Molecular Insights into the Variability in Infection and Immune Evasion Capabilities of SARS-CoV-2 Variants: A Sequence and Structural Investigation of the RBD Domain.

As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continuously emerge, an increasing number of mutations are accumulating in the Spike protein receptor-binding domain (RBD) region. Through sequence analysis of various Variants of Concern (VOC), we identified that they predominantly fall within the ο lineage although recent variants introduce any novel mutations in the RBD. Molecular dynamics simulations were employed to compute the binding free energy of these variants with human Angiotensin-converting enzyme 2 (ACE2). Structurally, the binding interface of the ο RBD displays a strong positive charge, complementing the negatively charged binding interface of ACE2, resulting in a significant enhancement in the electrostatic potential energy for the ο variants. Although the increased potential energy is partially offset by the rise in polar solvation free energy, enhanced electrostatic potential contributes to the long-range recognition between the ο variant's RBD and ACE2. We also conducted simulations of glycosylated ACE2-RBD proteins. The newly emerged ο (JN.1) variant has added a glycosylation site at N-354@RBD, which significantly weakened its binding affinity with ACE2. Further, our interaction studies with three monoclonal antibodies across multiple SARS-CoV-2 strains revealed a diminished neutralization efficacy against the ο variants, primarily attributed to the electrostatic repulsion between the antibodies and RBD interface. Considering the characteristics of the ο variant and the trajectory of emerging strains, we propose that newly developed antibodies against SARS-CoV-2 RBD should have surfaces rich in negative potential and, postbinding, exhibit strong van der Waals interactions. These findings provide invaluable guidance for the formulation of future therapeutic strategies.

Biological effect of black phosphorus nanosheets on the interaction between SARS-CoV-2 S protein and ACE2.

The binding of the spike glycoprotein (S protein) in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to angiotensin-converting enzyme 2 (ACE2) is the main pathway that leads to serious coronavirus disease 2019 (COVID-19) infection. In the biomedical applications of various nanomaterials, black phosphorus nanosheets (BP) have been receiving increasing attention owing to their excellent characteristics. In this study, the biological effect of BP on the interaction between the S protein and ACE2 was investigated by molecular dynamics simulations. The results indicated that the ACE2 could be quickly and stably adsorbed on the BP surface by non-specific binding and retain its structural integrity. Compared with the case without BP, the interaction of the S protein bound to ACE2 adsorbed on the BP surface was greatly weakened, including hydrogen bonds, salt bridges, and van der Waals forces. This study not only reveals that BP could effectively obstruct the binding of S protein and ACE2, which may provide a potential and reasonable drug carrier to further enhance the curative effect of inhibitors against SARS-CoV-2 infection, but also presents a novel interference mechanism for protein-protein interactions caused by nanomaterials.

A simple approach to the prediction of soil sorption of organophosphorus pesticides.

Organophosphorus pesticides (OP) affect the crops and environments, and the reliable approach to the prediction of soil sorption of pesticides is required. In this respect, we proposed a simple Chemometrics approach, in which the Tchebichef image moment (TM) method was used to extract useful information from the greyscale images of molecular structures and the quantitative model was established by stepwise regression to predict the soil sorption of OPs. Different squared correlation coefficients including the leave-one-out cross-validation (LOO-CV) (Q2) that concerns the training set and the (R2test) which concerns the external independent test set are more than 0.96. This reflects that the established model has considerably high accuracy and reliability. Compared with the literature on the strategies of quantitative structure-property relationship (QSPR), the proposed method is more suitable, in which the established model shows a high predictive ability. Our study provides another effective approach to predict the soil sorption of OPs and also extends the innovative pathway of QSPR modelling.

A simple approach to the determination of three curcuminoids with similar chemical structures in different substrates.

