The EN-TEx resource of multi-tissue personal epigenomes & variant-impact models.

Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of 1,635 open-access datasets from four donors (∼30 tissues × âˆ¼15 assays). The datasets are mapped to matched, diploid genomes with long-read phasing and structural variants, instantiating a catalog of >1 million allele-specific loci. These loci exhibit coordinated activity along haplotypes and are less conserved than corresponding, non-allele-specific ones. Surprisingly, a deep-learning transformer model can predict the allele-specific activity based only on local nucleotide-sequence context, highlighting the importance of transcription-factor-binding motifs particularly sensitive to variants. Furthermore, combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci. It also enables models for transferring known eQTLs to difficult-to-profile tissues (e.g., from skin to heart). Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.

Proteomics, modeling, and fluorescence assays delineate cytochrome b5 residues involved in binding and stimulation of cytochrome P450 17A1 17,20-lyase.

Cytochrome b5 (b5) is known to stimulate some catalytic activities of cytochrome P450 (P450, CYP) enzymes, although mechanisms still need to be defined. The reactions most strongly enhanced by b5 are the 17,20-lyase reactions of P450 17A1 involved in steroid biosynthesis. We had previously used a fluorescently labeled human b5 variant (Alexa 488-T70C-b5) to characterize human P450 17A1-b5 interactions, but subsequent proteomic analyses indicated that lysines in b5 were also modified with Alexa 488 maleimide in addition to Cys-70, due to disulfide dimerization of the T70C mutant. A series of b5 variants were constructed with Cys replacements for the identified lysine residues and labeled with the dye. Fluorescence attenuation and the function of b5 in the steroid lyase reaction depended on the modified position. Apo-b5 (devoid of heme group) studies revealed the lack of involvement of the b5 heme in the fluorescence attenuation. A structural model of b5 with P450 17A1 was predicted using AlphaFold-Multimer algorithms/Rosetta docking, based upon the individual structures, which predicted several new contacts not previously reported, that is, interactions of b5 Glu-48:17A1 Arg-347, b5 Glu-49:17A1 Arg-449, b5 Asp-65:17A1 Arg-126, b5 Asp-65:17A1 Arg-125, and b5 Glu-61:17A1 Lys-91. Fluorescence polarization assays with two modified b5 variants yielded Kd values (for b5-P450 17A1) of 120 to 380 nM, the best estimate of binding affinity. We conclude that both monomeric and dimeric b5 can bind to P450 17A1 and stimulate activity. Results with the mutants indicate that several Lys residues in b5 are sensitive to the interaction with P450 17A1, including Lys-88 and Lys-91.

High-Throughput Reclassification of SCN5A Variants.

Partial or complete loss-of-function variants in SCN5A are the most common genetic cause of the arrhythmia disorder Brugada syndrome (BrS1). However, the pathogenicity of SCN5A variants is often unknown or disputed; 80% of the 1,390 SCN5A missense variants observed in at least one individual to date are variants of uncertain significance (VUSs). The designation of VUS is a barrier to the use of sequence data in clinical care. We selected 83 variants: 10 previously studied control variants, 10 suspected benign variants, and 63 suspected Brugada syndrome-associated variants, selected on the basis of their frequency in the general population and in individuals with Brugada syndrome. We used high-throughput automated patch clamping to study the function of the 83 variants, with the goal of reclassifying variants with functional data. The ten previously studied controls had functional properties concordant with published manual patch clamp data. All 10 suspected benign variants had wild-type-like function. 22 suspected BrS variants had loss of channel function (<10% normalized peak current) and 22 variants had partial loss of function (10%-50% normalized peak current). The previously unstudied variants were initially classified as likely benign (n = 2), likely pathogenic (n = 10), or VUSs (n = 61). After the patch clamp studies, 16 variants were benign/likely benign, 45 were pathogenic/likely pathogenic, and only 12 were still VUSs. Structural modeling identified likely mechanisms for loss of function including altered thermostability and disruptions to alpha helices, disulfide bonds, or the permeation pore. High-throughput patch clamping enabled reclassification of the majority of tested VUSs in SCN5A.

Phylogenetic analysis of Blaberoidea reveals non-monophyly of taxa and supports the creation of multiple new subfamilies.

