While the existing antihypertensive drugs are effective at lowering BP, they have failed to be promising on prolong use due to unfavourable side effects and off target specificity. With the steadily rising incidence of hypertension and its related comorbid complications over the globe, researchers have recently moved its emphasis toward studying new targets and identifying novel anti-hypertensive agents with safe and effective therapeutic profile to fulfil this unmet demand. In order to fill this gap, rationalistic drug development for fast tracking lead molecules has become a complementary strategy. It is assisted by advancement of computer aided drug designing which includes homology modelling, docking based virtual screening, QM-MD stimulations, pharmacophore modelling, qQSAR and ADMET prediction. Recently, the use of pharmacogenomic approach through various bioinformatic tools and integration of ML algorithms have redefined the responses of the antihypertensive drug at the genetic levels. Herein, various in-silico based investigations have been highlighted covering various aspects of drug designing of novel antihypertensive agents which can provide an easy access to drug standardisation in the future for molecular and clinical management of hypertension.