This website illustrates my academic research during my postdoctoral work with Harel Weinstein at Weill Cornell Medical College and PhD work with Vincent Voelz at Temple university.

My postdoctoral academic research was focused on understanding function of membrane proteins that clear neurotransmitters from synaptic cleft. These family of proteins are called neurotransmitter:sodium symporters (NSS) since their function depends on electrochemical gradient of sodium ions across membrane. Important members of NSS family include dopamine transporter (DAT), serotonin transporter (SERT), and norepinephrine transporter (NTE) that remove dopamine, serotonin, and norepinephrine from synaptic cleft. Proper control of the amount of neurotransmitter in the synapse is important for many brain functions and imbalances are linked to brain related diseases like depression, bipolar disorders, ADHD, Schizophrenia, and Parkinson’s. In my research, I combine MD simulations with kinetic models based on Markov State Models (MSMs) to understand function of NSS family of proteins.

curriculum-vitae (PDF)

• Journal article: Mechanisms of Lipid Scrambling by the G Protein-Coupled Receptor Opsin, Giulia Morra, Asghar M. Razavi, Kalpana Pandey, Harel Weinstein, Anant K. Menon, George Khelashvili, Structure 26: 356–367, 2018
• Poster: Morra G., Razavi A., Pandey K., Weinstein H., & Menon A., Khelashvili G. (2018, February).The GPCR Opsin Translocates Lipids via a Dynamic Mechanism Specified by Markov State Model Analysis of Molecular Dynamics Trajectories. Poster presentation conducted at the meeting of the Biophysical Society, San Francisco, CA.

Experimental research has shown that the stability of the C-terminal hairpin of Protein G (GB1) increases with the number of tryptophan (Trp) residues. However, the increase in Trp residues also increase the folding time. To understand the roots of this behavior we performed extensive explicit water molecular dynamic (MD) simulations (~10 milliseconds total) on the GB1 hairpin and its Trp zipper mutants.

• Journal article: Kinetic network models of tryptophan mutations in β-hairpins reveal the importance of non-native interactions, Asghar M. Razavi and Vincent A. Voelz, Journal of Chemical Theory and Computation 11: 2801-2812, 2015
• Poster: Razavi, A. M., & Voelz, V. A. (2015, February). Kinetic network models of tryptophan mutations in β-hairpins reveal the importance of non-native interactions. Poster presented at the Biophysical Society 59th Annual Meeting, Baltimore, MD. [PDF]

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Markov state models (MSMs), which model conforma
tional dynamics as a network of transitions between metastable states, have 
been increasingly used to model the thermodynamics and kinetics of
biomolecules. In considering perturbations to molecular dynamics induced
 by sequence mutations, chemical modifications, or changes in external
 conditions, it is important to assess how transition rates change, 
independent of changes in metastable state definitions.

• Journal article: Surprisal Metrics for Quantifying Perturbed Conformational Dynamics in Markov State Models, Vincent A. Voelz, Brandon Elman, Asghar M. Razavi, and Guangfeng Zhou, Journal of Chemical Theory and Computation 10: 5716–5728, 2014
• Poster: Voelz, V., Elman, B., Razavi, A., & Zhou, G. Surprisal metrics for quantifying perturbed conformational dynamics in Markov state models. [PDF]

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The ability of biofilms to attach surfaces is crucial for their life cycle. LapA is a protein that is responsible for this strong adhesion. Another protein called LapG can cleave N-terminal of LapA, hence freeing bacteria from surface. Normally, LapG is in interaction with LapD protein and therefore it is not free to cleave LapA. In this computational/experimental project, our goal is to design small peptidomemtics that can interrupt LapD-LapG interactions, therefore LapG will be free to cleave LapA. Initially, we designed peptidomimetics with 7 and 9 residues (7-mers and 9-mers), however, after fast computational screening using replica exchange implicit solvent MD, 9-mer designs seen to be more potent.

• Journal article: Computational screening and selection of cyclic peptide hairpin mimetics by molecular simulation and kinetic network models, Asghar M. Razavi, William W. Wuest, Vincent A. Voelz, Journal of Chemical Information and Modeling 54: 1425–1432, 2014
• Poster: Razavi, A. M., Wuest, W. M., & Voelz, V. A. (2014, August). Computational screening and selection of cyclic peptide hairpin mimetics by molecular simulation and kinetic network models. Poster presented at the ACS National Meeting, San Francisco, CA. [PDF]

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