Abstract
BackgroundThe study of drug–target interactions (DTIs) affinity plays an important role in safety assessment and pharmacology. Currently, quantitative structure–activity relationship (QSAR) and molecular docking (MD) are most common methods in research of DTIs affinity. However, they often built for a specific target or several targets, and most QSAR and MD methods were based either on structure of drug molecules or on structure of receptors with low accuracy and small scope of application. How to construct quantitative prediction models with high accuracy and wide applicability remains a challenge. To this end, this paper screened molecular descriptors based on molecular vibrations and took molecule-target as a whole system to construct prediction models with high accuracy-wide applicability based on dissociation constant (Kd) and concentration for 50% of maximal effect (EC50), and to provide reference for quantifying affinity of DTIs.ResultsAfter comprehensive comparison, the results showed that RF models are optimal models to analyze and predict DTIs affinity with coefficients of determination (R2) are all greater than 0.94. Compared to the quantitative models reported in literatures, the RF models developed in this paper have higher accuracy and wide applicability. In addition, E-state molecular descriptors associated with molecular vibrations and normalized Moreau-Broto autocorrelation (G3), Moran autocorrelation (G4), transition-distribution (G7) protein descriptors are of higher importance in the quantification of DTIs.ConclusionThrough screening molecular descriptors based on molecular vibrations and taking molecule-target as whole system, we obtained optimal models based on RF with more accurate-widely applicable, which indicated that selection of molecular descriptors associated with molecular vibrations and the use of molecular-target as whole system are reliable methods for improving performance of models. It can provide reference for quantifying affinity of DTIs.
Highlights
The study of drug–target interactions (DTIs) affinity plays an important role in safety assessment and pharmacology
Data collection Based on open source database: PubChem, Drugbank, ChEMBL and Uniprot database, we performed data collection of drug molecules, target protein sequences, and Kd and EC50 values characterizing drug moleculetarget affinity
E-state molecular descriptors associated with molecular vibrations and G3, G4 and G7 protein descriptors are of higher importance in the quantification of DTIs
Summary
The study of drug–target interactions (DTIs) affinity plays an important role in safety assessment and pharmacology. Quantitative structure–activ‐ ity relationship (QSAR) and molecular docking (MD) are most common methods in research of DTIs affinity. They often built for a specific target or several targets, and most QSAR and MD methods were based either on structure of drug molecules or on structure of receptors with low accuracy and small scope of application. There are multiple interactions between targets and drug molecules-DTIs. DTIs plays an important role in pharmacology, biology and mechanism [3,4,5,6]. The research of DTIs will help to understand mechanisms or toxic side effects of drugs and repositioning of drugs [9,10,11,12]
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