DPI_CDF: druggable protein identifier using cascade deep forest.

BACKGROUND: Drug targets in living beings perform pivotal roles in the discovery of potential drugs. Conventional wet-lab characterization of drug targets is although accurate but generally expensive, slow, and resource intensive. Therefore, computational methods are highly desirable as an alternative to expedite the large-scale identification of druggable proteins (DPs); however, the existing in silico predictor's performance is still not satisfactory. METHODS: In this study, we developed a novel deep learning-based model DPI_CDF for predicting DPs based on protein sequence only. DPI_CDF utilizes evolutionary-based (i.e., histograms of oriented gradients for position-specific scoring matrix), physiochemical-based (i.e., component protein sequence representation), and compositional-based (i.e., normalized qualitative characteristic) properties of protein sequence to generate features. Then a hierarchical deep forest model fuses these three encoding schemes to build the proposed model DPI_CDF. RESULTS: The empirical outcomes on 10-fold cross-validation demonstrate that the proposed model achieved 99.13 % accuracy and 0.982 of Matthew's-correlation-coefficient (MCC) on the training dataset. The generalization power of the trained model is further examined on an independent dataset and achieved 95.01% of maximum accuracy and 0.900 MCC. When compared to current state-of-the-art methods, DPI_CDF improves in terms of accuracy by 4.27% and 4.31% on training and testing datasets, respectively. We believe, DPI_CDF will support the research community to identify druggable proteins and escalate the drug discovery process. AVAILABILITY: The benchmark datasets and source codes are available in GitHub: http://github.com/Muhammad-Arif-NUST/DPI_CDF .

Comparison of different strategies towards the chemical synthesis of long-chain scorpion toxin AaH-II.

Long-chain scorpion toxin AaH-II isolated from Androctonus australis Hector can selectively inhibit mammalian voltage-gated sodium ion channel Nav 1.7 responsible for pain sensation. Efficient chemical synthesis of AaH-II and its derivatives is beneficial to the study of the function and mechanism of Nav 1.7 and the development of potential peptide inhibitors. Herein, we compared three different strategies, namely, direct solid-phase peptide synthesis, hydrazide-based two-segment native chemical ligation, and hydrazide-based three-segment native chemical ligation for the synthesis of AaH-II. The hydrazide-based two-segment native chemical ligation affords the target toxin with the optimal efficiency, which provides a practically robust procedure for the preparation of tool molecules derived from AaH-II to study the biological functions and modulation of Nav 1.7. Our work highlights the importance of selecting suitable segment condensation approach in the chemical synthesis of protein toxins.

Ursolic acid reduces hepatocellular apoptosis and alleviates alcohol-induced liver injury via irreversible inhibition of CASP3 in vivo.

Alcoholic liver disease (ALD) is one of the pathogenic factors of chronic liver disease with the highest clinical morbidity worldwide. Ursolic acid (UA), a pentacyclic terpenoid carboxylic acid, has shown many health benefits including antioxidative, anti-inflammatory, anticancer, and hepatoprotective activities. We previously found that UA was metabolized in vivo into epoxy-modified UA containing an epoxy electrophilic group and had the potential to react with nucleophilic groups. In this study we prepared an alkynyl-modified UA (AM-UA) probe for tracing and capturing the target protein of UA from liver in mice, then investigated the mode by which UA bound to its target in vivo. By conducting proteome identification and bioinformatics analysis, we identified caspase-3 (CASP3) as the primary target protein of UA associated with liver protection. Molecule docking analysis showed that the epoxy group of the UA metabolite reacted with Cys-163 of CASP3, forming a covalent bond with CASP3. The binding mode of the UA metabolites (UA, CM-UA, and EM-UA) was verified by biochemical evaluation, demonstrating that the epoxy group produced by metabolism played an important role in the inhibition of CASP3. In alcohol-treated HepG2 cells, pretreatment with the UA metabolite (10 µM) irreversibly inhibited CASP3 activities, and subsequently decreased the cleavage of PARP and cell apoptosis. Finally, pre-administration of UA (20-80 mg· kg-1 per day, ig, for 1 week) dose-dependently alleviated alcohol-induced liver injury in mice mainly via the inhibition of CASP3. In conclusion, this study demonstrates that UA is a valuable lead compound for the treatment of ALD.

TargetCPP: accurate prediction of cell-penetrating peptides from optimized multi-scale features using gradient boost decision tree.

