Identification of potential marine bioactive compounds from brown seaweeds towards BACE1 inhibitors: molecular docking and molecular dynamics simulations approach.

The drug target protein ß-secretase 1 (BACE1) is one of the promising targets in the design of the drugs to control Alzheimer's disease (AD). Patients with neurodegenerative diseases are increasing in number globally due to the increase in the average lifetime. Neuro modulation is the only remedy for overcoming these age related diseases. In recent times, marine bioactive compounds are reported from Phaeophyceae (Brown Algae), Rhodophyta (Red Algae) and Chlorophyta (Green Algae) for neuro-modulation. Hence, an important attempt is made to understand the binding and stability of the identified bioactive compounds from the above marine algae using BACE1 as the molecular target. The docking study shows that the bioactive compound Fucotriphlorethol A ( - 17.27 kcal/mol) has good binding affinity and energy compared to other compounds such as Dieckol ( - 16.77 kcal/mol), Tetraphlorethol C ( - 15.12 kcal/mol), 2-phloroeckol ( - 14.98 kcal/mol), Phlorofucofuroeckol ( - 13.46 kcal/mol) and the co-crystal ( - 8.59 kcal/mol). Further, molecular dynamics simulations studies had been carried out for ß-secretase 1 complex with Fucotriphlorethol A and Phlorofucofuroeckol for 100 ns each. Results are compared with that of the co-crystal inhibitor. Molecular dynamics simulations studies also support the stability and flexibility of the two bioactive compounds Fucotriphlorethol A and Phlorofucofuroeckol with BACE1. Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-024-00210-7.

Identification of a novel drug molecule for neurodegenerative disease from marine algae through in-silico analysis.

Cognitive functions are lost due to the rapid hydrolysis of acetylcholine including Acetylcholinesterase (AChE) and Butyrylcholinesterase (BChE). Marine algae-derived compounds were reported for their neuroprotective activities and hence they can be utilised for treating neurodegenerative ailments like Alzheimer's Disease and Parkinson's Disease which are due to the loss of cognitive functions. Major attention is currently paid to seaweeds due to their health benefits and high nutritional values. Sea weeds are of a rich sense of natural bioactive compounds which antioxidants, pharmaceutical compounds, flavonoids and alkaloids. They also contain a high amount of vitamins A, D, E, C and Ca, K, Mg and Fe. Regular consumption of a marine algae-based diet may boost immunities. In searching for natural cholinesterase inhibitors, the present study is focussed on some marine bioactive compounds reported from brown, red and green algae. Molecular docking studies have been carried out along with molecular dynamics simulations studies and binding energy calculations resulting in three best bioactive compounds when AChE is used as the target. The results are compared with cocrystal studies. Two best compounds, namely, Diphlorethohydroxycarmalol and Phlorofucofuroeckol from the brown seaweeds are identified as the potential lead compounds for neurodegenerative diseases, Alzheimer's and Parkinson's.Communicated by Ramaswamy H. Sarma.

Unconjugated bilirubin and its derivative ameliorate IMQ-induced psoriasis-like skin inflammation in mice by inhibiting MMP9 and MAPK pathway.

Psoriasis is a chronic immune-mediated inflammatory skin disease that involves dysregulated proliferation of keratinocytes. Psoriatic skin lesions are characterized by redness, thickness, and scaling. The interleukin axis of IL-23/IL-17 is critically involved in the development of human psoriasis. Imiquimod (IMQ), an agonist of TLR7 is known to induce psoriatic-like skin inflammation in mice. The topical application of IMQ induces systemic inflammation with increased proinflammatory cytokines in serum and secondary lymphoid organs. Further, matrix metalloproteases (MMPs) have been implicated in the pathophysiology of psoriatic-like skin inflammation. The increased MMP9 activity and gene expression of proinflammatory cytokines in IMQ-induced psoriatic skin is mediated by the activation of the MAPK pathway. Moreover, the increased expression of neutrophil-specific chemokines confirmed the infiltration of neutrophils at the site of psoriatic skin inflammation. In contrast, expression of IL-10, an anti-inflammatory cytokine gene expression is reduced in IMQ-treated mice skin. Topical application of unconjugated bilirubin (UCB) and its derivative dimethyl ester of bilirubin (BD1) on IMQ-induced psoriatic mice skin significantly mitigated the symptoms of psoriasis by inhibiting the activity of MMP9. Further, UCB and BD1 reduced neutrophil infiltration as evidenced by decreased myeloperoxidase (MPO) activity and reduced gene expression of proinflammatory cytokines, and neutrophil-specific chemokines. Apart from these modulations UCB and BD1 reduced MAPK phosphorylation and upregulated anti-inflammatory cytokines. To conclude, UCB and BD1 immunomodulated the psoriatic skin inflammation induced by IMQ in mice by inhibiting neutrophil mediated MMP9, decreased proinflammatory cytokines gene expression and modulating the MAPK pathway.

