Phylogenomic analyses provide insights into primate evolution.

Comparative analysis of primate genomes within a phylogenetic context is essential for understanding the evolution of human genetic architecture and primate diversity. We present such a study of 50 primate species spanning 38 genera and 14 families, including 27 genomes first reported here, with many from previously less well represented groups, the New World monkeys and the Strepsirrhini. Our analyses reveal heterogeneous rates of genomic rearrangement and gene evolution across primate lineages. Thousands of genes under positive selection in different lineages play roles in the nervous, skeletal, and digestive systems and may have contributed to primate innovations and adaptations. Our study reveals that many key genomic innovations occurred in the Simiiformes ancestral node and may have had an impact on the adaptive radiation of the Simiiformes and human evolution.

iORbase: A database for the prediction of the structures and functions of insect olfactory receptors.

Insect olfactory receptors (iORs) with atypical 7-transmembrane domains, unlike Chordata olfactory receptors, are not in the GPCR protein family. iORs selectively bind to volatile ligands in the environment and affect essential insect behaviors. In this study, we constructed a new platform (iORbase, https://www.iorbase.com) for the structural and functional analysis of iORs based on a combined algorithm for gene annotation and protein structure prediction. Moreover, it provides the option to calculate the binding affinities and binding residues between iORs and pheromone molecules by virtual screening of docking. Furthermore, iORbase supports the automatic structural and functional prediction of user-submitted iORs or pheromones. iORbase contains the well-analyzed results of approximately 6 000 iORs and their 3D protein structures identified from 59 insect species and 2 077 insect pheromones from the literature, as well as approximately 12 million pairs of simulated interactions between functional iORs and pheromones. We also built 4 online modules, iORPDB, iInteraction, iModelTM, and iOdorTool to easily retrieve and visualize the 3D structures and interactions. iORbase can help greatly improve the experimental efficiency and success rate, identify new insecticide targets, or develop electronic nose technology. This study will shed light on the olfactory recognition mechanism and evolutionary characteristics from the perspectives of omics and macroevolution.

The Evolution History of Fe-S Cluster A-Type Assembly Protein Reveals Multiple Gene Duplication Events and Essential Protein Motifs.

Iron-sulfur (Fe-S) clusters play important roles in electron transfer, metabolic and biosynthetic reactions, and the regulation of gene expression. Understanding the biogenesis of Fe-S clusters is therefore relevant to many fields. In the complex process of Fe-S protein formation, the A-type assembly protein (ATAP) family, which consists of several subfamilies, plays an essential role in Fe-S cluster formation and transfer and is highly conserved across the tree of life. However, the taxonomic distribution, motif compositions, and the evolutionary history of the ATAP subfamilies are not well understood. To address these problems, our study investigated the taxonomic distribution of 321 species from a broad cross-section of taxa. Then, we identified common and specific motifs in multiple ATAP subfamilies to explain the functional conservation and nonredundancy of the ATAPs, and a novel, essential motif was found in Eumetazoa IscA1, which has a newly found magnetic function. Finally, we used phylogenetic analytical methods to reconstruct the evolution history of this family. Our results show that two types of ErpA proteins (nonproteobacteria-type ErpA1 and proteobacteria-type ErpA2) exist in bacteria. The ATAP family, consisting of seven subfamilies, can be further classified into two types of ATAPs. Type-I ATAPs include IscA, SufA, HesB, ErpA1, and IscA1, with an ErpA1-like gene as their last common ancestor, whereas type-II ATAPs consist of ErpA2 and IscA2, duplicated from an ErpA2-like gene. During the mitochondrial endosymbiosis, IscA became IscA1 in eukaryotes and ErpA2 became IscA2 in eukaryotes, respectively.

Comparison of the roles of estrogens and androgens in breast cancer and prostate cancer.

Breast cancer (BC) and prostate cancer (PC) are the second most common malignant tumors in women and men in western countries, respectively. The risks of death are 14% for BC and 9% for PC. Abnormal estrogen and androgen levels are related to carcinogenesis of the breast and prostate. Estradiol stimulates cancer development in BC. The effect of estrogen on PC is concentration-dependent, and estrogen can regulate androgen production, further affecting PC. Estrogen can also increase the risk of androgen-induced PC. Androgen has dual effects on BC via different metabolic pathways, and the role of the androgen receptor (AR) in BC also depends on cell subtype and downstream target genes. Androgen and AR can stimulate both primary PC and castration-resistant PC. Understanding the mechanisms of the effects of estrogen and androgen on BC and PC may help us to improve curative BC and PC treatment strategies.

Predicting combinative drug pairs via multiple classifier system with positive samples only.

