Membrane permeability is an important property of drugs in adsorption. Many prediction methods work well for small molecules, but the prediction of middle-molecule permeability is still difficult. In the present study, we modified a classical permeability model based on Fick's law to study passive membrane permeability. The model consisted of the distribution of solute from water to membrane and the diffusion of solute in each solvent. The diffusion coefficient is the inverse of the resistance, and we examined the inertial resistance in addition to the viscous resistance, the latter of which has been widely used in permeability prediction. Also, we examined three models changing the balance between the diffusion of solute in membrane and the conformational change of solute. The inertial resistance improved the prediction results in addition to the viscous resistance. The models worked well not only for small molecules but also for middle molecules, whose structures have more conformational freedom.
BackgroundComputer-aided drug design is still a state-of-the-art process in medicinal chemistry, and the main topics in this field have been extensively studied and well reviewed. These topics include compound databases, ligand-binding pocket prediction, protein-compound docking, virtual screening, target/off-target prediction, physical property prediction, molecular simulation and pharmacokinetics/pharmacodynamics (PK/PD) prediction. Message and Conclusion: However, there are also a number of secondary or miscellaneous topics that have been less well covered. For example, methods for synthesizing and predicting the synthetic accessibility (SA) of designed compounds are important in practical drug development, and hardware/software resources for performing the computations in computer-aided drug design are crucial. Cloud computing and general purpose graphics processing unit (GPGPU) computing have been used in virtual screening and molecular dynamics simulations. Not surprisingly, there is a growing demand for computer systems which combine these resources. In the present review, we summarize and discuss these various topics of drug design.
Background To suppress increases in kidney failure and cardiovascular disease due to lifestyle-related diseases other than diabetes, early intervention is desirable. We examined whether microalbuminuria could be predicted from proteinuria. Methods The participants consisted of adults who exhibited a urinary protein-to-creatinine ratio (uPCR) of < 0.5 g/gCr and an eGFR of ≥ 15 ml/min/1.73 m2 in their spot urine at their first examination for lifestyle-related disease. Urine was tested three times for each case, with microalbuminuria defined as a urinary albumin-to-creatinine ratio (uACR) of 30–299 mg/gCr, at least twice on three measurements. Youden’s Index was used as an index of the cut-off value (CO) according to the ROC curve. Results A single uPCR was useful for differentiating normoalbuminuria and micro- and macroalbuminuria in patients with non-diabetic lifestyle-related diseases. Regarding the GFR categories, the CO of the second uPCR was 0.09 g/gCr (AUC 0.89, sensitivity 0.76, specificity 0.89) in G1-4 (n = 197) and 0.07 g/gCr (AUC 0.92, sensitivity 0.85, specificity 0.88) in G1-3a (n = 125). Using the sum of two or three uPCR measurements was more useful than a single uPCR for differentiating microalbuminuria in non-diabetic lifestyle disease [CO, 0.16 g/gCr (AUC 0.91, sensitivity 0.85, specificity 0.87) and 0.23 g/gCr (AUC 0.92, sensitivity 0.88, specificity 0.84), respectively]. Conclusion Microalbuminuria in Japanese individuals with non-diabetic lifestyle-related diseases can be predicted from the uPCR, wherein the CO of the uPCR that differentiates normoalbuminuria and micro- and macroalbuminuria was 0.07 g/gCr for G1-3a, while that in G3b-4 was 0.09 g/gCr.
Background The utility of dipstick proteinuria for predicting microalbuminuria in non-diabetic lifestyle-related diseases compared with the urine protein-to-creatinine ratio (uPCR) and the effect of dipstick proteinuria on the cut-off value (CO) and accuracy of uPCR are unclear. Methods The subjects included Japanese patients ≥ 18 years old with lifestyle-related diseases who had an estimated glomerular filtration rate of ≥ 15 ml/min/1.73 m2 and uPCR of < 0.5 g/gCr at initiation. Urine dipstick, uPCR and urine albumin-to-creatinine ratio (uACR) were measured three times per case. Microalbuminuria was defined as uACR of 30–299 mg/gCr for at least 2 of 3 measurements. Youden’s Index was used as the optimal CO. Factors associated with microalbuminuria were analyzed using a logistic regression model. Results In 313 non-diabetic cases (median 70.8 years old), 3 dipstick proteinuria measurements were independently useful for detecting microalbuminuria, and the CO was set when a trace finding was obtained at least 1 of 3 times (sensitivity 0.56, specificity 0.80, positive predictive value [PPV] 0.73, negative predictive value [NPV] 0.65). A single uPCR measurement was more useful than 3 dipstick measurements, and was useful for detecting microalbuminuria even in cases with three consecutive negative proteinuria findings, indicating that the CO of the second uPCR with G1-3a (n = 136) was 0.06 g/gCr (sensitivity 0.76, specificity 0.84. PPV 0.68, NPV 0.89), while that with G3-b4 (n = 59) was 0.10 g/gCr (sensitivity 0.56, specificity 0.91. PPV 0.83, NPV 0.71). The sum of 3 uPCRs was useful for detecting microalbuminuria in cases with G1-3a (sensitivity 0.67, specificity 0.94, PPV 0.82, NPV 0.86) and G3b-4 (sensitivity 0.78, specificity 0.94, PPV 0.91 NPV 0.83), with both COs being 0.23 g/gCr. These COs of microalbuminuria did not change when trace or more proteinuria was included, although the sensitivity increased. A high uPCR and low urine specific gravity or creatinine level were independent factors for uACR ≥ 30 mg/gCr in cases with negative proteinuria, although the uPCR was a major predictive factor of a uACR ≥ 30 mg/gCr. Conclusions The uPCR (preferably determined using early-morning urine), including in dipstick-negative proteinuria cases with non-diabetic lifestyle-related diseases, can aid in the early detection of microalbuminuria. Trial registration Retrospectively registered.
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