We focus on an analytical overview of current natural product databases, and further discuss the good, bad or imperfection of current ones, in the hope of better integrating existing relevant outcomes, thus providing new routes for future drug discovery.

The relatively low capacity and capacity fade of spinel LiMn2O4 (LMO) limit its application as a cathode material for lithium‐ion batteries. Extending the potential window of LMO below 3 V to access double capacity would be fantastic but hard to be realized, as it will lead to fast capacity loss due to the serious Jahn–Teller distortion. Here using experiments combined with extensive ab initio calculations, it is proved that there is a cooperative effect among individual Jahn–Teller distortions of Mn3+O6 octahedrons in LMO, named as cooperative Jahn–Teller distortion (CJTD) in the text, which is the difficulty to access the capacity beyond one lithium intercalation. It is further proposed that the cationic disordering (excess Li at Mn sites and Li/Mn exchange) can intrinsically suppress the CJTD of Mn3+O6 octahedrons. The cationic disordering can break the symmetry of Mn3+ arrangements to disrupt the correlation of distortions arising from individual JT centers and prevent the Mn3+O bonds distorting along one direction. Interestingly, with the suppressed CJTD, the original octahedral vacancies in spinel LMO are activated and can serve as extra Li‐ion storage sites to access the double capacity with good reversible cycling stability in microsized LMO.

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods.Electronic supplementary materialThe online version of this article (doi:10.1186/s13073-017-0509-y) contains supplementary material, which is available to authorized users.

Autophagy, referring to an evolutionarily conserved, multi-step lysosomal degradation process, has been well-known to be initiated by Unc-51 like kinase 1 (ULK1) with some links to Parkinson’s disease (PD). MicroRNAs (miRNAs), small and non-coding endogenous RNAs 22 ~ 24 nucleotides (nt) in length, have been demonstrated to play an essential role for modulating autophagy. Recently, the relationships between miRNAs and autophagy have been widely reported in PD; however, how microRNAs regulate autophagy still remains in its infancy. Thus, in this study, we computationally constructed the ULK1-regulated autophagic kinase subnetwork in PD and further identified ULK1 able to negatively regulate p70S6K in starvation-induced autophagy of neuroblastoma SH-SY5Y cells. Combination of in silico prediction and microarray analyses, we identified that miR-4487 and miR-595 could target ULK1 and experimentally verified they could negatively or positively regulate ULK1-mediated autophagy. In conclusion, these results may uncover the novel ULK1-p70S6K autophagic pathway, as well as miR-4487 and miR-595 as new ULK1 target miRNAs. Thus, these findings would provide a clue to explore ULK1 and its target miRNAs as potential biomarkers in the future PD therapy.