MS12-P04 Identifying Amyloid and Partially Amyloid Structures from the Protein Data Bank Vince Grolmusz (Eötvös University, PIT Bioinformatics Group, Budapest, Hungary) Kristóf Takács (Eötvös University, PIT Bioinformatics Group, Budapest, Hungary) Bálint Varga (Eötvös University, PIT Bioinformatics Group, Budapest, Hungary)email: grolmusz@pitgroup.orgThe Protein Data Bank (PDB) contains 135 000 entries today. From these, relatively few amyloid structures can be identified, since amyloids  are insoluble in water. Therefore, mostly solid state NMR-recorded amyloid structures are deposited in the PDB. Based on the geometric analysis of these deposited structures we have prepared an automatically updated webserver, which generates the list of the deposited amyloid structures, and, additionally, those X-ray crystallography identifyid globular protein entries, which have amyloid-like substructures of a given size and characteristics. We have found that applying only the properly chosen geometric conditions, it is possible to identify the deposited amyloid structures, and a number of globular proteins with amyloid-like substructures. We have analyzed these globular proteins and have found that most of them are known to form amyloids more easily than many other globular proteins. Our results relate to the method of [1], who have applied a hybrid textual-search and geometric approach for finding amyloids in the PDB.

If one intends to identify a subset of the PDB for some applications, the identification algorithm needs to be re-run periodically, since in 2017, on the average, every day 30 new entries were deposited in the data bank. Our webserver is updated regularly and automatically, and the identified amyloid- and partial amyloid structures can be viewed on-line or their list can be downloaded from the site
https://pitgroup.org/amyloid. 
References:

1, Stanković, I. et al. (2017): Construction of Amyloid PDB Files Database. Transactions on Internet Research. 13 (1): 47-51.

Keywords: PDB, amyloids, webserver