Research Snippets

I am taking a multi-scale “Evolution-inspired” and/or “Evolution-informed” approach to understand some of the complex problems. One such area is the problem of “Antibiotic-resistance” or more broadly “Drug-resistance”. This is a global healthcare threat rendering known antibiotic formulations clinically ineffective on a longer term. Emergence of “multi-drug-resistant” bacterial forms has been the most common cause behind deadly nosocomial infections. The scenario is equally grim in all parts of world. This is an “Evolutionary” problem as the resistance is the result of “evolutionary-escape” variants arising because of drug induced “selection”. Using computer simulations, experimental evolution and molecular studies I am attempting to draft an “anti-evolution” approach whereby the “Escape routes” could be constrained and drugs could be made “Evolution-proof”.

Understanding intracellular antibiotic targeting and the associated mechanisms leading to bacterial growth inhibition has been a difficult problem. In one of our recent works (Elife 2021), we discovered the additional intracellular targets of the novel evolution-drug lead which was designed to delay the emergence of antibiotic resistance by inhibiting bacterial DHFR and its Trimethoprim resistant variants. Overexpression of DHFR only partially rescued inhibition of E. coli growth by the drug-lead suggesting that the compound also inhibits a non-DHFR target in the cell. We developed and deployed a multi-scale “systems-biology” guided pipeline to demystify the lead-compound’s intracellular mode of action and its plausible target. We utilized untargeted global metabolomics to create the comparative metabolome under compound treatment. We performed metabolic network analysis to capture the points metabolic flux disruptions and narrow down the potential metabolic points for further investigation. We deployed structural similarity search of the putative targets to identify the additional target of the “drug lead”. We validated in vivo and in vitro that besides DHFR the lead compound inhibits HPPK (folK), an essential protein upstream of DHFR in bacterial folate metabolism. Currently I am working with Prof. Mark Albers (Mark Albers | Harvard PhD Program in Neuroscience) and his team towards deploying this pipeline and integrating phylogentic information to demystify the plausible off-targets of Kinase inhibitors as a part of therapeutic development for ALS and Parkinsonism. This is a part of the HiTS program in the Lab of Systems Pharmacology, Harvard Medical School.

Protein misfolding and aggregation has been linked as one of the primary causative factors for multiple neurodegenerative diseases including Parkinsonism, Alzheimer’s disease and Amyotrophic Lateral Sclerosis (ALS). Understanding the factors leading towards protein misfolding/aggregation has been a hard problem. Aggregation of human cytosolic Cu–Zn superoxide dismutase (SOD1) is implicated in the motor neuron disease, amyotrophic lateral sclerosis (ALS). In one of our earlier studies (Cellular and Molecular Life Sciences 2019) we demystified the folding/aggregation landscape of SOD1 and decoded the conformational communication made by the two metal pockets by deploying a unique application of statistical cluster analysis based on Fourier Transform Infrared spectroscopic readouts. We provided a quantifiable picture of how conformational information at one particular site (for example, the copper-binding pocket) is related to the information at the second site (for example, the zinc-binding pocket), and how this relatedness is transferred to the global conformational information of the protein.

In our follow up work (Elife 2021), we investigated the role of these metal pockets in SOD1 folding/aggregation in membrane environment. Although more than 140 disease mutations of SOD1 are known, their stability or aggregation behaviors in membrane environment are not correlated with disease pathophysiology. We used multiple mutational variants of SOD1 to show that the absence of Zn, and not Cu, significantly impacts membrane attachment of SOD1 through two loop regions facilitating aggregation driven by lipid-induced conformational changes. These loop regions influence both the primary (through Cu intake) and the gain of function (through aggregation) of SOD1 presumably through a shared conformational landscape. Combining experimental and theoretical frameworks using representative ALS disease mutants, we develop a ‘co-factor derived membrane association model’ wherein mutational stress closer to the Zn (but not to the Cu) pocket is responsible for membrane association-mediated toxic aggregation and survival time scale after ALS diagnosis.

In another exciting journey with SOD1 we were exploring the evolutionary aspects of this protein. Superoxide dismutases are one of the primary enzymes of the cellular antioxidant defense system having their origin during the great oxidation era (2.4 to 2.0 Giga Annum/Billion years). Since the rise of oxygen-based metabolism and antioxidant defense systems are evolutionarily coupled, SODs are an interesting protein-family with a deep evolutionary history. Deploying an array of statistical analysis on the evolutionarily sampled sequence space and correlating them on the structural analysis we discovered the evolutionarily critical regions in the protein. We deployed statistical analysis of sequence space to decode evolutionarily co-varying residues in this protein (Biomolecules 2019). These were validated by applying graph theoretical modelling to understand the impact of the presence of metal ion co-factors in dictating the disordered (apo) to hidden disordered (wild-type SOD1) transition. Sequence space analysis coupled with structure networks helped us to map the evolutionarily coupled co-varying patches in the SOD1 and its metal-depleted variants. In addition, using structure network analysis, the residues with a major impact on the internal dynamics of the protein structure were investigated. Our results reveal that the bulk of these evolutionarily co-varying residues are localized in the loop regions and positioned differentially depending upon the metal residence and concomitant steric restrictions of the loops.

Short-lived transient conformations which a protein molecule samples in its “folding” process has a huge implication in deciding the final structure of the protein and its biological relevance. We used Intestinal Fatty Acid Binding Protein (IFABP) as our model protein system and tried to capture these transient on-pathway conformations. IFABP binds to long chain fatty acids and is a key participant in the intracellular transport of long-chain fatty acids coupled with their acyl-CoA esters. IFABP also helps maintain energy homeostasis by functioning as a lipid sensor. Resorting to an ensemble bio-physical approach we observed the presence of a low pH intermediate which is prone to aggregation. Although IFABP is a predominantly beta sheet protein, this low pH was found to contain a significant extent of alpha helical population. We concluded (Biochemistry 2016) that the early helix formation is the result of a local effect, which is originated by the interaction of the neighboring amino acids around the hydrophobic core residues. This early intermediate reorganizes subsequently, and this structural reorganization is initiated by the destabilizing interactions induced by the distant residues, unfavorable entropic costs and steric constrains of the hydrophobic side chains.This study re-emphasizes an overlap between the folding and aggregation landscape of a protein, where the fine-tuning between the local and global effects may be important for the protein to fold efficiently or to aggregate. The subsequent cell-based experiments clearly reveal that IFABP renders protective function over lipid stressed cell. (Cellular Physiology and Biochemistry 2018) Our array of computational analysis shows the change in the inner orchestration in IFABP upon ligand binding.

I teamed up with some extremely passionate scientists (collaborators) with domain expertise in nano(bio)technology. I spearheaded the establishment of cell-based assays for the nanoparticles and together we came up with robust protocols for the use of nanoparticles with a myriad of potential possibilities, spanning from heavy metal sensing to DNA damage identification. We have worked with a range of cell lines and some of our works have gone onto become cover stories in leading journals like Journal of Analytical and Bioanalytical Chemistry.

Currently we are working towards testing these nanoparticle-based probes in clinical contexts, thereby expanding its bio-medical potential. We are also engaging into collaborative dialogues with Industry partners to scale up some of our ventures. Our future ventures would aim at the development of evolution-informed nano-therapeutics.