Grobo-zrnato modeliranje monoklonskih protiteles in njihova lastna nihanja

Perovnik, Simon (author), Ravnik, Miha (mentor)

Grobo-zrnati modeli monoklonskih protiteles so pogosto uporabljeni za $\textit{in silico}$ opis statike in dinamike. V magistrskem delu raziščemo dva pristopa konstrukcije grobo-zrnatih modelov - algoritem strojnega učenja gručenje k-means in metodo bistvene dinamike. Z metodama reproduciramo grobo-zrnate modele, ki so kvalitativno podobni uveljavljenim 3, 6 in 12-delčnim grobo-zrnatim modelom proteinov, s čimer pokažemo smiselnost njune uporabe. V drugem delu naloge lastne nihajne načine, ki smo jih izračunali za uporabo metode bistvene dinamike, koreliramo s hitrostjo agregacije, kvalifikatorjem proteinskih formulacij in z vsoto amplitud nihanj v CDR zankah. Rezultati iskanja linearnih korelacij kažejo na verjetno povezanost lastnih nihajnih načinov in mehanizmov agregacije. V tem kontekstu prepoznamo dva nihajna načina, pri katerih opazimo znatnejše korelacije.

• Language: Slovenian
• Keywords: proteini, modeliranje, grobo-zrnati modeli, gručenje k-means, metoda bistvene dinamike, monoklonska protitelesa, lastni nihajni načini
• Work type: Master's thesis/paper
• Typology: 2.09 - Master's Thesis
• Organization: FMF - Faculty of Mathematics and Physics
• Year: 2024
• PID: 20.500.12556/RUL-158739
• COBISS.SI-ID: 199423491
• Publication date in RUL: 20.06.2024

PEROVNIK, Simon, 2024, Grobo-zrnato modeliranje monoklonskih protiteles in njihova lastna nihanja [online]. Master’s thesis. [Accessed 26 April 2025]. Retrieved from: https://repozitorij.uni-lj.si/IzpisGradiva.php?lang=eng&id=158739

Secondary language

• Language: English
• Title: Coarse-grain modelling of monoclocanal antibodies and their vibration modes

Abstract

Coarse-grained models of monoclonal antibodies are often used for $\textit{in silico}$ description of statics and dynamics. In this thesis, we investigate two approaches to the construction of coarse-grained models - the k-means machine learning algorithm and the essential dynamics method. We reproduce coarse-grained models of proteins that are qualitatively similar to established 3-, 6-, and 12-particle coarse-grained models using these methods, demonstrating the validity of their application. In the second part of the thesis, we correlate the normal modes computed using the essential dynamics method with the aggregation rate, a critical quality attribute of proteins and with the sum of amplitudes in CDR regions. The results of the linear correlation indicate a likely correlation between the normal modes and the aggregation mechanisms. In this context, we identify two oscillatory modes where more significant correlations are observed.

• Keywords: proteins, modeling, coarse-grained models, k-means clustering, essential dynamics method, monoclonal antibodies, normal modes