Exploring the artificial intelligence and machine learning models in the context of drug design difficulties and future potential for the pharmaceutical sectors.

Artificial intelligence (AI), particularly deep learning as a subcategory of AI, provides opportunities to accelerate and improve the process of discovering and developing new drugs. The use of AI in drug discovery is still in its early stages, but it has the potential to revolutionize the way new drugs are discovered and developed. As AI technology continues to evolve, it is likely that AI will play an even greater role in the future of drug discovery. AI is used to identify new drug targets, design new molecules, and predict the efficacy and safety of potential drugs. The inclusion of AI in drug discovery can screen millions of compounds in a matter of hours, identifying potential drug candidates that would have taken years to find using traditional methods. AI is highly utilized in the pharmaceutical industry by optimizing processes, reducing waste, and ensuring quality control. This review covers much-needed topics, including the different types of machine-learning techniques, their applications in drug discovery, and the challenges and limitations of using machine learning in this field. The state-of-the-art of AI-assisted pharmaceutical discovery is described, covering applications in structure and ligand-based virtual screening, de novo drug creation, prediction of physicochemical and pharmacokinetic properties, drug repurposing, and related topics. Finally, many obstacles and limits of present approaches are outlined, with an eye on potential future avenues for AI-assisted drug discovery and design.

Transcriptional regulatory mechanisms and signaling networks in cancer.

Cancer is a general term that refers to a wide range of illnesses that are characterized by the development of aberrant cells that have the capacity to divide uncontrollably, invade, and harm healthy tissue. It is caused by both genetic and epigenetic changes that suppress abnormal proliferation and prevent cells from surviving outside of their normal niches. Complex protein networks are responsible for the development of a suitable environment via multiple cells signaling pathways. The study of these pathways is essential for analysing network context and developing novel cancer therapies. Transcription factors (TFs) are actively involved in gene expression and maintain the combinatorial on-and-off states of the gene. In addition, the TFs regulate cell identity and state; these TFs cooperate to establish cell-type-specific gene expression. In this chapter, we describe the number of transcription factors and their role in the progression of cancer. The knowledge of transcriptional factors and their network is crucial for emphasizing the specific transcriptional addiction and for designing new anticancer therapies.

Effect of incubation period on the glycosylated protein content in germinated and ungerminated seeds of mung bean (Vigna radiata (L.) Wilczek).

The effects of different incubation periods on the contents of amino acids, proteins, glycosylated proteins and metabolites in germinated and ungerminated mung bean seeds were investigated in this study. The study employs soaking of mung bean seeds in water under laboratory conditions at 28 °C for 3, 6, and 9 h, followed by germination for 12, 24, 36, and 48 h. Seeds collected from different period of imbibition and germination were subjected to total protein extraction for phytochemical analysis. Germination of the seeds was found to be most successful after 6 h of soaking (rather than 9 h of incubation). Hence, seeds imbibed for 6 h were further investigated for germination at 28 °C for 12, 24, 36, and 48 h. Total protein was extracted from both imbibed and germinated seeds, followed by trypsin digestion. Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based peptide mass fingerprinting revealed 38 proteins in 6 h water-imbibed seeds and 50 proteins in 24 h germinated seeds. Among these, 16 were identified as glycosylated proteins and the maximum number of glycosylated proteins were detected in 6 h water-imbibed seeds and 24 h germinated seeds. Moreover, High Performance Liquid Chromatography (HPLC) was used to quantify amino acids from the extracted proteins. A total of 15 amino acids were detected, of which eight were essential and the remaining were non-essential; amino acid concentrations increased following 3, 6, and 9 h of imbibition when compared to the control. It was concluded from the study that seeds with 6 h of imbibition and 24 h of germination can be used as potential nutritional source of different amino acids, proteins, glycosylated proteins, and other bioactive metabolites in human diet.

