Rational Design of Hollow Structural Materials for Sodium-Ion Battery Anodes.

The development of sodium-ion battery (SIB) anodes is still hindered by their rapid capacity decay and poor rate capabilities. Although there have been some new materials that can be used to fabricate stable anodes, SIBs are still far from wide applications. Strategies like nanostructure construction and material modification have been used to prepare more robust SIB anodes. Among all the design strategies, the hollow structure design is a promising method in the development of advanced anode materials. In the past decade, research efforts have been devoted to modifying the synthetic route, the type of templates, and the interior structure of hollow structures with high capacity and stability. A brief introduction is made to the main material systems and classifications of hollow structural materials first. Then different morphologies of hollow structural materials for SIB anodes from the latest reports are discussed, including nanoboxes, nanospheres, yolk shells, nanotubes, and other more complex shapes. The most used templates for the synthesis of hollow structrual materials are covered and the perspectives are highlighted at the end. This review offers a comprehensive discussion of the synthesis of hollow structural materials for SIB anodes, which could be potentially of use to research areas involving hollow materials design for batteries.

Screening Power of End-Point Free-Energy Calculations in Cucurbituril Host-Guest Systems.

End-point free-energy methods as an indispensable component in virtual screening are commonly recognized as a tool with a certain level of screening power in pharmaceutical research. While a huge number of records could be found for end-point applications in protein-ligand, protein-protein, and protein-DNA complexes from academic and industrial reports, up to now, there is no large-scale benchmark in host-guest complexes supporting the screening power of end-point free-energy techniques. A good benchmark requires a data set of sufficient coverage of pharmaceutically relevant chemical space, a long-time sampling length supporting the trajectory approximation of the ensemble average, and a sufficient sample size of receptor-acceptor pairs to stabilize the performance statistics. In this work, selecting a popular family of macrocyclic hosts named cucurbiturils, we construct a large data set containing 154 host-guest pairs, perform extensive end-point sampling of several hundred nanosecond lengths for each system, and extract the free-energy estimates with a variety of end-point free-energy techniques, including the advanced three-trajectory dielectric-constant-variable regime proposed in our recent work. The best-performing end-point protocol employs GAFF2 for solute descriptions, the three-trajectory end-point sampling regime, and the MM/GBSA Hamiltonian in free-energy extraction, achieving a high ranking metrics of Kendall τ > 0.6, a Pearlman predictive index of ∼0.8, and a high scoring power of Pearson r > 0.8. The current project as the first large-scale systematic benchmark of end-point methods in host-guest complexes in academic publications provides solid evidence of the applicability of end-point techniques and direct guidance of computational setups in practical host-guest systems.

Comprehensive Evaluation of End-Point Free Energy Techniques in Carboxylated-Pillar[6]arene Host-Guest Binding: III. Force-Field Comparison, Three-Trajectory Realization and Further Dielectric Augmentation.

Host-guest binding, despite the relatively simple structural and chemical features of individual components, still poses a challenge in computational modelling. The extreme underperformance of standard end-point methods in host-guest binding makes them practically useless. In the current work, we explore a potentially promising modification of the three-trajectory realization. The alteration couples the binding-induced structural reorganization into free energy estimation and suffers from dramatic fluctuations in internal energies in protein-ligand situations. Fortunately, the relatively small size of host-guest systems minimizes the magnitude of internal fluctuations and makes the three-trajectory realization practically suitable. Due to the incorporation of intra-molecular interactions in free energy estimation, a strong dependence on the force field parameters could be incurred. Thus, a term-specific investigation of transferable GAFF derivatives is presented, and noticeable differences in many aspects are identified between commonly applied GAFF and GAFF2. These force-field differences lead to different dynamic behaviors of the macrocyclic host, which ultimately would influence the end-point sampling and binding thermodynamics. Therefore, the three-trajectory end-point free energy calculations are performed with both GAFF versions. Additionally, due to the noticeable differences between host dynamics under GAFF and GAFF2, we add additional benchmarks of the single-trajectory end-point calculations. When only the ranks of binding affinities are pursued, the three-trajectory realization performs very well, comparable to and even better than the regressed PBSA_E scoring function and the dielectric constant-variable regime. With the GAFF parameter set, the TIP3P water in explicit solvent sampling and either PB or GB implicit solvent model in free energy estimation, the predictive power of the three-trajectory realization in ranking calculations surpasses all existing end-point methods on this dataset. We further combine the three-trajectory realization with another promising modified end-point regime of varying the interior dielectric constant. The combined regime does not incur sizable improvements for ranks and deviations from experiment exhibit non-monotonic variations.