The determination of curcuminoids in mixtures is more difficult due to their similar chemical structures as well as serious interferences, thus the complex pretreatments of samples and the optimization of experimental conditions are often required. Here, owing to the mathematical separation of chemical signals by Tchebichef image moments, a simple and effective approach to the simultaneous quantitative analysis was proposed, and applied to the determination of the three curcuminoids in turmeric and curry based on their raw fluorescence 3D spectra. For the established linear models, the leave-one-out correlation coefficients (R loo-cv) were more than 0.9816 within the linear ranges, and the predictive correlation coefficients (R p) for the external independent samples were more than 0.9897. The intra- and inter-day precision (less than 6.82%, RSD), average spiked recovery (89.9% ~ 100.8%), LOD (less than 0.07 µg/mL) and LOQ (less than 0.23 µg/mL) suggest that the proposed approach is accurate and reliable. Compared with N-PLS and MCR-ALS methods, our method can obtain more satisfactory results. This study provides a convenient pathway for the rapid analysis of multi-target components with similar chemical structures in mixture of different substrates.

Novel Approach to the Analysis of Chemical Third-Order Data.

For the more complex samples, chemical higher-order data can be collected from various information sources, which become the necessary foundation of accurate analysis. In this article, the Tchebichef cubic moment (TCM) was developed for the analysis of chemical third-order data for the first time. Then, the proposed TCM approach was applied to the fluorescence excitation-emission time data for the analysis of adrenaline and noradrenaline in urinary samples (Data I) and the data fusion of the excitation-emission matrix (EEM), NMR, and liquid chromatography-mass spectrometry (LC-MS) spectra for the determination of the five target components (Data II). For Data I, all of the cross-validation correlation coefficients (Rcv2) of the obtained linear models on the calibration set were more than 0.9937 and the prediction root-mean-square errors (RMSEp) of the external independent test samples were less than 0.0250 µM. For Data II, all of the Rcv2 were higher than 0.9846 and RMSEp were less than 0.2267 µM. Compared with several conventional methods, the proposed method was more convenient and accurate. This study provides another effective approach to the analysis of complex samples based on their chemical third-order data.

A Simple Approach to the Toxicity Prediction of Anilines and Phenols Towards Aquatic Organisms.

Chemicals pollution in the environment has attracted attention all over the world, and the toxicity prediction of chemical pollutants has become quite important. In this paper, we introduce a simple approach to predict the toxicity of some chemical components, in which the Tchebichef image moment (TM) method was employed to extract useful chemical information from the images of molecular structures to establish quantitative structure-activity relationship (QSAR) prediction models. The proposed approach was applied to predict the toxicity of anilines and phenols for the aquatic organisms of P. subcapitata and V. fischeri, in which the obtained TMs were defined as the independent variables, while the biological toxicity (pEC50) was regarded to be the dependent variable. Then, the predictive models were established by stepwise regression, respectively. The obtained squared correlation coefficients of leave-one-out cross-validation (Q2) for training sets and the predictive squared correlation coefficients (Rp2) for test sets of the two groups of data were higher than 0.79 and 0.75, respectively, which indicated that the obtained models possessed satisfactory accuracy and reliability. Compared with several reported methods, the proposed approach was more convenient and has a higher predictive capability. Our study provides another perspective in QSAR research.

Molecular inhibitory mechanism study on the potent inhibitor brigatinib against four crizotinib-resistant ALK mutations.

As a potent and selective drug, brigatinib exhibits high efficacy against wild-type and mutant anaplastic lymphoma kinase (ALK) proteins to treat non-small cell lung cancer. In this work, the mechanisms of brigatinib binding to wild type and four mutant ALKs were investigated to gain insight into the dynamic energetic and structural information with respect to the design of novel inhibitors. Comparison between ALK-brigatinib and ALK-crizotinib suggests that the scaffold of brigatinib is well anchored to the residue Met1199 of hinge region by two hydrogen bonds, and the residue Lys1150 has the strong electrostatic interaction with the dimethylphosphine oxide moiety in brigatinib. These ALK mutations have significant influences on the flexibility of P-loop region and DFG sequences, but do not impair the hydrogen bonds between brigatinib and the residue Met1199 of hinge region. And mutations (L1196M, G1269A, F1174L, and R1275Q) induce diverse conformational changes of brigatinib and the obvious energy variation of residues Glu1167, Arg1209, Asp1270, and Asp1203. Together, the detailed explanation of mechanisms of those mutations with brigatinib further provide several guidelines for the development of more effective ALK inhibitors.