Time-resolved emission spectroscopy to elucidate the functional nature of heat-stable transcription factor.

A 22 kDa protein from Thermus thermophilus is characterised as a DNA binding transcription regulator and its function is established using the fluorescence spectroscopy technique. The steady-state fluorescence spectroscopy result shows significant binding of calf thymus DNA and protein molecule. To confirm, the DNA quenching effect in real-time, a time-resolved emission spectroscopy study was performed and the result shows good agreement with steady-state quenching analysis.

Syringol isolated from Eleusine coracana (L.) Gaertn bran suppresses inflammatory response through the down-regulation of cPLA2, COX-2, IκBα, p38 and MPO signaling in sPLA2 induced mice paw oedema.

Eleusine coracana (L.) Gaertn (E. coracana) is one of the highest consuming food crops in Asia and Africa. E. coracana is a plant with several medicinal values including anti-ulcerative, anti-diabetic, anti-viral and anti-cancer properties. However, the anti-inflammatory property of E. coracana remains to be elucidated. Therefore, the objective of present study was to investigate the potential in isolated molecule from E. coracana via a combination of in vitro, in vivo and in silico methods. In this study, we have isolated, purified and characterized an anti-inflammatory molecule from E. coracana bran extract known as syringol. Purification of syringol was accomplished by combination of GC-MS and RP-HPLC techniques. Syringol significantly inhibited the enzymes activity of sPLA2 (IC50 = 3.00 µg) and 5-LOX (IC50 = 0.325 µg) in vitro. The inhibition is independent of substrate concentration, calcium ion concentration and was irreversible. Syringol interacts with purified sPLA2 enzymes as evidenced by fluorescence and molecular docking studies. Further, the syringol molecule dose dependently inhibited the development of sPLA2 and λ-carrageenan induced edema. Furthermore, syringol decreases the expression of cPLA2, COX-2, IκBα, p38 and MPO in edematous tissues as demonstrated by western blots. These studies revealed that syringol isolated from E. coracana bran may develop as a potent anti-inflammatory molecule.

Identification of a Chlorogenic Ester as a Monoamine Oxidase (MAO-B) Inhibitor by Integrating "Traditional and Machine Learning" Virtual Screening and In Vitro as well as In Vivo Validation: A Lead against Neurodegenerative Disorders?

Parkinson's disease (PD) is the furthermost motor disorder of adult-onset dementia connected to memory and other cognitive abilities. Monoamine oxidases (MAOs) have gained significant attention in recent years owing to their possible therapeutic use against PD. Expression of MAO-B has been found to be elevated in PD patients for increased uptake of dopamine, producing hydrogen peroxide and finally causing neuronal injury. In this work, two new compounds have been identified as leads against MAO-B, and one of those compounds has been validated in vitro and in vivo. From the Protein Data Bank, MAO-B protein structures complexed with selegiline, 6-hydroxy-N-propargyl-1(R)-aminoindan, or a chromen derivative have been selected as templates for shape-based virtual screening (SB-VS) against the Traditional Chinese Medicinal (TCM) natural database. In parallel, using machine learning, a molecular-descriptor-based support vector model (SVM) was prepared and screened. For this purpose, naïve Bayesian, logistic regression, and random forest strategies were employed with the best specific molecular descriptor, which yielded a model with an overall accuracy (Q) of 0.81. Two common hit compounds lead-1 and lead-2 resulting from both shape and SVM screenings were analyzed through molecular docking and molecular dynamics (MD) simulation (200 ns). Also, from trajectory analysis such as molecular mechanics generalized Born surface area (MMGB/SA) and the residual interaction network (RIN) analyzer, both leads were found to bind at the active site with a favorable correlated motion, including domain movements. Lead-2, which is a chlorogenic ester, was synthesized and found to have no cytotoxic effect up to 50 µg/mL on Neuro-2A cells. The significant reactive oxygen species (ROS) scavenging activity by lead-2 could be correlated to its neuroprotective efficacy. Its capacity to inhibit human MAO-B through a competitive mode could be observed. An experimental zebra fish model confirms the neuroprotection by lead-2 by assessing the locomotor activities under malathion influence and treatment of lead-2. Also, histopathology analysis revealed that lead-2 could slow down degeneration in the brain. The present study emphasizes that integrating machine learning in parallel with traditional virtual screening may be useful to identify effective lead compounds for a given target.

