A strategy takes "Yiqing" tablets as an example to carry out simpler multi-component quantification and use fingerprint technology for comprehensive quality consistency evaluation

The comprehensive evaluation of the quality of traditional Chinese medicines (TCM) is an important issue for the continuous progress and exploration of TCM. In this study, a "Yiqing" tablet (YQT) was taken as an example, and the sample quality was comprehensively investigated by multi-component quantification, multi-dimensional fingerprint construction, and antioxidant activity analysis. Based on high performance liquid chromatography (HPLC) and fourier transform infrared spectroscopy (FTIR) fingerprint, accurate and fast multi-component quantification is achieved by reliable Multi-markers assay by mono-linear method (MAML) method and verified partial least squares regression (PLSR) model. The basic HPLC fingerprint and the special FTIR quantitative fingerprint were evaluated by SQFM, and the rich fingerprint qualitative and quantitative information of the sample was obtained. The characteristic parameter (blocking rate (BR)) characterizing antioxidant activity in the electrochemical (EC) fingerprint was excavated for the first time, and the fingerprint-efficacy analysis results with HPLC and FTIR were obtained through bivariate correlation analysis (BCA). The results showed that 25 components in the HPLC fingerprint and had antioxidant activity, and most bands of FTIR showed antioxidant activity. Finally, by combining the evaluation results of HPLC and FTIR fingerprint using the mean method, all samples were classified as first level, except for S1, demonstrating the consistency of sample quality. Based on the comprehensive quality evaluation system combining vertical and horizontal combination, this study provides a new idea for achieving comprehensive quality evaluation of TCM.

Neural networks prediction of the protein-ligand binding affinity with circular fingerprints

BACKGROUND

Protein-ligand binding affinity is of significant importance in structure-based drug design. Recently, the development of machine learning techniques has provided an efficient and accurate way to predict binding affinity. However, the prediction performance largely depends on how molecules are represented.

OBJECTIVE

Different molecular descriptors are designed to capture different features. The study aims to identify the optimal circular fingerprints for predicting protein-ligand binding affinity with matched neural network architectures.

METHODS

Extended-connectivity fingerprints (ECFP) and protein-ligand extended connectivity fingerprints (PLEC) encode circular atomic and bonding connectivity environments with the preference for intra- and inter-molecular features, respectively. Densely-connected neural networks are employed to map the circular fingerprints of protein-ligand complexes to binding affinitiesRESULTS:The performance of neural networks is sensitive to the parameters used for ECFP and PLEC fingerprints. The R2_score of the evaluated ECFP and PLEC fingerprints reaches 0.52 and 0.49, higher than that of the improperly set ECFP and PLEC fingerprints with R2_score of 0.45 and 0.38, respectively. Additionally, compared to the predictions from the standalone fingerprints, the ECFP+PLEC conjoint ones slightly improve the prediction accuracy with R2_score of approximately 0.55.

CONCLUSION

Both intra- and inter-molecular structural features encoded in the circular fingerprints contribute to the protein-ligand binding affinity. Optimizing the parameters of ECFP and PLEC can enhance performance. The conjoint fingerprint scheme can be generally extended to other molecular descriptors for enhanced feature engineering and improved predictive performance.

Fluorescence resonance energy transfer in revealing protein-protein interactions in living cells

Genes are expressed to proteins for a wide variety of fundamental biological processes at the cellular and organismal levels. However, a protein rarely functions alone, but rather acts through interactions with other proteins to maintain normal cellular and organismal functions. Therefore, it is important to analyze the protein-protein interactions to determine functional mechanisms of proteins, which can also guide to develop therapeutic targets for treatment of diseases caused by altered protein-protein interactions leading to cellular/organismal dysfunctions. There is a large number of methodologies to study protein interactions in vitro, in vivo and in silico, which led to the development of many protein interaction databases, and thus, have enriched our knowledge about protein-protein interactions and functions. However, many of these interactions were identified in vitro, but need to be verified/validated in living cells. Furthermore, it is unclear whether these interactions are direct or mediated via other proteins. Moreover, these interactions are representative of cell- and time-average, but not a single cell in real time. Therefore, it is crucial to detect direct protein-protein interactions in a single cell during biological processes in vivo, towards understanding the functional mechanisms of proteins in living cells. Importantly, a fluorescence resonance energy transfer (FRET)-based methodology has emerged as a powerful technique to decipher direct protein-protein interactions at a single cell resolution in living cells, which is briefly described in a limited available space in this mini-review.