The superfamily Blaberoidea is a highly species-rich group of cockroaches. High-level blaberoidean phylogenetics are still under debate owing to variable taxon sampling and incongruence between mitochondrial and nuclear evolution, as well as different methods used in various phylogenetic studies. We here present a phylogenetic analysis of Blaberoidea based on a dataset combining the mitochondrial genome with two nuclear markers from representatives of all recognized families within the superfamily. Our results support the monophyly of Blaberiodea, which includes Ectobiidae s.s. (=Ectobiinae), Pseudophyllodromiidae, Nyctiboridae, Blattellidae s.s. (=Blattellinae) and Blaberidae. Ectobiidae s.s. was recovered as sister to the remaining Blaberoidea in all inferences. Pseudophyllodromiidae was paraphyletic with respect to Anaplectoidea + Malaccina. Blattellidae s.s. excluding Anaplectoidea + Malaccina formed a monophyletic group that was sister to Blaberidae. Based on our results, we propose a revised classification for Blaberoidea: Anaplectoidinae subfam.nov. and Episorineuchora gen.nov., and two new combinations at species level within Pseudophyllodromiidae; Rhabdoblattellinae subfam.nov., Calolamprodinae subfam.nov., Acutirhabdoblatta gen.nov., as well as new combinations for three species within Blaberidae. Ancestral state reconstructions based on four morphological characters allow us to infer that the common ancestor of blaberoid cockroaches is likely to be a species with characteristics similar to those found in Ectobiidae, that is, front femur Type B, arolium present, abdomen with a visible gland and male genital hook on the left side.

Analysis of risk factors associated with the high incidence of amblyopia in preterm infants at the corrected gestational age of 12 months.

OBJECTIVE: To investigate the perinatal and in-hospital risk factors associated with the high incidence of amblyopia in preterm infants and to analyze the correlation between the amblyopia and neurodevelopment. METHODS: Children discharged from the neonatal intensive care unit (NICU) at 12 months of corrected gestational age were retrospectively included in this study. Ocular screening was performed in children. At the risk of amblyopia was determined according to the American Academy of Ophthalmology Guidelines for automated preschool vision screening factors. Differences in perinatal characteristics, complications during hospitalization, and treatment modalities between the two groups of children were analyzed, and multifactorial logistic regression analysis was used to identify the independent risk factors for amblyopia. The results of developmental assessment were collected retrospectively to analyze the correlation between amblyopia and various aspects of neurological development. RESULTS: A total of 128 preterm infants, 30 in the amblyopia risk group and 98 in the non-amblyopia risk group, were included in this study. Univariate analysis showed that the amblyopia risk group had lower birth weights, higher rates of asphyxia, preterm brain white matter injury, bronchopulmonary dysplasia (BPD), intraventricular hemorrhage (IVH), sepsis during hospitalization, and higher rates of treatment with pulmonary surfactant (PS), blood transfusion, invasive ventilator, and levothyroxine. Logistic regression analysis showed that BPD in the neonatal period (odds ratio [OR] 8.355, 95% confidence interval [CI] 1.492, 46.786), brain white matter injury (OR 16.742, 95% CI 0.684, 409.804), treatment with levothyroxine (OR 2.859, 95% CI 0.946, 8.639), and use of an invasive ventilator (OR 2.983, 95% CI 0.942, 9.445) were independent risk factors for amblyopia at 12 months of corrected gestational age, while the administration of glucocorticoids (OR 0.055, 95% CI 0.004, 0.737) was a protective factor. Regarding neurodevelopmental assessment, the number of infants with lagging fine motor development was greater in the amblyopia risk group. CONCLUSION: The presence of BPD in the neonatal period, brain white matter damage in preterm infants, and use of levothyroxine and invasive ventilator were high risk factors for amblyopia. The use of glucocorticoids therapy was a protective factor. Children with risk of amblyopia had a higher rate of poor fine motor development.

HA-Coated PLGA Nanoparticles Loaded with Apigenin for Colon Cancer with High Expression of CD44.

