BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Talks.cam//talks.cam.ac.uk// X-WR-CALNAME:Talks.cam BEGIN:VEVENT SUMMARY:Structural Biology\, Bioinformatics and Drug Discovery: Learning f rom Targeting Cancer to Combat Mycobacterial Infections - Professor Sir To m Blundell DTSTART:20240205T180000Z DTEND:20240205T193000Z UID:TALK210061@talks.cam.ac.uk CONTACT:Drishtant Chakraborty DESCRIPTION:Knowledge derived from genome sequences of humans and pathogen s has the potential to accelerate diagnosis\, prognosis\, and cure of dise ase. We have moved quickly into an era of precision medicine\, not only in familial diseases where a mutation in a human gene is important\, but als o for understanding somatic mutations in cancer. Equally important\, the g enome sequences of mycobacterial bacterial pathogens in tuberculosis\, cys tic fibrosis\, and leprosy\, can give clues about the choice of protein ta rgets in drug discovery. These include those of existing drugs\, and the d esign of new medicines to combat the increasing occurrence of drug resista nce.\n\nStructure-guided approaches\, both in academia and large pharma\, have informed drug discovery for nearly six decades. Over the past 24 year s\, fragment-based structure-guided techniques have proved effective in le ad discovery for cancer\, particularly in Astex\, a company I cofounded in 1999. In parallel in my academic laboratory in Cambridge University we ha ve used these techniques to target mycobacterial infections not only for t uberculosis\, but also for mycobacterial infections of patients with cysti c fibrosis and leprosy.\n\nComputational approaches\, using both statistic al and machine learning methods\, have proved to be of major complementary value\, particularly in understanding ligand binding and mechanisms of dr ug resistance. These have led to new ideas about repurposing and redesigni ng drugs for tuberculosis and other mycobacterial infections. LOCATION:Pfizer Lecture Theatre\, Department of Chemistry\, Lensfield Roa d END:VEVENT END:VCALENDAR