Science

This Physicist Looks at Matter Bottom Up

Satyavani Vemparala, a soft condensed matter physicist, is trying to uncover the mysteries of how atoms interact with each other with the help of computer simulations.

Courtesy: Life of Science

Courtesy: Life of Science

What happens when you add salt to liquid water? At first thought, it may not seem as if you need a physicist to answer this question (it dissolves, duh?), but it turns out you do. For example, there’s no clear picture of what happens to the individual atoms in the water molecules when salt is added. In what way are its structure and properties altered and how exactly are the atoms interacting with each other? “Water seems a simple enough system; we all know what it is, but there are a lot of questions at a fundamental atomic level that are not very clear,” says Vani Vemparala, a physicist who studies tries to answer such questions.

Understanding water at this ultra-zoomed-in level is really important – both from a biological point of view where water is the solvent or the medium in which thousands of chemical reactions and protein interactions in our body take place as well as from an industrial point of view because colloids such as gels and emulsions and polymers such as plastic constantly interact and aggregate in water. The solvent isn’t an idle medium. It may be affecting these interactions in unfound ways. It’s no wonder then that scientists around the world are trying to uncover such mysteries. Vemparala is one of them.

Vani’s simulation of salt in water. Courtesy: Life of Science

Vemparala’s simulation of salt in water. Courtesy: Life of Science

While some of these physicists are experimentalists working on ‘wet’ lab experiments involving real-time techniques like spectroscopy using actual water samples, Vemparala does her research using computer simulations – “I try to design a model that exactly mimics water and not any other liquid.” Vemparala’s simulations can predict how different factors can change the properties of water. For example, water molecules are linked by weak forces called hydrogen bonds. “You can think of water as a network of H-bonds. If I add something that disrupts this network, it can affect the properties of water globally… I’m adding something locally, but the effects may be global. Since water is an important solvent, altering its nature indirectly affects the interactions of the proteins, colloids, etc. sitting in it.”

Why computer models

But how reliable are these computer models, I asked Vemparala. Will they ever be as good enough as the real thing? Probably not, Vemparala readily admits. But the level of detail we’re trying to look at is so high that experiments in the lab using the real thing can never reach this. To better illustrate what she meant, Vemparala described to me another problem she’s working on, which also uses computer simulations.

“There’s a lot of talk these days about antibiotic resistance… the fear of a superbug. Sure, we can keep on making more and more powerful antibiotics, but the danger here is you could give rise to more and more resistant bacteria.” Scientists recognised that a change of paradigm in thinking about this problem was required. Why not turn to nature, they thought. “Take a frog, for example. It lives in the dirtiest water. How does it survive in a place infested with everything?” Vemparala asked. A special peptide (a smaller form of a protein) called magainin present on their skin certainly helps. It acts as the first line of defence against attacking microbes. “Suppose a foreign object enters your body. The immune system takes a while to understand the enemy and then design a defence specifically targeting this object. But besides this, you also need a very coarse line of defenders who just attack anything that can be attacked.” This peptide seemed to be performing this function for the frogs.

Courtesy: Life of Science

An explanation of how a frog survives in dirty water. Courtesy: Life of Science

 

Moreover, this same peptide could be isolated in small amounts from our own skin, tears and stomach linings. “So people realised that we do have these peptides, these inbuilt mechanisms, with which we can fight bacteria. And for some reason, bacteria are unable to develop resistance to these peptides over a time scale. In theory, we now have a set of these things that can replace antibiotics!” said Vemparala.

Can this peptide be replicated in the lab and used as an antibiotic in our markets? “Instead of replicating, which would be really expensive, we can design a polymer that mimics the properties of this peptide,” she said., “There is a polymer industry already, so the entire manufacturing set-up exists.”

But even making these “biomimetic” polymers is no easy task. “You have to realise that nature has taken millions of years of evolution to come up with these right solutions; you need to plug in selectivity – that is, we need a polymer that attacks bacteria but not your own cells,” Vemparala pointed out. At this crossroad, the science requires atomistic-level knowledge. There has to be an understanding of what is happening when the polymer interacts with a cell membrane of one our cells, to be able to predict whether it will work as an antimicrobial.

Labs that work on this problem around the world find this extremely challenging. “Most experiments don’t go into this much detail. They take a petri dish (a round flat container used to culture microbes), put in E.coli (a type of bacteria), put some fluorescent tags and add the polymer solution to be tested. If the E.coli dies, fluorescence is seen and they can say – hey, this polymer works. But at an atomistic level, it is not clear what this polymer is going and doing.”

A necessary trade-off

Computational researchers like Vemparala come in here. Since her post-doc days, Vemparala has been collaborating with an American wet lab experimentalist who designs these polymers. “We take these polymers, build simulations of their designs in complete atomistic detail and give feedback; we tell him – look, this is what happens, this is the best polymer, etc. Now he can go back into further design of these polymers.” This is the kind of complementary relationship that computational researchers have with experimentalists.

With the help of her work, Vemparala envisions a future where bedsheets in hospitals are coated with a polymeric material which can as a natural barrier to infections.

While lab experiments demonstrate large systems (that is, from a zoomed-out point of view) very well, simulations are best at modelling small systems (zoomed-in). Though experiments are trying to come down to the atomistic level, there’s a point beyond which they cannot go. Computational scientists like Vemparala approach the problem from the opposite side, but they can’t model very big systems. “There is that gap between the two approaches, still. The aim is to bridge this gap.”