Comprehensive evaluation of end-point free energy techniques in carboxylated-pillar[6]arene host-guest binding: I. Standard procedure.

Despite the massive application of end-point free energy methods in protein-ligand and protein-protein interactions, computational understandings about their performance in relatively simple and prototypical host-guest systems are limited. In this work, we present a comprehensive benchmark calculation with standard end-point free energy techniques in a recent host-guest dataset containing 13 host-guest pairs involving the carboxylated-pillar[6]arene host. We first assess the charge schemes for solutes by comparing the charge-produced electrostatics with many ab initio references, in order to obtain a preliminary albeit detailed view of the charge quality. Then, we focus on four modelling details of end-point free energy calculations, including the docking procedure for the generation of initial condition, the charge scheme for host and guest molecules, the water model used in explicit-solvent sampling, and the end-point methods for free energy estimation. The binding thermodynamics obtained with different modelling schemes are compared with experimental references, and some practical guidelines on maximizing the performance of end-point methods in practical host-guest systems are summarized. Further, we compare our simulation outcome with predictions in the grand challenge and discuss further developments to improve the prediction quality of end-point free energy methods. Overall, unlike the widely acknowledged applicability in protein-ligand binding, the standard end-point calculations cannot produce useful outcomes in host-guest binding and thus are not recommended unless alterations are performed.

Therapeutic target database 2020: enriched resource for facilitating research and early development of targeted therapeutics.

Knowledge of therapeutic targets and early drug candidates is useful for improved drug discovery. In particular, information about target regulators and the patented therapeutic agents facilitates research regarding druggability, systems pharmacology, new trends, molecular landscapes, and the development of drug discovery tools. To complement other databases, we constructed the Therapeutic Target Database (TTD) with expanded information about (i) target-regulating microRNAs and transcription factors, (ii) target-interacting proteins, and (iii) patented agents and their targets (structures and experimental activity values if available), which can be conveniently retrieved and is further enriched with regulatory mechanisms or biochemical classes. We also updated the TTD with the recently released International Classification of Diseases ICD-11 codes and additional sets of successful, clinical trial, and literature-reported targets that emerged since the last update. TTD is accessible at http://bidd.nus.edu.sg/group/ttd/ttd.asp. In case of possible web connectivity issues, two mirror sites of TTD are also constructed (http://db.idrblab.org/ttd/ and http://db.idrblab.net/ttd/).

Let-7 mediated airway remodelling in chronic obstructive pulmonary disease via the regulation of IL-6.

BACKGROUND: Myofibroblast differentiation and extracellular matrix (ECM) deposition are observed in chronic obstructive pulmonary disease (COPD). However, the mechanisms of regulation of myofibroblast differentiation remain unclear. MATERIALS AND METHODS: We detected let-7 levels in peripheral lung tissues, serum and primary bronchial epithelial cells of COPD patients and cigarette smoke (CS)-exposed mice. IL-6 mRNA was explored in lung tissues of COPD patients and CS-exposed mice. IL-6 protein was detected in cell supernatant from primary epithelial cells by ELISA. We confirmed the regulatory effect of let-7 on IL-6 by luciferase reporter assay. Western blotting assay was used to determine the expression of α-SMA, E-cadherin and collagen I. In vitro, cell study was performed to demonstrate the role of let-7 in myofibroblast differentiation and ECM deposition. RESULTS: Low expression of let-7 was observed in COPD patients, CS-exposed mice and CS extract (CSE)-treated human bronchial epithelial (HBE) cells. Increased IL-6 was found in COPD patients, CS-exposed mice and CSE-treated HBE cells. Let-7 targets and silences IL-6 protein coding genes through binding to 3' untranslated region (UTR) of IL-6. Normal or CSE-treated HBE cells were co-cultured with human embryonic lung fibroblasts (MRC-5 cells). Reduction of let-7 in HBE cells caused myofibroblast differentiation and ECM deposition, while increase of let-7 mimics decreased myofibroblast differentiation phenotype and ECM deposition. CONCLUSION: We demonstrate that CS reduced let-7 expression in COPD and, further, identify let-7 as a regulator of myofibroblast differentiation through the regulation of IL-6, which has potential value for diagnosis and treatment of COPD.

