Dans les champs de l'observation le hasard ne favorise que les esprits préparés.
In the fields of observation, chance only favors prepared minds.
- Louis Pasteur [Lecture, University of Lille (7 December 1854)]

Research Interests

Dr. Abrol’s research lab is focused on developing and using computational methods to probe how protein structure and biochemical (protein-ligand and protein-protein) interactions of G protein-coupled receptors (GPCRs) determine cellular signaling and physiology, as well as how this knowledge can be used for the rational design of drugs targeting GPCR signaling pathways.

GPCRs are integral membrane proteins that form the largest superfamily in the human genome. The activation of these receptors by a variety of bioactive molecules regulates key physiological processes (e.g., neurotransmission, cellular metabolism, secretion, cell growth, immunity, differentiation), through a balance of G protein-coupled and beta-arrestin-coupled signaling pathways. This has made them targets for ~50% drugs in the clinic. A molecular and structural understanding of these GPCR signaling pathways will have a broad impact on our understanding of cellular signaling and on drug discovery efforts targeting GPCRs.

Research in the Abrol Lab lies at the interface of Chemistry and Biology, where they are using computational biophysics and structural bioinformatics based methods to gain mechanistic insights into the biochemistry of GPCR signaling. The research is following three major themes to connect the sequence, structure, and signaling of GPCRs:

Theme 1: From Structure to Signaling - How do GPCRs behave as allosteric machines and exhibit biased signaling?
There are many challenges in experimental approaches to navigate the multiple conformations of GPCRs that can describe their pleiotropic function. We are developing the next generation of computational methods to describe the conformational space available to GPCRs (especially the high-energy functionally important conformations) and to predict their effects on intracellular signaling.

Theme 2: From Sequence to Structure - How do GPCRs fold in the membrane?
There are several examples of disease-associated single point mutations in GPCRs, in which the mutant GPCR is not stable enough to escape the quality control of endoplasmic reticulum, but can be rescued by pharmacological chaperones to reach its final membrane destination. These partially stable receptor single-point mutants require looking at the thermodynamics of how they insert and fold in the membrane to gain a mechanistic insight into their instability. We are developing methods to probe how small alpha-helical membrane proteins get inserted into the lipid bilayers by the Sec61 translocon machinery, to eventually understand this process for GPCRs.

Theme 3: From Sequence to Signaling - How do GPCR sequence variations (receptor paralogs or mutations) lead to observed signaling and disease?
Sequences contain a wealth of functional information, which has led to the development of many computational approaches to extract this information. We are developing structural bioinformatics tools that combine evolutionary methods using closely-related paralog and ortholog sequences with their structural and functional information to understand the role of specific residues and structural motifs in the functional divergence of GPCRs.

Theme 4: Structure Based Drug Design and Discovery - How to rationally design treatments targeting specific biochemical and pathophysiological pathways?
A mechanistic understanding of biochemical pathways implicated in disease pathologies can identify promising protein targets and therapeutics. We are applying structure-based approaches to increase this understanding so that we can discover drugs/therapeutics targeting diseases like diabetes, melanoma, breast cancer, and neurodegenerative diseases like Parkinson's, Alzheimer's, and multiple sclerosis. We are also applying these approaches to design the next generation of therapeutics with high efficacy and reduced side-effects.

Information for students interested in joining the lab

Students from Chemistry, Biochemistry, Biology, Physics, Math, and Computer Science will find highly multi-disciplinary research opportunities in the Abrol Lab, aimed at developing computational methods or applying existing methods or developing and applying new methods to understand the molecular mechanisms behind cellular signaling. Prior experience with computer programming is not necessary, however, students should be open to learning some programming as part of the research. There will also be joint research opportunities combining structural modeling of proteins with biochemical and biophysical experiments.