Cell-penetrating peptides (CPPs) are short length permeable proteins have emerged as drugs delivery tool of therapeutic agents including genetic materials and macromolecules into cells. Recently, CPP has become a hotspot avenue for life science research and paved a new way of disease treatment without harmful impact on cell viability due to nontoxic characteristic. Therefore, the correct identification of CPPs will provide hints for medical applications. Considering the shortcomings of traditional experimental CPPs identification, it is urgently needed to design intelligent predictor for accurate identification of CPPs for the large scale uncharacterized sequences. We develop a novel computational method, called TargetCPP, to discriminate CPPs from Non-CPPs with improved accuracy. In TargetCPP, first the peptide sequences are formulated with four distinct encoding methods i.e., composite protein sequence representation, composition transition and distribution, split amino acid composition, and information theory features. These dominant feature vectors were fused and applied intelligent minimum redundancy and maximum relevancy feature selection method to choose an optimal subset of features. Finally, the predictive model is learned through different classification algorithms on the optimized features. Among these classifiers, gradient boost decision tree algorithm achieved excellent performance throughout the experiments. Notably, the TargetCPP tool attained high prediction Accuracy of 93.54% and 88.28% using jackknife and independent test, respectively. Empirical outcomes prove the superiority and potency of proposed bioinformatics method over state-of-the-art methods. It is highly anticipated that the outcomes of this study will provide a strong background for large scale prediction of CPPs and instructive guidance in clinical therapy and medical applications.

A time-dependent genome-wide SNP-SNP interaction analysis of chicken body weight.

BACKGROUND: The important property of the quantitative traits of model organisms is time-dependent. However, the methodology for investigating the genetic interaction network over time is still lacking. Our study aims to provide insights into the mechanistic basis of epistatic interactions affecting the phenotypes of model organisms. RESULTS: We performed an exhaustive genome-wide search for significant SNP-SNP interactions associated with male birds' body weight (BW) (n = 475) at multiple time points (day of hatch (BW0) and 1, 3, 5, and 7 weeks (BW1, BW3, BW5, and BW7)). Statistical analysis detected 67, four, and two significant SNP pairs associated with BW0, BW1, and BW3, respectively, with a significance threshold at 8.67 × 10- 12 (Bonferroni-adjusted: 1%). Meanwhile, no significant SNP pairs associated with BW5 and BW7 were found. The SNP-SNP interaction networks of BW0, BW1, and BW3 were built and annotated. CONCLUSIONS: With strong annotated information and a strict significant threshold, SNP-SNP interactions underpinned the gene-gene interactions that might occur between chromosomes or within the same chromosome. Comparing and combing the networks, the results indicated that the genetic network for chicken body weight was dynamic and time-dependent.

Comparing Agent-Based Delivery of DNA and PNA Forced Intercalation (FIT) Probes for Multicolor mRNA Imaging.

Fluorogenic oligonucleotide probes allow mRNA imaging in living cells. A key challenge is the cellular delivery of probes. Most delivery agents, such as cell-penetrating peptides (CPPs) and pore-forming proteins, require interactions with the membrane. Charges play an important role. To explore the influence of charge on fluorogenic properties and delivery efficiency, we compared peptide nucleic acid (PNA)- with DNA-based forced intercalation (FIT) probes. Perhaps counterintuitively, fluorescence signaling by charged DNA FIT probes proved tolerant to CPP conjugation, whereas CPP-FIT PNA conjugates were affected. Live-cell imaging was performed with a genetically engineered HEK293 cell line to allow the inducible expression of a specific mRNA target. Blob-like features and high background were recurring nuisances of the tested CPP and lipid conjugates. By contrast, delivery by streptolysin-O provided high enhancements of the fluorescence of the FIT probe upon target induction. Notably, DNA-based FIT probes were brighter and more responsive than PNA-based FIT probes. Optimized conditions enabled live-cell multicolor imaging of three different mRNA target sequences.

Robust synthesis of C-terminal cysteine-containing peptide acids through a peptide hydrazide-based strategy.

A new robust strategy was reported for the epimerization-free synthesis of C-terminal Cys-containing peptide acids through mercaptoethanol-mediated hydrolysis of peptide thioesters prepared in situ from peptide hydrazides. This simple-to-operate and highly efficient method avoids the use of derivatization reagents for resin modification, thus providing a practical avenue for the preparation of C-terminal Cys-containing peptide acids.

Delivery of cell membrane impermeable peptides into living cells by using head-to-tail cyclized mitochondria-penetrating peptides.

A series of cyclic Arg-rich mitochondria-penetrating peptides were prepared with variation in the macrocycle size and the chirality of Arg residues. A cyclic heptapeptide was demonstrated to be an efficient mitochondria-specific delivery vector for delivering membrane impermeable peptides.

