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SUMMARY:Predicting the effect of mutations on protein-protein interactions
  - Nick Goldman\, EMBL
DTSTART:20180130T130000Z
DTEND:20180130T140000Z
UID:TALK100735@talks.cam.ac.uk
CONTACT:Dr Vivien Gruar
DESCRIPTION:"The physical interaction between proteins is central to almos
 t all aspects of biology\, being the fundamental to how inter- and intra-c
 ellular signals\nare processed and integrated\, the recognition of foreign
  bodies by the immune system\, and the assembly of supramolecular structur
 es which dictate the\nphysical and dynamic properties of the cell. Consequ
 ently\, the effect of mutations on these interactions has implications for
  the molecular etiology of\ndisease\, for constraining the permissible sub
 stitutions that can accrue through the course of evolution\, and the desig
 n of protein based therapeutics.\nThis project is to develop a method of p
 redicting how changes in protein sequence will affect the binding affinity
  of protein-protein interactions\,\ntrained from a large new data set of o
 ver 7000 experiments in which the affinities of wild-type and mutant prote
 ins have been measured. The project will\ninvolve integrating features cal
 culated from structure-based biophysical method using machine learning tec
 hniques. The resultant models will then be\nvalidated using external test 
 sets\, cross-validation and bootstrap sampling\, undertaken in such a way 
 as to account for the underlying biases in the\ntraining data. Should time
  permit\, the model may also be applied to pathological mutations in the O
 MIM database and the ""mutations influencing\ninteractions dataset"" from 
 the IntAct database. This project requires\, as a minimum\, competence in 
 programming and using linux and some familiarity with the basics of machin
 e learning. While not essential\, knowledge of molecular biology\, structu
 ral biology or physical chemistry would be advantageous."\n
LOCATION:MR3 Centre for Mathematical Sciences
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