Just last week, I attended my very first conference: an ALLODD one, no less! Held in the understatedly beautiful city of Strasbourg, this event was my first chance to finally meet my fellow PhD students in-person, after joining the program 5 months ago. Thankfully, three of them had already visited me in Athens, which made the initial apprehension of facing a group of 15 new (but amazing) people much easier.

The first two days of talks proved intense and demanded all the brainpower we could muster. But once the talks were over, we still had the perfect opportunity to replenish it, just as ‪Ilpo Vattulainen‬ advised, by eating Alsacian-style fish during the planned social events. Nonetheless, it was interesting to hear firsthand about the current role of allostery in research, both from the academic and pharmaceutical perspectives, after having spent countless hours reading about it in my first months of PhD.

On the third day, I was finally able to hear my colleagues explain their projects and share their progress in their own words. It is always alluring to learn about science outside one's own tiny research niche, and to witness the seamless flow of discussions that arose between different fields of research.

Attending the ESR-exclusive training activities (and equally importantly, our own unplanned socialization events after) was an invaluable opportunity to share and discuss between us about the challenges and achievements of undertaking a PhD, and find support in one another. I appreciated the chance to get to know my peers on a more personal level, exchanging stories and experiences, and realizing how serendipity brought us all together from different places and backgrounds.

As my TGV departed from Strasbourg, I was left with a pleasant sense of fulfillment and growth. And an even more intense urge to meet everyone again in just 4 months! See you soon.

One of the main issues with obtaining protein structures, especially that of transmembrane proteins, are their relative flexibility. This issue limits both of the most commonly used methods of obtaining larger protein structures: X-ray crystallography and cryo-electron microscopy (cryo-EM). Indeed, in their native environment, proteins are highly dynamic and cycle through different conformations depending on their immediate surroundings. However, X-ray crystallography can only obtain one protein conformation at a time and even the number of conformation obtained by cryo-EM is limited. Intermediary structures between the active and inactive form of a protein are particularly difficult to sample, resulting in a considerable bottleneck in the analysis of conformational changes.

Luckily, one particular spectroscopy method, pioneered 25 years ago by Altenbach et al. and which requires the insertion of paramagnetic probes, can help feel in the gaps. This Electron Paramagnetic Resonance (EPR) utilizes the ability of unpaired electrons to change between their two spin states (ms = ½ or ms = - ½) and the influence that the nearby environment and associated atoms has on them to derive a spectral line. One particularly useful application of this method for protein structural analysis is the double electron-electron resonance (DEER) measurements: the distance between a pair of labelled spins is measured, and then that distance can be measured again for the same protein under different conditions (for example in the presence of various ligands).

Nowadays, the most common way to establish spin labeling is by inserting reactive cysteines via site-selective mutagenesis at dynamically relevant sites in the protein of interest. The unpaired electrons within the accessible cysteines will then bind to the spin labels when incubated with the purified proteins under specific conditions.

My own project at the Scheerer laboratory will include performing this experiment on the melanocortin-4 receptor (MC4R) in different environments, such as in the presence of orthosteric and allosteric ligands, in collaboration with Matthias Elgeti’s laboratory at Leipzig University. So far, I am pleased to report that the wildtype MC4R has been successfully labeled by both MTSL (S-(1-oxyl-2,2,5,5-tetramethyl-2,5-dihydro-1H-pyrrol-3-yl)methyl methanesulfonothioate) and IDSL (bis(2,2,5,5-tetramethyl-3-imidazoline-1-oxyl-4-il)-disulfide spin label). MTSL is a nitroxide reagent with a high reactivity towards cysteines. Its high labeling efficiency combined with its small size, which minimizes the risk of interference with the protein structure and the folding pathway, have made it the most popular spin label for proteins. The reactive disulfide IDSL, on the other hand, labels cysteines via sulfhydryl-disulfide exchange reaction. Additionally, an intra-side chain S-N stabilizes the interaction, making IDSL an attractive label for DEER measurements.