CMAUP: a database of collective molecular activities of useful plants.

The beneficial effects of functionally useful plants (e.g. medicinal and food plants) arise from the multi-target activities of multiple ingredients of these plants. The knowledge of the collective molecular activities of these plants facilitates mechanistic studies and expanded applications. A number of databases provide information about the effects and targets of various plants and ingredients. More comprehensive information is needed for broader classes of plants and for the landscapes of individual plant's multiple targets, collective activities and regulated biological pathways, processes and diseases. We therefore developed a new database, Collective Molecular Activities of Useful Plants (CMAUP), to provide the collective landscapes of multiple targets (ChEMBL target classes) and activity levels (in 2D target-ingredient heatmap), and regulated gene ontologies (GO categories), biological pathways (KEGG categories) and diseases (ICD blocks) for 5645 plants (2567 medicinal, 170 food, 1567 edible, 3 agricultural and 119 garden plants) collected from or traditionally used in 153 countries and regions. These landscapes were derived from 47 645 plant ingredients active against 646 targets in 234 KEGG pathways associated with 2473 gene ontologies and 656 diseases. CMAUP (http://bidd2.nus.edu.sg/CMAUP/) is freely accessible and searchable by keywords, plant usage classes, species families, targets, KEGG pathways, gene ontologies, diseases (ICD code) and geographical locations.

NPASS: natural product activity and species source database for natural product research, discovery and tool development.

There has been renewed interests in the exploration of natural products (NPs) for drug discovery, and continuous investigations of the therapeutic claims and mechanisms of traditional and herbal medicines. In-silico methods have been employed for facilitating these studies. These studies and the optimization of in-silico algorithms for NP applications can be facilitated by the quantitative activity and species source data of the NPs. A number of databases collectively provide the structural and other information of ∼470 000 NPs, including qualitative activity information for many NPs, but only ∼4000 NPs are with the experimental activity values. There is a need for the activity and species source data of more NPs. We therefore developed a new database, NPASS (Natural Product Activity and Species Source) to complement other databases by providing the experimental activity values and species sources of 35 032 NPs from 25 041 species targeting 5863 targets (2946 proteins, 1352 microbial species and 1227 cell-lines). NPASS contains 446 552 quantitative activity records (e.g. IC50, Ki, EC50, GI50 or MIC mainly in units of nM) of 222 092 NP-target pairs and 288 002 NP-species pairs. NPASS, http://bidd2.nus.edu.sg/NPASS/, is freely accessible with its contents searchable by keywords, physicochemical property range, structural similarity, species and target search facilities.

Therapeutic target database update 2018: enriched resource for facilitating bench-to-clinic research of targeted therapeutics.

Extensive efforts have been directed at the discovery, investigation and clinical monitoring of targeted therapeutics. These efforts may be facilitated by the convenient access of the genetic, proteomic, interactive and other aspects of the therapeutic targets. Here, we describe an update of the Therapeutic target database (TTD) previously featured in NAR. This update includes: (i) 2000 drug resistance mutations in 83 targets and 104 target/drug regulatory genes, which are resistant to 228 drugs targeting 63 diseases (49 targets of 61 drugs with patient prevalence data); (ii) differential expression profiles of 758 targets in the disease-relevant drug-targeted tissue of 12 615 patients of 70 diseases; (iii) expression profiles of 629 targets in the non-targeted tissues of 2565 healthy individuals; (iv) 1008 target combinations of 1764 drugs and the 1604 target combination of 664 multi-target drugs; (v) additional 48 successful, 398 clinical trial and 21 research targets, 473 approved, 812 clinical trial and 1120 experimental drugs, and (vi) ICD-10-CM and ICD-9-CM codes for additional 482 targets and 262 drugs against 98 disease conditions. This update makes TTD more useful for facilitating the patient focused research, discovery and clinical investigations of the targeted therapeutics. TTD is accessible at http://bidd.nus.edu.sg/group/ttd/ttd.asp.

A protein network descriptor server and its use in studying protein, disease, metabolic and drug targeted networks.

