Direct compression is a tableting technique that involves a few steps in non-demanding manufacturing conditions. High strength and rapid disintegration of tablet formulations were previously achieved through the addition of cellulose nanofibers (CNFs), which have recently attracted attention as a high-performance biomass material. However, CNF addition results in greater variation in tablet weight and drug content, potentially due to differences in particle size between CNF and other additives. Herein, we used pulverized CNF to evaluate the effect of CNF particle size on the variation in tablet weight and drug content. Tablet formulations consisted of CNF with different particle sizes (approximately 100 µm [CNF₁₀₀] and 300 µm [CNF₃₀₀], at 0, 10, 30, or 50%), lactose hydrate, acetaminophen, and magnesium stearate. Ten powder formulations with different particle sizes and CNF concentrations were prepared; thereafter, the tablets were produced using a rotary tableting press with a compression force of 10 kN. The variation in weight and drug content as well as the tensile strength, friability, disintegration time, and drug dissolution of tablets were evaluated. CNF₁₀₀ addition to the tablets reduced the weight and drug content variation to a greater extent than CNF₃₀₀ addition. Using CNF₃₀₀, we produced tablets of sufficient strength and short disintegration time. These properties were also achieved with CNF₁₀₀ addition. Our findings suggest that adding CNF of small particle size to the tablet formulation can reduce the variation in weight and drug content while maintaining high strength and short disintegration time.

Virtual screening with high-performance computers is a powerful and cost-effective technique in drug discovery. A chemical database is searched to find candidate compounds firmly bound to a target protein, judging from the binding poses and/or binding scores. The severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) infectious disease has spread worldwide for the last three years, causing severe slumps in economic and social activities. SARS-Cov-2 has two viral proteases: 3-chymotrypsin-like (3CL) and papain-like (PL) protease. While approved drugs have already been released for the 3CL protease, no approved agent is available for PL protease. In this work, we carried out in silico screening for the PL protease inhibitors, combining docking simulation and molecular mechanics calculation. Docking simulations were applied to 8,820 molecules in a chemical database of approved and investigational compounds. Based on the binding poses generated by the docking simulations, molecular mechanics calculations were performed to optimize the binding structures and to obtain the binding scores. Based on the binding scores, 57 compounds were selected for in vitro assay of the inhibitory activity. Five inhibitory compounds were identified from the in vitro measurement. The predicted binding structures of the identified five compounds were examined, and the significant interaction between the individual compound and the protease catalytic site was clarified. This work demonstrates that computational virtual screening by combining docking simulation with molecular mechanics calculation is effective for searching candidate compounds in drug discovery.