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Pharmaceutical and Molecular Modeling:

Molecular modeling approaches can be a powerful way in studying of biological systems in either atomic or molecular scales. These methods provides us to investigate the chemical interactions formed between the atoms of the proteins, which lead to their secondary and tertiary structures. Classic molecular dynamics (MD) simulations which generate thousands of MD trajectory frames are feasible in sampling of structural conformations and essential in conformational transitions of proteins. Docking simulations can calculate the free energy released upon protein-protein or ligand-protein bindings. There various methods including Poisson–Boltzmann or generalized Born and surface area continuum solvation (MM/PBSA and MM/GBSA) which are used for free energy calculations of biological systems.    


Computer-Aided Drug Design (CADD) :

Molecular modeling methods are used in drug discovery studies, in which large ligand data based can be virtually screened and ranked according their binding affinities inside the targets. Different methods are mainly implemented for this purpose, including docking simulations and Quantitative structure–activity relationship models (QSAR models). The ligands reported from these methods can be good candidates for further analysis in vitro and in vivo.


 

Python Programming for Biologists:

I would so like to begin by writing a quote from Stephen Hawking:

"Whether you want to uncover the secrets of the universe, or you want to pursue a career in the 21st century, basic computer programming is an essential skill to learn."

class simulation(object):

    def __init__(self, time_step, MD_time):

        self.time_step = time_step

        self.MD_time = MD_time 

I highly recommend to the scientists, who work in molecular modeling fields, to be professional at least in one computer programming language - it can be Python, C++, C, TCL or FORTRAN. It must be noticed that we can be smarter that any computers but not faster, so in order to enhance the speed of our calculations, we need to program computers to work for us. I personally prefer to work with an object-oriented language like Python. All the purposes which are required in bioinformatic studies can be easily coded in Python. In addition to the programing by these facilities, we should not forget to develop new modules using our mathematics knowledge. We must keep in our mind that there will be no science, unless mathematics formulas are implemented. Mathematics is considered as a potent key in solving the problems in our researches - it can help us to think how to deal with the problems prior solving them. You are welcome to write me for any help in this area.


Position: Ph.D. in Physical Chemistry.

Address:



E-mail:
Website:
Phone:
Office:
Dr. Ramin Ekhteiari Salmas, Ph.D.
Istanbul Technical University, Faculty of Science,
Department of Chemistry, Physical Chemistry Division,
Ayazaga Campus, Maslak-34469
Istanbul, Turkey.
ekhteiarisalmas@itu.edu.tr
ramin.ekhteiari@gmail.com
https://sites.google.com/site/raminekhteiari/


رامین اختیاری سلماس