The genetic, proteomic, disease and pharmacological studies have generated rich data in protein interaction, disease regulation and drug activities useful for systems-level study of the biological, disease and drug therapeutic processes. These studies are facilitated by the established and the emerging computational methods. More recently, the network descriptors developed in other disciplines have become more increasingly used for studying the protein-protein, gene regulation, metabolic, disease networks. There is an inadequate coverage of these useful network features in the public web servers. We therefore introduced upto 313 literature-reported network descriptors in PROFEAT web server, for describing the topological, connectivity and complexity characteristics of undirected unweighted (uniform binding constants and molecular levels), undirected edge-weighted (varying binding constants), undirected node-weighted (varying molecular levels), undirected edge-node-weighted (varying binding constants and molecular levels) and directed unweighted (oriented process) networks. The usefulness of the PROFEAT computed network descriptors is illustrated by their literature-reported applications in studying the protein-protein, gene regulatory, gene co-expression, protein-drug and metabolic networks. PROFEAT is accessible free of charge at http://bidd2.nus.edu.sg/cgi-bin/profeat2016/main.cgi.

HEROD: a human ethnic and regional specific omics database.

MOTIVATION: Genetic and gene expression variations within and between populations and across geographical regions have substantial effects on the biological phenotypes, diseases, and therapeutic response. The development of precision medicines can be facilitated by the OMICS studies of the patients of specific ethnicity and geographic region. However, there is an inadequate facility for broadly and conveniently accessing the ethnic and regional specific OMICS data. RESULTS: Here, we introduced a new free database, HEROD, a human ethnic and regional specific OMICS database. Its first version contains the gene expression data of 53 070 patients of 169 diseases in seven ethnic populations from 193 cities/regions in 49 nations curated from the Gene Expression Omnibus (GEO), the ArrayExpress Archive of Functional Genomics Data (ArrayExpress), the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). Geographic region information of curated patients was mainly manually extracted from referenced publications of each original study. These data can be accessed and downloaded via keyword search, World map search, and menu-bar search of disease name, the international classification of disease code, geographical region, location of sample collection, ethnic population, gender, age, sample source organ, patient type (patient or healthy), sample type (disease or normal tissue) and assay type on the web interface. AVAILABILITY AND IMPLEMENTATION: The HEROD database is freely accessible at http://bidd2.nus.edu.sg/herod/index.php. The database and web interface are implemented in MySQL, PHP and HTML with all major browsers supported. CONTACT: phacyz@nus.edu.sg.

Therapeutic target database update 2016: enriched resource for bench to clinical drug target and targeted pathway information.

Extensive drug discovery efforts have yielded many approved and candidate drugs targeting various targets in different biological pathways. Several freely accessible databases provide the drug, target and drug-targeted pathway information for facilitating drug discovery efforts, but there is an insufficient coverage of the clinical trial drugs and the drug-targeted pathways. Here, we describe an update of the Therapeutic Target Database (TTD) previously featured in NAR. The updated contents include: (i) significantly increased coverage of the clinical trial targets and drugs (1.6 and 2.3 times of the previous release, respectively), (ii) cross-links of most TTD target and drug entries to the corresponding pathway entries of KEGG, MetaCyc/BioCyc, NetPath, PANTHER pathway, Pathway Interaction Database (PID), PathWhiz, Reactome and WikiPathways, (iii) the convenient access of the multiple targets and drugs cross-linked to each of these pathway entries and (iv) the recently emerged approved and investigative drugs. This update makes TTD a more useful resource to complement other databases for facilitating the drug discovery efforts. TTD is accessible at http://bidd.nus.edu.sg/group/ttd/ttd.asp.

CFam: a chemical families database based on iterative selection of functional seeds and seed-directed compound clustering.

Similarity-based clustering and classification of compounds enable the search of drug leads and the structural and chemogenomic studies for facilitating chemical, biomedical, agricultural, material and other industrial applications. A database that organizes compounds into similarity-based as well as scaffold-based and property-based families is useful for facilitating these tasks. CFam Chemical Family database http://bidd2.cse.nus.edu.sg/cfam was developed to hierarchically cluster drugs, bioactive molecules, human metabolites, natural products, patented agents and other molecules into functional families, superfamilies and classes of structurally similar compounds based on the literature-reported high, intermediate and remote similarity measures. The compounds were represented by molecular fingerprint and molecular similarity was measured by Tanimoto coefficient. The functional seeds of CFam families were from hierarchically clustered drugs, bioactive molecules, human metabolites, natural products, patented agents, respectively, which were used to characterize families and cluster compounds into families, superfamilies and classes. CFam currently contains 11,643 classes, 34,880 superfamilies and 87,136 families of 490,279 compounds (1691 approved drugs, 1228 clinical trial drugs, 12,386 investigative drugs, 262,881 highly active molecules, 15,055 human metabolites, 80,255 ZINC-processed natural products and 116,783 patented agents). Efforts will be made to further expand CFam database and add more functional categories and families based on other types of molecular representations.

