Complex network spectral moments for ATCUN motif DNA cleavage: first predictive study on proteins of human pathogen parasites.
The development of methods that can predict the metal-mediated biological activity based only on the 3D structure of metal-unbound proteins has become a goal of major importance. This work is dedicated to the amino terminal Cu(II)- and Ni(II)-binding (ATCUN) motifs that participate in the DNA cleavage and have antitumor activity. We have calculated herein, for the first time, the 3D electrostatic spectral moments for 415 different proteins, including 133 potential ATCUN antitumor proteins. Using these parameters as input for Linear Discriminant Analysis, we have found a model that discriminates between ATCUN-DNA cleavage proteins and nonactive proteins with 91.32% Accuracy (379 out of 415 of proteins including both training and external validation series). Finally, the model has predicted for the first time the DNA cleavage function of proteins from the pathogen parasites. We have predicted possible ATCUN-like proteins with a probability higher than 99% in nine parasite families such as Trypanosoma, Plasmodium, Leishmania, or Toxoplasma. The distribution by biological function of the ATCUN proteins predicted has been the following: oxidoreductases 70.5%, signaling proteins 62.5%, lyases 58.2%, membrane proteins 45.5%, ligases 44.4%, hydrolases 41.3%, transferases 39.2%, cell adhesion proteins 34.5%, metal binders 33.5%, translation proteins 25.0%, transporters 16.7%, structural proteins 9.1%, and isomerases 8.2%. The model is implemented at http://miaja.tic.udc.es/Bio-AIMS/ATCUNPred.php.
Munteanu
Cristian R
CR
Department of Information and Communication Technologies, Computer Science Faculty, University of A Coruña, Campus de Elviña, s/n 15071 A Coruña, Spain. muntisa@gmail.com
Vázquez
José M
JM
Dorado
Julián
J
Sierra
Alejandro Pazos
AP
Sánchez-González
Angeles
A
Prado-Prado
Francisco J
FJ
González-Díaz
Humberto
H
D000465:Algorithms; D000818:Animals; D001483:Base Sequence; D053837:DNA Cleavage; D016002:Discriminant Analysis; D006801:Humans; D008390:Markov Chains; D008958:Models, Molecular; D008969:Molecular Sequence Data; D010271:Parasites / Q000737:chemistry / Q000472:pathogenicity; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry / Q000378:metabolism; D012372:ROC Curve; D055672:Static Electricity
D011506:Proteins