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Conductometric monitoring of drug-gene and drug-protein interactions is of fundamental importance in functional proteomics. Here, we model our previously obtained findings and characterizations of an important antiblastic used in neuro-oncology (Temozolomide), interacting with selected proteins that represent predictive biomarkers of the rate survival of the patients, of the outcome of chemotherapy and resistance to drug itself (namely, BRIP1 and MLH1) acquired with Nucleic Acid Programmable Protein Arrays (NAPPA)based nanoconductometric sensor. Quasi-SMILES which are analogies of the traditional SMILES (simplified molecular input-line entry systems) used to represent molecular structure are suggested as a tool to represent complex substances which are acting under different conditions (dose, different peptides). By means of the optimal descriptors quasi-QSPR for conductance and frequency are established. Statistical quality of these models is satisfactory.

Quasi-QSPR to Predict Proteins Behavior Under Various Concentrations of Drug Using Nanoconductometric Assay