Therapeutic target database update 2014: a resource for targeted therapeutics.

Here we describe an update of the Therapeutic Target Database (http://bidd.nus.edu.sg/group/ttd/ttd.asp) for better serving the bench-to-clinic communities and for enabling more convenient data access, processing and exchange. Extensive efforts from the research, industry, clinical, regulatory and management communities have been collectively directed at the discovery, investigation, application, monitoring and management of targeted therapeutics. Increasing efforts have been directed at the development of stratified and personalized medicines. These efforts may be facilitated by the knowledge of the efficacy targets and biomarkers of targeted therapeutics. Therefore, we added search tools for using the International Classification of Disease ICD-10-CM and ICD-9-CM codes to retrieve the target, biomarker and drug information (currently enabling the search of almost 900 targets, 1800 biomarkers and 6000 drugs related to 900 disease conditions). We added information of almost 1800 biomarkers for 300 disease conditions and 200 drug scaffolds for 700 drugs. We significantly expanded Therapeutic Target Database data contents to cover >2300 targets (388 successful and 461 clinical trial targets), 20 600 drugs (2003 approved and 3147 clinical trial drugs), 20,000 multitarget agents against almost 400 target-pairs and the activity data of 1400 agents against 300 cell lines.

Lentivirus-mediated short hairpin RNA interference targeting TNF-alpha in macrophages inhibits particle-induced inflammation and osteolysis in vitro and in vivo.

BACKGROUND: Aseptic loosening is a significant impediment to joint implant longevity. Prosthetic wear particles are postulated to play a central role in the onset and progression of periprosthetic osteolysis, leading to aseptic loosening of the prosthesis. METHODS: We investigated the inhibitory effects of a lentivirus-mediated short hairpin RNA that targets the TNF-alpha gene on the particle-induced inflammatory and osteolytic changes via macrophages both in vitro and in vivo. An siRNA sequence targeting the mouse TNF-alpha gene from four candidates, transcribed in vitro, was screened and identified. A lentivirus vector expressing short hairpin RNA (shRNA) was then constructed in order to facilitate efficient expression of TNF-alpha-siRNA. Lentivirus-mediated shRNA was transduced into cells of the mouse macrophage line RAW 264.7. Ceramic and titanium particles were introduced 24 h after lentivirus transduction to stimulate cells. TNF-alpha expression, represented by both mRNA and protein levels, was quantified with real-time PCR and ELISA at all time intervals. Lentivirus-mediated shRNA suspension was locally administered into the murine calvarial model, followed by local injection of particles. A multi-slice spiral CT scan was used to evaluate the osteolysis of the calvaria by detecting the width of the cranial sutures. RESULTS: Macrophages developed pseudopods when co-cultured with particles. Lentivirus-mediated shRNA was shown to effectively inhibit the expression of TNF-alpha at both the mRNA and protein levels in RAW 264.7. The multi-slice spiral CT scan showed that the lentivirus-mediated shRNA significantly suppressed osteolysis of mouse calvaria. CONCLUSIONS: Our investigation highlighted the results that lentivirus-mediated shRNA targeting the TNF-alpha gene successfully inhibited particle-induced inflammatory and osteolytic changes both in vitro and in vivo. Therefore, lentivirus-mediated gene therapy may provide a novel therapeutic approach to aseptic joint loosening.

Potential role of miR-100 in cancer diagnosis, prognosis, and therapy.