Alisol A 24-Acetate Isolated from the Alismatis Rhizoma Improves Hepatic Lipid Deposition in Hyperlipidemic Mice by ABCA1/ABCG1 Pathway.

The Alisol A 24-acetate is an effective component of the Alismatis Rhizoma (AR) extract, which is often used in the treatment of hyperlipidemia. This study explored the effect and mechanism of the Alisol A 24-acetate from AR on lipid deposition in the liver of hyperlipidemic mice. After establishing hyperlipidemic mouse model (Model) by oral high-fat diet (HFD), the animals were treated with Alisol A 24-acetate for 4 weeks. The changes of blood lipid in mice were detected by ELISA. Hematoxylin and eosin (H&E) staining was used to evaluate the degree of liver lipid deposition in hyperlipidemic mice. Quantitative reverse transcriptase PCR (RT-qPCR) was used to detect the expression of ABCG1 and ABCA1 mRNA in the liver. The expression of ABCG1 and ABCA1 protein was detected by Western blotting (WB). After 4 weeks of high-fat diet, the levels of TC, TG, and LDL-C in the mouse were increased, and the HDL-C level was decreased. After treatment with Alisol A 24-acetate, the levels of TC, TG, and LDL-C in the blood of hyperlipidemic mouse were significantly reduced, and the level of HDL-C was increased. The results of H&E staining showed that the lipid deposition in the liver of hyperlipidemic mouse was improved after treatment with Alisol A 24-acetate. RT-qPCR and WB analysis documented that ABCG1 and ABCA1 mRNA and protein expression in hyperlipidemic mice were promoted after the Alisol A 24-acetate treatment. In conclusion, Alisol A 24-acetate effectively alleviates the liver lipid deposition in hyperlipidemic mice, and this effect is achieved mostly by promoting the expression of ABCG1 and ABCA1 at the mRNA and protein levels.

Wiring Specificity and Synaptic Diversity in the Mouse Lateral Central Amygdala.

The central amygdala (CeA) nucleus, a subcortical structure composed of mostly GABA-releasing (GABAergic) neurons, controls fear expression via projections to downstream targets in the hypothalamus and brainstem. The CeA consists of the lateral (CeL) and medial (CeM) subdivisions. The CeL strongly gates information transfer to the CeM, the main output station of the amygdala, but little is known about the functional organization of local circuits in this region. Using cluster analysis, we identified two major electrophysiologically distinct CeL neuron classes in mouse amygdala slices, the early-spiking (ES) and late-spiking (LS) neurons. These two classes displayed distinct autaptic transmission. Compared with LS neurons, ES neurons had strong and depressing autapses, which enhanced spike-timing precision. With multiple patch-clamp recordings, we found that CeL neurons made chemical, but not electrical, synapses. Analysis of individual connections revealed cannabinoid type 1 receptor-mediated suppression of the ES, but not of the LS cell output synapse. More interestingly, the efficacy of the ES→LS or LS→ES synapse was ~2-fold greater than that of the LS→LS or ES→ES synapse. When tested at 20 Hz, synapses between different neurons, but not within the same class, were markedly depressing and were more powerful to sculpt activity of postsynaptic neurons. Moreover, neurons of different classes also form synapses with higher degree of connectivity. We demonstrate that ES and LS neurons represent two functionally distinct cell classes in the CeL and interactions between presynaptic and postsynaptic neurons dictate synaptic properties between neurons. SIGNIFICANCE STATEMENT: The central lateral amygdala (CeL) is a key node in fear circuits, but the functional organization of local circuits in this region is largely unknown. The CeL consists of mostly GABAergic inhibitory neurons with different functional and molecular features. Here, we report that the presynaptic cell class determines functional properties of autapses and cannabinoid-mediated modulation of synaptic transmission between neurons, whereas presynaptic versus postsynaptic cell classes dictate the connectivity, efficacy, and dynamics of GABAergic synapses between any two neurons. The wiring specificity and synaptic diversity have a great impact on neuronal output in amygdala inhibitory networks. Such synaptic organizing principles advance our understanding of the significance of physiologically defined neuronal phenotypes in amygdala inhibitory networks.

Bivalent Display of Dicysteine on Peptide Nucleic Acids for Homogenous DNA/RNA Detection through in Situ Fluorescence Labelling.

