Computational protocol: A multifaceted study of stigma/style cysteine-rich adhesin (SCA)-like Arabidopsis lipid transfer proteins (LTPs) suggests diversified roles for these LTPs in plant growth and reproduction

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Protocol publication

[…] The amino acid sequences of 104 Arabidopsis LTPs were aligned with 29 plant LTPs from other species using default parameters (an open gap penalty of 10 and an extended gap penalty of 0.1 in pairwise alignments, an extended gap penalty of 0.2 in the multiple alignment, and a delay divergent setting of 30%; Gonnet 250 protein weight matrix) of ClustalX 2.0.10 (), and the aligned sequences were analysed using PAUP* 4.0 (). Pairwise amino acid divergence was calculated and a Neighbor–Joining (NJ; ) tree was constructed using PAUP*. Support for groups was examined by 1000 bootstrap replicates (). Parsimony analysis was also performed using the heuristic search option with tree–bisection–reconnection (TBR) branch swapping and the multiple parsimony (MULPARS) option on. A total of 591 aligned characters were used for maximum parsimony (MP) analysis. There are 84 constant characters, 222 variable but parsimony uninformative characters, and 285 parsimony informative characters in the data matrix. The heuristic search found 232 equally most parsimonious trees (tree length=7584, consistency index=0.4248, retention index=0.5050), and tree topologies were very similar to the NJ tree. Therefore, the discussion was based on the strict consensus tree of MP analysis. [...] Structural homology modelling for SCAs, tobacco LTP2, and Arabidopsis LTPs was performed using the SWISS-MODEL web server (http://swissmodel.expasy.org) (). The crystal structure of maize LTP with Protein Data Bank (PDB) () code 1MZL () was used as a structural homology template (∼56% identity to SCA, a lily LTP) (). The ESI clustering was performed using the computational protocol AESOP (Analysis of Electrostatic Similarities Of Proteins) (Kieslich et al., 2010). The spatial distributions of electrostatic potentials were calculated for all generated SCA-like Arabidopsis LTP homology models and the crystal structure of maize LTP (PDB Code 1MZL) using the Adaptive Poisson–Boltzmann Solver (APBS) (). Prior to the calculations, the three-dimensional coordinates for the 19 homology models and 1MZL were converted from the PDB format to the PQR format using PDB2PQR (). The generated PQR files incorporated van der Waals radii and partial charges obtained from the PARSE forcefield (). The linearized Poisson–Boltzmann equation () was solved in a 1293 grid with the same dimensions for all protein structures. After superimposition of their three-dimensional coordinates, the structures were centred in an identical way in the grid. A probe sphere with radius of 1.4 Å, representing a water molecule, was used to determine the protein molecular surface. An internal protein dielectric coefficient of 2 and solvent dielectric coefficient of 78.54 were used. A probe sphere with radius of 2.0 Å, representing a monovalent counterion, was used to determine the ion accessibility surface. An ionic strength corresponding to 50 mM salt concentration was used, which is the physiological ionic strength for SCAs with respect to pectin binding. SCAs can bind the pectin matrix until 50 mM NaCl is added ( in ). The temperature was set to 298K and pH to 7.0. The validity of the calculations extends to lower pH values in the range of 4–7. The normal pH of the cell wall is neutral. However, according to the acid-growth hypothesis, this can be lowered to 4.5 by an activated proton pump in the plasma membrane. The low pH can facilitate activity of an ECM protein such as expansin (). In a previous study of SCA proteins (), the calculated titration curves of SCAs showed plateau regions of about the same net charge in the pH range of 4 to ∼7. Pair-wise comparisons between all of the generated electrostatic potentials were calculated, based on electrostatic potential values outside the 2 Å ion-accessibility surface. The normalized scalar product ESI () was used, defined by , where ϕ(i,j,k) is the electrostatic potential value at grid point (i,j,k) and , and are scalar products for proteins a and b. A 20×20 distance matrix was generated, where 20 refers to the number of proteins used for clustering. The distance Da,b between proteins a and b was defined by . The generated distance matrix was imported into Matlab (The Mathworks, Inc., Natick, MA, USA), where hierarchical clustering was performed using average linkage. Isopotential contours were generated to visualize the spatial distributions of electrostatic potential using Chimera (UCSF) (). […]

Pipeline specifications

Software tools Clustal W, PAUP*, SWISS-MODEL, PDB2PQR
Databases ExPASy
Applications Phylogenetics, Protein structure analysis
Organisms Arabidopsis thaliana
Chemicals Polyethylene Glycols