Molecular mechanisms of tetrahydropyrrolo[1,2-c]pyrimidines as HBV capsid assembly inhibitors.

As an attractive therapeutic strategy for chronic hepatitis B virus (HBV), HBV capsid assembly inhibitors have got increased attention, which induce aberrant capsid assembly and thereby affect viral replication. In this work, molecular docking, molecular dynamics simulations, binding free energy calculations and per-residue energy decomposition were implemented to investigate the binding mechanism between tetrahydropyrrolopyrimidines scaffold inhibitors and HBV capsid protein. The obtained results displayed that the non-polar interaction, hydrogen bond interaction, polar interaction and π-π stacking interaction together help to stabilize the conformation of inhibitors in the interface of HBV core proteins, and residues Pro25, Thr33, Trp102, Ile105, Tyr118, Ile139, Leu140 (chain B), and Val124, Trp125, Thr128, Arg133 (chain C) were important participants during binding process. The replacement of the electronegative groups F, Cl and sulphonamide in inhibitor 28a would alter the major inhibitory effects of binding and activation. The models established by three-dimensional quantitative structure-activity relationship could be used to predict the anti-HBV activities of the tetrahydropyrrolopyrimidines molecules. This study will help understanding the molecular mechanisms and novel designed small molecules could act as better inhibitors.

Simultaneous quantification of multiple endogenous biothiols in cancer cells based on a multi-signal fluorescent probe.

Although a large number of fluorescent probes have been developed, the simultaneous quantitative analysis of intracellular thiols is still difficult due to the spectral overlap and the complexity of the intracellular environment. In this study, a multi-signal fluorescent probe was employed for the simultaneous quantification of intracellular glutathione (GSH), cysteine (Cys) and homocysteine (Hcy). As the feature variables of the target components, the Tchebichef image moments (TMs) calculated from the grayscale images of the 3D fluorescence spectra were used to establish the quantitative linear models by stepwise regression. The intra-day and inter-day precisions of the proposed method were less than 5.6% and 8.7%, respectively. The recoveries ranged from 97.0% to 105.9%. In addition, the proposed approach was applied to the simultaneous quantitative determination of Cys, GSH and Hcy in the MCF-10A cell (a type of normal cell) and MDA-MB-231 cancer cell. The obtained results indicated that the concentrations of the three thiols in the cancer cell were higher than those in the normal cell. This study not only provides an effective approach for the quantification of multi-target bio-molecules in complicated intracellular environments, but also further extends the applications of multi-signal fluorescent probes, which will promote the design of new multi-signal fluorescent probes.

Applications of Discrete Shmaliy Moments on the Quantitative Analysis of Multitarget Compounds Based on the Chemical Spectra.

To extract the features in first-order or second-order signals, the two kinds of discrete Shmaliy moment (DSM) methods were proposed and applied to the quantitative analysis of multitarget compounds in complexes based on the UV-vis and high-performance liquid chromatography with pulsed amperometric detector (HPLC-PAD) spectra of samples for the first time. All the statistical parameters demonstrated that the obtained models were accurate and the established analytical methods were reliable, even in the presence of a different degree of overlapping signals as well as various interferences. Compared with Tchebichef moment (TM) and other classical methods such as multivariate curve resolution-alternating least-squares (MCR-ALS), partial least-squares (PLS) regression, and N-way partial least-squares (N-PLS), the proposed methods are more convenient and efficient, which not only provides another suitable tool for the quantitative analysis of multitarget components in complex samples but also extends the application of moment invariants in chemical signal analyses.