Construction and characterization of protein-based cysteine nanosensor for the real time measurement of cysteine level in living cells

Cysteine plays a critical role in maintaining normal human metabolism, redox homeostasis, and immune regulation. Despite its functional versatility, cysteine metabolism in the human body is not well understood because of the lack of a robust tool for real-time measurement of cysteine at the cellular and sub-cellular level. In the present study, a genetically encoded nanosensor was developed using Cj0982 protein of Campylobacter jejuni, Enhanced Cyan Fluorescent Protein (ECFP) and Venus. The Cj0982 was sandwiched between ECFP and Venus for the construction of the nanosensor, named as Cys-FS (Cysteine-Fluorescent-Sensor). The Cys-FS is pH stable, specific to cysteine and has an affinity of 1.2 × 10^-5 M. A range of affinity mutants were also developed with a cumulative cysteine detection range from 800 nM to 3.5 mM. The Cys-FS nanosensor was expressed in bacterial, yeast and mammalian cells, and the dynamics of cysteine level was measured in living cells using the confocal microscopy. The results showed that the Cys-FS nanosensor successfully monitored the dynamics of cysteine in both prokaryotic and eukaryotic systems without disrupting the cell. Thus, this study presents a novel nanosensor that can measure cysteine in living cells. This nanosensor is minimally invasive and non-toxic.

Combining structural and bioactivity-based fingerprints improves prediction performance and scaffold hopping capability

This study aims at improving upon existing activity predictions methods by augmenting chemical structure fingerprints with bio-activity based fingerprints derived from high-throughput screening (HTS) data (HTSFPs) and thereby showcasing the benefits of combining different descriptor types. This type of descriptor would be applied in an iterative screening scenario for more targeted compound set selection. The HTSFPs were generated from HTS data obtained from PubChem and combined with an ECFP4 structural fingerprint. The bioactivity-structure hybrid (BaSH) fingerprint was benchmarked against the individual ECFP4 and HTSFP fingerprints. Their performance was evaluated via retrospective analysis of a subset of the PubChem HTS data. Results showed that the BaSH fingerprint has improved predictive performance as well as scaffold hopping capability. The BaSH fingerprint identified unique compounds compared to both the ECFP4 and the HTSFP fingerprint indicating synergistic effects between the two fingerprints. A feature importance analysis showed that a small subset of the HTSFP features contribute most to the overall performance of the BaSH fingerprint. This hybrid approach allows for activity prediction of compounds with only sparse HTSFPs due to the supporting effect from the structural fingerprint.

Recovering Actives in Multi-Antitarget and Target Design of Analogs of the Myosin II Inhibitor Blebbistatin

In multitarget drug design, it is critical to identify active and inactive compounds against a variety of targets and antitargets. Multitarget strategies thus test the limits of available technology, be that in screening large databases of compounds vs. a large number of targets, or in using in silico methods for understanding and reliably predicting these pharmacological outcomes. In this paper, we have evaluated the potential of several in silico approaches to predict the target, antitarget and physicochemical profile of (S)-blebbistatin, the best-known myosin II ATPase inhibitor, and a series of analogs thereof. Standard and augmented structure-based design techniques could not recover the observed activity profiles. A ligand-based method using molecular fingerprints was, however, able to select actives for myosin II inhibition. Using further ligand- and structure-based methods, we also evaluated toxicity through androgen receptor binding, affinity for an array of antitargets and the ADME profile (including assay-interfering compounds) of the series. In conclusion, in the search for (S)-blebbistatin analogs, the dissimilarity distance of molecular fingerprints to known actives and the computed antitarget and physicochemical profile of the molecules can be used for compound design for molecules with potential as tools for modulating myosin II and motility-related diseases.

Visualization of Multicolored in vivo Organelle Markers for Co-Localization Studies in Oryza sativa