Apigenin (API) possesses excellent antitumor properties but its limited water solubility and low bioavailability restrict its therapeutic impact. Thus, a suitable delivery system is needed to overcome these limitations and improve the therapeutic efficiency. Poly (lactic-co-glycolic acid) (PLGA) is a copolymer extensively utilized in drug delivery. Hyaluronic acid (HA) is a major extracellular matrix component and can specifically bind to CD44 on colon cancer cells. Herein, we aimed to prepare receptor-selective HA-coated PLGA nanoparticles (HA-PLGA-API-NPs) for colon cancers with high expression of CD44; chitosan (CS) was introduced into the system as an intermediate, simultaneously binding HA and PLGA through electrostatic interaction to facilitate a tighter connection between them. API was encapsulated in PLGA to obtain PLGA-API-NPs, which were then sequentially coated with CS and HA to form HA-PLGA-API-NPs. HA-PLGA-API-NPs had a stronger sustained-release capability. The cellular uptake of HA-PLGA-API-NPs was enhanced in HT-29 cells with high expression of CD44. In vivo, HA-PLGA-API-NPs showed enhanced targeting specificity towards the HT-29 ectopic tumor model in nude mice in comparison with PLGA-API-NPs. Overall, HA-PLGA-API-NPs were an effective drug delivery platform for API in the treatment of colon cancers with high expression of CD44.

Dominant negative effects of SCN5A missense variants.

PURPOSE: Up to 30% of patients with Brugada syndrome (BrS) carry loss-of-function (LoF) variants in the cardiac sodium channel gene SCN5A encoding for the protein NaV1.5. Recent studies suggested that NaV1.5 can dimerize, and some variants exert dominant negative effects. In this study, we sought to explore the generality of missense variant NaV1.5 dominant negative effects and their clinical severity. METHODS: We identified 35 LoF variants (<10% of wild type [WT] peak current) and 15 partial LoF variants (10%-50% of WT peak current) that we assessed for dominant negative effects. SCN5A variants were studied in HEK293T cells, alone or in heterozygous coexpression with WT SCN5A using automated patch clamp. To assess the clinical risk, we compared the prevalence of dominant negative vs putative haploinsufficient (frameshift, splice, or nonsense) variants in a BrS consortium and the Genome Aggregation Database population database. RESULTS: In heterozygous expression with WT, 32 of 35 LoF and 6 of 15 partial LoF variants showed reduction to <75% of WT-alone peak current, showing a dominant negative effect. Individuals with dominant negative LoF variants had an elevated disease burden compared with the individuals with putative haploinsufficient variants (2.7-fold enrichment in BrS cases, P = .019). CONCLUSION: Most SCN5A missense LoF variants exert a dominant negative effect. This class of variant confers an especially high burden of BrS.

Structural determinants of cholesterol recognition in helical integral membrane proteins.

Cholesterol is an integral component of mammalian membranes. It has been shown to modulate membrane fluidity and dynamics and alter integral membrane protein function. However, understanding the molecular mechanisms of how cholesterol impacts protein function is complicated by limited and conflicting structural data. Because of the nature of the crystallization and cryo-EM structure determination, it is difficult to distinguish between specific and biologically relevant interactions and a nonspecific association. The only widely recognized search algorithm for cholesterol-integral-membrane-protein interaction sites is sequence based, i.e., searching for the so-called "Cholesterol Recognition/interaction Amino acid Consensus" motif. Although these motifs are present in numerous integral membrane proteins, there is inconclusive evidence to support their necessity or sufficiency for cholesterol binding. Here, we leverage the increasing number of experimental cholesterol-integral-membrane-protein structures to systematically analyze putative interaction sites based on their spatial arrangement and evolutionary conservation. This analysis creates three-dimensional representations of general cholesterol interaction sites that form clusters across multiple integral membrane protein classes. We also classify cholesterol-integral-membrane-protein interaction sites as either likely-specific or nonspecific. Information gleaned from our characterization will eventually enable a structure-based approach to predict and design cholesterol-integral-membrane-protein interaction sites.

A Multitask Deep-Learning Method for Predicting Membrane Associations and Secondary Structures of Proteins.