In silico toxicity evaluation of dioxins using structure-activity relationship (SAR) and two-dimensional quantitative structure-activity relationship (2D-QSAR).

Prediction of pEC50 values of dioxins binding with the aryl hydrocarbon receptor (AhR) is of great significance for exploring how dioxins induce toxicity in human body and evaluating their environmental behaviors and risks. To reveal the factors that influence the toxicity of dioxins, provide more accurate mathematical models for predicting the pEC50 values of dioxins, and supplement the toxicity database of persistent organic pollutants, qualitative structure-activity relationship (SAR) and two-dimensional quantitative structure-activity relationship (2D-QSAR) were used in this study. The research objects in this study were 60 organic compounds with pEC50 values and 162 compounds without pEC50 values, which included polychlorinated dibenzofurans (PCDFs), polychlorinated dibenzo-p-dioxins (PCDDs), and polybrominated dibenzo-p-dioxins (PBDDs). The qualitative structure-activity relationship (SAR) was performed first and concluded that halogen substitutions at any of the 2, 3, 7, and 8 sites increased the pEC50 value of the compound. Moreover, two-dimensional quantitative structure-activity relationship (2D-QSAR) models were established by employing multiple linear regression (MLR) method and artificial neural network (ANN) algorithm to investigate the factors affecting the pEC50 values of dioxins molecules. MLR was used to establish the well-understood linear model and ANN was used to establish a more accurate non-linear model. Both models have good fitting, robustness, and predictive ability. Importantly, the ability of dioxins binding to AhR is mainly determined by molecular descriptors including E1m, SM09_AEA (dm), RDF065u, F05 [Cl-Cl], and Neoplastic-80. In addition, the pEC50 values of the 162 dioxins without toxicity data were predicted by MLR and ANN models, respectively.

Tchebichef image moment approach to the prediction of protein secondary structures based on circular dichroism.

Circular dichroism (CD) spectroscopy is a widely used technique for the evaluation of protein secondary structures that has a significant impact for the understanding of molecular biology. However, the quantitative analysis of protein secondary structures based on CD spectra is still a hard work due to the serious overlap of the spectra corresponding to different structural motifs. Here, Tchebichef image moment (TM) approach is introduced for the first time, which can effectively extract the chemical features in CD spectra for the quantitative analysis of protein secondary structures. The proposed approach was applied to analyze reference set and the obtained results were evaluated by the strict statistical parameters such as correlation coefficient, cross-validation correlation coefficient and root mean squared error. Compared with several specialized prediction methods, TM approach provided satisfactory results, especially for turns and unordered structures. Our study indicates that TM approach can be regarded as a feasible tool for the analysis of the secondary structures of proteins based on CD spectra. An available TMs package is provided and can be used directly for secondary structures prediction.

Molecular modeling study on resistance of WT/D473H SMO to antagonists LDE-225 and LEQ-506.

The smoothened (SMO) receptor, an essential signal transducer in the Hedgehog pathway, was targeted with antagonists to suppress the tumor. It is interesting that SMO D473H mutation confers resistance on inhibitor LDE-225 rather than LEQ-506. In this paper, the binding modes of them against the wild type and mutant SMO receptors were identified to gain insights into the resistant and non-resistant factors, based on a comprehensive protocol involving molecular docking, molecular dynamic simulations, free energy calculation and decomposition. A comparison of resistant LDE-225 and non-resistant LEQ-506 indicates that the volume of the binding cavity decreases seriously in the mutant complex with resistant LDE-225. In addition, the D473H mutation disrupts the hydrogen bond network with residues R400 and Q477, which results in the TM6 conformation inward. Owing to the absence of the hydrogen bond, residues R400 and Q477 make weak contributions to LDE-225. However, the D473H mutation along with TM6 conformational change has no effect on non-resistant LEQ-506. Finally, the resistance ascribes to adverse interaction between the greater polarity of mutant residue H473 and the nonpolar phenmethyl of LDE-225. The elaborate insights into structural and energetic mechanism of drug resistance provide an effective strategy to design rationally non-resistant antagonists.