Eukaryotic cells consist of a complex network of thousands of proteins present in different organelles where organelle-specific cellular processes occur. Identification of the subcellular localization of a protein is important for understanding its potential biochemical functions. In the post-genomic era, localization of unknown proteins is achieved using multiple tools including a fluorescent-tagged protein approach. Several fluorescent-tagged protein organelle markers have been introduced into dicot plants, but its use is still limited in monocot plants. Here, we generated a set of multicolored organelle markers (fluorescent-tagged proteins) based on well-established targeting sequences. We used a series of pGWBs binary vectors to ameliorate localization and co-localization experiments using monocot plants. We constructed different fluorescent-tagged markers to visualize rice cell organelles, i.e., nucleus, plastids, mitochondria, peroxisomes, golgi body, endoplasmic reticulum, plasma membrane, and tonoplast, with four different fluorescent proteins (FPs) (G3GFP, mRFP, YFP, and CFP). Visualization of FP-tagged markers in their respective compartments has been reported for dicot and monocot plants. The comparative localization of the nucleus marker with a nucleus localizing sequence, and the similar, characteristic morphology of mCherry-tagged Arabidopsis organelle markers and our generated organelle markers in onion cells, provide further evidence for the correct subcellular localization of the Oryza sativa (rice) organelle marker. The set of eight different rice organelle markers with four different FPs provides a valuable resource for determining the sub-cellular localization of newly identified proteins, conducting co-localization assays, and generating stable transgenic localization in monocot plants.

Computational refinement of spectroscopic FRET measurements

This article supplies raw data related to a research article entitled “Joint refinement of FRET measurements using spectroscopic and computational tools” (Kyrychenko et al., 2017) [1], in which we demonstrate the use of molecular dynamics simulations to estimate FRET orientational factors in a benchmark donor-linker-acceptor system of enhanced cyan (ECFP) and enhanced yellow (EYFP) fluorescent proteins. This can improve the recalculation of donor-acceptor distance information from single-molecule FRET measurements.

Joint refinement of FRET measurements using spectroscopic and computational tools

The variability of the orientation factor is a long-standing challenge in converting FRET efficiency measurements into donor-acceptor distances. We propose the use of molecular dynamics (MD) simulations to characterize orientation distributions and thus improve the accuracy of distance measurements. Here, we test this approach by comparing experimental and simulated FRET efficiencies for a model donor-acceptor pair of enhanced cyan and enhanced yellow FPs connected by a flexible linker. Several spectroscopic techniques were used to characterize FRET in solution. In addition, a series of atomistic MD simulations of a total length of 1.5 μs were carried out to calculate the distances and the orientation factor in the FRET-pair. The resulting MD-based and experimentally measured FRET efficiency histograms coincided with each other, allowing for direct comparison of distance distributions. Despite the fact that the calculated average orientation factor was close to 2/3, the application of the average κ² to the entire histogram of FRET efficiencies resulted in a substantial artificial broadening of the calculated distribution of apparent donor-acceptor distances. By combining single pair-FRET measurements with computational tools, we demonstrate that accounting for the donor and acceptor orientation heterogeneity is critical for accurate representation of the donor-acceptor distance distribution from FRET measurements.

An evaluation of genetically encoded FRET-based biosensors for quantitative metabolite analyses in vivo

A broad range of genetically-encoded fluorescence biosensors has been developed, allowing the detection of signaling intermediates and metabolites in real time. Many of these biosensors are based on Foerster Resonance Energy Transfer (FRET). The two biosensors of the well-known "Venus-flytrap" type exemplarily studied in this work are composed of a central sugar binding protein flanked by two green fluorescent protein derivatives, namely ECFP as well as Citrine and EYFP, respectively. In order to evaluate FRET-based biosensors as an in vivo tool for quantitative metabolite analyses, we have thoroughly studied the effects of pH, buffer salts, ionic strength, temperature and several intracellular metabolites on the signal intensity of both biosensors and both fluorescence proteins. Almost all micro-environmental variations led to considerably different FRET signals, because either the fluorescent proteins or the metabolite binding domains were affected by the tested parameters. This resulted not only in altered FRET ratios between the apo state and the saturated state but also in significant shifts of the apparent binding constant. This underlines the necessity of careful controls in order to allow reliable quantitative measurements in vivo.

Improving the spectral analysis of Fluorescence Resonance Energy Transfer in live cells: application to interferon receptors and Janus kinases

The observed Fluorescence Resonance Energy Transfer (FRET) between fluorescently labeled proteins varies in cells. To understand how this variation affects our interpretation of how proteins interact in cells, we developed a protocol that mathematically separates donor-independent and donor-dependent excitations of acceptor, determines the electromagnetic interaction of donors and acceptors, and quantifies the efficiency of the interaction of donors and acceptors. By analyzing large populations of cells, we found that misbalanced or insufficient expression of acceptor or donor as well as their inefficient or reversible interaction influenced FRET efficiency in vivo. Use of red-shifted donors and acceptors gave spectra with less endogenous fluorescence but produced lower FRET efficiency, possibly caused by reduced quenching of red-shifted fluorophores in cells. Additionally, cryptic interactions between jellyfish FPs artefactually increased the apparent FRET efficiency. Our protocol can distinguish specific and nonspecific protein interactions even within highly constrained environments as plasma membranes. Overall, accurate FRET estimations in cells or within complex environments can be obtained by a combination of proper data analysis, study of sufficient numbers of cells, and use of properly empirically developed fluorescent proteins.

