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A decision tree model for the prediction of homodimer folding mechanism
Authors:Abishek Suresh  Velmurugan Karthikraja  Sajitha Lulu  Uma Kangueane  Pandjassarame Kangueane
Affiliation:1.Biomedical Informatics, Pondicherry 607402;2.AIMST University, Semeling 08100, Malaysia
Abstract:The formation of protein homodimer complexes for molecular catalysis and regulation is fascinating. The homodimer formation through 2S(2 state), 3SMI (3 state with monomer intermediate) and 3SDI (3 state with dimer intermediate) folding mechanism is known for 47homodimer structures. Our dataset of forty-seven homodimers consists of twenty-eight 2S, twelve 3SMI and seven 3SDI. The dataset ischaracterized using monomer length, interface area and interface/total (I/T) residue ratio. It is found that 2S are often small in size with largeI/T ratio and 3SDI are frequently large in size with small I/T ratio. Nonetheless, 3SMI have a mixture of these features. Hence, we usedthese parameters to develop a decision tree model. The decision tree model produced positive predictive values (PPV) of 72% for 2S, 58%for 3SMI and 57% for 3SDI in cross validation. Thus, the method finds application in assigning homodimers with folding mechanism.
Keywords:folding   homodimer   decision tree   prediction   mechanism
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