Good day, Dr Sunita Sharma. I'm Arjun. I've had a look through your background and your professional record. I'm interested in hearing more about your work and how you see yourself fitting in here with our faculty. Ready to start?

Uh.

Take your time—no rush. Please share your professional journey in academia.

Hello, good morning. I'm Doctor Sunita Sharma and I started my academic journey as an undergraduate student at VIT Vellore. My undergraduate degree was in B.Tech Biotechnology and finished I started finished my degree from 2006 to 2010 and then I moved to UNC Charlotte that is University of North Carolina Charlotte.

Uh, to pursue my PhD, and it was a direct PhD from, uh, after B.Tech, uh, direct PhD and in the lab of Doctor Jerry Troutman, uh, and my PhD centered around.

UH enzymology and glycobiology like deciphering the whole pathway, how to UH synthesize sepia, enzymatic synthesis of CPA of B fragilis. UH My PhD finished in June of 2019 and after that I moved back to India and joined the Sharda University as an assistant professor.

On August 6th, 2020.

Uh and uh, since I've joined Shadow University, I've been here for the past 5 1/2 years. Uh, my role has been predominantly as a, as a teaching faculty, plus mentoring students in research and also developing my own research work and.

Recently I was in September of 2024 I was granted an award as a Co Pi with the UPCS UPCS 2 of the UP government which was to develop.

A A A I related using AI to basically identify multidrug resistance TB in patients. Yeah, that's it.

Thanks for sharing that, Professor Sharma.

OK.

Professor Sharma, let's begin by discussing your qualifications and expertise relevant to the Cancer Bioinformatics Professor role. From your resume, I see you hold a Ph.D. from the University of North Carolina, completed in 2019. Could you walk me through how your educational background and key skills—such as synthetic biology and computational biology—align with this position?

Uh, alright, so with this position, so I started as a biochemist. So my, uh, my uh, Co training was uh was or rather is a biochemist enzyme enzymes and that also uh enzymology pertaining to glycosyl transfers that is glycobiology. And during the course of my PhD with that I did at UNC Charlotte, I discovered an enzyme pile called pyrovile transferase and.

Paper which was written published in 2017.

Uh, where that was deciphered in this, uh, synthetic pathway of CPSA. So once I returned back to, uh, India, obviously I joined Shashada University, which which is a private university and predominantly I joined as a team on a teaching role and here.

Uh, uh, uh, along with the, uh, this main subject that I thought like biochemistry, enzymology and protein engineering and biochemistry lab and this bioinformatics lab. So when I joined Shadow University because there was no lab, OK, wet lab to do my wet pro enzymology works, I deviated like, let us decipher the enzyme that I'm working on the part that I discovered pyro.

Phrase and to, to, to know more about this enzyme. I embraced computational biology, biology specifically because I what I discovered during the, my research work is that it's actually a very wonderful enzyme for drug targeting. And there has been actually absolute minimal study on this enzyme. So. So I got a PhD student, Miss Shivani, who is who joined under me as a PhD scholar in May 2021.

And our task was to know about all about this enzyme. So we started with the phylogeny studies on this enzyme. So here comes how do we actually use? Sequence analysis to know about an about any enzyme family and pertaining to this cancer bioinformatics position. I mean what I feel given with how technologies that cancer now the treatment of cancer now should be more driven as a personalized treatment starting with the sequence of the. Patient like what type? Because in cancer also there are multitude cancer. So what type of cancer is the patient having and mapping that cancer that sequence of the went from the using that cancer sequence and then mapping which biomarker is having and and then you're there in this plants. Like how I have progress in this 5 is that I have tried to incorporate rather incorporating more of machine learning in my work like we're in right now I'm working with the parallel transfer, so I'm using.

Informatics and ML to generate conformance for for my enzyme because drug drug rediscovery works on a certain certain till a certain level, but after that you need to actually design your own molecule. So I'm using AI to design my own molecules and on a side I'm also using NGS and creating NGS pipeline to analyze all these along with the collaborative work with my other colleagues here at Chad University and also at. JYMCAJBC that JCBC.

