student in the US, I started the process by looking into the different labs I was interested in joining, before looking at the schools. Because I believe that the lab culture and the PI (Principal Investigator), in some ways matter more than the actual science happening in the lab. Once I was able to narrow down my list, I further divided it into sets of easy, moderate, and ambitious, based on my research , my GRE scores and other criteria. It was a standard application process. I took the GRE (Graduate Record Examination) exam (by preparing myself, didn’t go to any coaching classes, just took a lot of practice tests) and TOEFL-Test of English as a Foreign Language which is an additional exam testing our proficiency in English. Once I was done with the tests (I had a decent score in the GRE >300 and an above average score in TOEFL), I started applying for the schools on my list. I read through their websites, looked for labs that I was interested in, read their papers (that I could access) and was proactive in introducing myself as a prospective student, and I believed that helped a lot! I portrayed my passion for the field of Computational Chemistry in my personal statement (which is a part of the application package) and made sure that I contacted the professors whose labs I wanted to join. Finally, after I got fully funded admits with Graduate Assistantship from three top universities, University of Cincinnati, Kansas University and Northeastern University, I chose to go to Northeastern as it is situated in Boston, a city that is the hub for education and Pharma/Biotech, without realizing then that I would somehow end up in the Biochemistry research sector.
The first year in Boston (during 2017 – 2018) was a challenge. Being far away from home for the first time, in an entirely new country, adjusting to a new culture, making new friends, taking graduate level courses, and teaching undergrads for the first time, was challenging and fun! After a year of making mistakes and learning from them, I was at one of the well-known labs of Northeastern University, Boston! One thing I learned the hard way is that until we make mistakes, we never grow. To taste success in life, we must have a sip of failure first, it makes success taste even better! Here is how I failed in my first year: from choosing the wrong courses, to switching labs after 6 months of working like a maniac, but each mistake has taught me some of the most valuable lessons in my life. I’ve always believed in a quote by Steve Jobs- “You can’t connect the dots looking forward, you can only connect them looking backwards. So, you have to trust the dots will somehow connect in your future. You have to trust something – your gut, destiny, life, karma, whatever”. Every year of my PhD program has been different, and of course in 2020, the pandemic hit. Since my lab was a computational lab, we were still able to continue with our research, in fact we even started a new COVID-19 project that I am currently leading. So now, after almost five years, when I look back, I realize that my dots did connect perfectly. Every event that happened in my (academic) life has helped me reach where I am today, and I try to be grateful for that every single day of my life!
How did you get your first break?
I would say my first break was getting into ICT, Mumbai. The master’s program at ICT only has 20 seats (8-open category, 12-reservations) and they have their own entrance exam. I wanted to get into Indian Institute of Technology, IIT for my master’s but missed it by a few points as Iam from the open category. Even though I didn’t get into IIT, preparing for IIT-JAM (Joint Admission Test for Masters) , helped me crack the ICT entrance.
The second break was when I was able to get into the lab of my choice at ICT for research in computational chemistry !
What were some of the challenges you faced? How did you address them?
Challenge 1: After I enrolled at Northeastern, I joined a lab that was just starting, with me as potentially the first graduate student. The first two semesters were hectic as we had to teach during the day and take courses during the evenings. Apart from this, finding time to do research was getting difficult when I was expected to do much more. I wrapped up my work, published a collaborative paper with my results  and started looking at other options. I had to make a choice, either choose a different lab, or leave the program. I chose to rotate in a different group and found my current lab, the Ondrechen Research Group and I couldn’t be happier.
Challenge 2: One of the most stressful and hectic months in my entire academic life was my second year at Northeastern, July 2018, when I had to pass my PhD candidacy exams. We were given the topic exactly one week before the exam (Wherein if I failed, I’d get a one-way ticket back to India that would have shattered all my dreams) ! Sounds scary, right ! I was scared as well, but passing those exams in minimum attempts is an experience I will never forget in my life. It made me believe in myself.
