Drug-target interaction (DTI) is the basis of drug discovery and design. It is time consuming and costly to determine DTI experimentally. Hence, it is necessary to develop computational methods for the prediction of potential DTI. Based on complex network theory, three supervised inference methods were developed here to predict DTI and used for drug repositioning, namely drug-based similarity inference (DBSI), target-based similarity inference (TBSI) and network-based inference (NBI). Among them, NBI performed best on four benchmark data sets. Then a drug-target network was created with NBI based on 12,483 FDA-approved and experimental drug-target binary links, and some new DTIs were further predicted. In vitro assays confirmed that five old drugs, namely montelukast, diclofenac, simvastatin, ketoconazole, and itraconazole, showed polypharmacological features on estrogen receptors or dipeptidyl peptidase-IV with half maximal inhibitory or effective concentration ranged from 0.2 to 10 µM. Moreover, simvastatin and ketoconazole showed potent antiproliferative activities on human MDA-MB-231 breast cancer cell line in MTT assays. The results indicated that these methods could be powerful tools in prediction of DTIs and drug repositioning.

Metal halide perovskites (MHPs) are gaining increasing interest because of their extraordinary performance in optoelectronic devices and solar cells. However, developing an effective strategy for achieving the band-gap engineering of MHPs that will satisfy the practical applications remains a great challenge. In this study, high pressure is introduced to tailor the optical and structural properties of MHP-based cesium lead bromide nanocrystals (CsPbBr NCs), which exhibit excellent thermodynamic stability. Both the pressure-dependent steady-state photoluminescence and absorption spectra experience a stark discontinuity at ∼1.2 GPa, where an isostructural phase transformation regarding the Pbnm space group occurs. The physical origin points to the repulsive force impact due to the overlap between the valence electron charge clouds of neighboring layers. Simultaneous band-gap narrowing and carrier-lifetime prolongation of CsPbBr trihalide perovskite NCs were also achieved as expected, which facilitates the broader solar spectrum absorption for photovoltaic applications. Note that the values of the phase change interval and band-gap red-shift of CsPbBr nanowires are between those for CsPbBr nanocubes and the corresponding bulk counterparts, which results from the unique geometrical morphology effect. First-principles calculations unravel that the band-gap engineering is governed by orbital interactions within the inorganic Pb-Br frame through structural modification. Changes of band structures are attributed to the synergistic effect of pressure-induced modulations of the Br-Pb bond length and Pb-Br-Pb bond angle for the PbBr octahedral framework. Furthermore, the significant distortion of the lead-bromide octahedron to accommodate the Jahn-Teller effect at much higher pressure would eventually lead to a direct to indirect band-gap electronic transition. This study enables high pressure as a robust tool to control the structure and band gap of CsPbBr NCs, thus providing insight into the microscopic physiochemical mechanism of these compressed MHP nanosystems.

Oxidoreductase is the largest class of enzymes and has broad applications in biotechnology since a number of bioconversions involve oxidation/reduction reactions. Coenzymes are always required in oxidoreductase-catalyzed reactions, where nicotinamide coenzymes, NAD(P)H/NAD(P) + , are the most commonly used. They undergo reactions with substrates in biocatalytic processes by converting into their reductive or oxidative forms. The efficient and economical regeneration of nicotinamide coenzymes is therefore of particular significance for industrial applications due to their high cost and large usage. The principal methods used for the regeneration of nicotinamide coenzymes, including enzymatic, chemical, electrochemical and photochemical regeneration methods are surveyed with emphasis on the crucial issues and the state-of-art research relevant to each method. Screening and improving the performance of the enzymes, designing and implementing efficient regeneration routes as well as retaining/recycling coenzymes are the three key issues for the enzymatic method. Development of efficient catalysts with high selectivity is the top priority of the chemical regeneration method. For the electrochemical regeneration method, improvement of the electrode by modification of either the nano-materials or electron mediators is the major concern. The focus of the photochemical regeneration method lies in the exploitation of efficient visible-light photosensitizers.

The ongoing rapid expansion of the Word Wide Web (WWW) greatly increases the information of effective transmission from heterogeneous individuals to various systems. Extensive research for information diffusion is introduced by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theoretical and empirical studies, unification and comparison of different theories and approaches are lacking, which impedes further advances. In this article, we review recent developments in information diffusion and discuss the major challenges. We compare and evaluate available models and algorithms to receptively investigate their physical roles and optimization designs. Potential impacts and future directions are discussed. We emphasize that information diffusion has great scientific depth and combines diverse research fields which makes it interesting for physicists as well as interdisciplinary researchers.

The ongoing global pandemic of coronavirus disease 2019 (COVID-19) resulted from the outbreak of SARS-CoV-2 in December 2019. Currently, multiple efforts are being made to rapidly develop vaccines and treatments to fight COVID-19. Current vaccine candidates use inactivated SARS-CoV-2 viruses; therefore, it is important to understand the architecture of inactivated SARS-CoV-2. We have genetically and structurally characterized β-propiolactone-inactivated viruses from a propagated and purified clinical strain of SARS-CoV-2. We observed that the virus particles are roughly spherical or moderately pleiomorphic. Although a small fraction of prefusion spikes are found, most spikes appear nail shaped, thus resembling a postfusion state, where the S1 protein of the spike has disassociated from S2. Cryoelectron tomography and subtomogram averaging of these spikes yielded a density map that closely matches the overall structure of the SARS-CoV postfusion spike and its corresponding glycosylation site. Our findings have major implications for SARS-CoV-2 vaccine design, especially those using inactivated viruses.