The next step is now to obtain a “cysteine-less” variant, which cannot be labeled for EPR, as a negative control. This represents one of the unfortunate drawbacks of EPR spectroscopy, as this process is time-consuming, and we have to account for the unpredictable possibility that this might result in a loss of expression or structure. This is what I am currently doing, generating two virus containing “cysteine-less” mutants of MC4R: one of them had four reactive cysteines mutated into serines and the other had five (the same four and one additional cysteine that is believed to undergo post-translational modification in humans). My hope is that at least one of these MC4R mutants will not only be expressed in a large enough amount to be used in subsequent experiments, but also that EPR will show no labelling of the remaining cysteines. Indeed, we consider that the remaining native cysteines, being either involved in a disulfide bond or hidden within the transmembrane core, should not be available for labeling. If this experiment is successful, I will then be able to move on to constructs with cysteines inserted at interesting sites, such as in the transmembrane regions 5, 6 and 7 and on the intracellular loop 2, and thus begin the DEER measurements in earnest.

Time goes by so fast, that’s undeniable. I remember the day I started my PhD as if it was yesterday. Here I am today, almost in the second year of PhD. At this pace, I have no doubt that in the blink of an eye, I will be writing my thesis.

When I look back, what I can say is this last year was extremely unique and memorable with its highs and lows. Well, you more or less know about my journey from my previous blogpost, but what I hadn’t told you, also what I didn’t know, at that moment was the challenges that a computational chemist has to go through topped with the mysterious world of experiments, not only in academia but also in the corporate world. Now please bear with me and let me tell you the tale of the “shapeshifter” (that’s what I like to call myself lately)

As someone who chose the computational chemistry path back in the sophomore year of college, I was slowly straying away from the idea of performing experiments in the lab again. My practical lab courses were long gone. As the time passed by, my skills regarding experimental methods got rusty more and more.

After I had an interview to get the ESR4 position, Prof. Carles Curutchet asked me whether or not I would also be willing to do some experiments for the project. I thought it would be great to do both the experimental and the computational part of the job to be able to own it completely. Though I cannot deny that I was a little scared. As I was gaining more experience and deepening my knowledge in theoretical methods, my ability in performing experiments in the lab was decaying at the same pace. I was afraid of getting lost in things which could be pretty obvious to some wet chemists but clearly not to me, terrified by even the thought of failing…
As human beings, when it comes to unknown things, we are always a bit anxious and scared, aren’t we? It is because we don’t exactly know what we are facing and how to deal with it, but it is also somewhat intriguing and exciting, don’t you agree?

So, long story short, I didn’t chicken out and said yes to performing experiments besides the computational work I was supposed to do. In a few months, I found myself re-learning the fundamentals of working in a lab (general chemistry lab 101 reloading…) I was cautious as if I could possibly press a button and burn the whole lab down. I asked for guidance, talked to the PhD students, professors, read the manuals of the machines I was going to use before taking action. For each type of experiment, I was supposed to use a specific machine which was located in different labs of the department. So, in the morning I was in one lab, in the afternoon in another one. Even people seeing me here and there were not entirely sure which lab group I belonged to or who I was working with. After some time, in the experimental section of the department, I became someone everyone was used to seeing around but nobody knew much about, and little did they know that I was actually a member of the computational chemistry group. Having two different roles also made it complicated to explain what exactly I was doing. Yet, it was just the tip of the iceberg.

In February, I started my secondment at Gain Therapeutics. The company was located only 5 mins away from the pharmacy campus of University of Barcelona where I normally work at. So, in a way it was different than the usual secondment concept where you move to another country for a couple of months and work at another institution while a new culture is being introduced to your system. For me it was regular PhD work + secondment in the same city all blended in together. There were days I stopped by the university in the morning to get a sample and then went to work. It just added one more location to the whole equation of where I work.

In the company, I got a nice desk in a nice office, like any other member of the computational team, but as a part of my secondment plan, I was also supposed to perform some experiments in the Gain lab which was completely on the opposite side of the office. After going down with the elevator, taking a long walk down the hallway, passing through two turnstiles, scanning your card twice, opening several doors, congratulations you made it to the lab (In this case is it short for laboratory or labyrinth). After a short while, I figured out that the machine they had in the Gain lab was not suitable for my experiments. So, I had to use the one in the common area which was one story below the Gain lab and required going through another door with scanning your card, though that door required another type of authorization which I didn’t have as a visiting researcher. So, every time I had to use a machine, I either needed someone to accompany me or borrow someone else’s card. While working there in the lab, I got into the world of biologists, because most people working in the lab had a biology background. Actually, they were surprised when I told them I was a chemist (just a chemist, let alone the computational part).