Challenge 3: When I started my PhD journey, I had not accounted for a full-blown pandemic to mess it up. 2020 started off with uncertainty around the COVID-19 pandemic and I embarked on a side project involving the SARS-CoV-2 virus. This project was a massive success, and we received funding from the NSF (National Science Foundation) within a week of our application, to recruit undergrads as a part of the REU (Research Experiences for Undergraduates) program. We were also able to take part in a challenge that was aimed at screening a billion compounds against COVID-19 targets and were one among the top 20 teams selected worldwide.
Where do you work now? Can you talk about your role as a Computational Chemist?
I am currently a final-year PhD candidate at the Ondrechen Research Group at the Department of Chemistry and Chemical Biology at Northeastern University, Boston.
My PhD research involves using Computational Chemistry to solve problems related to neurological disorders like Parkinson’s and Alzheimer’s [1-3], develop novel therapeutics for COVID-19 (paper just submitted) and structural genomics .
We use homology modeling to build a 3D structure of the target followed by electrostatics-based site prediction methods and ligand library docking to design PET imaging ligands for Metabotropic Glutamate Receptor Subtype 2 (mGluR2 and mGluR4)-which belong to class C G-Protein coupled receptors-for imaging of the brain. Predicted compounds are synthesized and tested in vitro and in vivo by our collaborators.
So far, this work has resulted in three candidate compounds with high affinity and excellent selectivity over other mGluR subtypes and thus are potential PET imaging ligands for mGluR2 and potential drug candidates for the treatment of CNS (Neurological) disorders.
The COVID-19 project is the study of predicted secondary sites, such as allosteric sites, exosites, and other interaction sites, in addition to the known catalytic sites in target proteins. Thus, this work has the potential not only to discover new antiviral compounds, but also to improve understanding of how the viral proteins work, which is also important for all the future outbreaks.
The structural genomics project involves the prediction of the function of protein structures of unknown function, but with a new twist: This project seeks to identify the biochemical roles of individual, catalytically active amino acids in a protein structure. We use computed electrostatic and chemical properties of the individual amino acids in a protein 3D structure to distinguish between a glutamate that acts as a nucleophile and one that acts as a proton donor, for instance. We are looking for patterns in the electrostatic data to see if we can predict them using machine learning. In collaboration with a computer engineer, we use machine learning to classify large sets of labeled data from proteins of known function, so that the knowledge can be applied to protein structures of unknown functions. This is especially exciting because many Structural Genomics proteins bear little resemblance to proteins of known function. The ability to identify the biochemical roles of active site residues can provide some clues about biochemical function for newly discovered proteins.
What’s a typical day like?
Every year, my day has been different, but this year it looks like this-
- 5 am- Get my caffeine and go to the Gym from 6-8 am
- 8 am- Start working on my thesis- Reading literature, Writing and making Mind Maps when I get too confused
- Get to campus around 9.30 am- Start the day by answering any emails
- 10 am- Start thinking about what I need to get done for the day, meetings, presentations, reports and make a checklist of things to do
- 9-7 PM -Depends on how my day goes, some days are research-heavy (TROUBLESHOOTING, coding, Linux computing, building models, Docking, Molecular Dynamics, helping undergrads or other grad students) vs reading/writing- heavy (Finding relevant papers and organizing it, reading through the lit, writing reports for collaborators)
- Back home-7 pm- Chill, and then back to work on the thesis!!
The most important thing about graduate school is that YOU get to create Your Schedule, the trick is to be as organized as you can be.
What are the skills needed in your role?
To answer the question about skills, I’d say, any technical skills can be learnt during the PhD program. Here’s what set me up for success in my field:
- Curiosity and the urge to do something different from everyone else, which was experiments all day long!
- Willingness to learn
- Creative person in general- wanted to bring that to chemistry
- Interest in solving real world problems
- Rising to the challenge even after failing multiple times
The best part about my position is that I get to learn from and teach wonderful undergrads and masters students who join our lab! I was just awarded the Graduate Student Scholar Award by the American Chemical Society for Leadership in Mentoring. Mentoring is something that’s very close to my heart. I completely believe that we rise by lifting others, and I strive to help people every day. From training REU students during lockdown (2020), to talking at a virtual panel in July 2022 about leveraging molecular modeling skills for graduate school applications, organized by Schrödinger, mentoring has played an important role in my PhD life.