Understanding the binding mechanism of succinic acid against phospholipase A2 from bee venom.

Phospholipase A2 (PLA2 ) is responsible for the release of fatty acids from glycerophospholipids. PLA2 is commonly found in mammalian tissues. It is also found in venom from different animals ranging from insects, arachnid, and snakes. The release of arachidonic acid in large amount results in inflammation and pain. Identification of compounds that can inhibit the activity of PLA2 is of large scientific and medicinal interest as these compounds can act as antidotes toward snake bites and bee stings. Among the different compounds that have been tested for inhibition of PLA2 , a secondary metabolite succinic acid is identified to inhibit PLA2 activity. The inhibition was analyzed using an in vitro PLA2 inhibition assay and isothermal titration calorimetry (ITC) studies. The molecular mechanism of the mode of inhibition was studied using molecular docking and simulation studies.

Estrogenic Effect of Scoparia dulcis (Linn) Extract in Mice Uterus and In Silico Molecular Docking Studies of Certain Compounds with Human Estrogen Receptors.

BACKGROUND: Scoparia dulcis Linn. is reported to be used by women of Assam and Arunachal Pradesh in northeast India for treating menstrual disorders. Scoparia dulcis contains compounds that bind with estrogen receptors (ERα and ERß) evidenced by increased PCNA in endometrial epithelium. METHODS: Crude extract was orally administered at the dose of 500 mg/kg body weight/day to the female mice (60-70 days old) in five different groups. Each group containing six females included: (I) cyclic control, (II) cyclic extract treated, (III) Ovariectomized (OVX)-vehicle treated (Control), (IV) OVX-E2 treated (V) OVX- extract treated. Extract was administered for eight days to the cyclic groups and three days to the OVX groups. PCNA was detected immunohistochemically in uterine tissues and signals were analyzed by Image J software (NIH, USA). Compounds were separated by GC-MS and identified using NIST. In silico molecular docking studies was performed with human estrogen receptors (ERα and ERß). Molecular dynamics (MD) simulations of the best interacting compound was done using gromacs. RESULTS: The results showed cell proliferation in the uterine endometrium evidenced by PCNA. Two phytocompounds, Octadecanoic acid and methyl stearate showed binding affinity with ERα and ERß. CONCLUSION: Scoparia dulcis contains compounds having binding affinity with ERα and ERß. The present study is the first report on compounds from Scoparia dulcis showing binding affinity with human estrogen receptors which may have biological effect on female reproduction.

Therapeutic Targets and Computational Approaches on Drug Development for COVID-19.

World Health Organization declared coronavirus disease (COVID-19) caused by SARS coronavirus-2 (SARS-CoV-2) as pandemic. Its outbreak started in China in Dec 2019 and rapidly spread all over the world. SARS-CoV-2 has infected more than 800,000 people and caused about 35,000 deaths so far, moreover, no approved drugs are available to treat COVID-19. Several investigations have been carried out to identify potent drugs for COVID-19 based on drug repurposing, potential novel compounds from ligand libraries, natural products, short peptides, and RNAseq analysis. This review is focused on three different aspects; (i) targets for drug design (ii) computational methods to identify lead compounds and (iii) drugs for COVID-19. It also covers the latest literature on various hit molecules proposed by computational methods and experimental techniques.

Recent Trends in Drug Design and Discovery.

