Current pharmaceutical research and development (R&D) is a high-risk investment which is usually faced with some unexpected even disastrous failures in different stages of drug discovery. One main ...reason for R&D failures is the efficacy and safety deficiencies which are related largely to absorption, distribution, metabolism and excretion (ADME) properties and various toxicities (T). Therefore, rapid ADMET evaluation is urgently needed to minimize failures in the drug discovery process. Here, we developed a web-based platform called ADMETlab for systematic ADMET evaluation of chemicals based on a comprehensively collected ADMET database consisting of 288,967 entries. Four function modules in the platform enable users to conveniently perform six types of drug-likeness analysis (five rules and one prediction model), 31 ADMET endpoints prediction (basic property: 3, absorption: 6, distribution: 3, metabolism: 10, elimination: 2, toxicity: 7), systematic evaluation and database/similarity searching. We believe that this web platform will hopefully facilitate the drug discovery process by enabling early drug-likeness evaluation, rapid ADMET virtual screening or filtering and prioritization of chemical structures. The ADMETlab web platform is designed based on the Django framework in Python, and is freely accessible at
http://admet.scbdd.com/
.
The Caco-2 cell monolayer model is a popular surrogate in predicting the in vitro human intestinal permeability of a drug due to its morphological and functional similarity with human enterocytes. A ...quantitative structure–property relationship (QSPR) study was carried out to predict Caco-2 cell permeability of a large data set consisting of 1272 compounds. Four different methods including multivariate linear regression (MLR), partial least-squares (PLS), support vector machine (SVM) regression and Boosting were employed to build prediction models with 30 molecular descriptors selected by nondominated sorting genetic algorithm-II (NSGA-II). The best Boosting model was obtained finally with R 2 = 0.97, RMSEF = 0.12, Q 2 = 0.83, RMSECV = 0.31 for the training set and R T 2 = 0.81, RMSET = 0.31 for the test set. A series of validation methods were used to assess the robustness and predictive ability of our model according to the OECD principles and then define its applicability domain. Compared with the reported QSAR/QSPR models about Caco-2 cell permeability, our model exhibits certain advantage in database size and prediction accuracy to some extent. Finally, we found that the polar volume, the hydrogen bond donor, the surface area and some other descriptors can influence the Caco-2 permeability to some extent. These results suggest that the proposed model is a good tool for predicting the permeability of drug candidates and to perform virtual screening in the early stage of drug development.
The ureolytic bacterium Sporosarcina pasteurii is well-known for its capability of microbially induced calcite precipitation (MICP), representing a great potential in constructional engineering and ...material applications. However, the molecular mechanism for its biomineralization remains unresolved, as few studies were carried out.
The addition of urea into the culture medium provided an alkaline environment that is suitable for S. pasteurii. As compared to S. pasteurii cultivated without urea, S. pasteurii grown with urea showed faster growth and urease production, better shape, more negative surface charge and higher biomineralization ability. To survive the unfavorable growth environment due to the absence of urea, S. pasteurii up-regulated the expression of genes involved in urease production, ATPase synthesis and flagella, possibly occupying resources that can be deployed for MICP. As compared to non-mineralizing bacteria, S. pasteurii exhibited more negative cell surface charge for binding calcium ions and more robust cell structure as nucleation sites. During MICP process, the genes for ATPase synthesis in S. pasteurii was up-regulated while genes for urease production were unchanged. Interestingly, genes involved in flagella were down-regulated during MICP, which might lead to poor mobility of S. pasteurii. Meanwhile, genes in fatty acid degradation pathway were inhibited to maintain the intact cell structure found in calcite precipitation. Both weak mobility and intact cell structure are advantageous for S. pasteurii to serve as nucleation sites during MICP.