Prediction of residue-level structural attributes and protein-level structural classes helps model protein tertiary structures and understand protein functions. Existing methods are either specialized on only one class of proteins or developed to predict only a specific type of residue-level attribute. In this work, we develop a new deep-learning method, named Membrane Association and Secondary Structure Predictor (MASSP), for accurately predicting both residue-level structural attributes (secondary structure, location, orientation, and topology) and protein-level structural classes (bitopic, α-helical, ß-barrel, and soluble). MASSP integrates a multilayer two-dimensional convolutional neural network (2D-CNN) with a long short-term memory (LSTM) neural network into a multitasking framework. Our comparison shows that MASSP performs equally well or better than the state-of-the-art methods in predicting residue-level secondary structures, boundaries of transmembrane segments, and topology. Furthermore, it achieves outstanding accuracy in predicting protein-level structural classes. MASSP automatically distinguishes the structural classes of input sequences and identifies transmembrane segments and topologies if present, making it broadly applicable to different classes of proteins. In summary, MASSP's good performance and broad applicability make it well suited for annotating residue-level attributes and protein-level structural classes at the proteome scale.

Predicting changes in protein thermodynamic stability upon point mutation with deep 3D convolutional neural networks.

Predicting mutation-induced changes in protein thermodynamic stability (ΔΔG) is of great interest in protein engineering, variant interpretation, and protein biophysics. We introduce ThermoNet, a deep, 3D-convolutional neural network (3D-CNN) designed for structure-based prediction of ΔΔGs upon point mutation. To leverage the image-processing power inherent in CNNs, we treat protein structures as if they were multi-channel 3D images. In particular, the inputs to ThermoNet are uniformly constructed as multi-channel voxel grids based on biophysical properties derived from raw atom coordinates. We train and evaluate ThermoNet with a curated data set that accounts for protein homology and is balanced with direct and reverse mutations; this provides a framework for addressing biases that have likely influenced many previous ΔΔG prediction methods. ThermoNet demonstrates performance comparable to the best available methods on the widely used Ssym test set. In addition, ThermoNet accurately predicts the effects of both stabilizing and destabilizing mutations, while most other methods exhibit a strong bias towards predicting destabilization. We further show that homology between Ssym and widely used training sets like S2648 and VariBench has likely led to overestimated performance in previous studies. Finally, we demonstrate the practical utility of ThermoNet in predicting the ΔΔGs for two clinically relevant proteins, p53 and myoglobin, and for pathogenic and benign missense variants from ClinVar. Overall, our results suggest that 3D-CNNs can model the complex, non-linear interactions perturbed by mutations, directly from biophysical properties of atoms.

Composition-dependent phase transformation in side-chain liquid crystalline copolymers with mesogenic groups at different substituent positions.

Copolymerization is an effective approach to tailor the thermal and structural properties of liquid crystalline polymer materials, which is essential for various applications. In this work, two series of polynorbornene copolymers, A-r-B and A-r-C, with the biphenyl mesogenic side group at different substituent positions were synthesized via ring-opening metathesis polymerization in various compositions. The corresponding homopolymers A and C are liquid crystalline polymers, exhibiting an oblique columnar structure (Colob/p2) and lamellar structure, respectively, while homopolymer B is amorphous. The composition-dependent phase behaviors of copolymers were systematically studied with the combination of SAXS, GISAXS, AFM, DSC and POM techniques. With increasing molar content of A (xA), the self-organzied structure of copolymer A-r-B follows the sequence from amorphous to lamellar, undulated lamellar, and Colob/p2 structures, and that of A-r-C follows the sequence of lamellar, undulated lamellar, and Colob/p2 structures. Then, copolymers with undulated lamellar or Colob/p2 structures tend to enter lamellar phase first at higher temperature and then change to the isotropic state during heating. The composition-induced transition from lamellar to supramolecular columnar organization is somewhat reminiscent of block copolymers and other soft matter systems that can form ordered structures. Furthermore, the subsitituent number and position of rigid mesogenic units in the side chain can further modify the morphologies of self-organized phases.

Finding the needle in the haystack: towards solving the protein-folding problem computationally.