Uh, analyze, uh, uh, sequences using, uh, NGS pipeline. And, uh, with the, pertaining to my work, uh, there are also a few, couple of undergrads who are interested in learning this. So with them, I'm developing an algorithm which will actually map these SN PS singular single single nucleotide polymorphisms to specify biomarkers or that hallmark of a cancer. And then from that, uh, uh, just see if we can predict, uh, personalized treatment for that.

Uh, basically to uh.

So this is the work that I'm doing and moreover as as I mentioned previously that I was granted an award as a cool Pi with from the APCSD variant, I'm also using.

AI and and machine learning based techniques basically to identify multiple drug resistant TB in in patients, which is actually I feel the need of the hour. So that's my how my research skills actually fit the bioinformatics part and and how it can actually also come in cancer mathematics.

Right. The skills that I have developed over the course of the years. Thank you.

Thank you, Professor Sharma, for providing a comprehensive overview. Your progression from core biochemistry to bioinformatics and the integration of machine learning and AI in your research is indeed commendable, especially with its relevance in personalized medicine and cancer research. You mentioned using AI for drug design and NGS pipelines for sequence analysis. Could you elaborate specifically on a challenge you faced while implementing computational techniques for drug discovery or biomarker identification, and how you addressed it?

So actually the whole transition from being a wet lab person, like I love vet lab. It's not that I have ditched that, but I love vet lab. But of course due to positive funds and infrastructure when I move back, so I had to give a new direction to my research work and, and of course that was the need of the hour also at that time because a newly discovered enzyme and we know very little of of it. And it's a membrane bound enzyme, isn't it?

And so and so different. So getting a structure of that enzyme, this crystal structure very, very notoriously difficult. So how I moved is that from. So to solve that issue, I of of course, sort my answer using computational tools. So the first and foremost was actually getting, getting printing, predicting the structure for, for, for my enzyme. And this is a very novel enzyme and we know that for a novel enzyme.

Uh, we cannot go, uh, until, unless there is a structure that already exists in the PDB that is a protein data bank. Uh, it's difficult to go for homology modeling. For homology modeling, you need the minimum that the cut off for a, for, for a good structure that we need to render is like more than similarity of more than 40%. And with the pyro, while transfer is what I, when I, when I started studying this enzyme in more detail, that is. Uh, identifying all the 38,000 sequences, getting all the information and found out actually that there is no prokaryotic sequence, uh, sorry, structure of this enzyme in protein databank. The only structure that was available was actually of an exception that is eukary. This enzyme is not found and eukaryotes. So we found that there was one structure, but that also a partial structure there in the, in the chain a of that protein, there were few residues missing. So obviously cannot be used for homology modeling. So me and my.

When we devise a track wherein OK, alright, let's uh, use uh.

Avenissio method and Auburn issue method actually.

It was the first time using for it and I did face difficulties in validating, validating the enzymes, enzymes and at that time around like in the so I started this, this abanish modeling of my enzyme in late 2020 and sorry, late 2020 and when Shivani joined. My group as a research scholar.

At that time actually Alphafold exploded, so it came in the scenario and it was able to predict it. But later on what I found that the structure predicted by Alphafold was actually way way off and.

I mean lot of red errors in the terms of amino acid residues that were not falling in the in a correct confirmation and I had to reject that. So I, I went along with my my own plan and I have an issue actually gave me a very good.

Stable, very good structure that I had and this was actually done over a course of six with the with the limited reverse. Of course I did not have access any to any AI high computing system over here.

Everything was done on my students personal personal laptop and my my personal Mac Pro. And but thankfully in 2021, I was awarded an institutional grant by the shadow university, which enabled me to get a high performance performance system. And then all my work was conducted on them and the structure validation of the of these spiral transfers. So I'm, so I'm saying that I'm working on a huge family. So, so they're like ski six or seven parallel.

