Exploring the mechanism of Corbrin capsules in the intervention of AKI-COVID-19 based on network pharmacology combined with GEO dataset.

AIM: of the study: This study used network pharmacology and the Gene Expression Omnibus (GEO) database to investigate the therapeutic effects of Corbrin capsules on acute kidney injury (AKI)-COVID-19 (coronavirus disease 2019). MATERIALS AND METHODS: The active constituents and specific molecular targets of Corbrin capsules were obtained from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) and Swiss Target Prediction databases. The targets related to AKI and COVID-19 disease were obtained from the Online Mendelian Inheritance in Man (OMIM), GeneCards, and GEO databases. A protein-protein interaction (PPI) network was constructed by utilizing Cytoscape. To enhance the analysis of pathways associated with the pathogenesis of AKI-COVID-19, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed. Furthermore, immune infiltration analysis was performed by using single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT. Molecular docking was used to assess interactions between differentially expressed genes and active ingredients. Verification was performed by utilizing GEO databases and in vivo assays. RESULTS: This study revealed an overlap of 18 significantly differentially expressed genes between the Corbrin capsules group and the AKI-COVID-19 target group. Analysis of the PPI network identified TP53, JAK2, PIK3CA, PTGS2, KEAP1, and MCL1 as the top six core protein targets with the highest degrees. The results obtained from GO and KEGG analyses demonstrated that the target genes were primarily enriched in the apoptosis and JAK-STAT signaling pathways. Moreover, the analysis of immune infiltration revealed a notable disparity in the percentage of quiescent memory CD4 + T cells. Western blot analyses provided compelling evidence suggesting that the dysregulation of 6 core protein targets could be effectively reversed by Corbrin capsules. CONCLUSION: This study revealed the key components, targets, and pathways involved in treating AKI-related COVID-19 using Corbrin capsules. This study also provided a new understanding of the molecular mechanisms underlying this treatment.

Cell-specific polymerization-driven biomolecular condensate formation fine-tunes root tissue morphogenesis.

Formation of biomolecular condensates can be driven by weak multivalent interactions and emergent polymerization. However, the mechanism of polymerization-mediated condensate formation is less studied. We found lateral root cap cell (LRC)-specific SUPPRESSOR OF RPS4-RLD1 (SRFR1) condensates fine-tune primary root development. Polymerization of the SRFR1 N-terminal domain is required for both LRC condensate formation and optimal root growth. Surprisingly, the first intrinsically disordered region (IDR1) of SRFR1 can be functionally substituted by a specific group of intrinsically disordered proteins known as dehydrins. This finding facilitated the identification of functional segments in the IDR1 of SRFR1, a generalizable strategy to decode unknown IDRs. With this functional information we further improved root growth by modifying the SRFR1 condensation module, providing a strategy to improve plant growth and resilience.

Current Computational Methods for Protein-Peptide Complex Structure Prediction.

Peptide-mediated protein-protein interactions (PPIs) play an important role in various biological processes. The development of peptide-based drugs to modulate PPIs has attracted increasing attention due to the advantages of high specificity and low toxicity. In the development of peptide-based drugs, one of the most important steps is to determine the interaction details between the peptide and the target protein. In addition to experimental methods, recently developed computational methods provide a cost-effective way for studying protein-peptide interactions. In this article, we carefully reviewed recently developed protein-peptide docking methods, which were classified into three groups: template-based docking, template-free docking, and hybrid method. Then, we presented available benchmarking sets and evaluation metrics for assessing protein-peptide docking performance. Furthermore, we discussed the use of molecular dynamics simulations, as well as deep learning approaches in protein-peptide complex prediction.

Identification of Rab7 as an autophagy marker: potential therapeutic approaches and the effect of Qi Teng Xiao Zhuo granule in chronic glomerulonephritis.

