Skolnick     
Jeffrey Skolnick
Director
Center for the Study of Systems Biology
Georgia Institute of Technology

"PROGNOSTIX: A pipeline for personalized diagnostics and drug treatments"

Wednesday, April 19, 4:00 PM
Packard Lab 466

Abstract:   How can one convert the plethora of information provided by Next Generation Sequencing into clinically actionable suggestions for diagnostics and drug treatments? We describe the key tools in the PROGNOSTIX methodology that addresses these issues. We first present the ENTPRISE algorithm for predicting the likely disease association of missense variations. Compared to existing algorithms such as FATHMM whose false positive rate is 12.9%, the false positive rate of ENTPRISE is 5.4%. ENTPRISE and related tools thus provides a list of putative driver proteins for the disease(s) of interest. We then describe a comprehensive exome scale approach that predicts human protein targets and side effects of small molecules. For drug-protein interaction prediction, FINDSITEcomb is employed. Successful applications of the methodology include the identification of novel antibiotic leads, antiaging molecules and a repurposed drug successfully used to treat a form of chronic fatigue syndrome. We then applied the methodology to the entire human exome. Our predictions show that drugs are quite promiscuous, with the average (median) number of human targets per drug of 329 (38), while a given protein interacts with 57 drugs. Thus, drug side effects are inevitable and existing drugs may be useful for repurposing, with only ~1,000 human proteins likely causing serious side effects. Most importantly, we can predict the probability that a given small molecule will pass or fail an FDA Phase 1 safety trial with 80% precision and recall. The methodology is free to the academic community on the DR. PRODIS (DRugome, PROteome, and DISeasome) webserver at http://cssb.biology.gatech.edu/dr.prodis/. DR. PRODIS provides protein targets of drugs, drugs for a given protein target, associated diseases and side effects of drugs.

Bio:   Jeffrey Skolnick is the Director of the Center for the Study of Systems Biology in the School of Biological Sciences at the Georgia Institute of Technology. He is also the Mary and Maisie Gibson Chair in Computational Systems Biology and a Georgia Research Alliance Eminent Scholar in Computational Systems Biology. He attended graduate school in Chemistry at Yale University, receiving a Ph.D. in Chemistry in polymer statistical mechanics. He then held a postdoctoral fellowship at Bell Laboratories. Next, he joined the faculty of the Chemistry Department at Louisiana State University, Baton Rouge. Then, he moved to Washington University, where he was subsequently appointed Professor of Chemistry. Following an interest in biology, he joined the Department of Molecular Biology of the Scripps Research Institute, where he held the rank of Professor. Among his awards is Southeastern Universities Research Association (SURA), Distinguished Scientist Award an Alfred P. Sloan Research Fellowship and he is a Fellow of the American Association for the Advancement of Science, the Biophysical Society, and the St. Louis Academy of Science. He is the author of over 370 publications, has an h-index of 81, and has served on numerous editorial boards including the Scientific Reports, Peer J, Biology Direct, Biophysical Journal, Biopolymers, Proteins, and the Journal of Chemical Physics. He is also a cofounder of an early stage drug discovery company, PanXome and a structural proteomics company, GeneFormatics, and his software has been commercialized by Tripos.

© 2014-2016 Computer Science and Engineering, P.C. Rossin College of Engineering & Applied Science, Lehigh University, Bethlehem PA 18015.