Srivastav Ranganathan work email
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During my doctoral and post-doctoral research, I have had the opportunity to work on several research projects in the field of protein self-assembly and aggregation, protein-ligand interactions and biomolecular liquid-liquid phase separation. The varied nature of these projects have given me exposure to computational modelling and simulation techniques that span resolution (time and length-scale) as well as computational complexity. I’m proficient at atomistic molecular dynamics (NAMD, GROMACS, AutoDock), coarse-grained simulations (polymer models in LAMMPS), and Monte carlo simulations (Metropolis and kinetic monte Carlo) as well as master-equation-based approaches, as outlined by the several high-quality articles in peer-reviewed journals in my CV. Additionally, I have also learned the ability to transition between existing modelling and simulation tools and to develop my own analysis and simulation tools (using C, C++, TCL, Mathematica and MATLAB) wherever essential. I also have experience in compiling, tuning and optimizing parallel builds of several molecular-dynamics codes in UNIX/LINUX-based environments.Working on biomolecular simulations spanning several lengths and time scales has taught me to conceptualize and model systems with the most essential details, while reducing computational complexity wherever suitable.Simulation Skills:1.) Atomistic Molecular Dynamics Simulations (GROMACS, NAMD)2.) Enhanced Sampling and Non-Equilibrium Techniques (Wang-Landau, Metadynamics, Steered MD Simulations3.) Metropolis Monte Carlo Simulations (Lattice and Off-lattice)4.) Kinetic Monte Carlo (Gillespie Algorithm-based approaches)5.) Coarse-grained molecular dynamics (Go-Model, MARTINI)6.) Meso-scale simulations and coarse-grained polymer simulations using Langevin dynamics (LAMMPS)Modeling Tools:1.) AutoDock, AutoDock Vina, Haddock2.) Homology Modelling using MODELLER3.) Bioinformatics Analysis4.) Discovery Studio5.) Argus LabSoftware/Scripting Experience:1.) C,C++ 2.) Shell and Unix command-based scripting3.) MATHEMATICA4.) MATLAB5.) TCL scripting and molecular manipulations/analysis using VMD6.) LaTex
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Scientific Developer - BiomodelingOpeneye, Cadence Molecular Sciences Sep 2023 - Oct 2024Santa Fe, Nm, Us -
Postdoctoral ScientistHarvard University Oct 2017 - Sep 2023Cambridge, Massachusetts, UsSpatio-temporal organisation of the subcellular space is vital to the way key cellular processes function. While the presence of membrane-bound organelles in compartmentalizing biochemical reactions is well known, recent advances in cell biology have identified droplet-like, high-density clusters of proteins and RNA which form and dissolve in response to specific triggers. The primary focus of my postdoctoral research is to understand this phenomenon of liquid-liquid phase separation of bio-molecules in mechanistic detail using computational models of different resolutions. The key outcome of this work is to understand phase transitions in the cell and their relevance to disease and function. -
Research AssociateIndian Institute Of Technology, Bombay Aug 2017 - Aug 2018Mumbai, Maharashtra, InWorked as a Research Assistant in Prof. Ranjith Padinhateeri’s group at the Department of Biosciences and Bioengineering, IIT Bombay. During my tenure as a Research Assistant, I worked on studying how the importance of non-specific (promiscuous) interactions in the formation of functional biomolecular complexes using coarse-grained polymer simulations. -
Senior Research Fellow (Phd)Indian Institute Of Technology, Bombay Dec 2012 - Feb 2018Mumbai, Maharashtra, InAmyloid aggregation is a phenomenon in which proteins/peptides self-assemble into highly ordered structures that are associated with diseases like Alzheimer's` and Parkinson’s as well as several native biological functions. My doctoral work primarily focuses on providing a broad framework to explain the phenomenon of protein self-assembly into amyloids using computational models of different resolutions.◆ Atomistic Simulations. Molecular simulations were employed to identify the residue-specific andstructural aspects of protein aggregation as well as the role of other modulating factors in regulatingthe phenomenon. Parallel implementation of NAMD and GROMACS were used for these studies.◆ Coarse-grained polymer models. To study the physical fundamentals of amyloid formation and protein aggregation, we employed coarse-grained Langevin dynamics simulations of proteins where the physicochemical features of proteins were coarse-grained into effective simulation variables.◆ Kinetic Models. To understand the kinetics of protein aggregation, and the factors tuning this process, we developed a minimalistic kinetic model for protein aggregation which is analytically solvable and can be simulated using computationally less expensive simulations. A combination of kinetic Monte carlo and a master-equation-based approach was used to study this process.
Srivastav Ranganathan Education Details
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Harvard UniversityComputational Biology -
Indian Institute Of Technology, BombayComputational Biology And Biophysics
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Indian Institute Of Technology, BombayEnvironmental Engineering
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Dy Patil UniversityBiotechnology
Frequently Asked Questions about Srivastav Ranganathan
What is Srivastav Ranganathan's role at the current company?
Srivastav Ranganathan's current role is PhD. Computational Biophysics || Biomolecular Simulations.
What is Srivastav Ranganathan's email address?
Srivastav Ranganathan's email address is ad****@****ail.com
What schools did Srivastav Ranganathan attend?
Srivastav Ranganathan attended Harvard University, Indian Institute Of Technology, Bombay, Indian Institute Of Technology, Bombay, Dy Patil University.
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