Here I am now, performing some experiments + simulations at academia & company.

I can be a computational or an experimental chemist or both, I can be at the university or appear at the company or both. It feels like I have some magical powers and I can shapeshift from one to another like a druid (gamer detected). So, at this point I am not sure how to explain where I work, what I do exactly, which team I belong to. When I get asked such questions, oh I can guarantee that there is a long story on its way, but to keep it shorter and make it sound more like me I will summarize my current PhD life with an acrostic:

Little did I know that I was about to start one hell of a journey
I thought I’d just be on my PC without getting my hands dirty
Fast-forward a few months, I started to conduct an experiment
Eventually I found myself at Gain exploring company environment
One day you can find me around the spectrometer in the lab
For the rest, I am doing my simulations at the office looking fab
Partially a student at school, partially a researcher at the company
Half wet chemist, half computational, not wearing just one hat, but so many
Don’t underestimate the life of a comperimental chemist in academpany

It may be helpful!! :)

Just go to the enumerated points if you don’t have time for the backstory :)

Short backstory: as an early-stage researcher in the Allostery in Drug Discovery (ALLODD) Network within Marie Skłodowska-Curie Actions, I got lucky and honored by having an invitation by Dr. Zoe Cournia and Prof. Marco Cecchini (my Supervisor) to contribute, among many other authors, to the yet-to-be-published Review, which topic is connected with alchemical free energy calculations on certain systems, relevant to drug-design. While some final work is yet to be done before the publication, I wanted to share some of my insights on writing, which indeed was a novel experience for me.

Although at the first sight the question of “writing a Review” may seem trivial for those who at the beginning of their scientific career already have got their hands on drafting a scientific article in a peer-reviewed journal or have done decent literature work in their Bachelor’s or Master’s Thesis, writing a professional Review may require some additional techniques and persistence.

First, the difference between the typical introduction in a peer-reviewed article with your results and a Review is in how exhaustive you need to be to discuss a certain topic. Although in typical articles you certainly need to be well-informed of the current stage of scientific progress on your problem of interest, Reviews often discuss broader issues and may require a more complete literature analysis.

Additionally, in your typical article, you may know the most recent advances and key articles through your Supervisor – but a Review could go beyond the scope of their direct expertise, and includes all the most recent advances – which could’ve been missed unless a thorough work to find them was done. Just imagine how many new scientific articles are out there each month.

Thus, here are some tips for writing a scientific Review, at least what worked for me:

Secondments are an essential part of our scientific journey as Early-Stage Researchers in the ALLODD ITN consortium. Essentially, they are research stays, carefully planned by our supervisors to both complement our Ph.D. projects and give us experience and expertise in different fields than ours. It is a time to gain new knowledge, acquire new skills and network with people from outside your line of research. It gives us a chance to see the bigger picture in science and discover the numerous possibilities in Allostery and Drug Discovery.
 
In my case, my first secondment journey was from red-hot Barcelona to 10-degree Stockholm; from my familiar computational world to the not-so-familiar and complex reality of wet-lab experiments.
 
Imagine a computational chemist with a background in chemical engineering having to express and purify their first protein. That was me 6 months ago. Very excited, a little scared, optimistic and ready to learn. My experimental journey began in the group of Dr. Galdeano, at the University of Barcelona, where I was taught how to grow bacteria, how to express protein and how to purify it. I am extremely thankful to my colleagues from Galdeano’s lab, Roger and Andrea, for their patience with me and my rusty experimental skills. With their guidance, soon my protein was ready for shipping to Karolinska Institute, to the Mass Spec lab of prof. Roman Zubarev. Together with the protein, I shipped myself to Sweden, leaving aside my computational studies and embracing my new challenge: the world of the MS techniques.
 
