Drug Discovery Lab – Dr. Avraham Samson – ד”ר אברהם סמסון
Research| Lab Members | Publications| Courses | Contact
Cell Phone: +972-54-7958894
Location: Building A, Room 101
Development of computational tools for drug design
To assist drug design, we are developing computational tools to predict ligand binding sites. In the past, we developed a structure based program using normal mode accompanied exposure changes to predict ligand binding sites with 90% accuracy. As one would expect we are currently attempting to increase the accuracy to 100%. In addition, we are developing ligand optimization programs based on local motion in the binding site. In particular, we are optimizing drugs which bind to acetylcholine receptors, and acetylcholine esterases, and improve concentration in patients with Alzheimer’s and dementia.
Calculation of biomolecular motion and correlation with biological activity
To capture the motion involved in biological mechanisms, we are developing computational tools using molecular dynamics and normal modes. With these tools, we were able to calculate the motion associated with channel opening of the acetylcholine receptor, and show how this motion is inhibited by binding of snake toxin. In addition, we could calculate the conformational change exhibited by prion proteins and show the infection propagation in the mad cow disease. We are currently calculating motion of various biomolecules such as HIV glycoproteins, enzymes, receptors, channels, and the ribosome to explain biological activity.
Nuclear magnetic resonance (NMR)
NMR protein structure determination
We are determining the three-dimensional structure of proteins using NMR spectroscopy. In the past, we solved the structure of snake toxin, receptors, and HIV peptides. Now, we are determining the structures of small proteins, and peptides. In particular, we are solving the structure of prion peptides to test if our predicted conformational changes may be observed thus uncovering prion infectivity. In addition, we are using NMR spectroscopy to verify our bioinformatic predictions of drug design.