INTRODUCTION: Structure-based drug design is a wide area of identification of selective inhibitors of a target of interest. From the time of the availability of three dimensional structure of the drug targets, mostly the proteins, many computational methods had emerged to address the challenges associated with drug design process. Particularly, drug-likeness, druggability of the target protein, specificity, off-target binding, etc., are the important factors to determine the efficacy of new chemical inhibitors. OBJECTIVE: The aim of the present research was to improve the drug design strategies in field of design of novel inhibitors with respect to specific target protein in disease pathology. Recent statistical machine learning methods applied for structural and chemical data analysis had been elaborated in current drug design field. METHODS: As the size of the biological data shows a continuous growth, new computational algorithms and analytical methods are being developed with different objectives. It covers a wide area, from protein structure prediction to drug toxicity prediction. Moreover, the computational methods are available to analyze the structural data of varying types and sizes of which, most of the semi-empirical force field and quantum mechanics based molecular modeling methods showed a proven accuracy towards analysing small structural data sets while statistics based methods such as machine learning, QSAR and other specific data analytics methods are robust for large scale data analysis. RESULTS: In this present study, the background has been reviewed for new drug lead development with respect specific drug targets of interest. Overall approach of both the extreme methods were also used to demonstrate with the plausible outcome. CONCLUSION: In this chapter, we focus on the recent developments in the structure-based drug design using advanced molecular modeling techniques in conjunction with machine learning and other data analytics methods. Natural products based drug discovery is also discussed.

Identification of Potential Inhibitors for Targets Involved in Dengue Fever.

Lethality due to dengue infection is a global threat. Nearly 400 million people are affected every year, which approximately costs 500 million dollars for surveillance and vector control itself. Many investigations on the structure-function relationship of proteins expressed by the dengue virus are being made for more than a decade and had come up with many reports on small molecule drug discovery. In this review, we present a detailed note on viral proteins and their functions as well as the inhibitors discovered/designed so far using experimental and computational methods. Further, the phytoconstituents from medicinal plants, specifically the extract of the papaya leaves, neem and bael, which combat dengue infection via dengue protease, helicase, methyl transferase and polymerase are summarized.

Identification of novel NAD(P)H dehydrogenase [quinone] 1 antagonist using computational approaches.

NAD(P)H: quinone oxidoreductase 1 (NQO1) inhibitors are proved as promising therapeutic agents against cancer. This study is to determine potent NAD(P)H-dependent NQO1 inhibitors with new scaffold. Pharmacophore-based three-dimensional (3D) QSAR model has been built based on 45 NQO1 inhibitors reported in the literature. The structure-function correlation coefficient graph represents the relationship between phase activity and phase predicted activity for training and test sets. A QSAR model statistics shows the excellent correlation of the generated model. Pharmacophore hypothesis (AARR) yielded a statistically significant 3D QSASR model with a correlation coefficient of r2 = 0.99 as well as an excellent predictive power. From the analysis of pharmacophore-based virtual screening using by SPEC database, 4093 hits were obtained and were further filtered using virtual screening filters (HTVS, SP, XP) through structure based molecular docking. Based on glide energy and docking score, seven lead compounds show better binding affinity compared to the co-crystal inhibitor. The results of induced fit docking and prime/MM-GBSA suggest that leads AN-153/J117103 and AT-138/KB09997 binding with the catalytic site. Further, to understanding the stability of identified lead compounds MD simulations were done. The lead AN-153/J117103 showed the strong binding stable of the protein-ligand complex. Also the computed drug likeness reveals potential of this compound to treat cancer. AbbreviationsNQO1NAD(P)H-quinine oxidoreductase 1CPHcommon pharmacophore hypothesisPLSpartial least squireHBDhydrogen bond donorSDstandard deviationXPextra precisionIFDinduced fit dockingMM-GBSAmolecular mechanics generalized born surface areaMDSmolecular dynamics simulationRMSDroot mean square deviationRMSFroot mean square fluctuationRMSEroot mean square errorADMEabsorption distribution metabolism excretionsCommunicated by Ramaswamy H. Sarma.

In vitro DNA binding activity and molecular docking reveals pierisin-5 as an anti-proliferative agent against gastric cancer.