CONTEXT: Qi Teng Xiao Zhuo granule (QTXZG) is a traditional Chinese medicine (TCM) used for therapeutic effects on chronic glomerulonephritis (CGN). However, the underlying mechanism remains unclear. OBJECTIVE: To investigate the molecular mechanism of QTXZG on CGN by proteomics. MATERIALS AND METHODS: The CGN model was induced in Sprague-Dawley rats by injecting adriamycin (3.5 mg/kg, Day 1; 3.0 mg/kg, Day 14) twice through the tail vein. Urine samples were collected on the 21st day; and the rats divided randomly into control, adriamycin, QTXZG administration groups. Rats in the QTXZG group received QTXZG (10.8 g/kg); control and adriamycin groups were given physiological saline once per day for 30 days. Proteomics was applied to identify the candidate proteins combined with autophagy database and verified by immunofluorescence (IF) and western blots (WB). RESULTS: 278 differentially expressed proteins (DEPs) were identified based on proteomics and Rab7 was screened as an autophagy protein biomarker. In vitro cell experiments, we found that QTXZG (20%, IC50 = 23.47%) could decrease the expression of NLRP3, Caspase-1, IL-18, IL-1ß, while increasing the expression of Pink1, Parkin, Rab7, Podocalyxin. The cell apoptosis rate increased from 6.68 ± 0.07 to 11.03 ± 0.36%. Overexpression of Rab7 resulted in an increase in autophagy relevant protein expression. DISCUSSION AND CONCLUSION: TCM CGN-regulating herbs (QTXZG) can exert therapeutic effects by affecting the Rab7/Pink1/Parkin pathway to promote mitochondrial autophagy. New breakthroughs in targeted Rab7 may eventually enable such applications.

Template-guided method for protein-ligand complex structure prediction: Application to CASP15 protein-ligand studies.

Critical Assessment of Structure Prediction 15 (CASP15) added a new category of ligand prediction to promote the development of protein/RNA-ligand modeling methods, which have become important tools in modern drug discovery. A total of 22 targets were released, including 18 protein-ligand targets and 4 RNA-ligand targets. We applied our recently developed template-guided method to the protein-ligand complex structure predictions. The method combined a physicochemical, molecular docking method, and a bioinformatics-based ligand similarity method. The Protein Data Bank was scanned for template structures containing the target protein, homologous proteins, or proteins sharing a similar fold with the target protein. The binding modes of the co-bound ligands in the template structures were used to guide the complex structure prediction for the target. The CASP assessment results show that the overall performance of our method was ranked second when the top predicted model was considered for each target. Here, we analyzed our predictions in detail, and discussed the challenges including protein conformational changes, large and flexible ligands, and multiple diverse ligands in a binding pocket.

Discriminating physiological from non-physiological interfaces in structures of protein complexes: A community-wide study.

Reliably scoring and ranking candidate models of protein complexes and assigning their oligomeric state from the structure of the crystal lattice represent outstanding challenges. A community-wide effort was launched to tackle these challenges. The latest resources on protein complexes and interfaces were exploited to derive a benchmark dataset consisting of 1677 homodimer protein crystal structures, including a balanced mix of physiological and non-physiological complexes. The non-physiological complexes in the benchmark were selected to bury a similar or larger interface area than their physiological counterparts, making it more difficult for scoring functions to differentiate between them. Next, 252 functions for scoring protein-protein interfaces previously developed by 13 groups were collected and evaluated for their ability to discriminate between physiological and non-physiological complexes. A simple consensus score generated using the best performing score of each of the 13 groups, and a cross-validated Random Forest (RF) classifier were created. Both approaches showed excellent performance, with an area under the Receiver Operating Characteristic (ROC) curve of 0.93 and 0.94, respectively, outperforming individual scores developed by different groups. Additionally, AlphaFold2 engines recalled the physiological dimers with significantly higher accuracy than the non-physiological set, lending support to the reliability of our benchmark dataset annotations. Optimizing the combined power of interface scoring functions and evaluating it on challenging benchmark datasets appears to be a promising strategy.

An allosteric modulator activates BK channels by perturbing coupling between Ca2+ binding and pore opening.