An example of a 3D simulation. Credit: Life of Science

An example of a 3D simulation. Courtesy: Life of Science

It’s easy to imagine why it’s not easy to watch atoms interact in the lab – they’re simply too tiny – but why is it impossible for computers to simulate large systems? Not so much impossible, revealed Vemparala, as time-consuming.

She continued. “To simulate a protein interaction to show how that system evolves, I need an observation between two times – from t=0 to t=t. This time difference is called the timestep.” To observe the vibrations of atoms like carbon and hydrogen in proteins, the time step needs to be in pico or femtoseconds – that’s one trillionth or quadrillionth of a second. “Let’s say the process of a drug binding to a protein takes one second – this was determined experimentally. Now I have to see this on my machine. If my timestep is a femtosecond, to reach one second I have to do simulations for 10^15 (10 raised to the power of 15) steps. This is huge! That’s why it takes so long.”

Even with top-notch computing power and state-of-the-art simulations, the timescales can only be pushed to maybe hundreds of microseconds, said Vemparala. “That is a very, very short time from an experimental point of view. Since the systems we are trying to simulate are much bigger, we do parallel computing (divide up a system so that more computation can happen simultaneously). Still, it’s difficult to simulate big systems for long times. This is our problem.”

Vemparala calls computational modeling a double-edged sword. “On one end if you do everything atomistically, you get very good detail, but at such high resolution, it’s impossible to do very long times. So you have to have a trade-off somewhere.” We’re still some way from computer models being self-reliant but until then they are of tremendous use to narrow down candidate drugs or, in Vemparala’s case, candidate polymers from thousands to dozens, ending up saving a lot of time and resources.

Childhood and journey

Vemparala grew up in Hyderabad in a middle-class family. Both her parents worked. Like hordes of others, hers too wanted her to become an engineer and Vemparala, having a strength for maths, thought why not. “Someone says write engineering exam so a lot of us just do exactly that. Even the branch of engineering you end up studying is not because you want it but because your rank dictates that. There’s something very strange about this system.” In Vemparala’s case, she was not satisfied with her rank in the entrance exams so ended up taking up a BSc in electronics and maths instead and followed that up with an MSc. “Very few people have the luxury to say this is what I wanted to become from my childhood and I became exactly that. Most stories are in some sense accidents.”

After her M.Sc at the University of Hyderabad, she wanted to go abroad to pursue a Ph.D but being the eldest and most protected daughter, her parents hesitated to send her out of the country. So she did a second master’s in IIT Kharagpur before finally leaving to the US for a Ph.D. What had changed with her parents? Vemparala laughed, “I got married. That’s what changed.” She calls herself a child bride. “I assure you, nobody should get married at 24. People should take their time irrespective of circumstances.”

Luckily, things worked out for Vemparala and her chemical engineer husband who she knew from childhood. Both of them pursued their Ph.Ds in the US. They were apart from each other for around four years because their post-doctoral fellowships separated them. Nevertheless, this time she spent alone is something she cherishes. “Everyone should spend time by themselves. It’s rewarding because you learn to be independent, have your own life and get to explore your city.”

But four years apart is a long time so after their postdocs, Vemparala and her husband applied for multiple faculty positions, hoping that they could finally unite. When they both got jobs in Chennai, her at the Institute of Mathematical Sciences and him at IIT-Madras, they jumped at the chance to move back to India. It has now been ten years Vemparala has been a professor here.

Creating an equal space

Long-distance marriage is a phenomenon very common in academia, said Vemparala. “You’ll hear stories of people being apart for 10 years! It’s not easy to get jobs together.” This has come to be known as the ‘two-body problem’. And the fact that at 32-33 years old, the age at when many start looking for faculty positions, women also have to start thinking about starting a family does not help, says Vemparala. “The biological clock is ticking and so is the tenure clock.” Though she does not have children, Vemparala has known a lot of women to drop out of the sciences due to this.

This is the case all over the world said Vemparala, but US universities have been known to go out of the way at times to accommodate a couple. In India, some institutions have been known to do the opposite and concertedly keep a couple apart. Vemparala is unaware of the actual reason behind this but she has a suspicion – “Maybe they don’t trust a couple who works in the same area and co-authors research. It becomes difficult to say who wrote the paper.” She said that she personally knows of instances where the husband is assumed to have done all the work even though the co-author, his wife is the smarter and more industrious one.

Other than that, Vemparala points out that India actually has some really progressive policies with respect to maternity leave. “We (India) give good maternity leave – two years that you can divide and take at any point of time till the child is 16 years old. This is an excellent policy.” The challenges for India, she feels are the subtle biases. “There are issues like ‘boys’ clubs’ where women are consciously or subconsciously excluded. I’ve seen guys not being able to make eye contact with me and this is more in the sciences than anywhere else!” Some of her best collaborators are men, but Vemparala says that these are the outliers.

Among Vemparala’s four Ph.D students three are male and one is female. “When male students work with female faculty their perspectives broaden. It’s a good thing for female students also – they see you doing this and think: ‘Ah I don’t have to drop out after Ph.D’.”

Respect the basic sciences

Unlike in the health sciences, Vemparala acknowledges that her research may have no immediate impact. “If I tell you I’m putting salt in water and trying to understand its structure it’s difficult to sell this idea to the public.” But she is grateful that IMSc has no funding problems – “in fact our problem is that we underspend. All we need is computers and money for travel.” This pressure taken away gives scientists the freedom to pursue problems of their interest without worrying about applications. “We should have a healthy dose of respect for fundamental research that may not translate to anything but overall increases our understanding of the universe,” said Vemparala strongly.

This article originally appeared in The Life of Science.