20.500.12556/DKUM-72364 Inhibicija samo-replikacije proteinskih fibrilov Inhibition of self-replication of protein fibrils Proteinski fibrili nastanejo z agregacijo delno zvitih proteinov in so odgovorni ali pomembno vplivajo na mnogo hudih človeških bolezni, kot sta Alzeimerjeva ali diabetes tipa II. Samo-replikacija fibrilov je proces, v katerem obstoječi proteinski fibrili katalizirajo nastanek novih fibrilov na način, da ponudijo vezavno površino, kjer se proteini lažje srečajo in agregirajo. To prispeva k naglem in eksponentnem napredovanju bolezni. V magistrski nalogi predstavimo Monte Carlo simulacije računalniškega modela agregacije, v katerega vpeljemo inhibitorje. To so delci, ki se lahko vežejo na površino fibrilov in tako inhibirajo oziroma upočasnijo proces samo-replikacije. Takšen način inhibicije se izkaže za zelo učinkovit, ampak zaradi odbojne interakcije med delci naletimo tudi na pojav makromolekularnega gnečenja, ki povzroči, da se pri določeni pokritosti površine s proteini hitrost samo-replikacije poveča. Edinstven deskriptor hitrosti replikacije najdemo v povprečni velikosti skupka na površino vezanih proteinov, ki nosi informacijo o celotni porazdelitvi agregacijskih skupkov. Predstavimo teorije, ki uspešno razložijo vse značilnosti opažanega obnašanja. S pomočjo mrežnega modela napovemo, katere interakcije med delci na površini imajo največji inhibicijski potencial. Protein fibrils are formed by a process called amyloid aggregation and are implicated in many debilitating human diseases such as Alzheimer's or Type II Diabetes. Self-replication of fibrils is a process by which existing protein fibrils catalyse the formation of new fibrils by offering a surface on which proteins can bind, and therefore facilitate aggregation. This leads to exponential growth of fibril mass and fast propagation of amyloid diseases. In this thesis, we present simulations of a minimal but fairly complex computational model of aggregation with added inhibitory particles that can bind to the fibril surface. It turns out the mechanism of inhibition where inhibitors compete with proteins for the surface is very promising. However, we also find a manifestation of a macromolecular crowding effect which actually promotes self-replication at given protein coverage of the fibril surface. We find a unique descriptor for the rate of replication in the average protein aggregate size. We present theories that successfully explain all characteristics of observed simulation behaviour. By employing a lattice model, we predict which inter-particle interactions on the fibril surface have the largest inhibitory potential. agregacija amiloidov samo-sestavljanje proteinov inhibicija ra\v cunalni\v ske simulacije metoda Monte Carlo nukleacijski mehanizem gne\v cenje makromolekul krajina proste energije statisti\v cna mehanika mehka snov fizikalna kemija Amyloid Aggregation Self-assembly Protein Fibrils Inhibition Course-grained Simulation Monte Carlo Method Nucleation Mechanism Macromolecular Crowding Free Energy Landscape Statistical Mechanics Soft Matter Physical Chemistry true true false [S. Curk] Slovenski jezik Angleški jezik Magistrsko delo/naloga 2018-09-20 14:17:13 2018-11-20 14:58:17 2022-08-01 22:30:59 2019-07-11 19:16:38 2018 0 Maribor 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 577.3(043.2) 24130568 URN:SI:UM:DK:KAMTFQ19 MAG_Curk_Samo_2018.pdf MAG_Curk_Samo_2018.pdf 1 170CFAC6FDD65D387BCBA7547A28D181 098424d94dc559060780bbd03e1f9f11894ace0717c40f2c120f160ff3407f63 5e4931a2-7c10-11eb-bb7a-00155d0001ca 20.500.12556/dkum/51caf013-b6cf-4dea-a484-79039d4ef842 https://dk.um.si/Dokument.php?lang=slv&id=129969 Fakulteta za naravoslovje in matematiko 0 0 0