Molecular interactions of UvrB protein and DNA from Helicobacter pylori: Insight into a molecular modeling approach

Exploring the phytochemicals of Platycodon grandiflorus for TMPRSS2 inhibition in the search for SARS-CoV-2 entry inhibitors

Platycodon grandiflorus (Jacq.) A. DC. (Campanulaceae) is commonly known as a balloon flower whose rhizomes have been widely utilized in traditional Chinese medicine (TCM) and in various Japanese prescriptions for the treatment of respiratory diseases, diabetes, and inflammatory disorders. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19) global pandemic requires priming of the virus's spike (S) protein by cleavage of the S proteins by a multi-domain type II transmembrane serine protease, transmembrane protease serine 2 (TMPRSS2) to gain entry into the host cell. The current research aims at the screening of active phytocompounds of P. grandiflorus as potential inhibitors of cellular TMPRSS2 using molecular docking and molecular dynamics simulations approach. In silico toxicity analyses show that out of a total of 34 phytocompounds selected for the study, 12 compounds obey Lipinski’s rule of five and have favourable pharmacokinetic properties. The top three lead molecules identified here were Apigenin, Luteolin and Ferulic acid which exhibited binding energies of −7.47 kcal/mol, −6.8 kcal/mol and −6.62 kcal/mol respectively with corresponding inhibition constants of 3.33 µM, 10.39 µM and 13.95 µM. The complexes between the lead molecules and the receptor were held by hydrogen bond interactions with key residues such as Gly383, Gly385, Glu389, Lys390, Asp435, Ser436, Ser441, Cys465 and Lys467, and hydrophobic interactions with surrounding residues. The stability of the protein–ligand complexes was evaluated during 100 ns molecular dynamics (MD) simulation by analysing key geometric properties such as RMSD, RMSF, radius of gyration, total solvent accessible surface area and the number of hydrogen bonds. The binding free energies analysis using MD simulations revealed that the compounds and TMPRSS2 have favourable thermodynamic interactions, which are primarily driven by van der Waals forces. As a result, the selected bioactive phytochemicals from P. grandiflorus that target the cellular TMPRSS2 could offer an alternative treatment option against SARS-CoV-2 infections.

Rad5 HIRAN domain: Structural insights into its interaction with ssDNA through molecular modeling approaches

The Rad5 protein is an SWI/SNF family ubiquitin ligase that contains an N-terminal HIRAN domain and a RING C3HC4 motif. The HIRAN domain is critical for recognition of the stalled replication fork during the replication process and acts as a sensor to initiate the damaged DNA checkpoint. It is a conserved domain widely distributed in eukaryotic organisms and is present in several DNA-binding proteins from all kingdoms. Here we showed that distant species have important differences in key residues that affect affinity for ssDNA. Based on these findings, we hypothesized that different HIRAN domains might affect fork reversal and translesion synthesis through different metabolic processes. To address this question, we predicted the tertiary structure of both yeast and human HIRAN domains using molecular modeling. Structural dynamics experiments showed that the yeast HIRAN domain exhibited higher structural denaturation than its human homolog, although both domains became stable in the presence of ssDNA. Analysis of atomic contacts revealed that a greater number of interactions between the ssDNA nucleotides and the Rad5 domain are electrostatic. Taken together, these results provide new insights into the molecular mechanism of the HIRAN domain of Rad5 and may guide us to further elucidate differences in the ancient eukaryotes HIRAN sequences and their DNA affinity. Communicated by Ramaswamy H. Sarma.

