JOIN USIt is said that our body houses over 25,000 different proteins. If we consider the body as a huge factory of sorts, then proteins are like the workers in it; they deal with security, communication, transportation, structural stability, maintenance, and every other role that one can envision. But unlike actual human workers, proteins are molecules, made up of units called amino acids, strung together like a long chain of beads of different materials, sizes and shapes. Protein sequences are just permutations and combinations of 20 different amino acids.
Prof N Srinivasan and his team at the Molecular Biophysics Unit, Indian Institute of Science (IISc), Bengaluru, have studied the interrelation between protein sequences, their structures and functions. It is the amino acid chains of proteins that fold upon themselves, to give a final 3D conformation that each protein molecule adopts. Except that these 3D conformations are not static. Protein molecules are in perpetual motion, which includes fluctuations in atomic positions, segmental motions and rigid body movement of compact sub-modules.
These dynamics are vital for the protein’s function at different levels. For instance, during these dynamics, when different proteins bump into each other, they talk. And when they talk, they function. Needless to say, protein dynamics and their structural fluctuations are of a much greater consequence than was realised, opening up a whole new dimension to understanding protein biology.
Protein kinase
In a recent Indo-French collaborative effort with Alexandre G de Brevern from French Institute of Health and Medical Research, Paris, researchers at Prof Srinivasan’s lab compared structural fluctuations across a class of proteins called protein kinases. Protein kinases are a large super-family of enzymes involved in communication — sensing and responding to signals. Many diseases, including cancer, have been attributed to the erroneous functioning of specific kinase molecules. The researchers used a computational approach, wherein instead of applying the traditional and expensive method of Molecular Dynamics Simulations, they used a tool called Normal Mode Analysis (NMA) to study structural fluctuations in protein kinases.
NMA calculates the patterns of motion in a variety of structures, including buildings and bridges and is used worldwide. Molecular biologists use NMA to study motions within various bio-molecules. In the case of proteins, this tool predicts the inherent mobility associated with the protein as a whole and also with each sub-part of the protein.
Kalaivani, a PhD student in the Molecular Biophysics Unit, IISc, the lead author of the study, ‘Conservation of structural fluctuations in homologous protein kinases and its implications on functional sites’ in the journal Protein, illustrates this point with an analogy: “For instance, when we look at a gear system, we can anticipate how a part would move, based on how it is linked to another. This is what NMA does — it looks at the structure of the protein, then it computationally determines, based on the connectivity between atoms, how each part of this molecule would move and how that affects the motion in its neighbouring parts, thus calculating how the protein molecule would move, as a whole.”
The researchers compared the structural fluctuations of a particular kinase with other related and unrelated kinases and showed that the inherent motions of these molecules are more similar across functionally similar and related protein kinases, than the not-so-closely-related kinases. The more closely related the 2 proteins, the more they tend to move in a similar manner.
Interestingly, the researchers could identify regions (specific sub-parts) of different related kinases that exhibited extremely similar structural fluctuations. These specific regions turned out to be the part of the proteins that were actually involved in the characteristic protein interactions and thus responsible for their functional activity.
“One of the best applications of this (study) is in drug design,” says Kalaivani. When trying to create a new drug, chemists usually try and design drugs that bind to aberrant protein kinases, thus curbing their deviant behaviour. They target regions with a sequence unique to the kinase-gone-wrong and design molecules that can bind only to that particular site. But, at times it is observed that the drug also interacts with unintended proteins, causing severe side effects. And then, the drug already having passed through many stages of research and development, finally fails during clinical trials.
How is it that a drug designed to bind to a specific unique sequence of amino acids, ends up interacting with a whole bunch of unintended molecules? The answer lies in 3-dimensional structures. Parts of 2 different protein molecules, despite not sharing the same sequence, can possibly have the same structure. Vice-versa, the same sequence of amino acids, in different proteins can sometimes form different 3D structures, depending on its neighbouring amino acids.
Apparently, completely different amino acid sequences within entirely different protein kinases can result in the formation of the same local 3D structure. So, even when we identify a unique sequence of amino acids that is found only on our protein of interest, it is possible that the drug, designed to specifically bind to one protein, may find itself binding to a number of unintended binding partners within the cell, causing an unexpected biological response, and resulting in unwanted side effects.
“It’s like a jigsaw puzzle,” explains Kalaivani, “although, a number of pieces can physically fit into a given spot, the picture is made perfect only when the correct piece is placed in its spot. Using NMA as a tool, we are adding another dimension in screening for drug binding sites. Over and above assessing the structural compatibility of the drug and its target protein, one can look for regions on the target protein showing a unique pattern of mobility and confidently begin with designing drugs that uniquely interact only with the desired target.”
(The author is with Gubbi Labs, Bengaluru)