Places structures that I'm working on. So their structure validation it took a significant time and of course that why I'm interested in still getting the surface not just hit in the because as I mentioned that this enzyme is actually very less studied and it is actually a part of the.

A cell wall of a of a bacteria and very wonderful drug target because antimicrobial resistance is rising. So the need of the hour is to actually generate or rather synthesize or a new molecule which is not existing before which the bacterias and which can be used in combinational therapy. So that is why I'm interested in enzymes. So during the this whole whole course.

Genuinely their their structures of these enzymes via AB initial Robita and Rosetta. The combination of these were were used challenging a high line streaming the process actually line streaming like and then during the validation purpose which.

This. Uh, when we go for, uh, when I, uh, we go for MD's. So for MD's, which uh, uh, potential energy function to use, whether to use charm, whether to use or Opls or because each of these proteins are, are differently made. The only common thing that between these enzymes is that they perform the pyruvate transvisal reaction. And because there's a diversity in the. The way in the substrate in the acceptor cell because the pyruvate is the constant.

Donor substrate and the acceptor substrate is varied because saccharides can vary from a monosaccharide to to whatever hex hexa heptasaccharide like in WCFO its substrate is a disaccharide whereas in equal IW CAK the substrate is a heptasaccharide. So that variation it was difficult for me to to identify actually these substrates site and how to model it because they are blue creatures coming which are sometimes falling and the protein is.

Actually going into polymorphic binding. So, uh, this was the, uh, different challenges that I faced, like, uh, uh, validation of stuff. Because if structure is not validated, the downstream, uh, the, uh, the downstream processes like identifying ligands and then on base of the, those, the lead molecules, how they are linking, if the structured surface is strong, then identifying the, whatever lead molecule is identified, that actually gives me. A sort of incorrect result.

And delete. And if I was to you, if I were to use those encourages to later develop molecule, it will actually fail in the vet lab. So for me, the challenge was to get a good optimized, uh, structure and then go identify molecules that can actually work to inhibit this enzyme. And then from those identified molecules, I further want to identify like the processes it's going on to identify the pharmacophore and then design my own drugs using.

Own drugs both in the lab and right now my student is. One of my students is also writing a pipeline to uh, using uh, basically generative AI to generate.

Molecules, new molecules that can actually in in inhibit and hopefully it will be wound up within the next three to four months. Yes, thank you.

Thank you, Professor Sharma, for the detailed explanation. It clearly demonstrates your ability to transition from wet lab enzymology to computational bioinformatics, despite resource challenges, and tackle complex problems like novel enzyme structure prediction and drug design. It's also evident that you're equipping yourself with emerging technologies like generative AI to further streamline and enhance your research. One final question before we proceed: you’ve mentioned working with students on developing pipelines and algorithms. How do you balance guiding students in their projects while managing your ambitious research agenda? Could you provide an example of how you've fostered students’ growth in understanding bioinformatics concepts during such collaborative work?

Actually, I loved, I didn't realize that I loved teaching. So I, I, I mean now, so my personal goal is like, of course, I want to give something back to the humanity. So that drives me actually. And when I joined Shadow University, I thought, yes, six months I'll be here. Then I'll go go, I'll go somewhere in a recent, but unfortunately what?

Uh, due to channels, uh, challenges and then, uh, stability that, uh, I needed to provide to my family, I stuck with this, uh, job and, uh, and eventually I realized that I loved teaching. And what I feel is that teach, research and teaching goes in a hand in hand. So if I am researching something, if I'm unable to, uh, give it to the next generation, then, uh, whatever I've learned actually dies with me when whatever I move. So I need to give back.

To the give back to the students so how it works that students so I interact with them in the class I describe my research work and what the current technology wherever it's going in the in what direction is going and interested students are always welcome to come and interact with interact with me and I start with small projects. I start with small projects give them a simple basic and see if they are able to actually.

