Tyrosinase is involved in melanin biosynthesis and the abnormal accumulation of melanin pigments leading to hyperpigmentation disorders that can be treated with depigmenting agents. A natural product T1, bis(4-hydroxybenzyl)sulfide, isolated from the Chinese herbal plant, Gastrodia elata, is a strong competitive inhibitor against mushroom tyrosinase (IC50 = 0.53 μM, Ki = 58 ± 6 nM), outperforms than kojic acid. The cell viability and melanin quantification assay demonstrate that 50 μM of T1 apparently attenuates 20% melanin content of human normal melanocytes without significant cell toxicity. Moreover, the zebrafish in vivo assay reveals that T1 effectively reduces melanogenesis with no adverse side effects. The acute oral toxicity study evidently confirms that T1 molecule is free of discernable cytotoxicity in mice. Furthermore, the molecular modeling demonstrates that the sulfur atom of T1 coordinating with the copper ions in the active site of tyrosinase is essential for mushroom tyrosinase inhibition and the ability of diminishing the human melanin synthesis. These results evident that T1 isolated from Gastrodia elata is a promising candidate in developing pharmacological and cosmetic agents of great potency in skin-whitening.

Protein-protein interactions are critical determinants in biological systems. Engineered proteins binding to specific areas on protein surfaces could lead to therapeutics or diagnostics for treating diseases in humans. But designing epitope-specific protein-protein interactions with computational atomistic interaction free energy remains a difficult challenge. Here we show that, with the antibody-VEGF (vascular endothelial growth factor) interaction as a model system, the experimentally observed amino acid preferences in the antibody-antigen interface can be rationalized with 3-dimensional distributions of interacting atoms derived from the database of protein structures. Machine learning models established on the rationalization can be generalized to design amino acid preferences in antibody-antigen interfaces, for which the experimental validations are tractable with current high throughput synthetic antibody display technologies. Leave-one-out cross validation on the benchmark system yielded the accuracy, precision, recall (sensitivity) and specificity of the overall binary predictions to be 0.69, 0.45, 0.63, and 0.71 respectively, and the overall Matthews correlation coefficient of the 20 amino acid types in the 24 interface CDR positions was 0.312. The structure-based computational antibody design methodology was further tested with other antibodies binding to VEGF. The results indicate that the methodology could provide alternatives to the current antibody technologies based on animal immune systems in engineering therapeutic and diagnostic antibodies against predetermined antigen epitopes.

Humoral immunity against diverse pathogens is rapidly elicited from natural antibody repertoires of limited complexity. But the organizing principles underlying the antibody repertoires that facilitate this immunity are not well-understood. We used HER2 as a model immunogen and reverse-engineered murine antibody response through constructing an artificial antibody library encoded with rudimentary sequence and structural characteristics learned from high throughput sequencing of antibody variable domains. Antibodies selected in vitro from the phage-displayed synthetic antibody library bound to the model immunogen with high affinity and specificities, which reproduced the specificities of natural antibody responses. We conclude that natural antibody structural repertoires are shaped to allow functional antibodies to be encoded efficiently, within the complexity limit of an individual antibody repertoire, to bind to diverse protein antigens with high specificity and affinity. Phage-displayed synthetic antibody libraries, in conjunction with high-throughput sequencing, can thus be designed to replicate natural antibody responses and to generate novel antibodies against diverse antigens.

MPT0L145 has been developed as a FGFR inhibitor exhibiting significant anti-bladder cancer activity and via promoting autophagy-dependent cell death. Here, we aim to elucidate the underlying mechanisms. Autophagy flux, morphology, and intracellular organelles were evaluated by Western blotting, transmission electron microscope, and fluorescence microscope. Molecular docking and surface plasmon resonance assay were performed to identify drug-protein interaction. Lentiviral delivery of cDNA or shRNA and CRISPR/Cas9-mediated genome editing was used to modulate gene expression. Mitochondrial oxygen consumption rate was measured by a Seahorse XFe24 extracellular flux analyzer, and ROS level was measured by flow cytometry. MPT0L145 persistently increased incomplete autophagy and phase-lucent vacuoles at the perinuclear region, which were identified as enlarged and alkalinized late-endosomes. Screening of a panel of lipid kinases revealed that MPT0L145 strongly inhibits PIK3C3 with a value of 0.53 nmol/L. Ectopic expression of PIK3C3 reversed MPT0L145-increased cell death and incomplete autophagy. Four residues (Y670, F684, I760, D761) at the ATP-binding site of PIK3C3 are important for the binding of MPT0L145. In addition, MPT0L145 promotes mitochondrial dysfunction, ROS production, and DNA damage, which may in part, contribute to cell death. ATG5-knockout rescued MPT0L145-induced cell death, suggesting simultaneous induction of autophagy is crucial to its anticancer activity. Finally, our data demonstrated that MPT0L145 is able to overcome cisplatin resistance in bladder cancer cells. MPT0L145 is a first-in-class PIK3C3/FGFR inhibitor, providing an innovative strategy to design new compounds that increase autophagy, but simultaneously perturb its process to promote bladder cancer cell death. .

Broadly neutralizing antibodies developed from the IGHV1–69 germline gene are known to bind to the stem region of hemagglutinin in diverse influenza viruses but the sequence determinants for the antigen recognition, including neutralization potency and binding affinity, are not clearly understood. Such understanding could inform designs of synthetic antibody libraries targeting the stem epitope on hemagglutinin, leading to artificially designed antibodies that are functionally advantageous over antibodies from natural antibody repertoires. In this work, the sequence space of the complementarity determining regions of a broadly neutralizing antibody (F10) targeting the stem epitope on the hemagglutinin of a strain of H1N1 influenza virus was systematically explored; the elucidated antibody-hemagglutinin recognition principles were used to design a phage-displayed antibody library, which was then used to discover neutralizing antibodies against another strain of H1N1 virus. More than 1000 functional antibody candidates were selected from the antibody library and were shown to neutralize the corresponding strain of influenza virus with up to 7 folds higher potency comparing with the parent F10 antibody. The antibody library could be used to discover functionally effective antibodies against other H1N1 influenza viruses, supporting the notion that target-specific antibody libraries can be designed and constructed with systematic sequence-function information.