000			01812nam a2200145 4500
008			250821b |||||||| |||| 00| 0 eng d
100			_aChristy Saji
245			_aMOLECULAR DOCKING STUDIES WITH PHYTOCONSTITUENTS OF TINOSPORA SINENSIS TARGETING SARS-COV-2 PROTEIN USING AUTODOCK VINA
300			_aPage No. 22-27
520			_aDrug discovery is time-consuming and resource-intensive, but computational approaches offer a more efficient alternative. The urgency for antiviral treatments became evident during the SARS-CoV-2 pandemic due to the virus’s rapid spread and mutations. This study utilizes computational drug design techniques to assess the antiviral potential of Tinospora sinensis constituents against the SARS-CoV-2 main protease (PDB ID: 6LU7). The target protein was prepared using AutoDock tools, and molecular docking was conducted with AutoDock Vina. Of 37 compounds, 5 exhibited a binding affinity below -7 kcal mol-1, with tinosporaside showing the highest affinity and low toxicity. These results suggest that tinosporaside is a promising candidate for further development. By streamlining drug discovery, computational methods accelerate the identification of potential treatments, reducing costs and waste. This study underscores the value of computational methods in antiviral research and supports further investigation into combating SARS-CoV-2 and future viral threats.
654			_aAntidepressants _aclinical depression _aMajor depressive disorder [MDD] _abrain chemistry _atreatment resistant depression [TRD] _aelecroconvulsive therapy _adiagnostic and statistical manual of mental disorders[dsm-5]
700			_a Rajeswary K. Balachandrana
773	0		_0125265 _9113416 _dMumbai Indian Drugs Manufacturer's Association _tIndian Drugs _x0019-462X
942			_cJA
999			_c132517 _d132517