Integrating Statistical Predictions and Experimental Verifications for Enhancing Protein-Chemical Interaction Predictions in Virtual Screening

Predictions of interactions between target proteins and potential leads are of great benefit in the drug discovery process. We present a comprehensively applicable statistical prediction method for interactions between any proteins and chemical compounds, which requires only protein sequence data and chemical structure data and utilizes the statistical learning method of support vector machines. In order to realize reasonable comprehensive predictions which can involve many false positives, we propose two approaches for reduction of false positives: (i) efficient use of multiple statistical prediction models in the framework of two-layer SVM and (ii) reasonable design of the negative data to construct statistical prediction models. In two-layer SVM, outputs produced by the first-layer SVM models, which are constructed with different negative samples and reflect different aspects of classifications, are utilized as inputs to the second-layer SVM. In order to design negative data which produce fewer false positive predictions, we iteratively construct SVM models or classification boundaries from positive and tentative negative samples and select additional negative sample candidates according to pre-determined rules. Moreover, in order to fully utilize the advantages of statistical learning methods, we propose a strategy to effectively feedback experimental results to computational predictions with consideration of biological effects of interest. We show the usefulness of our approach in predicting potential ligands binding to human androgen receptors from more than 19 million chemical compounds and verifying these predictions by in vitro binding. Moreover, we utilize this experimental validation as feedback to enhance subsequent computational predictions, and experimentally validate these predictions again. This efficient procedure of the iteration of the in silico prediction and in vitro or in vivo experimental verifications with the sufficient feedback enabled us to identify novel ligand candidates which were distant from known ligands in the chemical space

Kinetic Exploration of Nanoscale Polymorphs through Interface Energy Adjustment

Traditionally, the study of polymorphism has relied on thermodynamics and mass-averaged measurements. This work introduces a novel approach by combining kinetic analysis and statistical mechanics with electron microscopic imaging to observe phase transitions directly. We demonstrate a remarkable impact of the crystal size on the kinetic stability of polymorphs at nanoscale domains, enabling in situ manipulation of phase transitions at 298 K through interface energy adjustments by size reduction. Starting with the B1 NaI polymorph, we synthesized the previously unknown B2 polymorph upon size reduction. Starting from the CsCl liquid phase, we produced B1, previously described only above 749 K, and then B2 via quick martensitic transformation

Differential Photosensitivity of Fibroblasts Obtained from Normal Skin and Hypertrophic Scar Tissues

It is unclear whether normal human skin tissue or abnormal scarring are photoreceptive. Therefore, this study investigated photosensitivity in normal skin tissue and hypertrophic scars. The expression of opsins, which are photoreceptor proteins, in normal dermal fibroblasts (NDFs) and hypertrophic scar fibroblasts (HSFs) was examined. After exposure to blue light (BL), changes in the expression levels of αSMA and clock-related genes, specifically PER2 and BMAL1, were examined in both fibroblast types. Opsins were expressed in both fibroblast types, with OPN3 exhibiting the highest expression levels. After peripheral circadian rhythm disruption, BL induced rhythm formation in NDFs. In contrast, although HSFs showed changes in clock-related gene expression levels, no distinct rhythm formation was observed. The expression level of αSMA was significantly higher in HSFs and decreased to the same level as that in NDFs upon BL exposure. When OPN3 knocked-down HSFs were exposed to BL, the reduction in αSMA expression was inhibited. This study showed that BL exposure directly triggers peripheral circadian synchronization in NDFs but not in HSFs. OPN3-mediated BL exposure inhibited HSFs. Although the current results did not elucidate the relationship between peripheral circadian rhythms and hypertrophic scars, they show that BL can be applied for the prevention and treatment of hypertrophic scars and keloids