Insilico drug repurposing using FDA approved drugs against Membrane protein of SARS-CoV-2

The novel coronavirus (SARS-CoV-2) outbreak has started taking away the millions of lives worldwide. Identification of known and approved drugs against novel coronavirus disease (COVID-19) seems to be an urgent need for the repurposing of the existing drugs. So, here we examined a safe strategy of using approved drugs of SuperDRUG2 database against modeled membrane protein (M-protein) of SARS-CoV-2 which is essential for virus assembly by using molecular docking-based virtual screening. A total of 3639 drugs from SuperDRUG2 database and additionally 14 potential drugs reported against COVID-19 proteins were selected. Molecular docking analyses revealed that nine drugs can bind the active site of M-protein with desirable molecular interactions. We therefore applied molecular dynamics simulations and binding free energy calculation using MM-PBSA to analyze the stability of the compounds. The complexes of M-protein with the selected drugs were simulated for 50 ns and ranked according to their binding free energies. The binding mode of the drugs with M-protein was analyzed and it was observed that Colchicine, Remdesivir, Bafilomycin A1 from COVID-19 suggested drugs and Temozolomide from SuperDRUG2 database displayed desirable molecular interactions and higher binding affinity towards M-protein. Interestingly, Colchicine was found as the top most binder among tested drugs against M-protein. We therefore additionally identified four Colchicine derivatives which can bind efficiently with M-protein and have better pharmacokinetic properties. We recommend that these drugs can be tested further through in vitro studies against SARS-CoV-2 M-protein.

Doxorubicin-Conjugated Innovative 16-mer DNA Aptamer-Based Annexin A1 Targeted Anti-Cancer Drug Delivery

Aptamers are small, functional single-stranded DNA or RNA oligonucleotides that bind to their targets with high affinity and specificity. Experimentally, aptamers are selected by the systematic evolution of ligands by exponential enrichment (SELEX) method. Here, we have used rational drug designing and bioinformatics methods to design the aptamers, which involves three different steps. First, finding a probable aptamer-binding site, and second, designing the recognition and structural parts of the aptamers by generating a virtual library of sequences, selection of specific sequence via molecular docking, molecular dynamics (MD) simulation, binding energy calculations, and finally evaluating the experimental affinity. Following this strategy, a 16-mer DNA aptamer was designed for Annexin A1 (ANXA1). In a direct binding assay, DNA1 aptamer bound to the ANXA1 with dissociation constants value of 83 nM. Flow cytometry and fluorescence microscopy results also showed that DNA1 aptamer binds specifically to A549, HepG2, U-87 MG cancer cells that overexpress ANXA1 protein, but not to MCF7 and L-02, which are ANXA1 negative cells. We further developed a novel system by conjugating DNA1 aptamer with doxorubicin and its efficacy was studied by cellular uptake and cell viability assay. Also, anti-tumor analysis showed that conjugation of doxorubicin with aptamer significantly enhances targeted therapy against tumors while minimizing overall adverse effects on mice health.

Chronic atrophic gastritis detection with a convolutional neural network considering stomach regions

BACKGROUND

The risk of gastric cancer increases in patients with Helicobacter pylori-associated chronic atrophic gastritis (CAG). X-ray examination can evaluate the condition of the stomach, and it can be used for gastric cancer mass screening. However, skilled doctors for interpretation of X-ray examination are decreasing due to the diverse of inspections.

AIM

To evaluate the effectiveness of stomach regions that are automatically estimated by a deep learning-based model for CAG detection.

METHODS

We used 815 gastric X-ray images (GXIs) obtained from 815 subjects. The ground truth of this study was the diagnostic results in X-ray and endoscopic examinations. For a part of GXIs for training, the stomach regions are manually annotated. A model for automatic estimation of the stomach regions is trained with the GXIs. For the rest of them, the stomach regions are automatically estimated. Finally, a model for automatic CAG detection is trained with all GXIs for training.

RESULTS

In the case that the stomach regions were manually annotated for only 10 GXIs and 30 GXIs, the harmonic mean of sensitivity and specificity of CAG detection were 0.955 ± 0.002 and 0.963 ± 0.004, respectively.

CONCLUSION

By estimating stomach regions automatically, our method contributes to the reduction of the workload of manual annotation and the accurate detection of the CAG.