Fluorogenic probes that signal the presence of specific DNA or RNA sequences are key enabling tools for molecular disease diagnosis and imaging studies. Usually, at least one fluorophore is attached through covalent bonding to an oligonucleotide probe. However, the additional conjugation step increases costs. Here we introduce a method that avoids the requirement for the preparation of fluorescence-labelled oligonucleotides and provides the opportunity to alter the fluorogenic reporter dye without resynthesis. The method is based on adjacent hybridization of two dicysteine-containing peptide nucleic acid (PNA) probes to form a bipartite tetracysteine motif that binds profluorescent bisarsenical dyes such as FIAsH, ReAsH or CrAsH. Binding is accompanied by strong increases in fluorescence emission (with response factors of up to 80-fold and high brightness up to 50 mL mol-1 cm-1 ). The detection system provides sub-nanomolar limits of detection and allows discrimination of single nucleotide variations through more than 20-fold changes in fluorescence intensity. To demonstrate its usefulness, the FIAsH-based readout of the bivalent CysCys-PNA display was interfaced with a rolling-circle amplification (RCA) assay used to detect disease-associated microRNA let-7a.

Light-Enhanced Antibacterial Activity of Graphene Oxide, Mainly via Accelerated Electron Transfer.

Before graphene derivatives can be exploited as next-generation antimicrobials, we must understand their behavior under environmental conditions. Here, we demonstrate how exposure to simulated sunlight significantly enhances the antibacterial activity of graphene oxide (GO) and reveal the underlying mechanism. Our measurements of reactive oxygen species (ROS) showed that only singlet oxygen (1O2) is generated by GO exposed to simulated sunlight, which contributes only slightly to the oxidation of antioxidant biomolecules. Unexpectedly, we find the main cause of oxidation is light-induced electron-hole pairs generated on the surface of GO. These light-induced electrons promote the reduction of GO, introducing additional carbon-centered free radicals that may also enhance the antibacterial activities of GO. We conclude that GO-mediated oxidative stress mainly is ROS-independent; simulated sunlight accelerates the transfer of electrons from antioxidant biomolecules to GO, thereby destroying bacterial antioxidant systems and causing the reduction of GO. Our insights will help support the development of graphene for antibacterial applications.

Peptide o-aminoanilides as crypto-thioesters for protein chemical synthesis.

Fully unprotected peptide o-aminoanilides can be efficiently activated by NaNO2 in aqueous solution to furnish peptide thioesters for use in native chemical ligation. This finding enables the convergent synthesis of proteins from readily synthesizable peptide o-aminoanilides as a new type of crypto-thioesters. The practicality of this approach is shown by the synthesis of histone H2B from five peptide segments. Purification or solubilization tags, which are sometimes needed to improve the efficiency of protein chemical synthesis, can be incorporated into the o-aminoanilide moiety, as demonstrated in the preparation of the cyclic protein lactocyclicin Q.

New semi-synthesis of ubiquitin C-terminal conjugate with 7-amino-4-methylcoumarin.

The ligation of peptide hydrazides at a Gly site carrying a removal auxiliary was found to be an efficient process. This technology was successfully used for the synthesis of ubiquitin C-terminal conjugates. Recombinant Ub(1-75)-NHNH2 was prepared through the hydrozinolysis of the Ub(1-75)-intein fusion protein. It was ligated with a glycine derivative modified with an acid-sensitive thiol auxiliary. The final acid treatment produced the desired bioactive ubiquitin conjugates in practical quantities. Thus, the method described here extends the protocols of expressed protein ligation.

iMRSAPred: Improved Prediction of Anti-MRSA Peptides Using Physicochemical and Pairwise Contact-Energy Properties of Amino Acids.

Methicillin-resistant Staphylococcus aureus (MRSA) is a growing concern for human lives worldwide. Anti-MRSA peptides act as potential antibiotic agents and play significant role to combat MRSA infection. Traditional laboratory-based methods for annotating Anti-MRSA peptides are although precise but quite challenging, costly, and time-consuming. Therefore, computational methods capable of identifying Anti-MRSA peptides accelerate the drug designing process for treating bacterial infections. In this study, we developed a novel sequence-based predictor "iMRSAPred" for screening Anti-MRSA peptides by incorporating energy estimation and physiochemical and sequential information. We successfully resolved the skewed imbalance phenomena by using synthetic minority oversampling technique plus Tomek link (SMOTETomek) algorithm. Furthermore, the Shapley additive explanation method was leveraged to analyze the impact of top-ranked features in the prediction task. We evaluated multiple machine learning algorithms, i.e., CatBoost, Cascade Deep Forest, Kernel and Tree Boosting, support vector machine, and HistGBoost classifiers by 10-fold cross-validation and independent testing. The proposed iMRSAPred method significantly improved the overall performance in terms of accuracy and Matthew's correlation coefficient (MCC) by 5.45 and 0.083%, respectively, on the training data set. On the independent data set, iMRSAPred improved accuracy and MCC by 3.98 and 0.055%, respectively. We believe that the proposed method would be useful in large-scale Anti-MRSA peptide prediction and provide insights into other bioactive peptides.