Four factors are demonstrated to benefit the super performance of S. pasteurii in MICP. First, the good correlation of biomass growth and urease production of S. pasteurii provides sufficient biomass and urease simultaneously for improved biomineralization. Second, the highly negative cell surface charge of S. pasteurii is good for binding calcium ions. Third, the robust cell structure and fourth, the weak mobility, are key for S. pasteurii to be nucleation sites during MICP.
The Pt catalysts supported on hexagonal BN (Pt/BN) are highly active and stable for propane combustion, with the highest specific reaction rate of 92.3 μmol gPt –1 s–1 and turnover frequency of 0.037 ...s–1 obtained on a 0.2Pt/BN catalyst at 220 °C. The Pt oxide in the catalyst could be partially reduced to the metallic state by propane during the reaction, which is beneficial for the improvement of activity, indicating that metallic Pt might be the active sites. The highly dispersed Pt particles stabilized at the grain boundary of BN could be more easily reduced in the reaction than those on the surface and thus are more active. Moreover, kinetic investigation reveals that the apparent activation energy of the Pt species at the grain boundary (111.6 ± 8.0 kJ mol–1) is much lower than that on the surface (172.4 ± 16.5 kJ mol–1), suggesting different reaction pathways on these catalysts and the possible participation of the grain boundary of the BN support in the reaction.
Background
With the increasing development of biotechnology and informatics technology, publicly available data in chemistry and biology are undergoing explosive growth. Such wealthy information in ...these data needs to be extracted and transformed to useful knowledge by various data mining methods. Considering the amazing rate at which data are accumulated in chemistry and biology fields, new tools that process and interpret large and complex interaction data are increasingly important. So far, there are no suitable toolkits that can effectively link the chemical and biological space in view of molecular representation. To further explore these complex data, an integrated toolkit for various molecular representation is urgently needed which could be easily integrated with data mining algorithms to start a full data analysis pipeline.
Results
Herein, the python library
PyBioMed
is presented, which comprises functionalities for online download for various molecular objects by providing different IDs, the pretreatment of molecular structures, the computation of various molecular descriptors for chemicals, proteins, DNAs and their interactions.
PyBioMed
is a feature-rich and highly customized python library used for the characterization of various complex chemical and biological molecules and interaction samples. The current version of
PyBioMed
could calculate 775 chemical descriptors and 19 kinds of chemical fingerprints, 9920 protein descriptors based on protein sequences, more than 6000 DNA descriptors from nucleotide sequences, and interaction descriptors from pairwise samples using three different combining strategies. Several examples and five real-life applications were provided to clearly guide the users how to use
PyBioMed
as an integral part of data analysis projects. By using
PyBioMed
, users are able to start a full pipelining from getting molecular data, pretreating molecules, molecular representation to constructing machine learning models conveniently.
Conclusion
PyBioMed
provides various user-friendly and highly customized APIs to calculate various features of biological molecules and complex interaction samples conveniently, which aims at building integrated analysis pipelines from data acquisition, data checking, and descriptor calculation to modeling.
PyBioMed
is freely available at
http://projects.scbdd.com/pybiomed.html
.
Drug–target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug ...reactions, drug–drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user’s molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75–100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug–drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at
http://targetnet.scbdd.com
.
The development of micro/nanofluidic techniques has recently revived interest in dynamic shear flow at liquid–solid interfaces. When the nature of the liquid–solid boundaries was revisited, the slip ...of the fluids relative to the solid wall was predicted theoretically and confirmed experimentally. This indicates that the molecular-level structures of the liquid–solid interfaces will be influenced by the liquid flow over certain temporal and spatial criteria. However, the fluid flow at the boundary layer still cannot be precisely predicted and effectively controlled, somehow limiting its practical applications. Here, we summarize the recent advances for the microscopic structures at the liquid–solid interfaces upon shear flow. Special attention was given to a second-order nonlinear optical technique, sum frequency generation vibrational spectroscopy, which is a powerful tool for exploring the molecular-level structures and structural dynamics at the liquid–solid interfaces and offering new insights into the molecular mechanisms of the fluid slip at the interfaces. Moreover, we discuss the possible approaches for controlling the interfacial slip at the molecular level and highlight the current challenges and opportunities. Although the theoretical framework of the slip at the liquid–solid interfaces is still incomplete, we hope that this Perspective will complement and enhance our understanding of various interfacial properties and phenomena with respect to practical non-equilibrium dynamic processes happening at the interfaces.