BK type Ca2+-activated K+ channels activate in response to both voltage and Ca2+. The membrane-spanning voltage sensor domain (VSD) activation and Ca2+ binding to the cytosolic tail domain (CTD) open the pore across the membrane, but the mechanisms that couple VSD activation and Ca2+ binding to pore opening  are not clear. Here we show that a compound, BC5, identified from in silico screening, interacts with the CTD-VSD interface and specifically modulates the Ca2+ dependent activation mechanism. BC5 activates the channel in the absence of Ca2+ binding but Ca2+ binding inhibits BC5 effects. Thus, BC5 perturbs a pathway that couples Ca2+ binding to pore opening to allosterically affect both, which is further supported by atomistic simulations and mutagenesis. The results suggest that the CTD-VSD interaction makes a major contribution to the mechanism of Ca2+ dependent activation and is an important site for allosteric agonists to modulate BK channel activation.

Predicting Protein-Peptide Complex Structures by Accounting for Peptide Flexibility and the Physicochemical Environment.

Predicting protein-peptide complex structures is crucial to the understanding of a vast variety of peptide-mediated cellular processes and to peptide-based drug development. Peptide flexibility and binding mode ranking are the two major challenges for protein-peptide complex structure prediction. Peptides are highly flexible molecules, and therefore, brute-force modeling of peptide conformations of interest in protein-peptide docking is beyond current computing power. Inspired by the fact that the protein-peptide binding process is like protein folding, we developed a novel strategy, named MDockPeP2, which tries to address these challenges using physicochemical information embedded in abundant monomeric proteins with an exhaustive search strategy, in combination with an integrated global search and a local flexible minimization method. Only the peptide sequence and the protein crystal structure are required. The method was systemically assessed using a newly constructed structural database of 89 nonredundant protein-peptide complexes with the peptide sequence length ranging from 5 to 29 in which about half of the peptides are longer than 15 residues. MDockPeP2 yielded a total success rate of 58.4% (70.8, 79.8%) for the bound docking (i.e., with the bound receptor and fully flexible peptides) and 19.0% (44.8, 70.7%) for the challenging unbound docking when top 10 (100, 1000) models were considered for each prediction. MDockPeP2 achieved significantly higher success rates on two other datasets, peptiDB and LEADS-PEP, which contain only short- and medium-size peptides (≤ 15 residues). For peptiDB, our method obtained a success rate of 62.0% for the bound docking and 35.9% for the unbound docking when the top 10 models were considered. For LEADS-PEP, MDockPeP2 achieved a success rate of 69.8% when the top 10 models were considered. The program is available at https://zougrouptoolkit.missouri.edu/mdockpep2/download.html.

A Selective Tether Recruits Activated Response Regulator CheB to Its Chemoreceptor Substrate.

Methylesterase/deamidase CheB is a key component of bacterial chemotaxis systems. It is also a prominent example of a two-component response regulator in which the effector domain is an enzyme. Like other response regulators, CheB is activated by phosphorylation of an aspartyl residue in its regulatory domain, creating an open conformation between its two domains. Studies of CheB in Escherichia coli and related organisms have shown that its enzymatic action is also enhanced by a pentapeptide-binding site for the enzyme at the chemoreceptor carboxyl terminus. Related carboxyl-terminal pentapeptides are found on >25,000 chemoreceptor sequences distributed across 11 bacterial phyla and many bacterial species, in which they presumably play similar roles. Yet, little is known about the interrelationship of CheB phosphorylation, pentapeptide binding, and interactions with its substrate methylesters and amides on the body of the chemoreceptor. We investigated by characterizing the binding kinetics of CheB to Nanodisc-inserted chemoreceptor dimers. The resulting kinetic and thermodynamic constants revealed a synergy between CheB phosphorylation and pentapeptide binding in which a phosphorylation mimic enhanced pentapeptide binding, and the pentapeptide served not only as a high-affinity tether for CheB but also selected the activated conformation of the enzyme. The basis of this selection was revealed by molecular modeling that predicted a pentapeptide-binding site on CheB which existed only in the open, activated enzyme. Recruitment of activated enzyme by selective tethering represents a previously unappreciated strategy for regulating response regulator action, one that may well occur in other two-component systems. IMPORTANCE Two-component signal transduction systems are a primary means by which bacteria sense and respond to their environment. Response regulators are key components of these systems. Phosphorylation of response regulators by cognate histidine kinases generate active conformations which act on specific targets, DNA sequences or proteins. The targets have been considered passive in this process. Our characterization of interaction between response regulator CheB and its target chemoreceptor revealed active participation of the target in response regulator action. We found that a pentapeptide sequence at the carboxyl terminus of Escherichia coli chemoreceptors is a selective tether that binds only phosphorylated CheB, thus selecting the form of this two-component enzyme active for covalent modification of the selecting chemoreceptor. Analogous pentapeptides are found on chemoreceptors in many bacterial species and are presumably also selective tethers. There may well be other, uncharacterized examples of active participation of target molecules in response to regulator action.