Ligand-independent interaction of the type I interferon receptor complex is necessary to observe its biological activity

Ectopic coexpression of the two chains of the Type I and Type III interferon (IFN) receptor complexes (IFN-αR1 and IFN-αR2c, or IFN-λR1 and IL-10R2) yielded sensitivity to IFN-alpha or IFN-lambda in only some cells. We found that IFN-αR1 and IFN-αR2c exhibit FRET only when expressed at equivalent and low levels. Expanded clonal cell lines expressing both IFN-αR1 and IFN-αR2c were sensitive to IFN-alpha only when IFN-αR1 and IFN-αR2c exhibited FRET in the absence of human IFN-alpha. Coexpression of RACK-1 or Jak1 enhanced the affinity of the interaction between IFN-αR1 and IFN-αR2c. Both IFN-αR1 and IFN-αR2c exhibited FRET with Jak1 and Tyk2. Together with data showing that disruption of the preassociation between the IFN-gamma receptor chains inhibited its biological activity, we propose that biologically active IFN receptors require ligand-independent juxtaposition of IFN receptor chains assisted by their associated cytosolic proteins.

Receptor-mediated Ca2+ and PKC signaling triggers the loss of cortical PKA compartmentalization through the redistribution of gravin

A-Kinase Anchoring Proteins (AKAPs) direct the flow of cellular information by positioning multiprotein signaling complexes into proximity with effector proteins. However, certain AKAPs are not stationary but can undergo spatiotemporal redistribution in response to stimuli. Gravin, a 300kD AKAP that intersects with a diverse signaling array, is localized to the plasma membrane but has been shown to translocate to the cytosol following the elevation of intracellular calcium ([Ca(2+)]i). Despite the potential for gravin redistribution to impact multiple signaling pathways, the dynamics of this event remain poorly understood. In this study, quantitative microscopy of cells expressing gravin-EGFP revealed that Ca(2+) elevation caused the complete translocation of gravin from the cell cortex to the cytosol in as little as 60s of treatment with ionomycin or thapsigargin. In addition, receptor mediated signaling was also shown to cause gravin redistribution following ATP treatment, and this event required both [Ca(2+)]i elevation and PKC activation. To understand the mechanism for Ca(2+) mediated gravin dynamics, deletion of calmodulin-binding domains revealed that a fourth putative calmodulin binding domain called CB4 (a.a. 670-694) is critical for targeting gravin to the cell cortex despite its location downstream of gravin's membrane-targeting domains, which include an N-terminal myristoylation site and three polybasic domains. Finally, confocal microscopy of cells co-transfected with gravin-EYFP and PKA RII-ECFP revealed that gravin redistribution mediated by ionomycin, thapsigargin, and ATP each triggered the gravin-dependent loss of PKA localized at the cell cortex. Our results support the hypothesis that gravin redistribution regulates cross-talk between PKA-dependent signaling and receptor-mediated events involving Ca(2+) and PKC.

The 1.6 Å resolution structure of a FRET-optimized Cerulean fluorescent protein

Genetically encoded cyan fluorescent proteins (CFPs) bearing a tryptophan-derived chromophore are commonly used as energy-donor probes in Förster resonance energy transfer (FRET) experiments useful in live cell-imaging applications. In recent years, significant effort has been expended on eliminating the structural and excited-state heterogeneity of these proteins, which has been linked to undesirable photophysical properties. Recently, mCerulean3, a descendant of enhanced CFP, was introduced as an optimized FRET donor protein with a superior quantum yield of 0.87. Here, the 1.6 Å resolution X-ray structure of mCerulean3 is reported. The chromophore is shown to adopt a planar trans configuration at low pH values, indicating that the acid-induced isomerization of Cerulean has been eliminated. β-Strand 7 appears to be well ordered in a single conformation, indicating a loss of conformational heterogeneity in the vicinity of the chromophore. Although the side chains of Ile146 and Leu167 appear to exist in two rotamer states, they are found to be well packed against the indole group of the chromophore. The Ser65 reversion mutation allows improved side-chain packing of Leu220. A structural comparison with mTurquoise2 is presented and additional engineering strategies are discussed.