How does your work benefit society?
When I joined my PhD program, my passion was to solve complex real-world problems. And then in 2020, the COVID-19 pandemic hit, which none of us had accounted for. I took the first SARS-CoV-2 structure deposited in the Protein Data Bank and started a virtual screening experiment with the first antiviral compound library I could find. When I saw the virtual screening results, I was excited to see some good binders and I consulted my advisor, Dr. Ondrechen and we developed the COVID-19 project. Little did I know when I started my own endeavor that a few months later we would be awarded an NSF-RAPID award for the project with the help of some of my preliminary calculations. We just submitted our computational predictions to Frontiers in Chemistry for their special edition, “Women in Computational Chemistry”. Given the heavy toll that COVID-19 has taken on human lives and health, as well as the serious social and economic impacts, there is an urgent need to learn as much as possible to characterize the components of the SARS-CoV-2 virus and how these biomolecules function. Some new insights into the functioning of three viral proteins emerged from our work. The project uncovers key interactions with nearby amino acids that facilitate the functional roles of the catalytic residues. New, possible, and functionally important binding sites were found, together with sets of potential ligands that could serve as chemical probes or inhibitors. This work expands on the current knowledge of the biochemical activity, and potential approaches for control of SARS-CoV-2 protein targets.
Can you explain the benefits of Computational Chemistry based approaches over traditional approaches?
Innovative approaches using computational chemistry deliver proven results, particularly in the areas of lead identification and optimization, as the drug discovery process is increasingly under pressure to improve efficiency. Computational chemistry provides insights into the biological activity and interactions of molecules across a variety of target classes, allowing the identification of new candidates that would otherwise have been overlooked. Using the computer in this way saves hours of lab time or millions of dollars in wet screening costs in the case of High Throughput Screening (HTS). While the goal of creating one molecule in silico that then becomes a drug is still far off, new computational techniques like those developed by several companies like Schrödinger, BioSolveIT, OpenEyeScientific, DeepMind and Cresset have a significant impact on the discovery process.
It is time to reinvent the traditional image of a chemist in everyone’s mind- a cartoon image of a chemist standing amid boiling, fuming beakers and test-tubes in a chemistry lab that is filled with dangerous chemicals. Many twenty-first-century research chemists are likely to be seen in front of huge computer screens creating vivid three-dimensional images of a new compound. These researchers may employ computer-assisted drug design (CADD) software that incorporates computational techniques to create pharmacophores, which are collections of generalized molecular features linked to specific biological functions. Scientists may also have access to sophisticated molecular modeling software for creating virtual designer molecules such as drug candidates or catalysts that could accelerate chemical compound production. In the last two decades, computational power and software have advanced to the point where mathematical models can create three-dimensional structures of molecules as complex as novel proteins and link receptor structures to drug candidates. Chemists can work “in silico” using computational techniques to perform virtual experiments to narrow their choices for the ideal drug or catalyst before moving into a “wet” laboratory to test the designs. Is computational chemistry a reliable guide to the properties of new compounds? According to the research and development results of every major chemistry and biochemical laboratory, it is.
Tell us an example of a specific memorable work you did that is very close to you!
For the COVID-19 project, we were also able to recruit seven undergrads, with funding from the NSF-REU program during the lockdown. All of us formed the NUWAVE team and took part in the Joint European Disruptive Initiative (JEDI) Grand Challenge for screening a billion compounds against SARS-CoV-2 proteins. This was one of the best experiences I had as a team lead where I was able to train graduate and undergraduate students to run molecular docking simulations on Glide with several ligand libraries and analyze the results which resulted in our team being selected to the top 30 teams for scientific review and to top 20 teams whose computational results are going to be studied experimentally (Stage 2), from around 130 teams that participated worldwide. Some of our predicted compounds are being synthesized in the US and Europe (Stage 3).This was one of my first experiences conceiving a successful project and seeing it to the very end!
