Artificial intelligence in drug-target interaction prediction for its potential applications in personalized medicine
Meghna Goswami, Priyanka Patel, Shubhalaxmi Sahoo
The post human genome project era has opened new avenue in the field of drug discovery which depends greatly over the massive data generated from the genomic and transcriptomic sequencing projects, across the globe, specifically based on various genetic and metabolic disorders. With the developments in the computational performances and algorithmic efficiency, now it is becoming possible to analyze the huge sequencing data. This review targets the machine learning and network based techniques of Artificial Intelligence (AI) for the prediction of drug target interaction (DTI) which is utmost essentiality for drug discovery aiming personalized medicine or individualized therapeutics. Personalized medicine is the new generation medicine practice with an obligation to develop systemic drug’s efficacy and dosage as per individual requirements. This personalized therapeutic dosage and effects of drug molecules can be achievable by the study of DTI research with the use of AI.