The influenza A subtype H1N1 (H1N1/09) pandemic raised public concerns due to drug resistance strains. Drug resistance occurs from conformational changes causing the original drug to lose binding ability and exhibit biological effects. The world's largest TCM Database@Taiwan was employed to screen for potential leads that simultaneously bind to H1 and N1. Three de novo compounds derived from Rosemarinus officinalis and Guatteria amplifolia were identified as having dual binding properties to H1 and N1. Structural analysis indicated that the candidates bind to multiple residues in both H1 and N1. In addition, the de novo derivatives were predicted as bioactive using four different computational models. The compounds are validated as potent dual targeting influenza drug candidates through multiple validations. Key advantages of the candidates include (1) binding to H1 and N1 through multiple amino acids, and (2) not binding to known mutation residues in H1 or N1. Such advantages can reduce drug resistance caused by single point mutations. On a broader context, features important for successful H1N1 drug development are discussed in hopes of providing starting templates for drug development and improvements. drug discovery and design. Computational docking is important for investigating ligand-protein interactions and elucidating binding mechanisms [51] [52] [53] [54] [55] [56] [57] . Since publication of the pioneer paper in 1977 [58] , it has been established that low-frequency motions existing in proteins and DNA can help reveal dynamic mechanisms underlying fundamental biological functions [59] [60] [61] [62] [63] . NMR observation later confirmed such inferences and the findings were applied to medical treatments [64] [65] [66] [67] . In recent years, application of molecular dynamics to investigate internal motions and biological functions of biomacromolecules has opened new frontiers. Vast amounts of information on molecular recognition and binding [68] [69] [70] [71] , conformations or conformational changes [72] [73] [74] [75] , molecular mechanisms of bioactivity and stability [76] [77] [78] [79] , and drug discovery [80] [81] [82] [83] [84] have been found. To understand interaction of drugs with proteins or DNA, consideration should be given not only to the static structures but dynamical information obtained by simulation through a dynamic process. In this regard, both docking and MD simulation were utilized in this study to provide comprehensive analysis protein-ligand interactions under static and dynamic conditions. Much effort has been placed on developing new, effective influenza treatments, but most have focused on neuraminidase or M2 as the target protein [37, 38, [85] [86] [87] . To date, no hemagglutinin inhibitor is available. Traditional Chinese medicine (TCM) has been used extensively for finding effective drugs [88] , and we have successfully designed novel medicinal compounds and identified potential drug leads through traditional Chinese Medicine Database@Taiwan (TCM@Taiwan) [89] . Preliminary studies conducted in this lab show potential for TCM compounds to serve as neuramindase and hemagglutinin inhibitors individually [90] [91] [92] [93] [94] [95] . In view of the current needs for drugs effective against native and mutant H1N1/09 and our promising preliminary results, the present study integrates the concept of ''dual targeting'' with the aforementioned computational tools and TCM in the attempt to identify dual-targeting inhibitors of H1N1 that may be useful for drug development.