Preparing a database of corrected protein structures important in cell signaling pathways.

Background and purpose: Precise structures of macromolecules are important for structure-based drug design. Due to the limited resolution of some structures obtained from X-ray diffraction crystallography, differentiation between the NH and O atoms can be difficult. Sometimes a number of amino acids are missing from the protein structure. In this research, we intend to introduce a small database that we have prepared for providing the corrected 3D structure files of proteins frequently used in structure-based drug design protocols.

Experimental approach: 3454 soluble proteins belonging to the cancer signaling pathways were collected from the PDB database from which a dataset of 1001 was obtained. All were subjected to corrections in the protein preparation step. 896 protein structures out of 1001 were corrected successfully and the decision on the remained 105 proposed twelve for homology modeling to correct the missing residues. Three of them were subjected to molecular dynamics simulation for 30 ns.

Findings / results: 896 corrected proteins were perfect and homology modeling on 12 proteins with missing residues in the backbone resulted in acceptable models according to Ramachandran, z-score, and DOPE energy plots. RMSD, RMSF, and Rg values verified the stability of the models after 30 ns molecular dynamics simulation.

Conclusion and implication: A collection of 1001 proteins were modified for some defects such as adjustment of the bond orders and formal charges, and addition of missing side chains of residues. Homology modeling corrected the amino missing backbone residues. This database will be completed for quite a lot of water-soluble proteins to be uploaded to the internet.