In Silico Evaluation of Bioactive Compounds of Artemisia pallens Targeting the Efflux Protein of Multidrug-Resistant Acinetobacter baumannii (LAC-4 Strain).

Acinetobacter baumannii (A. baumannii) is one of the major representative aetiologies of recalcitrant nosocomial infections. Genotypic and phenotypic alterations in A. baumannii have resulted in a significant surge in multidrug resistance (MDR). Of all the factors responsible for the development of antimicrobial resistance (AMR), efflux protein pumps play a paramount role. In pursuit of a safe alternative for the prevention and control of A. baumannii infections, bioactive compounds from the aerial parts of the medicinal plant Artemisia pallens were studied. GC-MS analysis of the ethanol extract of A. pallens detected five major compounds: lilac alcohol A, spathulenol, lilac alcohol C, n-hexadecanoic acid, and vulgarin. In silico examinations were performed using the Schrödinger suite. Homology modelling was performed to predict the structure of the efflux protein of A. baumannii-LAC-4 strain (MDR Ab-EP). The identified bioactive compounds were analysed for their binding efficiency with MDR Ab-EP. High binding efficiency was observed with vulgarin with a glide score of -4.775 kcal/mol and stereoisomers of lilac alcohol A (-3.706 kcal/mol) and lilac alcohol C (-3.706 kcal/mol). Our molecular dynamic simulation studies unveiled the stability of the ligand-efflux protein complex. Vulgarin and lilac alcohol A possessed strong and stable binding efficiency with MDR Ab-EP. Furthermore, validation of the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of the ligands strongly suggested that these compounds could serve as a lead molecule in the development of an alternate drug from A. pallens.

HPREP: a comprehensive database for human proteome repeats.

Amino acid repeats are found to play important roles in both structures and functions of the proteins. These are commonly found in all kingdoms of life, especially in eukaryotes and a larger fraction of human proteins composed of repeats. Further, the abnormal expansions of shorter repeats cause various diseases to humans. Therefore, the analysis of repeats of the entire human proteome along with functional, mutational and disease information would help to better understand their roles in proteins. To fulfill this need, we developed a web database HPREP (http://bioinfo.bdu.ac.in/hprep) for human proteome repeats using Perl and HTML programming. We identified different categories of well-characterized repeats and domain repeats that are present in the human proteome of UniProtKB/Swiss-Prot by using in-house Perl programming and novel repeats by using the repeat detection T-REKS tool as well as XSTREAM web server. Further, these proteins are annotated with functional, mutational and disease information and grouped according to specific repeat types. The developed database enables the users to search by specific repeat type in order to understand their involvement in proteins. Thus, the HPREP database is expected to be a useful resource to gain better insight regarding the different repeats in human proteome and their biological roles.

Gray code representation of the universal genetic code: Generation of never born protein sequences using Toeplitz matrix approach.

In this paper, we identify all possible Gray Code and Partitioned Gray Code representations of the Universal Genetic Code for n = 2-bit and 3-bit binary numbers. We analyse the Hamming Distance matrices of all these Gray code and Partitioned Gray Code possibilities for which we obtain the Toeplitz and Partitioned Toeplitz Matrices, respectively. We use this Gray Code and Partitioned Gray Code representations of the Universal Genetic Code combined with the novel Toeplitz matrix approach to generate many Never Born Protein (NBP) Sequences, which exhibit intrinsic structural stability. In general, Never Born Protein sequences may have many potential applications in synthetic biology and opens a new vista in understanding this new subset of proteins for better applications in drug discovery, synthesis of fine chemicals, etc.

Combined QSAR Model and Chemical Similarity Search for Novel HMGCoA Reductase Inhibitors for Coronary Heart Disease.

BACKGROUND: Coronary heart disease generally occurs due to cholesterol accumulation in the walls of the heart arteries. Statins are the most widely used drugs which work by inhibiting the active site of 3-Hydroxy-3-methylglutaryl-CoA reductase (HMGCR) enzyme that is responsible for cholesterol synthesis. A series of atorvastatin analogs with HMGCR inhibition activity have been synthesized experimentally which would be expensive and time-consuming. METHODS: In the present study, we employed both the QSAR model and chemical similarity search for identifying novel HMGCR inhibitors for heart-related diseases. To implement this, a 2D QSAR model was developed by correlating the structural properties to their biological activity of a series of atorvastatin analogs reported as HMGCR inhibitors. Then, the chemical similarity search of atorvastatin analogs was performed by using PubChem database search. RESULTS AND DISCUSSION: The three-descriptor model of charge (GATS1p), connectivity (SCH-7) and distance (VE1_D) of the molecules is obtained for HMGCR inhibition with the statistical values of R2= 0.67, RMSEtr= 0.33, R2 ext= 0.64 and CCCext= 0.76. The 109 novel compounds were obtained by chemical similarity search and the inhibition activities of the compounds were predicted using QSAR model, which were close in the range of experimentally observed threshold. CONCLUSION: The present study suggests that the QSAR model and chemical similarity search could be used in combination for identification of novel compounds with activity by in silico with less computation and effort.

