The sequence-structure-function paradigm of proteins has been changed by the occurrence of intrinsically disordered proteins (IDPs). Benefiting from the structural disorder, IDPs are of particular importance in biological processes like regulation and signaling. IDPs are associated with human diseases, including cancer, cardiovascular disease, neurodegenerative diseases, amyloidoses, and several other maladies. IDPs attract a high level of interest and a substantial effort has been made to develop experimental and computational methods. So far, more than 70 prediction tools have been developed since 1997, within which 17 predictors were created in the last five years. Here, we presented an overview of IDPs predictors developed during 2010–2014. We analyzed the algorithms used for IDPs prediction by these tools and we also discussed the basic concept of various prediction methods for IDPs. The comparison of prediction performance among these tools is discussed as well.

Breast cancer is one of the most lethal types of cancer in women worldwide due to the late stage detection and resistance to traditional chemotherapy. The human epidermal growth factor receptor 2 (HER2) is considered as a validated target in breast cancer therapy. Even though a substantial effort has been made to develop HER2 inhibitors, only lapatinib has been approved by the U.S. Food and Drug Administration (FDA). Side effects were observed in a majority of the patients within one year of treatment initiation. Here, we took advantage of bioinformatics tools to identify novel effective HER2 inhibitors. The structure-based virtual screening combined with ADMET (absorption, distribution, metabolism, excretion and toxicity) prediction was explored. In total, 11,247 natural compounds were screened. The top hits were evaluated by an in vitro HER2 kinase inhibition assay. The cell proliferation inhibition effect of identified inhibitors was evaluated in HER2-overexpressing SKBR3 and BT474 cell lines. We found that ZINC15122021 showed favorable ADMET properties and attained high binding affinity against HER2. Moreover, ZINC15122021 showed high kinase inhibition activity against HER2 and presented outstanding cell proliferation inhibition activity against both SKBR3 and BT474 cell lines. Results reveal that ZINC15122021 can be a potential HER2 inhibitor.

Hyperlipidemia is thought as an important contributor to coronary disease, diabetes and fatty liver. Liver X receptors β (LXRβ) was considered as a validated target for hyperlipidemia therapy due to its role in regulating cholesterol homeostasis and immunity. However, many current drugs applied in clinic are not selectively targeting LXRβ and they can also activate LXRα which activate SREBP-1c worked as activator of lipogenic genes. Therefore, exploiting agonists selectively targeting LXRβ are urgent. Here, computational tools were used to screen potential agonists selectively targeting LXRβ from 112 terpenes of Alismatis Rhizoma. Firstly, structural analysis between selective and nonselective agonists were used to explore key residues of selective binding with LXRβ. Our data indicated that Phe²⁷¹, Ser²⁷⁸, Met³¹², His⁴³⁵, Trp⁴⁵⁷ were important to compounds binding with LXRβ, suggesting that engaging ligand interaction with these residues may provide directions for development of ligands with improved selective profiles. Then, ADMET analysis, molecular docking, MD simulations and calculation of binding free energy and its decomposition were executed to screen the agonists whose bioactivity were favorable from 112 terpenes of Alismatis Rhizoma. We found that two triterpenes 16-hydroxy-alisol B 23-acetate and Alisol M 23-acetate showed favorable ADMET properties and high binding affinity against LXRβ. These compounds could be considered as promising selective agonists targeting LXRβ. Our work provides an alternative strategy for screening agonists selectively targeting LXRβ from Alismatis Rhizoma for hyperlipidemia disease treatment.