Identification of GCC-box and TCC-box motifs in the promoters of differentially expressed genes in rice (Oryza sativa L.): Experimental and computational approaches

The transcription factor selectively binds with the cis-regulatory elements of the promoter and regulates the differential expression of genes. In this study, we aimed to identify and validate the presence of GCC-box and TCC-box motifs in the promoters of upregulated differentially expressed genes (UR-DEGs) and downregulated differentially expressed genes (DR-DEGs) under anoxia using molecular beacon probe (MBP) based real-time PCR. The GCC-box motif was detected in UR-DEGs (DnaJ and 60S ribosomal protein L7 genes), whereas, the TCC-box was detected in DR-DEGs (DnaK and CPuORF11 genes). In addition, the mechanism of interaction of AP2/EREBP family transcription factor (LOC_Os03g22170) with GCC-box promoter motif present in DnaJ gene (LOC_Os06g09560) and 60S ribosomal protein L7 gene (LOC_Os08g42920); and TCC-box promoter motif of DnaK gene (LOC_Os02g48110) and CPuORF11 gene (LOC_Os02g01240) were explored using molecular dynamics (MD) simulations analysis including binding free energy calculations, principal component analyses, and free energy landscapes. The binding free energy analysis revealed that AP2/EREBP model residues such as Arg68, Arg72, Arg83, Lys87, and Arg90 were commonly involved in the formation of hydrogen bonds with GCC and TCC-box promoter motifs, suggesting that these residues are critical for strong interaction. The movement of the entire protein bound to DNA was restricted, confirming the stability of the complex. This study provides comprehensive binding information and a more detailed view of the dynamic interaction between proteins and DNA.

Structural study to analyze the DNA-binding properties of DsrC protein from the dsr operon of sulfur-oxidizing bacterium Allochromatium vinosum

Our environment is densely populated with various beneficial sulfur-oxidizing prokaryotes (SOPs). These organisms are responsible for the proper maintenance of biogeochemical sulfur cycles to regulate the turnover of biological sulfur substrates in the environment. Allochromatium vinosum strain DSM 180^T is a gamma-proteobacterium and is a member of SOP. The organism codes for the sulfur-oxidizing dsr operon, which is comprised of dsrABEFHCMKLJOPNRS genes. The Dsr proteins formed from dsr operon are responsible for formation of sulfur globules. However, the molecular mechanism of the regulation of the dsr operon is not yet fully established. Among the proteins encoded by dsr genes, DsrC is known to have some regulatory functions. DsrC possesses a helix-turn-helix (HTH) DNA-binding motif. Interestingly, the structural details of this interaction have not yet been fully established. Therefore, we tried to analyze the binding interactions of the DsrC protein with the promoter DNA structure of the dsr operon as well as a random DNA as the control. We also performed molecular dynamics simulations of the DsrC-DNA complexes. This structure-function relationship investigation revealed the most probable binding interactions of the DsrC protein with the promoter region present upstream of the dsrA gene in the dsr operon. As expected, the random DNA structure could not properly interact with DsrC. Our analysis will therefore help researchers to predict a plausible biochemical mechanism for the sulfur oxidation process. Graphical Abstract Interaction of Allochromatium vinosum DsrC protein with the promoter region present upstream of the dsrA gene.

Exploration for novel inhibitors showing back-to-front approach against VEGFR-2 kinase domain (4AG8) employing molecular docking mechanism and molecular dynamics simulations

Background

Angiogenesis is a process of formation of new blood vessels and is an important criteria demonstrated by cancer cells. Over a period of time, these cancer cells infect the other parts of the healthy body by a process called progression. The objective of the present article is to identify a drug molecule that inhibits angiogenesis and progression.