For the next three months in the lab at Karolinska Institute, I learned something new every day- not only about the MS experiments but also about the experimental work style. During the first few weeks, together with my ESR colleague, Bohdana Sokolova, I was trained on how to prepare HDX-MS samples, how to handle MS instruments and how to analyze MS data. Along with the HDX-MS methodology, I also learned experimental design from A to Z, planning based on instruments’ availability and lab time organization. It was a time of everyday lessons; some were easy and some were hard.
 
The hardest lesson for me was accepting that experiments don’t always work out. My optimism wavered when my first HDX tests did not give the expected results. My hopes diminished as we stumbled upon drawback after drawback. Sometimes the established experimental technique works perfectly for your project, but other times it needs parameters’ optimization and even further development to meet the needs of the scientist. Even then, the method may not provide the results it did in others’ research and it may even lead to a dead end. But I learned this is okay! I understood failure is a natural part of the experimental process and it is essential to be aware of the opportunities and the limitations of each technique. With every method mastered you also gain experience on how and when to use it and this lesson will always stay with me.
 
In the line of learning and acquiring new skills, my experimental journey did not end with the HDX-MS technique. With Dr. Gaetani’s guidance, I set off to gain experience in the Proteome Integral Solubility Alteration (PISA) assay, developed in Zubarev’s lab.
 
Now imagine a computational chemist in a cell lab- again, that was me. It was not easy at first- everything about the cell lab was new to me; every skill, every piece of information sounded foreign. And, of course, I did make some mistakes. But each mistake turned into a lesson. Through trial and error, through practice and patience, in the last week of my secondment, I felt like a well-oiled machine with tissue culturing and cell treatment. And it was likewise with every other part of the 5-day PISA procedure I had to master to be able to perform the designed experiments.
 
It was an amazing experience- careful planning each day according to the instruments’ availability; getting familiar with many different practices; working on a tight schedule with many tasks. Some days nothing was working, some days went smoothly and exactly as planned- a true experimental rollercoaster. And just like that, I conducted the planned PISA experiments and my secondment journey came to an end. I felt a huge sense of fulfillment- the three months experimental stay in Stockholm has turned me, a computer-based young scientist, into an experimentalist. I wouldn’t say that now I am an expert on MS-based methods; but I am sure the skills and experience I got from Karolinska Institute will help me through the next steps of my career and I am grateful for this opportunity to everyone involved.
 
Now that I am back to my computational studies, I am looking forward to my next secondment and to learning more about the experimental part of drug discovery. And I would recommend to every computational scientist that hasn’t been in the lab for a long time- go out of your comfort zone, make the journey and experience research from the other side. It is worth the rollercoaster!
 
And some unforgettable moments from the journey (whenever I remembered to take a photo)!

Here we are, it's been a year since I started the ALLODD journey… and what a year!

In January 2022 I settled down in Germany, which administratively was not so smooth. After a few days, I officially started in the lab at the biggest site and also headquarters of Merck. It is like a small town (we are more than 12´000 people working there). Despite being the only non-German speaker in the lab, any single person speaks English, which made my first months a lot easier that I would expect by being somewhere you don’t speak the language. Actually, I learned German at school a few years ago and let me say it is not like riding a bike you will forget if you do not practice! I hope, by the end of the project, to be able to speak fluently in German. This is also why I applied to learn more scientifically and personally.

As the first weeks and months go by, I was learning more about the different machines in the lab and their corresponding assays, as well as going deeper in the literature.

September was the opportunity to go to Barcelona in Prof. Dr. Curutchet lab as my first secondment. Moving from Darmstadt to Barcelona was definitely a weather improvement. Even though the surroundings were not new for me, I discovered there a new scientific world: the computational world. From opening a terminal to running my first molecular dynamic simulation, it was a very broad journey. This was also my first experience working at the University, as I did all my internships in private companies. I enjoyed my stay in the group, I am very thankful for the time they devoted to me, to explain and help me or to discover new restaurants.

Now back in Germany, it´s time for me to be reunited with the lab experiments and my cells: Saccharomyces cerevisiae. Yes, those are the same cells used in bakery or brewery (I had to adapt to the German culture 😉).
Being part of an ITN also means business-travel, during this first year, we met in-person twice with the wonderful people of the ALLODD network. Vienna, Barcelona and soon Strasbourg and Budapest, we emphasized the words network and partnerships!

The best is yet to come!