Perform perform it and they are actually. If they're stuck in it, are they able to actually?

Handle the issue handle the issue means do problem solving because in research work and as a student who is actually going going to come in bio dramatics, they need to do problem solving. Problem solving skills are very memorable so.

So I said so if a student's unable to solve a problem, then we sit with them then analyze what they have done, where they are going wrong and discuss the future steps that need they need to say. So actually quite one on hand and it becomes challenging because my time is also limited and their time is also limited. So I devise a meeting point where they need to come and meet me, discuss the project and then we say where we are going. And it actually has helped me not wherein my students have gone, gone to actually win presentation awards in both intern.

And national conferences. So one of those very, uh, beautiful achievement was of my, uh, Shiva, uh, PSD scholar who is about to wrap up her PhDs that we went and presented her work in, in. International Conference of Informatics in held in Kyoto University last like November, October 20, November, December of November 2024. And we were awarded the best presentation of paperwork for in the category of drug discovery. And so it can see that the work that me and my students are doing are actually at international level and it is being recognized that it's it's being awarded at similar national level. My Btech biotechnology students, they were awarded the second prize.

The held at JP Institute of Technology Noida just on the the on the analysis that they had done done with me. So mentoring students actually comes naturally to me. I love to interact with them. Help them grow within. Like one of my students I mentioned is helping me with the generative AI so he said ma'am I do not want to do vet biology but rather I'm more interesting in the drive work. So we came up how I can fit that student.

In my research school and he was like, yes, I can, I can try using try building a pipeline of generative A for generating these structures. And he's actually processing. We have a rudimentary, rudimentary pattern designer which will be more refined with the with the data set that I'm trying to provide him to him right now. Yes, thank you.

Thank you, Professor Sharma. Your approach to mentoring students is clearly impactful, with emphasis on problem-solving, fostering independent thought, and tailoring projects to fit individual interests. The recognition received by your students, both nationally and internationally, reflects your ability to guide and inspire them in high-quality research and innovative work. Now let's proceed to verify more specifics about your qualifications and experience. Could you provide insights on how your research publications and consultancy experience have contributed to advancing the academic community or addressing industry challenges?

So as I said, my publications started when obviously I I, I I was in UNC Charlotte as a PhD scholars. I published 3 impactful research papers, 2IN carbohydrate research and one in this a CSA chemical Biology and the paper that was published in ACS Chemical Biology actually was has been the highlight of my. Research very much impactful that it it it started with that and then once I moved to.

A move to Sharada, of course, I came here and I did a bit of collaborative work with when and I joined Sharda when the COVID was actually at, at its at its peak when the the second second delta wave was actually going in. And then I, I collaborated with my colleagues over here in both in immunology who were in immunology, virology and various institutes to write actually paper how COVID was. Impact impacting on the kidneys and the and the lungs and the lungs of the patient. So those papers were.

For, uh, pub published also. And then of course, I wrote a review, uh, uh, review as a of, of my PhD, but that's a book chapter that was published also. And uh, and recently, uh, I published, like my work have been published in this took as conference papers. Currently I'm working on the manuscripts that the whole work that I have been doing for the past 3 1/2 years once I acquired the workstation it has. Accumulated and then those two papers are in are in communication.

One is with the the this Oxford B MB MC and the other is in process of of submission. So hopefully I'm hoping to hear soon from Oxford, Oxford BMC, the current book that I have done on the Spiriva transferase and the structure illustration, the phylogenetic work. Yes, thank you.

Uh, right now one is it with the.

Thank you, Professor Sharma. Your publications evidently reflect a range of impactful research, from enzymology and synthetic pathways to collaborative efforts addressing critical health concerns like COVID. Your ongoing work on pyruvyltransferase is particularly notable for its depth and relevance, with pending publications promising further contributions to the academic community. Regarding consultancy, can you share an example of how your involvement in industry-linked projects or academic consultancy has helped solve real-world problems or benefited research translation into practical applications?