Identification and Analysis of Long Repeats of Proteins at the Domain Level.

Amino acid repeats play an important role in the structure and function of proteins. Analysis of long repeats in protein sequences enables one to understand their abundance, structure and function in the protein universe. In the present study, amino acid repeats of length >50 (long repeats) were identified in a non-redundant set of UniProt sequences using the RADAR program. The underlying structures and functions of these long repeats were carried out using the Gene3D for structural domains, Pfam for functional domains and enzyme and non-enzyme functional classification for catalytic and binding of the proteins. From a structural perspective, these long repeats seem to predominantly occur in certain architectures such as sandwich, bundle, barrel, and roll and within these architectures abundant in the superfolds. The lengths of the repeats within each fold are not uniform exhibiting different structures for different functions. We also observed that long repeats are in the domain regions of the family and are involved in the function of the proteins. After grouping based on enzyme and non-enzyme classes, we observed the abundant occurrence of long repeats in specific catalytic and binding of the proteins. In this study, we have analyzed the occurrence of long repeats in the protein sequence universe apart from well-characterized short tandem repeats in sequences and their structures and functions of the proteins at the domain level. The present study suggests that long repeats may play an important role in the structure and function of domains of the proteins.

Analysing the antidepressant and drug efflux competence of Clitoria ternateaL. as P-glycoprotein inhibitor to facilitate blood brain barrier

Clitoria ternateaL. is a vital ayurvedic herbfeatured with a wide spectrum of mental health benefits. The present study investigates the competence of the plant against depression and to inhibit the membrane efflux protein P-glycoprotein (P-gp) that can regulate and restrict drug permeation into the brain. Antidepressant competence of the aqueous plant extract was assessed by animal despair studies on depression induced female mice models. The P-glycoprotein inhibitory potential of active phytocompounds was evaluated by molecular docking assay and substantiated by a cell line study. The in vivostudies exhibited a significant difference in the immobility time thereby establishing antidepressant activity. The histopathological sections from cortex region of treated brain showed decreased degenerative changes. Ten imperative phytocompounds facilitated docking complexes against P-glycoprotein among which Kaempferol 3-O-(2״,6״-di-O-rhamnopyranosyl) glucopyranoside exhibited a finest docking score of -12.569 kcal mol-1. Conversely it was attested by the rhodamine transport assay that demonstrated the inhibitory potential to surpass blood brain barrier. The outcome of the study endorses the efficacy of Clitoria ternateaL. as an idyllic brain drug and facilitates brain permeability.

QSAR Analysis of Multimodal Antidepressants Vortioxetine Analogs Using Physicochemical Descriptors and MLR Modeling.

BACKGROUND: Vortioxetine is a multimodal antidepressant drug with combined effects on SERT as an inhibitor, 5-HT1A as agonist and 5-HT3A as an antagonist. Series of vortioxetine analogs have been reported as multi antidepressant compounds and they block serotonin transport into the neuronal cells, activate the postsynaptic 5-HT1A receptors and eliminate the low activity of 5-HT3A receptors. OBJECTIVE: To explore the important properties of vortioxetine analogs involved in antidepressant activity by developing 2D QSAR models. METHODS: Selections of significant descriptors were performed by Least Absolute Shrinkage and Selection Operator (LASSO) method and, the Multiple Linear Regression (MLR) method and All Subsets and GA algorithm included in QSARINS software were used for generating QSAR models. Further, the virtual screening was performed based on bioactivity and structure similarity using the PubChem database. RESULTS: The four descriptor model of complementary information content (CIC2), solubility (bcutp3), mass (bcutm8) and partial charge in van der Waals surface area (PEOEVSA7) of the molecules is obtained for SERT inhibition with the significant statistics of R2= 0.69, RMSEtr= 0.44, R2 ext= 0.62 and CCCext= 0.78. For 5-HT1A agonist, the two descriptor model of molecular shape (Kappm3) and van der Waals volume of the atoms (bcutv11) with R2= 0.78, RMSEtr= 0.33, R2 ext = 0.83, and CCCext= 0.87 is established. The three descriptor model of information content (IC3), solubility (bcutp9) and electronegativity (GATSe5) of the molecules with R2= 0.61, RMSEtr= 0.34, R2 ext= 0.69 and CCCext= 0.72 is obtained for 5-HT3A antagonist. The antidepressant activities of 16 virtual screened compounds were predicted using the developed models. CONCLUSION: The developed QSAR models may be useful to predict antidepressant activity for the newly synthesized vortioxetine analogs.