BACKGROUND AND OBJECTIVE: Due to the synergistic effects of drugs, drug combination is one of the effective approaches for treating complex diseases. However, the identification of drug combinations by dose-response methods is still costly. It is promising to develop supervised learning-based approaches to predict potential drug combinations on a large scale. Nevertheless, these approaches have the inadequate utilization of heterogeneous features, which causes the loss of information useful to classification. Moreover, they have an intrinsic bias, because they assume unknown drug pairs as non-combinations, of which some could be real drug combinations in practice. METHODS: To address above issues, this work first designs a two-layer multiple classifier system (TLMCS) to effectively integrate heterogeneous features involving anatomical therapeutic chemical codes of drugs, drug-drug interactions, drug-target interactions, gene ontology of drug targets, and side effects. To avoid the bias caused by labelling unknown samples as negative, it then utilizes the one-class support vector machines, (which requires no negative instance and only labels approved drug combinations as positive instances), as the member classifiers in TLMCS. Last, both a 10-fold cross validation (10-CV) and a novel prediction are performed to validate the performance of TLMCS. RESULTS: The comparison with three state-of-the-art approaches under 10-CV exhibits the superiority of TLMCS, which achieves the area under the receiver operating characteristic curve = 0.824 and the area under the precision-recall curve = 0.372. Moreover, the experiment under the novel prediction demonstrates its ability, where 9 out of the top-20 predicted combinative drug pairs are validated by checking the published literature. Furthermore, for each of the newly-validated drug combinations, this work analyses the combining mode of the member drugs and investigates their relationship in terms of drug targeting pathways. CONCLUSIONS: The proposed TLMCS provides an effective framework to integrate those heterogeneous features and is trained by only positive samples such that the bias of taking unknown drug pairs as negative samples can be avoided. Furthermore, its results in the novel prediction reveal five types of drug combinations and three types of drug relationships in terms of pathways.

Effects of large gradient high magnetic field (LG-HMF) on the long-term culture of aquatic organisms: Planarians example.

Large gradient high magnetic field (LG-HMF) is a powerful tool to study the effects of altered gravity on organisms. In our study, a platform for the long-term culture of aquatic organisms was designed based on a special superconducting magnet with an LG-HMF, which can provide three apparent gravity levels (µ g, 1 g, and 2 g), along with a control condition on the ground. Planarians, Dugesia japonica, were head-amputated and cultured for 5 days in a platform for head reconstruction. After planarian head regeneration, all samples were taken out from the superconducting magnet for a behavioral test under geomagnetic field and normal gravity conditions. To analyze differences among the four groups, four aspects of the planarians were considered, including head regeneration rate, phototaxis response, locomotor velocity, and righting behavior. Data showed that there was no significant difference in the planarian head regeneration rate under simulated altered gravity. According to statistical analysis of the behavioral test, all of the groups had normal functioning of the phototaxis response, while the planarians that underwent head reconstruction under the microgravity environment had significantly slower locomotor velocity and spent more time in righting behavior. Furthermore, histological staining and immunohistochemistry results helped us reveal that the locomotor system of planarians was affected by the simulated microgravity environment. We further demonstrated that the circular muscle of the planarians was weakened (hematoxylin and eosin staining), and the epithelial cilia of the planarians were reduced (anti-acetylated tubulin staining) under the simulated microgravity environment. Bioelectromagnetics. 2018;39:428-440. © 2018 Wiley Periodicals, Inc.

Ligand-binding characterization of simulated ß-adrenergic-like octopamine receptor in Schistocerca gregaria via progressive structure simulation.

It is important to design insecticides having both low drug resistance and less undesirable toxicity for desert locust control. Specific GPCRs of Schistocerca gregaria, especially ß-adrenergic-like octopamine receptor (SgOctßR), can be considered as its potential effective insecticide targets. However, either the unavailability of SgOctßR's structure or the inadequate capability of its sequence lead the development of insecticide for Schistocerca gregaria meets its plateau. To relax this difficulty, this paper develops a promising progressive structure simulation from SgOctßR's sequence, to its predicted structure of SgOctßR in vacuum, to its conformation as well as its complex with endogenous ligand octopamine in a solvent-membrane system. The combined approach of multiple sequence alignment, static structural characterization, and dynamic process of conformational change during binding octopamine reveal three important aspects. The first one is the characterization of SgOctßR's active pocket, including the attending secondary structure elements, its hydrophobic residues and nonpolar surface. The second one is the interaction with octopamine, especially the involved hydrogen bonds and an aromatic stacking of pi-pi interactions. The third one is the potential binding sites, including six highly conserved residues and one highly variable residue for locust insecticide design. This work is definitely helpful for the further structure-based drug design for efficient and eco-friendly insecticides, as well as site-directed mutagenesis biochemical research of SgOctßR.

Measurement of contact angles in a simulated microgravity environment generated by a large gradient magnetic field.