Yes. So academic consultancies and industry consultancies, I, I was, I'm actually invited, I have been invited to the Ministry of Environment wherein they have called on for synthetic biologists to actually review the consortium of synthetic biology how, how it's to graduate, to lay guidelines, how experiments or rather work in synthetic biology can influence our country and what is India's.

Meeting was conducted I think Columbia and I was part of that consortium with the with the Ministry of Environment. It can be verified by Doctor Abhilasha. She was the one who who invited me as a panelist there to to there. And also I was invited as a as a panelist or not rather to discuss like with the oil Oil India Limit Limited. They are what they are having is they have a their oil fields in Jodhpur region area and. They actually want to extract oil from there, but the region is rather.

Uh, stand up point view in, in, in the synthetic biology when, uh, this whole, uh, uh.

Uh, the, uh, the problem is that it is very thick oil, very thick oil and you cannot go and mine it and you, because if, if they're heavy machinery goes there, it will sink. So what I provide, the solution I provided them was that they look for microbial enhanced or, or oil recovery wherein various types of microorganisms. They are incubated there, which break down the larger hydrocarbon components into a more small, smaller chain.

Such that it will be easier to extract that oil rather than just going mining and then the, uh, having unforcing damages to human, accidental damages to human life. So these are the two major concerns that I had recently. And recently I was also in talks with, with an industry in Pune where they wanted my expertise in because I have become very much fluent in.

In identifying drug, drug, drug leads and identifying structures computationally. So they wanted my expertise and that is a talk that is still in progress and they're having some issues with regarding fees etcetera. So pending the the those stocks then I get I will have one more consultancy. Yes, thank you.

In.

Thank you, Professor Sharma. Your involvement in academic and industry-linked consultancies clearly demonstrates your ability to address complex challenges—whether it’s shaping national guidelines for synthetic biology, advising on environmentally sustainable oil extraction methods, or applying computational expertise to drug discovery. With this, we've touched on various aspects of your qualifications and experience. Given your breadth of expertise and contributions, could you summarize what you consider to be your strongest asset or unique value as a candidate for the Cancer Bioinformatics Professor role?

Uh, the strongest point is that I am a biochemist at heart and also I, and I have refined myself that I, I know how to apply the current technologies. So vet lab and Rylab, both of them, both skills I have equally developed because ultimately cancer bioinformatics will start from a biochemistry perspective. So these two qualities, they are very difficult to, to achieve.

I think, and that is my unique point from above from a biochemist because everything life starts at biochemistry. So I started with biochemistry and then I'm using the current technologies to understand that cancer happens at a biomolecular level, at a, at a chemical level, a biomolecule level. And for that to understand what is happening at a biochemical, I'm using technology. So I'm blending those two perfectly and that is my strength.

As a candidate for this position, thank you.

Thank you, Professor Sharma. Your ability to harmonize foundational biochemistry with advanced computational and bioinformatics tools is indeed a compelling strength for this role. It highlights your multidisciplinary approach and capacity to address complex biological challenges like cancer at both molecular and technological levels. We’ve covered a substantial amount of ground today. Before we conclude, is there anything further you’d like to add or emphasize about your candidacy or contributions?

Uh, not just in research and as a personal human being also, I, I am, I empathize with everyone, my students, faculties, anyone. And moreover, I'm able to communicate in three languages. English is the primary first language. Hindi is my mother language and Tamil is my third language because I have married, I'm married to a, to a South Indian. My husband is South Indian. So, uh, I can speak.

Thank you.

Please yes, I'm I have been a very uh, honest with my answers, what I have done, what I have achieved and what, who am, who am I? Everything is uh, crystal clear in this. Thank you.

Thank you, Professor Sharma. Your multilingual abilities, paired with your empathetic approach to mentoring and collaboration, further underscore your well-rounded strengths, both academically and personally. If there’s nothing more to discuss or clarify, do you confirm that you are ready to conclude this interview?

Yes.