Prediction of protein tertiary structures from amino acid sequence and understanding the mechanisms of how proteins fold, collectively known as "the protein folding problem," has been a grand challenge in molecular biology for over half a century. Theories have been developed that provide us with an unprecedented understanding of protein folding mechanisms. However, computational simulation of protein folding is still difficult, and prediction of protein tertiary structure from amino acid sequence is an unsolved problem. Progress toward a satisfying solution has been slow due to challenges in sampling the vast conformational space and deriving sufficiently accurate energy functions. Nevertheless, several techniques and algorithms have been adopted to overcome these challenges, and the last two decades have seen exciting advances in enhanced sampling algorithms, computational power and tertiary structure prediction methodologies. This review aims at summarizing these computational techniques, specifically conformational sampling algorithms and energy approximations that have been frequently used to study protein-folding mechanisms or to de novo predict protein tertiary structures. We hope that this review can serve as an overview on how the protein-folding problem can be studied computationally and, in cases where experimental approaches are prohibitive, help the researcher choose the most relevant computational approach for the problem at hand. We conclude with a summary of current challenges faced and an outlook on potential future directions.

Esophageal Histological Precursor Lesions and Subsequent 8.5-Year Cancer Risk in a Population-Based Prospective Study in China.

INTRODUCTION: Data on the associations between esophageal histological lesions and risk of esophageal squamous cell carcinoma (ESCC) in general populations are limited. We aimed to investigate these associations in a large Chinese general population to inform future Chinese ESCC screening guidelines. METHODS: We performed endoscopic screening of 21,111 participants aged 40-69 years from 3 high-risk areas of China in 2005-2009, and followed the cohort through 2016. Cumulative incidence and mortality rates of ESCC were calculated by baseline histological diagnosis, and hazard ratios of ESCC, overall and by age and sex, were assessed using the Cox proportional hazards models. RESULTS: We identified 143 new ESCC cases (0.68%) and 62 ESCC deaths (0.29%) during a median follow-up of 8.5 years. Increasing grades of squamous dysplasia were associated with the increasing risk of ESCC incidence and mortality. The cumulative ESCC incidence rates for severe dysplasia/carcinoma in situ, moderate dysplasia (MD), and mild dysplasia were 15.5%, 4.5%, and 1.4%, respectively. Older individuals (50-69 years) had 3.1 times higher ESCC incidence than younger individuals (40-49 years), and men had 2.4 times higher ESCC incidence than women. DISCUSSION: This study confirmed that increasing grades of squamous dysplasia are associated with increasing risk of ESCC and that severe dysplasia and carcinoma in situ require clinical treatment. This study suggests that in high-risk areas of China, patients with endoscopically worrisome MD should also receive therapy, the first screening can be postponed to 50 years, and endoscopic surveillance intervals for unremarkable MD and mild dysplasia can be lengthened to 3 and 5 years, respectively.

Deletion of p53 and Hyper-Activation of PIK3CA in Keratin-15+ Stem Cells Lead to the Development of Spontaneous Squamous Cell Carcinoma.

Squamous cell carcinoma (SCC) is the second commonest type of skin cancer, and SCCs make up about 90% of head and neck cancers (HNSCCs). HNSCCs harbor two frequent molecular alterations, namely, gain-of-function alterations of phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) and loss-of-function mutations of tumor protein p53 (TP53). However, it remains poorly understood whether HNSCCs harboring different genetic alterations exhibit differential immune tumor microenvironments (TME). It also remains unknown whether PIK3CA hyperactivation and TP53 deletion can lead to SCC development spontaneously. Here, we analyzed the Cancer Genome Atlas (TCGA) datasets of HNSCCs and found that patients with both PIK3CA and TP53 alterations exhibited worse survival, significantly lower CD8 tumor infiltrating lymphocytes (TILs) and higher M0 macrophages than other controls. To better model human tumorigenesis, we deleted TP53 and constitutively activated PIK3CA in mouse keratin-15-expressing stem cells, which leads to the spontaneous development of multilineage tumors including SCCs, termed Keratin-15-p53-PIK3CA (KPPA) tumors. KPPA tumors were heavily infiltrated with myeloid-derived suppressor cells (MDSCs), with a drastically increased ratio of polymorphonuclear-MDSC (PMN-MDSC) versus monocytic-MDSC (M-MDSC). CD8 TILs expressed more PD-1 and reduced their polyfunctionality. Overall, we established a genetic model to mimic human HNSCC pathogenesis, manifested with an immunosuppressive TME, which may help further elucidate immune evasion mechanisms and develop more effective immunotherapies for HNSCCs.