Omnidirectional Monolithic Marker for Intra-Operative MR-Based Positional Sensing in Closed MRI.

We present a design of an inductively coupled radio frequency (ICRF) marker for magnetic resonance (MR)-based positional tracking, enabling the robust increase of tracking signal at all scanning orientations in quadrature-excited closed MR imaging (MRI). The marker employs three curved resonant circuits fully covering a cylindrical surface that encloses the signal source. Each resonant circuit is a planar spiral inductor with parallel plate capacitors fabricated monolithically on flexible printed circuit board (FPC) and bent to achieve the curved structure. Size of the constructed marker is Ø3-mm ×5 -mm with quality factor > 22, and its tracking performance was validated with 1.5 T MRI scanner. As result, the marker remains as a high positive contrast spot under 360° rotations in 3 axes. The marker can be accurately localized with a maximum error of 0.56 mm under a displacement of 56 mm from the isocenter, along with an inherent standard deviation of 0.1-mm. Accrediting to the high image contrast, the presented marker enables automatic and real-time tracking in 3D without dependency on its orientation with respect to the MRI scanner receive coil. In combination with its small form-factor, the presented marker would facilitate robust and wireless MR-based tracking for intervention and clinical diagnosis. This method targets applications that can involve rotational changes in all axes (X-Y-Z).

Asparaginyl Endopeptidase-Mediated Peptide Cyclization for Phage Display.

We report here an enzymatic strategy for asparaginyl endopeptidase-mediated peptide cyclization. Incorporation of chloroacetyl groups into the recognition sequence of OaAEP1 enabled intramolecular cyclization with Cys residues. Combining this strategy and phage display, we identified nanomolar macrocyclic peptide ligands targeting TEAD4. One of the bicyclic peptides binds to TEAD4 with a KD value of 139 nM, 16 times lower than its linear analogue, demonstrating the utility of this platform in discovering high-affinity macrocyclic peptide ligands.

Employing unnatural promiscuity of sortase to construct peptide macrocycle libraries for ligand discovery.

With the increasing attention paid to macrocyclic scaffolds in peptide drug development, genetically encoded peptide macrocycle libraries have become invaluable sources for the discovery of high-affinity peptide ligands targeting disease-associated proteins. The traditional phage display technique of constructing disulfide-tethered macrocycles by cysteine oxidation has the inherent drawback of reduction instability of the disulfide bond. Chemical macrocyclization solves the problem of disulfide bond instability, but the involved highly electrophilic reagents are usually toxic to phages and may bring undesirable side reactions. Here, we report a unique Sortase-mediated Peptide Ligation and One-pot Cyclization strategy (SPLOC) to generate peptide macrocycle libraries, avoiding the undesired reactions of electrophiles with phages. The key to this platform is to mine the unnatural promiscuity of sortase on the X residue of the pentapeptide recognition sequence (LPXTG). Low reactive electrophiles are incorporated into the X-residue side chain, enabling intramolecular cyclization with the cysteine residue of the phage-displayed peptide library. Utilizing the genetically encoded peptide macrocycle library constructed by the SPLOC platform, we found a high-affinity bicyclic peptide binding TEAD4 with a nanomolar KD value (63.9 nM). Importantly, the binding affinity of the bicyclic peptide ligand is 102-fold lower than that of the acyclic analogue. To our knowledge, this is the first time to mine the unnatural promiscuity of ligases to generate peptide macrocycles, providing a new avenue for the construction of genetically encoded cyclic peptide libraries.

Thioproline-Based Oxidation Strategy for Direct Preparation of N-Terminal Thiazolidine-Containing Peptide Thioesters from Peptide Hydrazides.

We describe a simple and robust oxidation strategy for preparing N-terminal thiazolidine-containing peptide thioesters from peptide hydrazides. We find for the first time that l-thioproline can be used as a protective agent to prevent the nitrosation of N-terminal thiazolidine during peptide hydrazide oxidation. The thioproline-based oxidation strategy has been successfully applied to the chemical synthesis of CC chemokine ligand-2 (69aa) and omniligase-C (113aa), thereby demonstrating its utility in hydrazide-based native chemical ligation.