Analysis of Species-Selectivity of Human, Mouse and Rat Cytochrome P450 1A and 2B Subfamily Enzymes using Molecular Modeling, Docking and Dynamics Simulations.

Cytochrome P450 (CYP) 1A and 2B subfamily enzymes are important drug metabolizing enzymes, and are highly conserved across species in terms of sequence homology. However, there are major to minor structural and macromolecular differences which provide for species-selectivity and substrate-selectivity. Therefore, species-selectivity of CYP1A and CYP2B subfamily proteins across human, mouse and rat was analyzed using molecular modeling, docking and dynamics simulations when the chiral molecules quinine and quinidine were used as ligands. The three-dimensional structures of 17 proteins belonging to CYP1A and CYP2B subfamilies of mouse and rat were predicted by adopting homology modeling using the available structures of human CYP1A and CYP2B proteins as templates. Molecular docking and dynamics simulations of quinine and quinidine with CYP1A subfamily proteins revealed the existence of species-selectivity across the three species. On the other hand, in the case of CYP2B subfamily proteins, no role for chirality of quinine and quinidine in forming complexes with CYP2B subfamily proteins of the three species was indicated. Our findings reveal the roles of active site amino acid residues of CYP1A and CYP2B subfamily proteins and provide insights into species-selectivity of these enzymes across human, mouse, and rat.

Molecular Dynamics Simulations of Novel Potential Inhibitors for Penicillin Binding Protein 2B of the Resistant 5204 Strain of Streptococcus Pneumoniae.

BACKGROUND: Top five best hit compounds (ZINC59376795, ZINC60175365, ZINC36922620, ZINC39550705 and ZINC36953975) were obtained through our high throughput virtual screening (HTVS) analysis with resistant 5204-PBP2B (5204 Penicillin Binding Protein 2B) and sensitive R6-PBP2B (R6 Penicillin Binding Protein 2B) proteins of Streptococcus pneumoniae. OBJECTIVE: To gain insight in molecular docking and dynamics simulations of these top five best hit compounds with both resistant 5204-PBP2B and sensitive R6-PBP2B targets. METHODS: We have employed Glide XP docking and molecular dynamics simulations of these five best hit compounds with 5204-PBP2B and R6-PBP2B targets. The stability analysis has been carried out through DFT, prime-MM/GBSA binding free energy, RMSD, RMSF and Principal Component Analysis. RESULTS: The reference drug, penicillin G forms stable complex with sensitive R6-PBP2B protein. Similar stability is observed for the mutant resistant 5204-PBP2B with the top scoring compound ZINC592376795 which implies that this compound may act as an effective potential inhibitor. The compound ZINC59376795 forms a total of five hydrogen bonds with resistant 5204-PBP2B protein of which three are with mutated residues. Similarly, the other four compounds including penicillin G also form hydrogen bonds with mutated residue. The MD simulations and stability analysis of the complexes of wild and mutant forms are evaluated for a trajectory period of 16ns and further MD simulations of ZINC59376795 with resistant 5204-PBP2B and sensitive R6-PBP2B confirmed the stability for 50 ns. CONCLUSION: These results suggest that the top five best hit compounds are found to be a promising gateway for the further development of anti-pneumococcal therapeutics.

Network analysis and cross species comparison of protein-protein interaction networks of human, mouse and rat cytochrome P450 proteins that degrade xenobiotics.

Cytochrome P450 (CYP) enzymes that degrade xenobiotics play a critical role in the metabolism and biotransformation of drugs and xenobiotics in humans as well as experimental animal models such as mouse and rat. These proteins function as a network collectively as well as independently. Though there are several reports on the organization, regulation and functionality of various CYP enzymes at the molecular level, the understanding of organization and functionality of these proteins at the holistic level remain unclear. The objective of this study is to understand the organization and functionality of xenobiotic degrading CYP enzymes of human, mouse and rat using network theory approaches and to study species differences that exist among them at the holistic level. For our analysis, a protein-protein interaction (PPI) network for CYP enzymes of human, mouse and rat was constructed using the STRING database. Topology, centrality, modularity and robustness analyses were performed for our predicted CYP PPI networks that were then validated by comparison with randomly generated network models. Network centrality analyses of CYP PPI networks reveal the central/hub proteins in the network. Modular analysis of the CYP PPI networks of human, mouse and rat resulted in functional clusters. These clusters were subjected to ontology and pathway enrichment analysis. The analyses show that the cluster of the human CYP PPI network is enriched with pathways principally related to xenobiotic/drug metabolism. Endo-xenobiotic crosstalk dominated in mouse and rat CYP PPI networks, and they were highly enriched with endogenous metabolic and signaling pathways. Thus, cross-species comparisons and analyses of human, mouse and rat CYP PPI networks gave insights about species differences that existed at the holistic level. More investigations from both reductionist and holistic perspectives can help understand CYP metabolism and species extrapolation in a much better way.