Contribution of Cotranslational Folding Defects to Membrane Protein Homeostasis.

Membrane proteins are prone to misfolding and degradation within the cell, yet the nature of the conformational defects involved in this process remain poorly understood. The earliest stages of membrane protein folding are mediated by the Sec61 translocon, a molecular machine that facilitates the lateral partitioning of the polypeptide into the membrane. Proper membrane integration is an essential prerequisite for folding of the nascent chain. However, the marginal energetic drivers of this reaction suggest the translocon may operate with modest fidelity. In this work, we employed biophysical modeling in conjunction with quantitative biochemical measurements in order to evaluate the extent to which cotranslational folding defects influence membrane protein homeostasis. Protein engineering was employed to selectively perturb the topological energetics of human rhodopsin, and the expression and cellular trafficking of engineered variants were quantitatively compared. Our results reveal clear relationships between topological energetics and the efficiency of rhodopsin biogenesis, which appears to be limited by the propensity of a polar transmembrane domain to achieve its correct topological orientation. Though the polarity of this segment is functionally constrained, we find that its topology can be stabilized in a manner that enhances biogenesis without compromising the functional properties of rhodopsin. Furthermore, sequence alignments reveal this topological instability has been conserved throughout the course of evolution. These results suggest that topological defects significantly contribute to the inefficiency of membrane protein folding in the cell. Additionally, our findings suggest that the marginal stability of rhodopsin may represent an evolved trait.

Accelerating chemical exchange saturation transfer MRI with parallel blind compressed sensing.

PURPOSE: Chemical exchange saturation transfer is a novel and promising MRI contrast method, but it can be time-consuming. Common parallel imaging methods, like SENSE, can lead to reduced quality of CEST. Here, parallel blind compressed sensing (PBCS), combining blind compressed sensing (BCS) and parallel imaging, is evaluated for the acceleration of CEST in brain and breast. METHODS: The CEST data were collected in phantoms, brain (N = 3), and breast (N = 2). Retrospective Cartesian undersampling was implemented and the reconstruction results of PBCS-CEST were compared with BCS-CEST and k-t sparse-SENSE CEST. The normalized RMSE and the high-frequency error norm were used for quantitative comparison. RESULTS: In phantom and in vivo brain experiments, the acceleration factor of R = 10 (24 k-space lines) was achieved and in breast R = 5 (30 k-space lines), without compromising the quality of the PBCS-reconstructed magnetization transfer rate asymmetry maps and Z-spectra. Parallel BCS provides better reconstruction quality when compared with BCS, k-t sparse-SENSE, and SENSE methods using the same number of samples. Parallel BCS overperforms BCS, indicating that the inclusion of coil sensitivity improves the reconstruction of the CEST data. CONCLUSION: The PBCS method accelerates CEST without compromising its quality. Compressed sensing in combination with parallel imaging can provide a valuable alternative to parallel imaging alone for accelerating CEST experiments.

Endoscopy screening effect on stage distributions of esophageal cancer: A cluster randomized cohort study in China.

Efficacy of endoscopic screening for esophageal cancer is not sufficiently definitive and lacks randomized controlled trial evidence. The present study proved short-term screening efficacy through describing and comparing disease stage distributions of intervention and control populations. Villages from Linzhou and Cixian were cluster randomly allocated to the intervention or to the control group and the target population of 52 729 and 43 068 individuals was 40-69 years old, respectively, and the actual enrolled numbers were 18 316 and 21 178, respectively. TNM stage information and study-defined stage information of esophageal cases from 2012 to 2016 were collected. Stage distributions were compared between the intervention and control groups in the total target population, as well as in the subgroup populations in terms of enrolment and before or after intervention. There were a total of 199 and 141 esophageal cancer cases in the intervention and control groups, respectively. For the target population, distributions of TNM stage were borderline significant between the two groups after intervention (P = .093). However, subgroup analysis of the enrolled population during the after-intervention period had statistical significance for both TNM and study-defined stage. Natural TNM stage distributions were approximately 32%, 41%, 24% and 3% for stages I to IV vs 71%, 19%, 7% and 3% in the intervention population. The natural study-defined stage distributions from early, middle to advanced stages were approximately 18%, 49% and 33% vs 59%, 33% and 8%. Early-stage esophageal cancer cases accounted for a higher proportion after endoscopy screening, and the efficacy in the target population depends on the intervention compliance.

