What Are the Best Pollinator Candidates for Camelia oleifera: Do Not Forget Hoverflies and Flies.

Camellia oleifera Abel. is an important woody oil plant, and its pollination success is essential for oil production. We conducted this study to select the best pollinator candidates for C. oleifera using principal component analysis and multi-attribute decision-making. Field observations of the flower-visiting characteristics of candidate pollinators were conducted at three sites. The insect species that visited flowers did not considerably differ between regions or time periods. However, the proportion of each species recorded did vary. We recorded eleven main candidates from two orders and six families at the three sites. The pollen amount carried by Apis mellifera was significantly higher than that of other insects. However, the visit frequency and body length of Apis mellifera were smaller than those of Vespa velutina. Statistical analysis showed that A. mellifera is the best candidate pollinator; Eristaliscerealis is a good candidate pollinator; Phytomia zonata, A. cerana, and V. velutina were ordinary candidate pollinators; and four fly species, Episyrphus balteatus, and Eristalinus arvorum were classified as inefficient candidate pollinators. Our study shows that flies and hoverflies play an important role in the pollination system. Given the global decline in bee populations, the role of flies should also be considered in C. oleifera seed production.

Chromosome-level genome of Camellia lanceoleosa provides a valuable resource for understanding genome evolution and self-incompatibility.

The section Oleifera (Theaceae) has attracted attention for the high levels of unsaturated fatty acids found in its seeds. Here, we report the chromosome-scale genome of the sect. Oleifera using diploid wild Camellia lanceoleosa with a final size of 3.00 Gb and an N50 scaffold size of 186.43 Mb. Repetitive sequences accounted for 80.63% and were distributed unevenly across the genome. Camellia lanceoleosa underwent a whole-genome duplication event approximately 65 million years ago (65 Mya), prior to the divergence of C. lanceoleosa and Camellia sinensis (approx. 6-7 Mya). Syntenic comparisons of these two species elucidated the genomic rearrangement, appearing to be driven in part by the activity of transposable elements. The expanded and positively selected genes in C. lanceoleosa were significantly enriched in oil biosynthesis, and the expansion of homomeric acetyl-coenzyme A carboxylase (ACCase) genes and the seed-biased expression of genes encoding heteromeric ACCase, diacylglycerol acyltransferase, glyceraldehyde-3-phosphate dehydrogenase and stearoyl-ACP desaturase could be of primary importance for the high oil and oleic acid content found in C. lanceoleosa. Theanine and catechins were present in the leaves of C. lanceoleosa. However, caffeine can not be dectected in the leaves but was abundant in the seeds and roots. The functional and transcriptional divergence of genes encoding SAM-dependent N-methyltransferases may be associated with caffeine accumulation and distribution. Gene expression profiles, structural composition and chromosomal location suggest that the late-acting self-incompatibility of C. lanceoleosa is likely to have favoured a novel mechanism co-occurring with gametophytic self-incompatibility. This study provides valuable resources for quantitative and qualitative improvements and genome assembly of polyploid plants in sect. Oleifera.

Allelopathic Effects of Castanea henryi Aqueous Extracts on the Growth and Physiology of Brassica pekinensis and Zea mays.

The present study investigated the allelopathic effects of aqueous extracts of Castanea henryi litter on the growth and physiological responses of Brassica pekinensis and Zea mays. Treatment with high concentrations of leaf extract (0.05 g/ml for B. pekinensis and 0.10 g/ml for Z. mays) significantly increased malonaldehyde content and reduced seed germination, seedling growth, chlorophyll content, and the activity levels of antioxidant enzymes. These effects generally increased with increasing extract concentration. However, in Z. mays, low extract concentrations actually promoted seed germination, shoot growth, chlorophyll content, and antioxidant enzyme activity. The allelopathic effects of the various C. henryi extracts decreased as follows: leaf extract > twig extract > shell extract. Eleven potential allelochemicals including rutin, quercetin, luteolin, procyanidin A2, kaempferol, allantoin, propionic acid, salicylic acid, jasmonic acid, methylmalonic acid, and gentisic acid were identified in the leaves of C. henryi which were linked to the strongest allelopathic effects. These findings suggest that the allelopathic effects of C. henryi differ depending on receptor plant species, and that leaves are the most allelopathic litter in C. henryi.

Chemogenomics knowledgebase and systems pharmacology for hallucinogen target identification-Salvinorin A as a case study.