The contact angle is an important parameter that is essential for studying interfacial phenomena. The contact angle can be measured using commercially available instruments. However, these well-developed instruments may not function or may be unsuitable for use in some special environments. A simulated microgravity generated by a large gradient magnetic field is such an environment in which the current measurement instruments cannot be installed. To measure the contact angle in this environment, new tools must be designed and manufactured to be compatible with the size and physical environment. In this study, we report the development and construction of a new setup that was specifically designed for use in a strong magnetic field to measure the contact angle between a levitated droplet and a solid surface. The application of the setup in a large gradient magnetic field was tested, and the contact angles were readily measured.

Predicting existing targets for new drugs base on strategies for missing interactions.

BACKGROUND: There has been paid more and more attention to supervised classification models in the area of predicting drug-target interactions (DTIs). However, in terms of classification, unavoidable missing DTIs in data would cause three issues which have not yet been addressed appropriately by former approaches. Directly labeled as negatives (non-DTIs), missing DTIs increase the confusion of positives (DTIs) and negatives, aggravate the imbalance between few positives and many negatives, and are usually discriminated as highly-scored false positives, which influence the existing measures sharply. RESULTS: Under the framework of local classification model (LCM), this work focuses on the scenario of predicting how possibly a new drug interacts with known targets. To address the first two issues, two strategies, Spy and Super-target, are introduced accordingly and further integrated to form a two-layer LCM. In the bottom layer, Spy-based local classifiers for protein targets are built by positives, as well as reliable negatives identified among unlabeled drug-target pairs. In the top layer, regular local classifiers specific to super-targets are built with more positives generated by grouping similar targets and their interactions. Furthermore, to handle the third issue, an additional performance measure, Coverage, is presented for assessing DTI prediction. The experiments based on benchmark datasets are finally performed under five-fold cross validation of drugs to evaluate this approach. The main findings are concluded as follows. (1) Both two individual strategies and their combination are effective to missing DTIs, and the combination wins the best. (2) Having the advantages of less confusing decision boundary at the bottom layer and less biased decision boundary at the top layer, our two-layer LCM outperforms two former approaches. (3) Coverage is more robust to missing interactions than other measures and is able to evaluate how far one needs to go down the list of targets to cover all the proper targets of a drug. CONCLUSIONS: Proposing two strategies and one performance measure, this work has addressed the issues derived from missing interactions, which cause confusing and biased decision boundaries in classifiers, as well as the inappropriate measure of predicting performance, in the scenario of predicting interactions between new drugs and known targets.

A Systematic Analysis of the Structures of Heterologously Expressed Proteins and Those from Their Native Hosts in the RCSB PDB Archive.

Recombinant expression of proteins has become an indispensable tool in modern day research. The large yields of recombinantly expressed proteins accelerate the structural and functional characterization of proteins. Nevertheless, there are literature reported that the recombinant proteins show some differences in structure and function as compared with the native ones. Now there have been more than 100,000 structures (from both recombinant and native sources) publicly available in the Protein Data Bank (PDB) archive, which makes it possible to investigate if there exist any proteins in the RCSB PDB archive that have identical sequence but have some difference in structures. In this paper, we present the results of a systematic comparative study of the 3D structures of identical naturally purified versus recombinantly expressed proteins. The structural data and sequence information of the proteins were mined from the RCSB PDB archive. The combinatorial extension (CE), FATCAT-flexible and TM-Align methods were employed to align the protein structures. The root-mean-square distance (RMSD), TM-score, P-value, Z-score, secondary structural elements and hydrogen bonds were used to assess the structure similarity. A thorough analysis of the PDB archive generated five-hundred-seventeen pairs of native and recombinant proteins that have identical sequence. There were no pairs of proteins that had the same sequence and significantly different structural fold, which support the hypothesis that expression in a heterologous host usually could fold correctly into their native forms.

A quality comparison of protein crystals grown under containerless conditions generated by diamagnetic levitation, silicone oil and agarose gel.

High-quality crystals are key to obtaining accurate three-dimensional structures of proteins using X-ray diffraction techniques. However, obtaining such protein crystals is often a challenge. Several containerless crystallization techniques have been reported to have the ability to improve crystal quality, but it is unknown which is the most favourable way to grow high-quality protein crystals. In this paper, a quality comparison of protein crystals which were grown under three containerless conditions provided by diamagnetic levitation, silicone oil and agarose gel was conducted. A control experiment on a vessel wall was also simultaneously carried out. Seven different proteins were crystallized under the four conditions, and the crystal quality was assessed in terms of the resolution limit, the mosaicity and the Rmerge. It was found that the crystals grown under the three containerless conditions demonstrated better morphology than those of the control. X-ray diffraction data indicated that the quality of the crystals grown under the three containerless conditions was better than that of the control. Of the three containerless crystallization techniques, the diamagnetic levitation technique exhibited the best performance in enhancing crystal quality. This paper is to our knowledge the first report of improvement of crystal quality using a diamagnetic levitation technique. Crystals obtained from agarose gel demonstrated the second best improvement in crystal quality. The study indicated that the diamagnetic levitation technique is indeed a favourable method for growing high-quality protein crystals, and its utilization is thus potentially useful in practical efforts to obtain well diffracting protein crystals.