Dissimilar Ligands Bind in a Similar Fashion: A Guide to Ligand Binding-Mode Prediction with Application to CELPP Studies.

The molecular similarity principle has achieved great successes in the field of drug design/discovery. Existing studies have focused on similar ligands, while the behaviors of dissimilar ligands remain unknown. In this study, we developed an intercomparison strategy in order to compare the binding modes of ligands with different molecular structures. A systematic analysis of a newly constructed protein-ligand complex structure dataset showed that ligands with similar structures tended to share a similar binding mode, which is consistent with the Molecular Similarity Principle. More importantly, the results revealed that dissimilar ligands can also bind in a similar fashion. This finding may open another avenue for drug discovery. Furthermore, a template-guiding method was introduced for predicting protein-ligand complex structures. With the use of dissimilar ligands as templates, our method significantly outperformed the traditional molecular docking methods. The newly developed template-guiding method was further applied to recent CELPP studies.

Modulating the voltage sensor of a cardiac potassium channel shows antiarrhythmic effects.

Cardiac arrhythmias are the most common cause of sudden cardiac death worldwide. Lengthening the ventricular action potential duration (APD), either congenitally or via pathologic or pharmacologic means, predisposes to a life-threatening ventricular arrhythmia, Torsade de Pointes. IKs (KCNQ1+KCNE1), a slowly activating K+ current, plays a role in action potential repolarization. In this study, we screened a chemical library in silico by docking compounds to the voltage-sensing domain (VSD) of the IKs channel. Here, we show that C28 specifically shifted IKs VSD activation in ventricle to more negative voltages and reversed the drug-induced lengthening of APD. At the same dosage, C28 did not cause significant changes of the normal APD in either ventricle or atrium. This study provides evidence in support of a computational prediction of IKs VSD activation as a potential therapeutic approach for all forms of APD prolongation. This outcome could expand the therapeutic efficacy of a myriad of currently approved drugs that may trigger arrhythmias.

A PIP2 substitute mediates voltage sensor-pore coupling in KCNQ activation.

KCNQ family K+ channels (KCNQ1-5) in the heart, nerve, epithelium and ear require phosphatidylinositol 4,5-bisphosphate (PIP2) for voltage dependent activation. While membrane lipids are known to regulate voltage sensor domain (VSD) activation and pore opening in voltage dependent gating, PIP2 was found to interact with KCNQ1 and mediate VSD-pore coupling. Here, we show that a compound CP1, identified in silico based on the structures of both KCNQ1 and PIP2, can substitute for PIP2 to mediate VSD-pore coupling. Both PIP2 and CP1 interact with residues amongst a cluster of amino acids critical for VSD-pore coupling. CP1 alters KCNQ channel function due to different interactions with KCNQ compared with PIP2. We also found that CP1 returned drug-induced action potential prolongation in ventricular myocytes to normal durations. These results reveal the structural basis of PIP2 regulation of KCNQ channels and indicate a potential approach for the development of anti-arrhythmic therapy.

