Line 16: | Line 16: | ||
<div class='textbody'> | <div class='textbody'> | ||
− | <p>Determine which constructs would be interesting</br> | + | <p><b>1.</b>Determine which constructs would be interesting</br> |
− | <p>Interpret our experiments results</br> | + | <p><b>2.</b>Interpret our experiments results</br> |
</p> | </p> | ||
− | + | </div> | |
<div class='textbody h2'> | <div class='textbody h2'> |
Revision as of 00:42, 8 December 2018
Modeling
Our project is based on the consequences of a conformational change of antimicrobial peptides. Results generated by the testing group showed that MIC is not a reliable criteria to understand the activity of our StarCores while it has been previously used for species. It was crucial to have some models to:
1.Determine which constructs would be interesting
2.Interpret our experiments results
RESULTS
Our Modelling workflow could be summed up as :
-> Two hackathons to screen the most promising cores and AMPs based on rationnal criteria.
-> Homology modeling of the 210 constructs with Modeller on Pymol.
-> Molecular Dynamic simulations to test the stability of the predicted structures using Yasara and Inserm Cluster.
I. Homology Modelling
Followed by cores and AMPs selection, we were interested in determing the model of the fusion. This led us to the modeling expert, Antoine Tally, who guided us to standardise a protocol for our analysis. Aim: To construct an atomic-resolution model of Star-core monomer via comparative homology modelling
Making fusion protein of 2 known PDB files using CHIMERA
Monomer construct on Chimera using Modeller graphic interface
Construct optimization on Chimera
Superpozition on Pymol thanks to handmade script called Superpoz.py
II. Molecular dynamic simulation
OBJECTIVE:
-Study behaviour of fusion molecule in vicinity of cell.
-Assess the stability of Star cores in terms of protein folding, structural characteristics and energy.
-Define constraints and parameters for simulations.
-Use Yasara to analyze MDS data.
CONCLUSION
In this project, we combinatorially fused a set of known AMPs to structurally diverse, self-assembling protein cores to produce star-shaped complexes.
We selected 14 cores that already exist and 15 AMPs, hence over 200 fusions were designed and expressed in a cell-free system, then screened for activity, biocompatibility, and membrane selectivity.
To study the behaviour of in-vitro synthesised molecules we designed the fusion molecules for all constructs using Chimera, Modeller and Pymol. We visualized the assembly and fusion monomer (core + AMP) and studied their behavioural attributes, changes in folding of alpha helix and beta sheath using Yasara as it mimics atom behaviour in real life. Using visualization and MDS studies we confirm that proteins folds well and on an average maintain constant RMSF (Root Mean Square Fluctuations) with all amino acid residues, also expressed well in cell free system.
METHODS
These protocols were defined under certain parameters:
AMPs are relatively small, so we assumed that structural changes would be minimal, enabling us to perform Homology modelling.
AMPs are only fused on the N/C terminals thus oriented outside the homomultimeric self-assembling protein, the modelisation should keep the geometry of the nude core, displaying the fusionned peptides on the surface of the core. It enabled us to structure superposition.
However we verified this hypothesis with our stability MD assay developped with Marc Baaden.
Homology Modelling
What is homology modelling?
Homology modelling is comparative modelling of proteins. It is a comparative protein modelling method designed to find the most probable structure for a sequence given its alignment with related structures. The three-dimensional (3D) model is obtained by optimally satisfying spatial restraints derived from the alignment and expressed as probability density functions (pdfs) for the features restrained. For example, the probabilities for main-chain conformations of a modelled residue may be restrained by its residue type, main-chain conformation of an equivalent residue in a related protein, and the local similarity between the two sequences. Several such pdfs are obtained from the correlations between structural features in 17 families of homologous proteins which have been aligned on the basis of their 3D structures. The pdfs restrain C alpha-C alpha distances, main-chain N-O distances, main-chain and side-chain dihedral angles. A smoothing procedure is used in the derivation of these relationships to minimize the problem of a sparse database. The 3D model of a protein is obtained by optimization of the molecular pdf such that the model violates the input restraints as little as possible. The molecular pdf is derived as a combination of pdfs restraining individual spatial features of the whole molecule. The optimization procedure is a variable target function method that applies the conjugate gradients algorithm to positions of all non-hydrogen atoms. The method is automated. We used modeller to predict all our models. The steps are:
1. Obtain reference PDB structures representing the core and antimicrobial peptide protein monomers | 2. Use MODELLER via CHIMERA interface for homology modelling | 3. Choose the best fusion protein model that represents the Star core monomer |
---|