Methods

In this pursuit, ligand based pharmacophore virtual screening was employed, generating a pharmacophore model, Hypo1 consisting of four features. Furthermore, this Hypo1 was validated recruiting, Fischer’s randomization, test set method and decoy set method. Later, Hypo1 was allowed to screen databases such as Maybridge, Chembridge, Asinex and NCI and were further filtered by ADMET filters and Lipinski’s Rule of Five. A total of 699 molecules that passed the above criteria, were challenged against 4AG8, an angiogenic drug target employing GOLD v5.2.2.

Results

The results rendered by molecular docking, DFT and the MD simulations showed only one molecule (Hit) obeyed the back-to-front approach. This molecule displayed a dock score of 89.77, involving the amino acids, Glu885 and Cys919, Asp1046, respectively and additionally formed several important hydrophobic interactions. Furthermore, the identified lead molecule showed interactions with key residues when challenged with CDK2 protein, 1URW.

Conclusion

The lead candidate showed several interactions with the crucial residues of both the targets. Furthermore, we speculate that the residues Cys919 and Leu83 are important in the development of dual inhibitor. Therefore, the identified lead molecule can act as a potential inhibitor for angiogenesis and progression.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4050-1) contains supplementary material, which is available to authorized users.

UvrB protein of Corynebacterium pseudotuberculosis complements the phenotype of knockout Escherichia coli and recognizes DNA damage caused by UV radiation but not 8-oxoguanine in vitro

In prokaryotic cells, the UvrB protein plays a central role in nucleotide excision repair, which is involved in the recognition of bulky DNA lesions generated by chemical or physical agents. The present investigation aimed to characterize the uvrB gene of Corynebacterium pseudotuberculosis (CpuvrB) and evaluate its involvement in the DNA repair system of this pathogenic organism. In computational analysis, the alignment of the UvrB protein sequences of Escherichia coli, Mycobacterium tuberculosis, Bacillus caldotenax and Corynebacterium pseudotuberculosis showed high similarity and the catalytic amino acid residues and functional domains are preserved. A CpUvrB model was constructed by comparative modeling and presented structural similarity with the UvrB of E. coli. Moreover, in molecular docking analysis CpUvrB showed favorable interaction with EcUvrA and revealed a preserved ATP incorporation site. Heterologous functional complementation assays using E. coli uvrB-deficient cells exposed to UV irradiation showed that the CpUvrB protein contributed to an increased survival rate in relation to those in the absence of CpUvrB. Damaged oligonucleotides containing thymine dimer or 8-oxoguanine lesion were synthesized and incubated with CpUvrB protein, which was able to recognize and excise UV irradiation damage but not 8-oxoguanine. These results suggest that CpUvrB is involved in repairing lesions derived from UV light and encodes a protein orthologous to EcUvrB.

Sulfonanilide Derivatives in Identifying Novel Aromatase Inhibitors by Applying Docking, Virtual Screening, and MD Simulations Studies

Breast cancer is one of the leading causes of death noticed in women across the world. Of late the most successful treatments rendered are the use of aromatase inhibitors (AIs). In the current study, a two-way approach for the identification of novel leads has been adapted. 81 chemical compounds were assessed to understand their potentiality against aromatase along with the four known drugs. Docking was performed employing the CDOCKER protocol available on the Discovery Studio (DS v4.5). Exemestane has displayed a higher dock score among the known drug candidates and is labeled as reference. Out of 81 ligands 14 have exhibited higher dock scores than the reference. In the second approach, these 14 compounds were utilized for the generation of the pharmacophore. The validated four-featured pharmacophore was then allowed to screen Chembridge database and the potential Hits were obtained after subjecting them to Lipinski's rule of five and the ADMET properties. Subsequently, the acquired 3,050 Hits were escalated to molecular docking utilizing GOLD v5.0. Finally, the obtained Hits were consequently represented to be ideal lead candidates that were escalated to the MD simulations and binding free energy calculations. Additionally, the gene-disease association was performed to delineate the associated disease caused by CYP19A1.