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Human society is facing the threat of various viruses. Proteases are promising targets for the treatment of viral infections. In this study, we collected and profiled 170 protease sequences from 125 viruses that infect humans. Approximately 73 of them are viral 3-chymotrypsin-like proteases (3CLpro), and 11 are pepsin-like aspartic proteases (PAPs). Their sequences, structures, and substrate characteristics were carefully analyzed to identify their conserved nature for proposing a pan-3CLpro or pan-PAPs inhibitor design strategy. To achieve this, we used computational prediction and modeling methods to predict the binding complex structures for those 73 3CLpro with 4 protease inhibitors of SARS-CoV-2 and 11 protease inhibitors of HCV. Similarly, the complex structures for the 11 viral PAPs with 9 protease inhibitors of HIV were also obtained. The binding affinities between these compounds and proteins were also evaluated to assess their pan-protease inhibition via MM-GBSA. Based on the drugs targeting viral 3CLpro and PAPs, repositioning of the active compounds identified several potential uses for these drug molecules. As a result, Compounds 1–2, modified based on the structures of Ray1216 and Asunaprevir, indicate potential inhibition of DENV protease according to our computational simulation results. These studies offer ideas and insights for future research in the design of broad-spectrum antiviral drugs. [ABSTRACT FROM AUTHOR]

In order to improve the surface quality of zirconia ceramic workpieces, the magnetic compound fluid polishing tool were utilized. This was done to lessen the material's surface roughness, minimize surface and subsurface damage. With a focus on the effects of magnet speed, processing gap, and abrasive particle size in the polishing fluid on surface roughness and material removal rate, a 3-factor, 3-level orthogonal test was created using Taguchi's method. The weights of each factor on the two evaluation indices were then analyzed using ANOVA. The best process parameter combination for surface roughness was 300 r/min for the magnet speed, 0.5 mm for the processing gap, and 1.25 µm for the abrasive particle size; the best process parameter combination for material removal rate was 400 r/min for the magnet speed, 0.5 mm for the processing gap, and 2 µm for the abrasive particle size. With these processing parameters, the surface roughness can reach up to 4.5 nm, and the material removal rate can reach up to 0.117 µm/min. The optimization effect is significant. The polishing prediction model was developed using a BP neural network that has been genetic algorithm optimized. The prediction error was 3.948 4%. [ABSTRACT FROM AUTHOR]

Ion concentration polarization (ICP) is a promising mechanism for concentrating and/or separating charged molecules. This work simulates the extraction of Li+ ions in a diluted high Mg2+/Li+ ratio salt lake brines based on free flow ICP focusing (FF-ICPF). The model solution of diluted brine continuously flows through the system with Li+ slightly concentrated and Mg2+ significantly removed by ICP driven by external pressure and perpendicular electric field. In a typical case, our results showed that this system could focus Li+ concentration by ~1.28 times while decreasing the Mg2+/Li+ ratio by about 85% (from 40 to 5.85). Although Li+ and Mg2+ ions are not separated as an end product, which is preferably required by the lithium industry, this method is capable of decreasing the Mg2+/Li+ ratio significantly and has great potential as a preprocessing technology for lithium extraction from salt lake brines. [ABSTRACT FROM AUTHOR]

Human society is facing the threat of various viruses. Proteases are promising targets for the treatment of viral infections. In this study, we collected and profiled 170 protease sequences from 125 viruses that infect humans. Approximately 73 of them are viral 3-chymotrypsin-like proteases (3CL pro ), and 11 are pepsin-like aspartic proteases (PAPs). Their sequences, structures, and substrate characteristics were carefully analyzed to identify their conserved nature for proposing a pan-3CL pro or pan-PAPs inhibitor design strategy. To achieve this, we used computational prediction and modeling methods to predict the binding complex structures for those 73 3CL pro with 4 protease inhibitors of SARS-CoV-2 and 11 protease inhibitors of HCV. Similarly, the complex structures for the 11 viral PAPs with 9 protease inhibitors of HIV were also obtained. The binding affinities between these compounds and proteins were also evaluated to assess their pan-protease inhibition via MM-GBSA. Based on the drugs targeting viral 3CL pro and PAPs, repositioning of the active compounds identified several potential uses for these drug molecules. As a result, Compounds 1 - 2 , modified based on the structures of Ray1216 and Asunaprevir, indicate potential inhibition of DENV protease according to our computational simulation results. These studies offer ideas and insights for future research in the design of broad-spectrum antiviral drugs.