Drug abuse is a serious problem worldwide. Recently, hallucinogens have been reported as a potential preventative and auxiliary therapy for substance abuse. However, the use of hallucinogens as a drug abuse treatment has potential risks, as the fundamental mechanisms of hallucinogens are not clear. So far, no scientific database is available for the mechanism research of hallucinogens. We constructed a hallucinogen-specific chemogenomics database by collecting chemicals, protein targets and pathways closely related to hallucinogens. This information, together with our established computational chemogenomics tools, such as TargetHunter and HTDocking, provided a one-step solution for the mechanism study of hallucinogens. We chose salvinorin A, a potent hallucinogen extracted from the plant Salvia divinorum, as an example to demonstrate the usability of our platform. With the help of HTDocking program, we predicted four novel targets for salvinorin A, including muscarinic acetylcholine receptor 2, cannabinoid receptor 1, cannabinoid receptor 2 and dopamine receptor 2. We looked into the interactions between salvinorin A and the predicted targets. The binding modes, pose and docking scores indicate that salvinorin A may interact with some of these predicted targets. Overall, our database enriched the information of systems pharmacological analysis, target identification and drug discovery for hallucinogens.

Computational Advances for the Development of Allosteric Modulators and Bitopic Ligands in G Protein-Coupled Receptors.

Allosteric modulators of G protein-coupled receptors (GPCRs), which target at allosteric sites, have significant advantages against the corresponding orthosteric compounds including higher selectivity, improved chemical tractability or physicochemical properties, and reduced risk of receptor oversensitization. Bitopic ligands of GPCRs target both orthosteric and allosteric sites. Bitopic ligands can improve binding affinity, enhance subtype selectivity, stabilize receptors, and reduce side effects. Discovering allosteric modulators or bitopic ligands for GPCRs has become an emerging research area, in which the design of allosteric modulators is a key step in the detection of bitopic ligands. Radioligand binding and functional assays ([(35)S]GTPγS and ERK1/2 phosphorylation) are used to test the effects for potential modulators or bitopic ligands. High-throughput screening (HTS) in combination with disulfide trapping and fragment-based screening are used to aid the discovery of the allosteric modulators or bitopic ligands of GPCRs. When used alone, these methods are costly and can often result in too many potential drug targets, including false positives. Alternatively, low-cost and efficient computational approaches are useful in drug discovery of novel allosteric modulators and bitopic ligands to help refine the number of targets and reduce the false-positive rates. This review summarizes the state-of-the-art computational methods for the discovery of modulators and bitopic ligands. The challenges and opportunities for future drug discovery are also discussed.

Allosteric Binding Site and Activation Mechanism of Class C G-Protein Coupled Receptors: Metabotropic Glutamate Receptor Family.

Metabotropic glutamate receptors (mGluR) are mainly expressed in the central nervous system (CNS) and contain eight receptor subtypes, named mGluR1 to mGluR8. The crystal structures of mGluR1 and mGluR5 that are bound with the negative allosteric modulator (NAM) were reported recently. These structures provide a basic model for all class C of G-protein coupled receptors (GPCRs) and may aid in the design of new allosteric modulators for the treatment of CNS disorders. However, these structures are only combined with NAMs in the previous reports. The conformations that are bound with positive allosteric modulator (PAM) or agonist of mGluR1/5 remain unknown. Moreover, the structural information of the other six mGluRs and the comparisons of the mGluRs family have not been explored in terms of their binding pockets, the binding modes of different compounds, and important binding residues. With these crystal structures as the starting point, we built 3D structural models for six mGluRs by using homology modeling and molecular dynamics (MD) simulations. We systematically compared their allosteric binding sites/pockets, the important residues, and the selective residues by using a series of comparable dockings with both the NAM and the PAM. Our results show that several residues played important roles for the receptors' selectivity. The observations of detailed interactions between compounds and their correspondent receptors are congruent with the specificity and potency of derivatives or compounds bioassayed in vitro. We then carried out 100 ns MD simulations of mGluR5 (residue 26-832, formed by Venus Flytrap domain, a so-called cysteine-rich domain, and 7 trans-membrane domains) bound with antagonist/NAM and with agonist/PAM. Our results show that both the NAM and the PAM seemed stable in class C GPCRs during the MD. However, the movements of "ionic lock," of trans-membrane domains, and of some activation-related residues in 7 trans-membrane domains of mGluR5 were congruent with the findings in class A GPCRs. Finally, we selected nine representative bound structures to perform 30 ns MD simulations for validating the stabilities of interactions, respectively. All these bound structures kept stable during the MD simulations, indicating that the binding poses in this present work are reasonable. We provided new insight into better understanding of the structural and functional roles of the mGluRs family and facilitated the future structure-based design of novel ligands of mGluRs family with therapeutic potential.