Cardozo Lab

The function of our lab within the framework of the larger Zolla-Pazner Vaccine Design Team is to determine the structural basis of why certain V3 sequences bind or do not bind to certain broadly neutralizing antibodies.  The first step in this process is to extract by molecular modeling the blueprint, or set of rules, that explains how the antibody can bind to V3 loops with so many different sequences.  This rule or blueprint can then be applied to the set of all known sequences in order to partition them into clusters known to be neutralized by existing antibodies and clusters not yet addressed.  Thus, we narrow down millions of potential V3 loop sequences, each of which is designed to produce a type specific antibody (we would need millions of antibodies induced by our vaccine) into a few clusters for a few broadly neutralizing antibodies.  Then, we will design the ideal V3 sequence to induce the target antibodies in rabbits.  We also identify optimal V3 sequences to explore the unaddressed viruses/sequences. These sequences are then encoded in engineered pseudoviruses and antibodies that bind them are identified.

It has been demonstrated the endoplasmic reticulum (ER) stress is present in all solid tumors and tumor cells respond to ER stress through the activation of the unfolded protein response (UPR). The requirement for UPR in tumor growth raises the possibility of the development of inhibitors that directly inactivate the activators of the UPR for the purpose of chemotherapy. PERK, a transmembrane kinase, is one of such key upstream activoators of the UPR. The final goal of the project is to design an inhibitor of PERK. The first step is the structure prediction of PERK using homology modeling.

Alpna Agarwal

Thesis project: Role of lipid metabolic pathway intermediates as potential ligands of nuclear receptor superfamily

The nuclear receptor superfamily is a large family of ligand-inducible transcription factors that has been targeted for therapeutic purposes including the treatment of cancer, hyper- and hypo-thyroidism, diabetes, cardiovascular disease and others due to its diverse roles. Most of the nuclear receptors have known ligands but many others are still waiting for their ligand partner to be discovered, if any ligand exists for them at all. My project involves the use of docking, a high throughput computational tool for discovering new ligands of nuclear receptor superfamily especially for orphan receptors. Identification of new ligands would provide ideas about the diversity of binding partners for nuclear receptors and their regulation. More importantly, it will provide information about the underlying metabolic pathways controlled by these receptors and their relationship to different patho-physiological conditions that exist in humans.

Second Project: Structure based discovery of ubiquitin ligase SCFb-TRCP inhibitor

The ubiquitin ligase SCFb-TRCP, a ring finger family, multisubunit protein, regulates cell growth and cancer development by regulating the turn over of IkB and b-catenin, Cdc25a, Emi1 and PDCD4. My project involves the rational discovery of an inhibitor that can block the interaction between ubiquitin ligase SCFb-TRCP and its substrates by utilizing the computational tools such as homology modeling, docking and VLS. Lead compounds discovered from this project may be exploited for the development of highly potent and specific drugs with minimum side effects.

Thesis Title: The Use of VLS to Design a Competitive Inhibitor of the Interaction between Aldolase and TRAP in Plasmodium falciparum

Malaria affects hundreds of millions of people worldwide, and hampers the social and economic development of the regions in which it is endemic. While effective treatments for malaria exist, parasite resistance to these drugs is growing rapidly, and there is a critical need for new mechanisms to combat this disease. Several studies have indicated that the interaction between a transmembrane adhesin – TRAP – and intracellular aldolase is crucial for parasite motility and infection, making it a promising new target for drug discovery. My project involves the use of computational tools such as Homology Modeling, Docking, and Virtual Ligand Screening to develop a small molecule inhibitor of TRAP-aldolase binding. Compounds identified through this project may be lead candidates for the creation of a new, safe, and effective anti-malarial agent.

My research involves developing and refining computational methods for predicting antibody binding to V3 loop structures from diverse HIV isolates. I work with MolSoft's ICM toolset and scripting language to coax informative models from heterogeneous data sources. In collaboration with our lab's consortium partners, I hope to find a unique subset of anti-V3 antibodies which would confer protection against all known HIV isolates.