PremPDI evaluates the change in binding affinity between proteins and DNA caused by single-site mutations in their sequence. The predictions are based on the structure of the protein-DNA complex.
The PremPDI model uses molecular mechanics force fields and fast side-chain optimization algorithms built via multiple linear regression (MLR) method, training on experimental data of binding affinity changes (ΔΔG) for 219 mutations from 49 protein-DNA complexes.
The PremPDI structure optimization protocol. First we introduced a single mutation on the wild-type structure using the BuildModel module from FoldX (1) software. This step optimized the configurations of the mutated side chain and the neighboring side chains to avoid steric clashes. Missing heavy side chain atoms and hydrogen atoms were added for the wild type and mutant using VMD program (2) based on the topology file from the CHARMM36 force field (3). Then a 100-step energy minimization in the gas phase was carried out for both wild type and mutant using harmonic restraints applied on the backbone atoms of all residues. Energy minimization is used to optimize the side chain conformations, repair distorted geometries and remove steric clashes. Minimization was done only for protein-DNA complexes, and binding partners were retained assuming the rigid-body binding. The energy minimization was carried out with NAMD program version 2.12 (4) using the CHARMM36 force field (3). The current structure optimization protocol was chosen based on its accuracy and speed.
The PremPDI energy function incorporates nine distinct features contributed significantly to the quality of multiple linear regression model (MLR) for the calculation of ΔΔG value affecting protein-DNA interactions.
The features that contribute significantly to the quality of energy model are described below.
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More details can be found in our paper.