Background Monoclonal antibodies targeting programmed death ligand 1 (PD-L1) signaling currently approved for defective mismatch repair (dMMR)/microsatellite instability high (MSI-H) tumors must be ...delivered by intravenous infusion. Envafolimab, a humanized single-domain anti-PD-L1 antibody fused to an Fc fragment, represents a potential advance because it can be conveniently administered subcutaneously. Methods This open-label, single-arm, phase 2 study evaluated the efficacy and safety of envafolimab in patients with previously treated advanced dMMR/MSI-H tumors from 25 clinical sites across China. Adults with histologically confirmed locally advanced or metastatic malignant dMMR/MSI-H solid tumors received weekly 150 mg subcutaneous envafolimab injections in a 28-day treatment cycle. The primary efficacy endpoint was the objective response rate (assessed by a blinded independent review committee). Secondary efficacy outcomes were disease control rate, duration of response, progression-free survival, and overall survival. Results One hundred and three patients (65 with colorectal cancer, 18 with gastric cancer, and 20 with other solid tumors) were enrolled. Median follow-up was 11.5 months. The objective response rate was 42.7% (95% confidence interval CI 33.0-52.8), and the disease control rate was 66.0% (95% CI 56.0-75.1). Median duration of response was not reached; the duration of response rate at 12 months was 92.2% (95% CI 77.5-97.4). Median progression-free survival was 11.1 months (95% CI 5.5 to not evaluable). Overall survival at 12 months was 74.6% (95% CI 64.7-82.1). Sixteen patients (16%) had at least one grade 3 or 4 related treatment-emergent adverse event. No grade 5 treatment-emergent adverse events related to envafolimab were reported. Injection site reactions, all grade 1-2, were reported in nine patients (9%), but there were no infusion reactions. Eight patients (8%) had grade 3 or 4 immune-related adverse events. Conclusions This is the first pivotal phase 2 study to examine the efficacy and safety of a single-domain immune checkpoint antibody in the treatment of cancer. Envafolimab was effective and had acceptable safety in the treatment of previously treated advanced dMMR/MSI-H solid tumors. As the first single-domain PD-L1-targeting antibody administered by rapid subcutaneous injection, envafolimab has the potential to be a significant advance in the treatment of cancer. Trial registration ClinicalTrials.gov, NCT03667170. Registered 10 September 2018--Retrospectively registered, Keywords: Envafolimab, PD-L1, dMMR/MSI-H, Subcutaneous injection
Semiconductor photocatalysts are hardly employed for overall water splitting beyond 700 nm, which is due to both thermodynamic aspects and activation barriers. Metallic materials as photocatalysts ...are known to overcome this limitation through interband transitions for creating electron–hole pairs; however, the application of metallic photocatalysts for overall water splitting has never been fulfilled. Black tungsten nitride is now employed as a metallic photocatalyst for overall water splitting at wavelengths of up to 765 nm. Experimental and theoretical results together confirm that metallic properties play a substantial role in exhibiting photocatalytic activity under red‐light irradiation for tungsten nitride. This work represents the first red‐light responsive photocatalyst for overall water splitting, and may open a promising venue in searching of metallic materials as efficient photocatalysts for solar energy utilization.
Black tungsten nitride can be employed as a metallic photocatalyst for overall water splitting at wavelengths of up to 765 nm. Experimental and theoretical results together confirm that metallic properties play a substantial role in exhibiting photocatalytic activity under red‐light irradiation for tungsten nitride. CB=conduction band.
PDF