When my turn came to write a blog post, most of my colleagues have already had a chance to talk about their experience as fresh PhDs. Joining a high-level research group, meeting renowned scientists, winter schools, conferences, exchanges abroad – many things that one could only dream of in undergrad are most frequently mentioned in the reflections on first months of doctorate studies. But alas, from my own experience and discussions with other PhD students I dare say that the feeling that often hides behind this refined façade is frustration. Questions like ‘where is this going?’ and ‘am I doing enough?’ used to pop up in my head all the time adding to the general state of confusion as a newly-started PhD student. Having successfully survived 5 months of my new role, I would like to leave some tips for those who are just starting their journey and myself on how to get through first months of PhD studies.
‘Accept your destiny’
First of all, it is normal to feel confused. We will skip first four stages of Bart Simpson’s scheme right to the last one – acceptance. Embrace the idea that you will not be perfect on this path, you might not see the global idea behind the project, you might not understand everything, you might make mistakes, and it is completely okay. Regardless of what you have been doing before, no one is fully prepared to be a PhD student. Once you have accepted your fate, you can move on to the next step.

‘What can I do to make this journey as smooth as possible?’
Start learning about your project asap. PhD is a combination of studies, research work and – most importantly – managing a project, and you cannot lead this project without knowing the direction where you are going. So read the literature, discuss it with your supervisors, make sure to have a clear vision of everything that is supposed to happen during these 3 (or 4) years.

‘Use the opportunities’

Consider your time as a graduate student a mutually beneficial agreement between you and the scientific community: you provide an in-depth research on a certain topic and in exchange get an opportunity to grow personally and professionally. PhD studies provide space to improve a large variety of skills. Always wanted to start writing? Launch a personal or write articles for biotech media. Interested in trying yourself as a mentor? Volunteer to supervise an undergraduate student or work as a TA in a course. Organizing conferences, starting a pop-science podcast, exploring bioenterpreneurship – there are countless possibilities out there waiting for you to uncover them! Think about your passions and try to find ways to express them as a part of your studies from day one, it will certainly bring a splash of color into your routine work (and enrich your CV😉).

‘Network’
This is your unique chance to meet like-minded people ready to change the world. So put yourself out there, attend workshops, conferences, learn about things that others are doing (even if they are not directly applicable to your field or rather especially if they are not directly applicable to your field).
‘Healthy balance’

Last but not least, remember that research is just one part of your life. As important as your work is for you, it is crucial to find that ‘equilibrium state’ where you could have space for healthy sleep, sport, hobbies and private life. PhD is a marathon and not a sprint, so make sure you have enough energy to make it to the finish line!

It has been already 6 months since I arrived to the lively, ancient and history filled city of Urbino. This is not only my first time leaving my country behind, but it is also my first time living by myself, so jumping into this project has definitely proved to be a real challenge.

A time comes for all of us to become an independent adult and deal with all kinds of new (and sometimes scary, of course) issues and situations. And if that you add the fact that your known environment, people and even language change it can become a challenging situation to be in.

The biggest tip I can give to anyone is don’t be afraid to ask. And I mean in any situation you may find yourself in. Especially if you are a new to a city, of course you are not expected to know where things are or how anything works there. Being an introverted person myself, I usually struggled trying to approach people and asking the most basic stuff. However, something I learned is that people want to help. Even if you don’t share a common language, there is always a way to communicate and let them know what you need.
This tip basically applies to most of the situations you can get yourself into:

• Looking for a place to live in? Sure, internet is always a way to go, but you are already there. Why not look around and ask the locals? Why not check agencies by yourself? This is also a great way to start knowing your way around the place you are about to start living into.
• You want to know where to buy groceries or the best places to eat at your new home? Ask the locals, your roommate(s), your colleagues. You never know who will lead you to your go-to place for Friday night dinner.
• “Oh no, I have no clue on how to get from my place to another!” Public transport and the way it works is usually very different depending on the city (and, of course, on the country). But who will know more about it that people that use daily? Don’t be afraid to ask when the bus is coming, where do you need to jump in, or if that bus actually takes you where you want to go. For the record: I even had to ask how to validate a ticket when I already was inside the bus.

