Prof. Dan Thomas Major
- Chemistry & Biology
- In silico drug development & enzyme design
- Development of the EnzyDock program
- Theoretical study of enzymatic and solution-phase reactions
- Molecular Dynamics and Monte Carlo simulations of proteins
- Renewable energy
- Simulations & modeling of Li- & Na-ion batteries & electrolytes
- AI, Machine learning, Cheminformatics in chemistry, biology & renewable energy
- Extensive interaction with experimental groups
CV
ACADEMIC BACKGROUND
Prof. Major completed his undergraduate studies in chemistry and computer sciences at Bar-Ilan University in 1997. He received his Ph.D. from Bar-Ilan University in 2003 under Prof. Bilha Fischer. During his Ph.D. he worked on molecular properties of nucleotide derivatives, theoretical modeling of G-protein coupled receptors, as well as molecular recognition.
He did a post-doctorate at the University of Minnesota under Prof. Jiali Gao during the years 2003-2006. During his post-doctorate he was involved in development and application of theoretical methods for enzyme catalysis.
Since 2007 he is a Faculty member in the Chemistry Department at Bar-Ilan University. His main research interests are in the field of computational chemistry, computational biochemistry, and computational nanotechnology.
ACADEMIC AWARDS AND DISTINCTIONS
- Excellence in teaching, Rector’s Office, Bar-Ilan University, 2016.
- Krill Prize (Wolf Foundation), 2009.
- Alon Fellowship, 2008-2010.
- Fulbright Scholarship, 2003-2004.
- Excellence in teaching, Rector’s Office, Bar-Ilan University, 2001.
- Eshkol Scholarship, 2000-2003.
- Excellent young scientist from the Israeli Chemical Society, 2001.
- Moris Benin Prize, 1999.
- Bar-Ilan University Chemistry Department Prize, 1998.
- Wolf Foundation Prize, young scientist, 1998.
- Rachel and Reuven Jacobs Prize, 1997.
RESEARCH INTERESTS
- Chemistry & Biology
- In silico drug development
- In silico enzyme design
- Development of EnzyDock, the docking program for enzymes
- Predicting chemistry using AI
- AI, Machine learning, Deep learning, and Cheminformatics of chemistry & biology
- Theoretical study of enzymatic and solution-phase reactions
- Molecular Dynamics and Monte Carlo simulations of proteins
- Software development
- Renewable energy
- Fundamentals of Li- and Na-ion batteries
- Simulations & modeling of Li- and Na-ion batteries
- Simulations & modeling of electrolytes
- AI, Machine learning, Deep learning, Cheminformatics of renewable energy systems
- Experimental interaction
- Most of our projects are conducted in close collaboration with experimental groups
LINKS
- Research Gate: https://www.researchgate.net/profile/Dan_Major
- Google Scholar: https://scholar.google.co.il/citations?user=yt2cPyIAAAAJ&hl=en
Research
- Chemistry & Biology
- In silico drug development
- In silico enzyme design
- Development of EnzyDock, the docking program for enzymes
- Predicting chemistry using AI
- AI, Machine learning, Deep learning, and Cheminformatics of chemistry & biology
- Theoretical study of enzymatic and solution-phase reactions
- Molecular Dynamics and Monte Carlo simulations of proteins
- Software development
- Renewable energy
- Fundamentals of Li- and Na-ion batteries
- Simulations & modeling of Li- and Na-ion batteries
- Simulations & modeling of electrolytes
- AI, Machine learning, Deep learning, Cheminformatics of renewable energy systems
- Experimental interaction
- Most of our projects are conducted in close collaboration with experimental groups
Research Gallery
Enzymes:
Terpene synthases sense their substrates in a binary manner via one of two reactive oxygen atoms. We hypothesize that this alteration in binding, and subsequent chemistry, is due to these enzymes originating from plants or microorganisms.