Prediction of phosphorylation sites based on Krawtchouk image moments.

Protein phosphorylation is one of the most pervasive post-translational modifications and regulates diverse cellular processes in organisms. Under the catalysis of protein kinases, protein phosphorylation usually occurred in the residues serine (S), threonine (T), or tyrosine (Y). In this contribution, we proposed a novel scheme (named KMPhos) for the theoretical prediction of protein phosphorylation sites. First, the numerical matrix was obtained from a protein sequence fragment by replacing the characters of the residues with the chemical descriptors of amino acid molecules to approximately describe the chemical environment of the protein fragment, which was turned to the grayscale image. Then the Krawtchouk image moments were calculated and used to establish the support vector machine models. The accuracies of 10-fold cross validation for the obtained models on the training set are up to 89.7%, 88.6%, and 90.1% for the residues S, Y, and T, respectively. For the independent test set, the prediction accuracies are up to 90.7% (S), 87.8% (T), and 89.3% (Y). The results of ROC and other evaluations are also satisfactory. Compared with several specialized prediction tools, KMPhos provided the higher accuracy and reliability. An available KMPhos package is provided and can be used directly for phosphorylation sites prediction.

Insights into mechanism of pyrido[2,3-d]pyrimidines as DYRK1A inhibitors based on molecular dynamic simulations.

DYRK1A is characterized by the early development and regulation of neuronal proliferation, and its over expression gives rise to neurological abnormalities. As the promising DYRK1A inhibitors, the binding mechanism between DYRK1A and pyrido[2,3-d]pyrimidines derivatives at molecular level are still veiled. In this article, it was achieved to get the structural insights into pyrido[2,3-d]pyrimidines derivatives as DYRK1A inhibitors by means of comprehensive computational approaches involving molecular docking, molecular dynamics simulation, free energy calculation, and energy decomposition analysis. The calculated energy values were highly consistent with the experimental activities. Based on the individual energy terms analysis, the van der Waals interaction was the major leading force in the DYRK1A-ligand interaction. Lys188 was the important residue that formed the hydrogen bond, which improved the inhibitory activity. Furthermore, four novel inhibitors with higher predicted activity were designed based on the obtained findings and confirmed by molecular simulations. Our study is expected to provide significant drug design strategy for the development of more promising DYRK1A inhibitors. Proteins 2016; 84:1108-1123. © 2016 Wiley Periodicals, Inc.

Quantitative analysis of multiple components based on liquid chromatography with mass spectrometry in full scan mode.

Although liquid chromatography with mass spectrometry in full scan mode can obtain all the signals simultaneously in a large range and low cost, it is rarely used in quantitative analysis due to several problems such as chromatographic drifts and peak overlap. In this paper, we propose a Tchebichef moment method for the simultaneous quantitative analysis of three active compounds in Qingrejiedu oral liquid based on three-dimensional spectra in full scan mode of liquid chromatography with mass spectrometry. After the Tchebichef moments were calculated directly from the spectra, the quantitative linear models for three active compounds were established by stepwise regression. All the correlation coefficients were more than 0.9978. The limits of detection and limits of quantitation were less than 0.11 and 0.49 µg/mL, respectively. The intra- and interday precisions were less than 6.54 and 9.47%, while the recovery ranged from 102.56 to 112.15%. Owing to the advantages of multi-resolution and inherent invariance properties, Tchebichef moments could provide favorable results even in the situation of peaks shifting and overlapping, unknown interferences and noise signals, so it could be applied to the analysis of three-dimensional spectra in full scan mode of liquid chromatography with mass spectrometry.

Longest distance shifting: A simple and efficient approach for the alignment of shifted chromatographic peaks.