MicroRNAs (miRNAs) are small non-coding RNAs that function by base pairing with messenger RNAs, thereby regulating protein expression. Functional studies indicate that miRNAs are involved in the regulation of almost every biological pathway. Moreover, changes in miRNA expression are associated with several human pathologies, including cancer. Dysregulation and aberrant expression of microRNA-100 (miR-100) have been reported to be involved in tumorigenesis and tumor progression of several cancer types, suggesting that miR-100 might serve as a diagnostic and/or prognostic marker for human malignancy. In this review, we summarize the potential application of miR-100 in cancer treatment and as a new molecular marker for cancer prognosis and diagnosis. We will provide a brief introduction to miR-100 and discuss its role as a non-invasive biomarker and a potential therapeutic target in human cancers.

Copper-catalysed direct radical alkenylation of alkyl bromides.

A copper-catalysed direct radical alkenylation of various benzyl bromides and α-carbonyl alkyl bromides has been developed. Compared with the recent radical alkenylations which mostly focused on secondary or tertiary alkyl halides, this transformation shows good reactivity to primary alkyl halides and tertiary, secondary alkyl halides were also tolerated. The key initiation step of this transformation is a copper-induced single-electron reduction of C-Br bonds to generate alkyl radical species.

Therapeutic target database update 2012: a resource for facilitating target-oriented drug discovery.

Knowledge and investigation of therapeutic targets (responsible for drug efficacy) and the targeted drugs facilitate target and drug discovery and validation. Therapeutic Target Database (TTD, http://bidd.nus.edu.sg/group/ttd/ttd.asp) has been developed to provide comprehensive information about efficacy targets and the corresponding approved, clinical trial and investigative drugs. Since its last update, major improvements and updates have been made to TTD. In addition to the significant increase of data content (from 1894 targets and 5028 drugs to 2025 targets and 17,816 drugs), we added target validation information (drug potency against target, effect against disease models and effect of target knockout, knockdown or genetic variations) for 932 targets, and 841 quantitative structure activity relationship models for active compounds of 228 chemical types against 121 targets. Moreover, we added the data from our previous drug studies including 3681 multi-target agents against 108 target pairs, 116 drug combinations with their synergistic, additive, antagonistic, potentiative or reductive mechanisms, 1427 natural product-derived approved, clinical trial and pre-clinical drugs and cross-links to the clinical trial information page in the ClinicalTrials.gov database for 770 clinical trial drugs. These updates are useful for facilitating target discovery and validation, drug lead discovery and optimization, and the development of multi-target drugs and drug combinations.

Clustered patterns of species origins of nature-derived drugs and clues for future bioprospecting.

Many drugs are nature derived. Low drug productivity has renewed interest in natural products as drug-discovery sources. Nature-derived drugs are composed of dozens of molecular scaffolds generated by specific secondary-metabolite gene clusters in selected species. It can be hypothesized that drug-like structures probably are distributed in selective groups of species. We compared the species origins of 939 approved and 369 clinical-trial drugs with those of 119 preclinical drugs and 19,721 bioactive natural products. In contrast to the scattered distribution of bioactive natural products, these drugs are clustered into 144 of the 6,763 known species families in nature, with 80% of the approved drugs and 67% of the clinical-trial drugs concentrated in 17 and 30 drug-prolific families, respectively. Four lines of evidence from historical drug data, 13,548 marine natural products, 767 medicinal plants, and 19,721 bioactive natural products suggest that drugs are derived mostly from preexisting drug-productive families. Drug-productive clusters expand slowly by conventional technologies. The lack of drugs outside drug-productive families is not necessarily the result of under-exploration or late exploration by conventional technologies. New technologies that explore cryptic gene clusters, pathways, interspecies crosstalk, and high-throughput fermentation enable the discovery of novel natural products. The potential impact of these technologies on drug productivity and on the distribution patterns of drug-productive families is yet to be revealed.

Visible-light-mediated decarboxylation/oxidative amidation of α-keto acids with amines under mild reaction conditions using O(2).

Photochemistry has ushered in a new era in the development of chemistry, and photoredox catalysis has become a hot topic, especially over the last five years, with the combination of visible-light photoredox catalysis and radical reactions. A novel, simple, and efficient radical oxidative decarboxylative coupling with the assistant of the photocatalyst [Ru(phen)3 ]Cl2 is described. Various functional groups are well-tolerated in this reaction and thus provides a new approach to developing advanced methods for aerobic oxidative decarboxylation. The preliminary mechanistic studies revealed that: 1) an SET process between [Ru(phen)3 ](2+) * and aniline play an important role; 2) O2 activation might be the rate-determining step; and 3) the decarboxylation step is an irreversible and fast process.