Once you overcome the, let’s say, external issues, you are only left to deal with yourself and your (in)ability to keep you alive. If you can manage your time and your housekeeping tasks, you are guaranteed to succeed in your solo quest to survive.

When moving from Barcelona (1.6 Mil Population) to Urbino (14.4 k Population) I already expected a big change, not only in the city itself but also in the daily life. And that is exactly what I got.

I now live in a quiet and beautiful walled city, surrounded by a landscape I never imagined.

The flow of information from protein sequence over structure to physiological function has been boggling physicists’, chemists’, and biologists’ minds for over half a century. First postulated by Christian Anfinsen in the 1970s, the ‘thermodynamic hypothesis’ describes a unique relationship in which the amino acid sequence of a protein should be sufficient to determine its structure [1]. Yet, it was during the same time when Cyrus Levinthal famously noted that, theoretically, it would take longer than the age of the universe for a typical protein to sample all possible conformations in order to reach its correct fold [2]. Opening one of the biggest challenges in biology, advances in computational methods, as well as the drastic increase in experimental structures and sequences being published, just recently narrowed down the ‘sequence-structure gap’ that Anfinsen and Levinthal opened. Culminating in AlphaFold 2 [3], sequence-based structure prediction has reached astonishing accuracy, representing a huge leap forward in biology and also in drug discovery.
 
Is it that simple? While it is true that structure models represent a great starting point for many research endeavors, the same scientific advances that brought us AlphaFold revealed gaps in the sequence-structure-function paradigm. It is now common knowledge that proteins are not static at all, as suggested by models obtained from predictions or crystallographic structures, but highly dynamic. These dynamics range from bond vibrations to large conformational changes, come in networks, and often modulate protein function – a phenomenon collectively described as allostery [4]. But what is the relationship between sequence and the structural dynamics that govern function? If the sequence-structure-function paradigm holds true, these dynamics should be imprinted in the sequence and should evolve alongside the often highly conserved active site of a protein. More specifically, to maintain biological robustness, a network of energetically coupled residues should translate into a joint evolutionary constraint between each participating residue - they co-evolve or co-mutate [5].
 
Besides positional conservation, information about co-evolution is contained in multiple sequence alignments (MSAs) of homologous sequences, as these reflect the ‘evolutionary history’ of a protein family. By applying statistical models to MSAs, the interdependency of the variability of each sequence position, the ‘co-evolutionary coupling’, can be obtained and can be interpreted as direct or indirect physical connectivity between residues. A plethora of methods that build on this principle have been developed and succeeded in deciphering residue-residue couplings for structure prediction and identification of functional domains for ligand binding or allosteric regulation [6]. However, experimental validation of dynamic co-evolving networks that modulate protein function is challenging. In particular, when these dynamics take place in the absence of global structural changes.
 
In a recent study, Torgeson et al. [7] combined co-evolutionary analysis and nuclear magnetic resonance (NMR) spectroscopy to identify previously undescribed dynamic networks of the protein tyrosine phosphatase (PTP) PTP1B. PTP1B’s structure, dynamics and function, as well as that of its homologs have been rigorously characterized, making it an ideal system to study the impact of co-evolution on functional dynamics.
 
Torgeson et al. applied so called pseudolikelihood maximization direct coupling analysis (plmDCA) [8] to an MSA of PTP1B homologs to derive co-evolutionary couplings and then used a spectral clustering approach to split the structure into strongly coupled co-evolving domains, referred to as evolutionary domains (EDs) [9]. Supporting the idea of co-evolutionary analysis to identify functionally critical residue groups, four of the obtained EDs have been previously verified experimentally in PTP1B. However, further clustering revealed additional, yet uncharacterized subdomains.
 
More than 16 Å from away from the active side, one of these subdomains contains an extended hydrophobic pocket that appeared to be, other than the already characterized EDs, contiguous in space rather than in sequence. Selectively mutating central positions in the domain, either independently or as triple mutants, reduced thermal stability in all cases, but increased the catalytic turnover rate (kcat) of the enzyme by more than 2-fold. Strikingly, structural analysis by 2D-[1H,15N] and 2D-[1H,13C] transverse relaxation optimized spectroscopy (TROSY) NMR and X-ray crystallography revealed no large conformational changes due to the mutations and previously described allosteric pathways of PTP1B remained unchanged.
 
