Ra'ed S. A. Khashan PhD, RPh

Ra'ed Khashan

Ra'ed S.A. Khashan PhD, RPh

Assistant Professor of Pharmaceutical Sciences

Education

PhD Pharmaceutical Sciences (University of North Carolina at Chapel Hill)

MS Pharmaceutical Sciences (The University of Texas at Austin)

BS Computer Science with minor in Chemistry (Yarmouk University)

BS Pharmacy (Jordan University of Science and Technology)

Research Interests

  • Computer-Aided Drug Design (CADD) (i.e., using molecular modeling software to aid in the rational discovery and optimization of lead compounds)
  • Molecular Dynamics Simulation (i.e., using MD simulation to provide mechanistic understanding of the signal transduction process at molecular level)
  • Development of Efficient Computer Algorithms (i.e., construct competent computer software to solve cheminformatics and bioinformatics problems)

 

For more information, please visit our website at http://www.khashanlab.org

Synopsis

At Molecular Modeling & Simulation Laboratory (MMSL), our research employs computer power to identify novel theoretical models that will aid in discovering new molecular entities, mastering difficult biological processes, and improving the computer-aided drug design process. It crosses the borders of many disciplines such as chemistry, biology, physics, and computer sciences, and so the ultimate goal is to employ the broad background acquired by our research team to unlock the mystery of challenging problems in the field of molecular modeling and simulation. The end result would be advancing the discovery of better therapeutic agents with higher efficacy, potency, and selectivity. Our research projects can be categorized into the following three major research areas.

First, utilizing state-of-the-art hardware and molecular modeling software to discover and optimize lead compounds. This area of research exploits structure-based and ligand-based drug design software tools developed in-house and by others to identify small molecules that can interfere with biological processes to provide pharmacological treatments. Such tools include pharmacophore modeling, QSAR studies, and docking, followed by lead optimization using bioisosteric replacement. In this realm, collaboration with experimentalists will be indispensable to produce a high-quality and successful research outcome.

Second, inspecting the association between structure, dynamics, and function of important drug targets using molecular dynamics simulation techniques. In this area of research group, molecular dynamics (MD) simulation is utilized to achieve mechanistic understanding for important biological processes at molecular level. MD simulation can shed light on the binding process of endogenous molecules to their targets; i.e., what are the conformational changes (induced by this binding) that triggers the signal transduction process. Collaboration with experimentalists is also indispensable in this realm as well, and their data are used to validate the simulation process. If the simulation model is valid, it can be used to provide answers and insights which will advance our understanding of such biological processes, and thus, support rational drug design and discovery process.

Third, developing efficient computer algorithms to solve cheminformatics and bioinformatics problems. This research area employs graph representation of native structures of molecules, macromolecules, or interfaces between them, followed by efficient subgraph mining, to identify frequent and common structural features (motifs) that can then be used to predict the structure or function of biomolecules. This approach was successfully used in the field of cheminformatics to develop molecular descriptors, identify common pharmacophoric groups, generate fragment-based virtual library, and extract ligand-receptor interaction patterns to assess in docking small molecules; a novel idea for which the CCG Excellence Award was granted. The same approach was also applied to solve bioinformatics problems as well; frequent geometric motifs of interfacial residues were extracted and used to assess in docking protein-protein complexes, and frequent geometric motifs of internal residues were extracted and used to assess in identifying correct protein folds.

As a teacher, Dr. Khashan strives to cultivate an interactive setting where students can express themselves freely, be creative, and use critical thinking when solving problems. Every effort is made to use cutting-edge technological tools to help students. Concepts are usually explained very simply so that students can understand it rather than memorize it, thus, they shall never forget it. In addition, being a licensed Pharmacist with over ten years of experience in community pharmacy, he can easily connect the concepts learned to their applications in real world. This will help Doctor of Pharmacy Students understand the concepts better, and clearly see their use in practice. Dr. Khashan is a member of the American Association of Pharmaceutical Sciences (AAPS) and the American Society of Chemistry (ACS), and he has received several teaching awards including the American Association of Colleges of Pharmacy (AACP) Teacher of the Year Award.

Selected Scholarly Activity

Khashan, R. Generating “Fragment-Based Virtual Library” Using Pocket Similarity Search of Ligand-Receptor Complexes. Chapter 3: Fragment-Based Methods in Drug Discovery, Methods in Molecular Biology. Edited by: Anthony E. Klon. 1289, 23-30 (2015).

Khashan, R., Zheng, W. and Tropsha, A. The Development of Novel Chemical Fragment-Based Descriptors Using Frequent Common Subgraph Mining Approach and Their Application in QSAR Modeling. Molecular Informatics, 33 (3), 201-215 (2014).

Khashan, R. FragVLib - A Free Program for Generating "Fragment-based Virtual Library" Using Pocket Similarity Search of Ligand-Receptor Complexes. Journal of Cheminformatics, 4 (1), 18 (2012).

Khashan, R., Zheng, W. and Tropsha, A. Scoring Protein Interaction Decoys using Exposed Residues (SPIDER): A Novel Multi-Body Interaction Scoring Function based on Frequent Geometric Patterns of Interfacial Residues. Proteins: Structure, Function, and Bioinformatics, 80(9), 2207-17 (2012).

Fleishman, S., Whitehead, T., Strauch, E., Khashan, R., Bush, S., Fouches, D., Tropsha, A., et al. Community-Wide Assessment of Protein-Interface Modeling Suggests Improvements to Design Methodology. Journal of Molecular Biology, 414 (2), 289-302 (2011).

Khashan, R., Zheng, W. and Tropsha, A. Fragment based design and biophores using geometric and chemical patterns of interactions at interface of ligand-receptor complex crystal structures. Abstracts of papers presented at the 240th American Chemical Society National Meeting. Boston, MA, August 2010.

Khashan, R., Zheng, W., Wang, W. and Tropsha, A. Development of scoring functions for protein ligand binding based on frequent geometric and chemical patterns of inter-atomic interactions at their interfaces. Abstracts of papers presented at the 234th American Chemical Society National Meeting. Boston, MA, August 2007.

Oloff, S., Khashan, R., Plourde, R. and Tropsha, A. Development of valididated QSAR models of P2Y12 receptor antagonists and& their application to database mining. Abstract of papers presented at the 227th American Chemical Society National Meeting. Anaheim, CA, March 2004.

Contact Information

Office location: McNeil Science and Technology Center, Room 108
Mailing address: Box #80
University of Sciences
600 South 43rd Street
Philadelphia, PA 19104-4495
Office Phone: 215-596-7153
Office Fax: 215-596-1161
Email:

r [dot] khashan [at] usciences [dot] edu