The　rapid　spread　of　severe　acute　respiratory　syndrome　coronavirus　2　(SARS-CoV-2)　worldwide　has　led　to　over　600　million　cases　of　coronavirus　disease　2019　(COVID-19).　Identifying　effective　molecules　that　can　counteract　the　virus　is　imperative.　SARS-CoV-2　macrodomain　1　(Mac1)　represents　a　promising　antiviral　drug　target.　In　this　study,　we　predicted　potential　inhibitors　of　SARS-CoV-2　Mac1　from　natural　products　using　in　silico-based　screening.　Based　on　the　high-resolution　crystal　structure　of　Mac1　bound　to　its　endogenous　ligand　ADP-ribose　(ADPr),　we　first　performed　a　docking-based　virtual　screening　of　Mac1　inhibitors　against　a　natural　product　library　and　obtained　five　representative　compounds　(MC1–MC5)　by　clustering　analysis.　All　five　compounds　were　stably　bound　to　Mac1　during　500 ns　long　molecular　dynamics　simulations.　The　binding　free　energy　of　these　compounds　to　Mac1　was　calculated　using　molecular　mechanics　generalized　Born　surface　area　and　further　refined　with　localized　volume-based　metadynamics.　The　results　demonstrated　that　both　MC1　(−9.8 ± 0.3 kcal/mol)　and　MC5　(−9.6 ± 0.3 kcal/mol)　displayed　more　favorable　affinities　to　Mac1　with　respect　to　ADPr　(−8.9 ± 0.3 kcal/mol),　highlighting　their　potential　as　potent　SARS-CoV-2　Mac1　inhibitors.　Overall,　this　study　provides　potential　SARS-CoV-2　Mac1　inhibitors,　which　may　pave　the　way　for　developing　effective　therapeutics　for　COVID-19.　　　　　　　　　　　　Communicated　by　Ramaswamy　H.　Sarma