Cefpiramide Sodium

Accurate prediction of human clearance (CL) is essential in early drug development. Single Species Scaling (SSS) using rat pharmacokinetic (PK) data, particularly with unbound plasma fraction (f_u,plasma), is widely used. However, its accuracy declines for compounds with extremely low f_u,plasma, and no systematic method has addressed this limitation.

We developed a new approach, called Fraction-based Linear EXtrapolation SSS (FLEX-SSS fu Rat), which switches between SSS fu Rat and SSS Rat formulas based on an optimized fu threshold. The threshold and scaling coefficients were derived using a training set of 200 compounds. Additionally, a random forest (RF) machine learning model was built using molecular descriptors. Both models were validated using an external dataset of 62 compounds.

All five predictive models showed comparable performance; among them, the consensus model combining FLEX-SSS fu Rat and RF yielded the best result: 40.3% within 2-fold error, only 16.1% above 5-fold, and GMFE of 2.7.

This study is the first to systematically validate SSS fu Rat using an independent dataset. The integration of threshold-based allometry and machine learning enabled more accurate human CL prediction, supporting informed decisions in first-in-human dose selection.

The 3C-like protease of severe acute respiratory syndrome coronavirus 2, known as the main protease (M^pro), is an attractive drug target for the treatment of coronavirus disease 2019. This study reports the discovery of novel M^pro inhibitors using several in silico techniques, including docking, molecular dynamics (MD), and fragment molecular orbital (FMO) calculations. We performed docking calculations on 5950 compounds with bioactivity, and 12 compounds were selected. An enzymatic assay was conducted, revealing that BP-1-102 exhibits significant M^pro inhibitory activity with an IC₅₀ of 11.1 μM. The identification of seed compounds from the experiments on a few compounds demonstrates the effectiveness of our docking calculations. Furthermore, the detailed analyses using MD and FMO calculations suggested an interaction mechanism in which the hydroxyl group of BP-1-102 forms a hydrogen bond with E166 of M^pro. The M^pro inhibitory activity of SH-4-54, a derivative without the aforementioned hydroxyl group, was investigated and observed to be significantly reduced, with an IC₅₀ of 81.5 μM. This result strongly supports the suggested interaction mechanism.