In the absence of global structural change, Torgesen et al. reasoned that an increase in kcat could be driven by side-chain dynamics in the µs – ms time range – a relationship that has been previously shown to govern the catalytic cycle of PTP1B [10]. To proof this hypothesis, they conducted so called constant time 13C Carr-Purcell Meiboom-Gill (ct-CPMG) relaxation dispersion experiments that allow for measurements of side-chain dynamics and extraction of a model that describes the conformational exchange between two populations A and B with the exchange rate kex. In measuring relaxation dispersion in the absence and the presence of a substrate-mimicking inhibitor, they could show that under conditions of catalysis (i.e., when the inhibitor is bound) the overall fast dynamics of the free mutated PTP1B are quenched and that residues cluster into three groups based on their kex values. Although these three groups were also identified for the wildtype, the exchange rates of the groups differed. Remarkably, one group contained many residues of the distal co-evolutionary subdomain described above and showed ~2-fold increase in kex from wildtype to mutant PTP1B – an increase that mirrors the 2-fold increase in kcat that was observed in enzymatic assays. The correlation of catalysis and side-chain dynamics in this group of residues was further supported by the resemblance between kcat and the fitted unidirectional exchange rate kAB. Most importantly, this also reflects the reciprocity of this regulatory pathway, because changes in the active site, e.g., binding of a substrate, changed the dynamics in the subdomain, while perturbations in the subdomain due to mutations influenced catalytic activity.
 
But what is the purpose of this regulatory subdomain? While highly conserved residues of the hydrophobic subdomain support the N-terminal portion of an α-helix, which directly connects to the catalytic loop, less conserved residues flank the C-terminal portion of that α-helix. Accordingly, sequence variations in this less conserved part could enable fine-tuning of the kinetic properties of PTPs without perturbing specificity of the active site or the allosteric regulation.
 
In mechanistically proving the relationship between a co-evolving non-catalytic subdomain and its impact on enzymatic catalysis Torgesen et al.’s study provides a good view on how functional dynamics can leave a footprint in protein sequences throughout evolution. The combination of co-evolutionary analysis with NMR-based analysis of side-chain dynamics proved to be critical in dissecting the regulatory network, otherwise invisible in static X-ray structures. Although this is just one of the few examples in which the energetic connectivity that underlies residue co-evolution was studied experimentally in detail, the study demonstrates that sequence analysis can be instrumental in mechanistic studies of protein dynamics. Finally, and most importantly, by showing that functional dynamics are indeed encoded in sequence, the study supports addition of dynamics as a missing part to the sequence-structure-function paradigm.

References
1. Anfinsen, C. B. Principles that Govern the Folding of Protein Chains. Science 181, 223–230 (1973).
2. Levinthal, C. Are there pathways for protein folding? J Chim Phys 65, 44–45 (1968).
3. Jumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021).
4. Wodak, S. J. et al. Allostery in Its Many Disguises: From Theory to Applications. Structure 27, 566–578 (2019).
5. Göbel, U., Sander, C., Schneider, R. & Valencia, A. Correlated mutations and residue contacts in proteins. Proteins Struct Funct Bioinform 18, 309–317 (1994).
6. Juan, D. de, Pazos, F. & Valencia, A. Emerging methods in protein co-evolution. Nat Rev Genet 14, 249–261 (2013).
7. Torgeson, K. R. et al. Conserved conformational dynamics determine enzyme activity. Sci Adv 8, eabo5546 (2022).
8. Ekeberg, M., Lövkvist, C., Lan, Y., Weigt, M. & Aurell, E. Improved contact prediction in proteins: Using pseudolikelihoods to infer Potts models. Phys Rev E 87, 012707 (2013).
9. Granata, D., Ponzoni, L., Micheletti, C. & Carnevale, V. Patterns of coevolving amino acids unveil structural and dynamical domains. Proc National Acad Sci 114, E10612–E10621 (2017).
10. Torgeson, K. R., Clarkson, M. W., Kumar, G. S., Page, R. & Peti, W. Cooperative dynamics across distinct structural elements regulate PTP1B activity. J Biol Chem 295, 13829–13837 (2020).