The preprocessing of chromatograms, such as the alignment of retention time shifts, is often a crucial step in the proper data analysis chain. Here, an efficient approach to align shifted chromatographic signals, longest distance shifting, is presented and highlighted. The performance of this novel strategy was demonstrated by using both simulated chromatograms that covered the different kinds of retention time shifts and the real experimental chromatograms of Pudilan Xiaoyan Tablets obtained by high-performance liquid chromatography with photodiode array detection. The averaged correlation coefficient for experimental chromatograms were in the range of 0.9517-0.9840 and the peak factor was 0.9989. As a comparison, all the chromatograms have also been aligned using correlation optimized warping and Interval Correlation Optimized Shifting algorithms. The obtained results indicate that the longest distance shifting algorithm is simpler, faster and more effective, and will be potentially suitable for the alignment of other types of signals.

The application of a Tchebichef moment method to the quantitative analysis of multiple compounds based on three-dimensional HPLC fingerprint spectra.

Three-dimensional (3D) fingerprint spectra provide a wealth of information for the quantitative analysis of multiple target compounds in mixtures. In this paper, a Tchebichef moment method based on the 3D fingerprint spectra obtained from high performance liquid chromatography coupled with a photodiode array detector was proposed and used to determine notoginsenoside R1, ginsenoside Rg1, ginsenoside Re and ginsenoside Rb1 in samples of a traditional Chinese Medicine (Sanqi Panax Notoginseng). The correlation coefficients of the established models were more than 0.9955 within the test ranges, the recovery ranged from 98.41% to 108.00%, and the intra- and inter-day precisions were less than 3.83% and 5.04%, respectively. The obtained results indicated that the Tchebichef moment method had effective feature representation capability and provided satisfactory quantification accuracy. Furthermore, several moment methods applied in analytical chemistry were compared, which provided a valuable insight into the application of moment methods in the analytical field.

High-performance liquid chromatography with photodiode array detection and chemometrics method for the analysis of multiple components in the traditional Chinese medicine Shuanghuanglian oral liquid.

Shuanghuanlian oral liquid, a traditional Chinese medicine preparation, is a mixture of three herbs (Flos Lonicerae, Radix Scutellariae and Fructus Forsythiae). In this study, the quantitative analysis of three main active compounds, chlorogenic acid, forsythin and baicalin in samples from different manufacturers was performed rapidly by high-performance liquid chromatography coupled with photodiode array detection followed by Contour Projection coupled to stepwise regression treatment of the obtained three-dimensional spectra in which the partial overlap between adjacent target components existed. The method was validated for linearity (R>0.9940), precision (RSD<1.25%), recovery (92.20-102.50%), limit of detection (0.01-0.02 µg/mL) and limit of quantification (0.03-0.07 µg/mL). The results indicated that the combination of the three-dimensional spectra of traditional Chinese medicine and Contour Projection-stepwise regression offered an accurate, simple, low-cost and eco-friendly way for the rapid quantitative analysis of Shuanghuanlian oral liquid samples.

Fast determination of four active compounds in Sanqi Panax Notoginseng Injection samples by high-performance liquid chromatography with a chemometric method.

The application of chemometric methods could decrease the requirements of separation and simplify time-consuming pretreatment and experimental optimization. In this report, the accumulated projection method was developed and utilized for the rapid simultaneous quantification of four active components (notoginsenoside R1, ginsenosides Rg1, ginsenosides Re, and ginsenosides Rb1) in Sanqi Panax Notoginseng Injection samples. The proposed method is based on the three-dimensional fingerprint spectra obtained from high-performance liquid chromatography coupled with photodiode array detection. Although the chromatograms consisted of overlapping peaks, retention time shifts, and unknown interference, all established models showed good linearity (R > 0.9869) within test ranges. The relative standard deviation for intra- and interday precision of the four compounds did not exceed 2.4 and 4.7%, respectively, and the overall recovery was 91.2-106.8%. Compared with N-way principal component analysis, our method provides more satisfactory results, which indicate that the proposed approach is simple, fast, and reliable for the determination of the four analytes in Sanqi Panax Notoginseng Injection samples.