Your advice to students based on your experience?
I am going to break this down into different parts:
Choosing a PhD advisor:
Having changed graduate labs myself, I am now able to answer this question after almost four years. But I wish someone had told me this back then.
This is one of THE MOST IMPORTANT relationships in your life, so it might take you a while to figure out what works best. And it’s totally OKAY to walk away from a lab that doesn’t align with your goals and your values. It’s ultimately up to you. You always have a choice.
Identify potential advisors whose research aligns with your field of interests and always have more than one lab that you are interested in joining! Some universities have an option of “rotations”. This helps in figuring out whether the lab environment works for you without having to commit to anything. If the university you are enrolled in has lab-rotations, try it out. It helps you figure out the lab culture, interact with the current students in a more meaningful way, discuss more about the research going on in the lab while evaluating if it is a good fit for you or not.
One of the most important things which seems to be obvious is to see if you are interested in the PI’s research. Before you commit your time to work with a PI, talk to them, get to know the various ongoing projects in their group and do some background research (read their publications, research the kind of collaborations they have) on the PI’s area of expertise and see if it aligns with your interests and more importantly ask yourself – “Does the field of research by PI / team excite me?”- You’ll be working on this for a reasonable amount of time, so it’s essential to be excited about the research and own it!
Talk, talk, and talk to the current lab members, offer to take them for a cup of coffee to have a casual conversation about the lab environment and the PI’s involvement in every student’s research. They will always have tips for new grads, because often people are willing to help you. You just have to ask.
If possible, try to figure out the PI’s reputation in the department. Some students are comfortable working with a PI who is more experienced but might not be able to dedicate as much time to his/her students, while some may be comfortable with a PI who is more involved. Again, talking to current students and asking them about their advisor’s involvement is a good idea here.
One other thing to keep in mind is that when you join a new lab and are about to graduate (in about 5 years), the PI is also up for tenure. Hence, this might put you both under a lot of pressure. Some people like working in that environment, some don’t . You just need to think about what works for you and what kind of external environment brings out the best researcher in you.
Research to see what the graduated students of the PI are doing currently and if they are placed in good positions. While the PIs do not get involved in their student’s career, their guidance counts a lot and ultimately you want to build a good name for yourself while working with them, and this in turn helps build your network even outside the lab in the form of meaningful collaborations which comes in handy when applying for future jobs or Post-Doc positions. Keep in mind that a PhD is more than just getting a degree and getting out. So, keep an open mind to get more out of your rapport with the PI and the committee than just a higher degree!
General PhD Advice:
- Communication skills, both writing and speaking are underrated. If you need help with something, you need to have the courage to ask, and ask the right question to the right person. This is where building a network of peers, professionals and mentors is critical.
- PhD can become very isolated very quickly, therefore finding your “tribe” is equally important.
- You have to be responsible for your own deadlines and be able to manage time effectively. Being a PhD student/candidate comes with a million other responsibilities apart from just doing research. Being able to manage your time and work within personal deadlines is an important thing to learn during your PhD.
- You will need help, a lot of it. Be ready to ask for help when you need it. Getting stuck while doing a PhD is not uncommon, so by cultivating a habit of asking for help when you need it will help you from getting overwhelmed. Also, having a support system for times when things are rough helps a lot. Find your tribe early into the PhD and stick with them till the end!
- Every PhD (even the ones from the same lab) is different. Try not to compare yourself to someone whose project is going well (or not so great). Every PhD is a personal journey, and everyone starts from a different place in their lives, comes into the program with a different set of experiences. By comparing yourself with someone who got their PhD in X years with Y papers, you’re only hurting your mental health. Be patient with yourself and understand that every result- positive or negative-is a learning experience.
