Nagarajan Vaidehi, Ph.D.
- Professor, Department of Molecular Imaging & Therapy
Nagarajan Vaidehi, Ph.D.
- Developing physics-based computational methods to study protein structure, dynamics and drug design
- 2018 - present, Professor, Department of Molecular Imaging & Therapy, Diabetes Metabolism Research Institute, City of Hope, Duarte, CA
- 2005 - 2018, Professor, Department of Molecular Immunology, Beckman Research Institute of City of Hope, Duarte, CA
- 1998 - 2005, Director of Biosimulations, Materials and Process Simulation Center, Caltech, Pasadena, CA
- 1994 - 1998, Senior Scientist, Materials and Process Simulation Center, Caltech, Pasadena, CA
- Molecular Imaging & Therapy
- 1986, Indian Institute of Technology, Ph.D., Theoretical Chemistry
- 1981, Indian Institute of Technology, M.Sc., Chemistry (minor- Physics and Mathematics), Highest Honors
- 1991 - 1994, Post-doctoral Fellow at Caltech
- 1990 - 1991, Post-doctoral Fellow, University of Southern California, Prof. A. Warshel
- 1989 - 1990, Post-doctoral fellow at University of Exeter, UK
Our research projects include:
- Development of constrained molecular dynamics methods – GNEIMO
- Development of coarse grained conformational sampling method for G-protein coupled receptors (GPCRs) – GPCRSimKit
- Development of computational method for designing thermostable mutants for GPCRs – LITiConDesign
- Development and application of computational methods to identify allosteric sites for drug design in protein-protein complexes – AlloBindSite
- Application of these methods to design drugs with functional specificity for GPCRs targeting pancreatic cancer and other cancers – Chemokine
A hierarchical framework for constrained molecular dynamics method
- Study of large scale conformational dynamics of proteins wherein we showed the NMR based ensemble of conformations of calmodulin was sampled by GNEIMO method.
- Structural refinement of homology models of proteins.
- Ab initio folding of simple proteins.
A multiscale computational framework for studying G-protein coupled receptors (GPCRs)
A computational method for designing thermostable mutants for GPCRs
G-protein coupled receptors are membrane proteins and play an important part in cellular signal transduction. Solving the three dimensional structures of these proteins is critical and is becoming viable lately. However the biggest bottleneck in obtaining sufficient quantities of the pure protein is that GPCRs are conformationally flexible, and hence aggregate at higher concentrations during purification. A solution to this challenge is to derive thermostable mutants of GPCRs that are amenable to purification techniques. However the experiments involved in identifying the residue positions that lead to thermostability as well as the thermostable mutants is both expensive and time consuming. There are about 300 mutations that need to be done just to be able to identify positions that lead to thermostability. Our goal is to develop a fast computational screening method, LITiConDesign to design and thermally stable mutants of several GPCRs. We will target class A GPCRs in their agonist and antagonist bound structures. This project is in collaboration with Dr. Chris Tate (MRC, Cambridge, UK) and Dr. Reinhard Grisshammer (NINDS).
Development of computational method to identify allosteric sites for drug design in protein-protein complexes
Computational methods for studying the dynamics of GPCR conformations: In my laboratory, we have developed novel computational methods to map the potential energy surface and the dynamics of GPCR conformational states and use them for drug design, as seen in the figure, which shows the potential energy surface of an antagonist bound GPCR (right) and the binding site of an antagonist bound to a GPCR used for drug design (left). We have applied these techniques to design drugs for β adrenergic receptors (targets for hypertension and asthma) and chemokine receptors. Using these methods, we also design thermally stable mutant GPCRs for several class A GPCRs that would strongly aid the crystallization of these receptors.
Development of computational methods to identify allosteric sites to disrupt protein-protein interactions: We are developing computational alanine scanning methods.