Improving prediction of helix-helix packing in membrane proteins using predicted contact numbers as restraints.

One of the challenging problems in tertiary structure prediction of helical membrane proteins (HMPs) is the determination of rotation of α-helices around the helix normal. Incorrect prediction of helix rotations substantially disrupts native residue-residue contacts while inducing only a relatively small effect on the overall fold. We previously developed a method for predicting residue contact numbers (CNs), which measure the local packing density of residues within the protein tertiary structure. In this study, we tested the idea of incorporating predicted CNs as restraints to guide the sampling of helix rotation. For a benchmark set of 15 HMPs with simple to rather complicated folds, the average contact recovery (CR) of best-sampled models was improved for all targets, the likelihood of sampling models with CR greater than 20% was increased for 13 targets, and the average RMSD100 of best-sampled models was improved for 12 targets. This study demonstrated that explicit incorporation of CNs as restraints improves the prediction of helix-helix packing. Proteins 2017; 85:1212-1221. © 2017 Wiley Periodicals, Inc.

[Effect of Water Extract of Ginseng on Biological Bechaviors of Lung Cancer A549 Cells and the Expression of F-actin in Co-culture System of TAMs and A549 Cells].

Objective To study the effect of Water Extract of Ginseng (WEG) on the prolifera- tion/metastasis of lung cancer A549 cells and the expression of F-actin in co-culture system of tumor as- sociated macrophages (TAMs) and A549 cells. Methods Human acute leukemia mononuclear strain THP-1 was induced to become TAMs using Phorbol-12-myristate-13-acetate (PMA) combined IL-4 and IL- 13. The supernant of TAMs and A549 cells were co-cultured. A co-culture model was set up by simulating microenvironment of lung cancer. Then cells were divided into the blank control group (A549) , the co- culture group (A549 +TAMs) , high, middle, and low dose WEG groups (TAMs +A549 + high, middle, and low dose WEG). The effects of WEG on the proliferation/metastasis of lung cancer A549 cells and the expression of F-actin under various conditions were detected using MTT method, Real time cell analysis (RTCA) , and high content screening (HCS). Results Compared with the blank control group, the pro- liferation of A549 cells was obviously increased, cell migration was obviously elevated, and the area of cell skeleton was markedly enlarged in the TAMs + A549 group, with statistical difference (P <0. 05). Compared with the TAMs +A549 group, the proliferation and migration of A549 cells were inhibited, the area of cell skeleton and the number of microfilaments were reduced dose-dependently (P <0. 05). Conclusion WEG could effectively inhibit the proliferation and migration of A549 cells, which might be a- chieved by adjusting immunoactivities of TAMs, and further it affected biological behaviors of tumor cells.

Accurate Prediction of Contact Numbers for Multi-Spanning Helical Membrane Proteins.

Prediction of the three-dimensional (3D) structures of proteins by computational methods is acknowledged as an unsolved problem. Accurate prediction of important structural characteristics such as contact number is expected to accelerate the otherwise slow progress being made in the prediction of 3D structure of proteins. Here, we present a dropout neural network-based method, TMH-Expo, for predicting the contact number of transmembrane helix (TMH) residues from sequence. Neuronal dropout is a strategy where certain neurons of the network are excluded from back-propagation to prevent co-adaptation of hidden-layer neurons. By using neuronal dropout, overfitting was significantly reduced and performance was noticeably improved. For multi-spanning helical membrane proteins, TMH-Expo achieved a remarkable Pearson correlation coefficient of 0.69 between predicted and experimental values and a mean absolute error of only 1.68. In addition, among those membrane protein-membrane protein interface residues, 76.8% were correctly predicted. Mapping of predicted contact numbers onto structures indicates that contact numbers predicted by TMH-Expo reflect the exposure patterns of TMHs and reveal membrane protein-membrane protein interfaces, reinforcing the potential of predicted contact numbers to be used as restraints for 3D structure prediction and protein-protein docking. TMH-Expo can be accessed via a Web server at www.meilerlab.org .