- Your interpersonal skills will get you that industry job, not just the technical skills. Technical skills are important, no doubt. But getting a PhD means you are a master of learning. And that means, if given enough time, someone with a PhD can learn anything. So, when it comes to two candidates who have the same set of technical skills, the interviewer goes with someone who’s easy to work with, who has good people skills ( communication-verbal and non-verbal, empathy, teamwork, listening). Making sure that you develop that during the PhD years will go a long way.
- Seeking mentors outside the lab is important for your professional growth. LinkedIn is a great place to reach out to potential mentors, conferences can be a great place too!
- Embrace the reality that nothing might go exactly according to your plan. When I came to the US a couple of years ago, I remember having a concrete plan for my PhD, but as time passed, I had to make some difficult decisions. While I was worried about the uncertainties that lay ahead, in the end everything worked out great! I wish I could go back and tell my younger self, “You are going to be okay!”. Always having that space and understanding that nothing goes exactly as you want, gives you the freedom to explore yourself as you evolve! Every path is unique and special. Eventually you will get to where you envision yourself to be and appreciate every milestone that made it possible!
In the immediate future I want to complete my thesis and defend it to get my PhD. Once I am done, I am looking at industry roles where I am challenged every day to utilize all the skills I have learnt. I am also a very passionate writer, so that is another field I am exploring at the moment. But one thing that is going to be a constant is to give back to the community. I have been blessed to have amazing parents and mentors in my life, so I am learning to be one such person by giving back, to create the next generation of scientists! I am very excited to see where my post-PhD life takes me!
- Synthesis and characterization of 5-(2-fluoro-4-[11C]methoxyphenyl)-2,2-dimethyl-3,4-dihydro-2H-pyrano[2,3-b]pyridine-7-carboxamide as a PET imaging ligand for metabotropic glutamate receptor 2Gengyang Yuan, MaevaDhaynaut, Yu La, Nicolas J. Guehl, Dalena Huynh, Suhasini Iyengar, Sepideh Afshar, Hao Wang, Sung-Hyun Moon, Mary Jo Ondrechen, Changning Wang, Timothy Shoup, Georges El Fakhri, Marc D. Normandin, Anna-Liisa Brownell, J. Med. Chem. 2022, 65, 3, 2593–2609
- Design, synthesis, and characterization of [ 18 F]mG2P026 as a high contrast PET imaging ligand for metabotropic glutamate receptor 2Gengyang Yuan, MaevaDhaynaut, Nicolas J. Guehl, Sepideh Afshar, Dalena Huynh, Sung-Hyun Moon, Suhasini Iyengar, Hye Jin Kang, Mary Jo Ondrechen, Georges El Fakhri, Marc D. Normandin, Anna-Liisa Brownell, Submitted to J. Med. Chem. – Apr 2022
- Design, Synthesis and Characterization of Benzimidazole Derivatives as PET Imaging Ligands for Metabotropic Glutamate Receptor Subtype 2 (mGluR2),Gengyang Yuan, Xiying Qu, Baohui Zheng, Ramesh Neelamegam, Sepideh Afshar, Suhasini Iyengar, Chuzhi Pan, Junfeng Wang, Hye Jin Kang, Mary Jo Ondrechen, PekkaPoutiainen, Georges El Fakhri, Zhaoda Zhang, and Anna-Liisa Brownell, , J. Med. Chem. 2020, 63, 20, 12060–12072
- Electrostatic fingerprints of catalytically active amino acids inenzymesSuhasini M. Iyengar, , Kelly K. Barnsley, Rholee Xu, Aleksandr Prystupa, Mary Jo Ondrechen, Protein Science.2022;31:e4291
- Cyclic Thiosulfinates and Cyclic Disulfides Selectively Cross-Link Thiols While Avoiding Modification of Lone Thiols. Donnelly, D. P.; Dowgiallo, M. G.;Salisbury, J. P.; Aluri, K. C.; Iyengar, S.; Chaudhari, M.; Mathew, M.;Miele, I.; Auclair, J. R.; Lopez, S. A.; Manetsch, R.; Agar, J. N. J. Am. Chem. Soc. 2018,140, 7377.