A strategy for selecting the pH of protein solutions to enhance crystallization.

The pH of a solution is an important parameter in crystallization that needs to be controlled in order to ensure success. The actual pH of the crystallization droplet is determined by the combined contribution of the buffers in the screening and protein solutions, although the contribution of the latter to the pH is often ignored. In this study, the effects of the buffer and protein solution pH values on the results of screening are systematically investigated. It was found that these parameters significantly affected the results and thus the following strategy for the selection of appropriate pH values is proposed: (i) when screening with only one protein solution, the pH should be as low, as high or as divergent from the pI as possible for a basic, acidic or neutral protein, respectively, within its stable pH range; (ii) when screening with two protein solutions, the pH values should be well separated from one another; and (iii) when multiple pH values are utilized, an even distribution of pH values is the best approach to increase the success rate of crystallization.

Correlation between protein sequence similarity and crystallization reagents in the biological macromolecule crystallization database.

The protein structural entries grew far slower than the sequence entries. This is partly due to the bottleneck in obtaining diffraction quality protein crystals for structural determination using X-ray crystallography. The first step to achieve protein crystallization is to find out suitable chemical reagents. However, it is not an easy task. Exhausting trial and error tests of numerous combinations of different reagents mixed with the protein solution are usually necessary to screen out the pursuing crystallization conditions. Therefore, any attempts to help find suitable reagents for protein crystallization are helpful. In this paper, an analysis of the relationship between the protein sequence similarity and the crystallization reagents according to the information from the existing databases is presented. We extracted information of reagents and sequences from the Biological Macromolecule Crystallization Database (BMCD) and the Protein Data Bank (PDB) database, classified the proteins into different clusters according to the sequence similarity, and statistically analyzed the relationship between the sequence similarity and the crystallization reagents. The results showed that there is a pronounced positive correlation between them. Therefore, according to the correlation, prediction of feasible chemical reagents that are suitable to be used in crystallization screens for a specific protein is possible.

Correlation between protein sequence similarity and x-ray diffraction quality in the protein data bank.

As the most widely utilized technique to determine the 3-dimensional structure of protein molecules, X-ray crystallography can provide structure of the highest resolution among the developed techniques. The resolution obtained via X-ray crystallography is known to be influenced by many factors, such as the crystal quality, diffraction techniques, and X-ray sources, etc. In this paper, the authors found that the protein sequence could also be one of the factors. We extracted information of the resolution and the sequence of proteins from the Protein Data Bank (PDB), classified the proteins into different clusters according to the sequence similarity, and statistically analyzed the relationship between the sequence similarity and the best resolution obtained. The results showed that there was a pronounced correlation between the sequence similarity and the obtained resolution. These results indicate that protein structure itself is one variable that may affect resolution when X-ray crystallography is used.

[Investigations of drug addiction mechanism in planarians].

Drug abuse harms people's health and lead to a series of economic, social and political problems. However, the problems of physical damage, physical dependence and withdrawal syndrome caused by drug abuse still exist. Planarians have been a new animal experimental model in vivo for neuropharmacology, because they possess a primitive central nervous system and neurotransmitter systems similarly to mammalians. In addition, they have the advantage of convenience and low cost and no ethics problems compared with mammalian models. The advantages of planarian as experimental model in vivo and the progress of the investigations of drug addiction mechanism in planarians are summarized, and the trends in this field are discussed in this review.

A containerless levitation setup for liquid processing in a superconducting magnet.

Containerless processing of materials is considered beneficial for obtaining high quality products due to the elimination of the detrimental effects coming from the contact with container walls. Many containerless processing methods are realized by levitation techniques. This paper describes a containerless levitation setup that utilized the magnetization force generated in a gradient magnetic field. It comprises a levitation unit, a temperature control unit, and a real-time observation unit. Known volume of liquid diamagnetic samples can be levitated in the levitation chamber, the temperature of which is controlled using the temperature control unit. The evolution of the levitated sample is observed in real time using the observation unit. With this setup, containerless processing of liquid such as crystal growth from solution can be realized in a well-controlled manner. Since the levitation is achieved using a superconducting magnet, experiments requiring long duration time such as protein crystallization and simulation of space environment for living system can be easily succeeded.