MDockPeP: A Web Server for Blind Prediction of Protein-Peptide Complex Structures.

Protein-peptide interactions mediate a wide range of important cellular tasks. In silico prediction of protein-peptide complex structure is highly desirable for mechanistic investigation of these processes and for therapeutic design. Recently, we developed a docking-based method for predicting protein-peptide complex structures, which starts with the peptide sequence and globally docks the all-atom, flexible peptide onto the protein structure. The produced modes are then evaluated with a statistical potential-based scoring function. The method has been implemented into an online server, MDockPeP server, which is freely available at http://zougrouptoolkit.missouri.edu/mdockpep . The server can be used for protein-peptide complex structure prediction. The server can also be used for initial-stage sampling of the protein-peptide binding modes for computational-demanding simulation or docking methods.

Performance of human and server prediction in CAPRI rounds 38-45.

CAPRI challenges offer a variety of blind tests for protein-protein interaction prediction. In CAPRI Rounds 38-45, we generated a set of putative binding modes for each target with an FFT-based docking algorithm, and then scored and ranked these binding modes with a proprietary scoring function, ITScorePP. We have also developed a novel web server, Rebipp. The algorithm utilizes information retrieval to identify relevant biological information to significantly reduce the search space for a particular protein. In parallel, we have also constructed a GPU-based docking server, MDockPP, for protein-protein complex structure prediction. Here, the performance of our protocol in CAPRI rounds 38-45 is reported, which include 16 docking and scoring targets. Among them, three targets contain multiple interfaces: Targets 124, 125, and 136 have 2, 4, and 3 interfaces, respectively. In the predictor experiments, we predicted correct binding modes for nine targets, including one high-accuracy interface, six medium-accuracy binding modes, and six acceptable-accuracy binding modes. For the docking server prediction experiments, we predicted correct binding modes for eight targets, including one high-accuracy, three medium-accuracy, and five acceptable-accuracy binding modes.

Two-stage electro-mechanical coupling of a KV channel in voltage-dependent activation.

In voltage-gated potassium (KV) channels, the voltage-sensing domain (VSD) undergoes sequential activation from the resting state to the intermediate state and activated state to trigger pore opening via electro-mechanical (E-M) coupling. However, the spatial and temporal details underlying E-M coupling remain elusive. Here, utilizing KV7.1's unique two open states, we report a two-stage E-M coupling mechanism in voltage-dependent gating of KV7.1 as triggered by VSD activations to the intermediate and then activated state. When the S4 segment transitions to the intermediate state, the hand-like C-terminus of the VSD-pore linker (S4-S5L) interacts with the pore in the same subunit. When S4 then proceeds to the fully-activated state, the elbow-like hinge between S4 and S4-S5L engages with the pore of the neighboring subunit to activate conductance. This two-stage hand-and-elbow gating mechanism elucidates distinct tissue-specific modulations, pharmacology, and disease pathogenesis of KV7.1, and likely applies to numerous domain-swapped KV channels.

PepPro: A Nonredundant Structure Data Set for Benchmarking Peptide-Protein Computational Docking.

We present a nonredundant benchmark, coined PepPro, for testing peptide-protein docking algorithms. Currently, PepPro contains 89 nonredundant experimentally determined peptide-protein complex structures, with peptide sequence lengths ranging from 5 to 30 amino acids. The benchmark covers peptides with distinct secondary structures, including helix, partial helix, a mixture of helix and ß-sheet, ß-sheet formed through binding, ß-sheet formed through self-folding, and coil. In addition, unbound proteins' structures are provided for 58 complexes and can be used for testing the ability of a docking algorithm handling the conformational changes of proteins during the binding process. PepPro should benefit the docking community for the development and improvement of peptide docking algorithms. The benchmark is available at http://zoulab.dalton.missouri.edu/PepPro_benchmark. © 2019 Wiley Periodicals, Inc.

Predicting protein-ligand binding modes for CELPP and GC3: workflows and insight.

