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Modelling antibody orientation at bacterial surfaces

Kumra, Vibha LU (2017) FYTK02 20162
Computational Biology and Biological Physics
Abstract
Bacteria and humans have co-evolved since their common existence. They have thereby developed very specific defence and target mechanisms against one another. Understanding the complex biomolecular processes behind these interactions can be of great use for developing treatments against bacterial diseases. The aim of this thesis project was to verify, and introduce a model for understanding, the implications of previous findings regarding the binding tendencies of antibodies to bacterial surface proteins. Antibodies typically bind to substances foreign to the host via regions referred to as Fab, exposing the Fc region that can then be recognized by the immune system. However, certain bacterial proteins express a so called IgGFc-binding... (More)
Bacteria and humans have co-evolved since their common existence. They have thereby developed very specific defence and target mechanisms against one another. Understanding the complex biomolecular processes behind these interactions can be of great use for developing treatments against bacterial diseases. The aim of this thesis project was to verify, and introduce a model for understanding, the implications of previous findings regarding the binding tendencies of antibodies to bacterial surface proteins. Antibodies typically bind to substances foreign to the host via regions referred to as Fab, exposing the Fc region that can then be recognized by the immune system. However, certain bacterial proteins express a so called IgGFc-binding region enabling additional binding via Fc. This can prevent these bacteria from being recognized and eliminated from the host organism. The goal of this model was to calculate the binding orientation probability of antibodies at bacterial surfaces. The binding probability was calculated for S types of antibodies characterized by their concentration c and binding constant K to a specific site i on the bacterial protein of length N . Transfer matrices, describing the probability of site i being in a certain state m, provided site i + 1 is in state m0 , were generated. Each antibody was ascribed a binding constant
from a gaussian distribution of standard deviation σ and mean value KD . Additional experiments were performed in order to confirm whether or not the previous experimental findings were reproducible. The model was found to best fit the experimental values for the parameters σ = 45 (µg/ml)−1 and mean KD = 140 (µg/ml)−1 . The dissociation constant for the Fc binding region was determined to be 1500 (µg/ml)−1 Both our experimental and theoretical results imply that bacterial proteins with a IgGFc-binding region effectively reduce the amount of Fab-binding. The
theoretically obtained values were consistent with the measured experimental values. This model incorporated many important aspects of the antibody-bacterial protein binding system and was an improvement from the previous model. However, in order to draw any general conclusions about the model it is necessary to perform additional experiments with a higher level of precision. (Less)
Popular Abstract (Swedish)
Varför gör vissa bakterier oss sjuka men inte andra? Hur kommer det sig att vissa bakterier lyckas överleva och infektera särskilda delar av kroppen men väldigt sällan andra? Bakterier och människor har evolverat länge tillsammans och har därmed lyckats utveckla specifika angrepps och försvarsmekanismer mot varandra.

Det är känt sedan tidigare att några bakterier uttrycker proteiner med förmågan att binda humana proteiner på ett satt som gör det möjligt for dessa bakterier att undgå vårt immunförsvar. Dessa bakterier överlever vanligtvis i hals och på hud men kan ge upphov till allvarliga invasiva infektioner.

Detta arbete ämnar undersöka interaktionen mellan bakterier med den ovannämnda förmågan och människor. Inbindning till... (More)
Varför gör vissa bakterier oss sjuka men inte andra? Hur kommer det sig att vissa bakterier lyckas överleva och infektera särskilda delar av kroppen men väldigt sällan andra? Bakterier och människor har evolverat länge tillsammans och har därmed lyckats utveckla specifika angrepps och försvarsmekanismer mot varandra.

Det är känt sedan tidigare att några bakterier uttrycker proteiner med förmågan att binda humana proteiner på ett satt som gör det möjligt for dessa bakterier att undgå vårt immunförsvar. Dessa bakterier överlever vanligtvis i hals och på hud men kan ge upphov till allvarliga invasiva infektioner.

Detta arbete ämnar undersöka interaktionen mellan bakterier med den ovannämnda förmågan och människor. Inbindning till bakterie mättes i olika halter av humant protein, så kallade antikroppar. En teoretisk modell for att räkna ut sannolikheten for typ av inbindning att ske har utvecklats. Interaktionen involverar många olika typer av antikroppar som har olika benägenhet att binda in till olika platser på det bakteriella proteinet. Dessutom kan alla antikroppar “vändas om” och binda starkt till en plats på det bakteriella proteinet som på så sätt inaktiverar antikropparnas försvar. Proteinerna vinner på att hamna i ett lägre energitillstånd. De frigör energi vid inbindning och benägenheten att binda in är beroende av hur mycket energi kan frigöras.

Resultaten visade att den normala antikroppsbindningen minskas signifikant i närvaro av bakteriernas proteindel med formågan att undgå immunförsvaret. Modellen visar sig stämma väl överens med mätningarna. Mätningarna kunde dock variera lite for mycket och det behövs flera experimentella resultat for att kunna dra någon slutsats om hur väl modellen beskriver den verkliga interaktionen. (Less)
Please use this url to cite or link to this publication:
author
Kumra, Vibha LU
supervisor
organization
course
FYTK02 20162
year
type
M2 - Bachelor Degree
subject
language
English
id
8899158
date added to LUP
2017-01-25 14:39:00
date last changed
2017-10-06 15:56:13
@misc{8899158,
  abstract     = {Bacteria and humans have co-evolved since their common existence. They have thereby developed very specific defence and target mechanisms against one another. Understanding the complex biomolecular processes behind these interactions can be of great use for developing treatments against bacterial diseases. The aim of this thesis project was to verify, and introduce a model for understanding, the implications of previous findings regarding the binding tendencies of antibodies to bacterial surface proteins. Antibodies typically bind to substances foreign to the host via regions referred to as Fab, exposing the Fc region that can then be recognized by the immune system. However, certain bacterial proteins express a so called IgGFc-binding region enabling additional binding via Fc. This can prevent these bacteria from being recognized and eliminated from the host organism. The goal of this model was to calculate the binding orientation probability of antibodies at bacterial surfaces. The binding probability was calculated for S types of antibodies characterized by their concentration c and binding constant K to a specific site i on the bacterial protein of length N . Transfer matrices, describing the probability of site i being in a certain state m, provided site i + 1 is in state m0 , were generated. Each antibody was ascribed a binding constant
from a gaussian distribution of standard deviation σ and mean value KD . Additional experiments were performed in order to confirm whether or not the previous experimental findings were reproducible. The model was found to best fit the experimental values for the parameters σ = 45 (µg/ml)−1 and mean KD = 140 (µg/ml)−1 . The dissociation constant for the Fc binding region was determined to be 1500 (µg/ml)−1 Both our experimental and theoretical results imply that bacterial proteins with a IgGFc-binding region effectively reduce the amount of Fab-binding. The
theoretically obtained values were consistent with the measured experimental values. This model incorporated many important aspects of the antibody-bacterial protein binding system and was an improvement from the previous model. However, in order to draw any general conclusions about the model it is necessary to perform additional experiments with a higher level of precision.},
  author       = {Kumra, Vibha},
  language     = {eng},
  note         = {Student Paper},
  title        = {Modelling antibody orientation at bacterial surfaces},
  year         = {2017},
}