Scoring functions have been widely used to assess protein-ligand binding affinity in structure-based drug discovery. However, currently commonly used scoring functions face some challenges including poor correlation between calculated scores and experimental binding affinities, target-dependent performance, and low sensitivity to analogues. In this account, we propose a new empirical scoring function termed ID-Score. ID-Score was established based on a comprehensive set of descriptors related to protein-ligand interactions; these descriptors cover nine categories: van der Waals interaction, hydrogen-bonding interaction, electrostatic interaction, π-system interaction, metal-ligand bonding interaction, desolvation effect, entropic loss effect, shape matching, and surface property matching. A total of 2278 complexes were used as the training set, and a modified support vector regression (SVR) algorithm was used to fit the experimental binding affinities. Evaluation results showed that ID-Score outperformed other selected commonly used scoring functions on a benchmark test set and showed considerable performance on a large independent test set. ID-Score also showed a consistent higher performance across different biological targets. Besides, it could correctly differentiate structurally similar ligands, indicating higher sensitivity to analogues. Collectively, the better performance of ID-Score enables it as a useful tool in assessing protein-ligand binding affinity in structure-based drug discovery as well as in lead optimization.
We report the design, synthesis, and biological evaluation of heterocyclic-fused pyrimidines as tubulin polymerization inhibitors targeting the colchicine binding site with significantly improved therapeutic index. Additionally, for the first time, we report high-resolution X-ray crystal structures for the best compounds in this scaffold, 4a, 4b, 6a, and 8b. These structures not only confirm their direct binding to the colchicine site in tubulin and reveal their detailed molecular interactions but also contrast the previously published proposed binding mode. Compounds 4a and 6a significantly inhibited tumor growth in an A375 melanoma xenograft model and were accompanied by elevated levels of apoptosis and disruption of tumor vasculature. Finally, we demonstrated that compound 4a significantly overcame clinically relevant multidrug resistance in a paclitaxel resistant PC-3/TxR prostate cancer xenograft model. Collectively, these studies provide preclinical and structural proof of concept to support the continued development of this scaffold as a new generation of tubulin inhibitors.
Lipopolysaccharide (LPS) derived from Gram-negative bacteria activates plasma membrane signaling via Toll-like receptor 4 (TLR4) on host cells and triggers innate inflammatory responses, but the underlying mechanisms remain to be fully elucidated. Here we reveal a role for annexin A2 (AnxA2) in host defense against infection as anxa2−/− mice were highly susceptible to Gram-negative bacteria-induced sepsis with enhanced inflammatory responses. Computing analysis and biochemical experiments identified that constitutive AnxA2 expression facilitated TLR4 internalization and its subsequent translocation into early endosomal membranes. It activated the TRAM-dependent endosomal signaling, leading to the release of anti-inflammatory cytokines. Importantly, AnxA2 deficiency prolonged TLR4-mediated signaling from the plasma membrane, which was attributable to pro-inflammatory cytokine production (IL-6, TNFα and IL-1β). Thus, AnxA2 directly exerted negative regulation of inflammatory responses through TLR4-initiated TRAM-TRIF pathway occurring on endosomes. This study reveals AnxA2 as a critical regulator in infection-initiated inflammation, which protects the host from excessive inflammatory damage.
NMR-filtered virtual screening led to the identification of non-Zn(ii)-chelating metallo-β-lactamase inhibitors, which mimic interactions made by the bicyclic β-lactam antibiotic substrates as they initially bind to the enzymes.
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