Drug Design Data Resource (D3R) continues to release valuable benchmarking datasets to promote improvement and development of computational methods for new drug discovery. We have developed several methods for protein-ligand binding mode prediction during the participation in the D3R challenges. In the present study, these methods were integrated, automated, and systematically tested using the large-scale data from Continuous Evaluation of Ligand Pose Prediction (CELPP) and a subset of Grand challenge 3 (GC3). The results show that current molecular docking methods benefit from the increasing number of protein-ligand complex structures deposited in Protein Data Bank. Using an appropriate protein structure for docking significantly improves the success rate of the binding mode prediction. The results of our template-based method and docking method are compared and discussed. Our future direction include the combination of these two methods for binding mode prediction.

LncRNAs expression in adriamycin-induced rats reveals the potential role of LncRNAs contributing to chronic glomerulonephritis pathogenesis.

BACKGROUND: Chronic glomerulonephritis (CGN) is the most common form of primary glomerular disease with unclear molecular mechanisms. Currently, limited study on long non-coding RNAs (lncRNAs) in CGN is available. Our study aimed to identify potential lncRNAs and genes in the normal and adriamycin-induced CGN rats, which to explore the potential molecular mechanisms of CGN pathogenesis. METHODS: To identify LncRNAs specifically expressed in CGN, the expression of LncRNAs in glomerular tissues of rats from the adriamycin-induced group (n = 3) was compared with that in the control group (n = 3) using RNA-sequencing and real-time polymerase chain reaction (RT-PCR). Identification of differentially expressed lncRNAs and mRNAs were performed between the 2 groups. Gene ontology (GO) and pathway enrichment analyses were performed to analyze the biological functions and pathways for the differentially expressed mRNAs. LncRNA-mRNA co-expression network was constructed to analyses for the genes. The protein-protein interaction (PPI) network was visualized. RESULTS: A total of 114 significantly up-regulated and 86 down-regulated lncRNAs, 1038 up-regulated and 88 down-regulated mRNAs were identified. Additionally, Il6, with the highest connectivity degree in PPI network, was noteworthy enriched in various kinds pathways. Coding-non-coding gene co-expression networks (CNC network) were drawn based on the correlation analysis between the differentially expressed LncRNAs and mRNAs. Ten LncRNAs, NONRATT000964.2, NONRATT018086.2, NONRATT023684.2, NONRATT009530.2, NONRATT006315.2, NONRATT026805.2, MSTRG.9260.1, NONRATT009155.2, MSTRG.7681.1, NONRATT009275.2, were selected to analyze the relationship between LncRNAs and CGN via the CNC network and GO analysis. Real-time PCR result confirmed that the six LncRNAs were specifically expressed in the CGN rats. CONCLUSIONS: The ten LncRNAs were differentially expressed and might play important roles in the development of CGN. Key genes, such as Il6, Ptprc, TOP2a, Fos, Myc, etc., may be crucial biomarkers for CGN.

MDockPeP: An ab-initio protein-peptide docking server.

Protein-peptide interactions play a crucial role in a variety of cellular processes. The protein-peptide complex structure is a key to understand the mechanisms underlying protein-peptide interactions and is critical for peptide therapeutic development. We present a user-friendly protein-peptide docking server, MDockPeP. Starting from a peptide sequence and a protein receptor structure, the MDockPeP Server globally docks the all-atom, flexible peptide to the protein receptor. The produced modes are then evaluated with a statistical potential-based scoring function, ITScorePeP. This method was systematically validated using the peptiDB benchmarking database. At least one near-native peptide binding mode was ranked among top 10 (or top 500) in 59% (85%) of the bound cases, and in 40.6% (71.9%) of the challenging unbound cases. The server can be used for both protein-peptide complex structure prediction and initial-stage sampling of the protein-peptide binding modes for other docking or simulation methods. MDockPeP Server is freely available at http://zougrouptoolkit.missouri.edu/mdockpep. © 2018 Wiley Periodicals, Inc.