Pierisin-5 is a DNA dependent ADP ribosyltransferase (ADRT) protein from the larvae of Indian cabbage white butterfly, Pieris canidia. Interestingly, Pierisin-5 ADP-ribosylates the DNA as a substrate, but not the protein and subsequently persuades apoptotic cell death in human cancer cells. This has led to the investigation on the DNA binding activity of Pierisin-5 using in vitro and in silico approaches in the present study. However, both the structure and the mechanism of ADP-ribosylation of pierisin-5 are unknown. In silico modeled structure of the N-terminal ADRT catalytic domain interacted with the minor groove of B-DNA for ribosylation with the help of ß-NAD+ which lead to a structural modification in DNA (DNA adduct). The possible interaction between calf thymus DNA (CT-DNA) and purified pierisin-5 protein was studied through spectral-spatial studies and the blue shift and hyperchromism in the UV-Visible spectra was observed. The DNA adduct property of pierisin-5 protein was validated by in vitro cytotoxic assay on human gastric (AGS) cancer cell lines. Our study is the first report of the mechanism of DNA binding property of pierisin-5 protein which leads to the induction of cytotoxicity and apoptotic cell death against cancer cell lines.Communicated by Ramaswamy H. Sarma.

Combinatorial inhibition of Angiotensin converting enzyme, Neutral endopeptidase and Aminopeptidase N by N-methylated peptides alleviates blood pressure and fibrosis in rat model of dexamethasone-induced hypertension.

Angiotensin converting enzyme (ACE), neutral endopeptidase (NEP) and aminopeptidase N (APN) are responsible for generation of vasoactive peptides that regulates vasoconstriction, vasodilation and natriuresis, which altogether regulate blood pressure. Cumulative inhibition of ACE, NEP and APN effectively blocks the progression of respective pathways. In this study, N-methylated peptide inhibitors F-N(Me)H-L, V-N(Me)F-R and R-N(Me)V-Y were synthesized against ACE, NEP and APN respectively, using their respective physiological substrates. F-N(Me)H-L inhibited ACE activity with an IC50 of 83 nmol/L, V-N(Me)F-R inhibited NEP activity with an IC50 of 1.173 µmol/L and R-N(Me)V-Y inhibited APN activity with an IC50 of 3.94 nmol/L respectively. Further, the anti-hypertensive effect of N-methylated peptides was evaluated using rat model of dexamethasone-induced hypertension. Individual peptides and their cocktail treatment were started from day 6 of the study period and blood pressure was measured on every alternate day during 15 day study. Administration of F-N(Me)H-L (138 ± 3 mmHg) and cocktail of all the three peptides at a dose of 100 mg/kg significantly reduced systolic blood pressure (SBP) compared to dexamethasone group (SBP of Groups-dexamethasone; (167 ± 5 mmHg), F-N(Me)H-L (138 ± 3 mmHg), and Cocktail (122 ± 3 mmHg). Anti-hypertensive, anti-hypertrophic and anti-fibrotic effects of N-methylated peptides and cocktail was further reflected by the decreased levels of circulating Ang II and increased ANP levels in sera of hypertensive rats along with decrease in collagen deposition in heart and kidney. Though, ACE inhibition is adequate to reduce SBP, targeting NEP and APN along with ACE is beneficial in tackling hypertension and associated fibrosis of heart.

Crystal structures and Hirshfeld surface analyses of 4,4'-{[1,3-phenyl-enebis(methyl-ene)]bis-(-oxy)}bis-(3-meth-oxy-benzaldehyde) and 4,4'-{[(1,4-phenyl-ene-bis(methyl-ene)]bis-(-oxy)}bis-(3-meth-oxy-benzalde-hyde).

The title compounds, C24H22O6 (I) and C24H22O6 (II), each crystallize with half a mol-ecule in the asymmetric unit. The whole mol-ecule of compound (I) is generated by twofold rotation symmetry, the twofold axis bis-ecting the central benzene ring. The whole mol-ecule of compound (II) is generated by inversion symmetry, the central benzene ring being located on an inversion center. In (I), the outer benzene rings are inclined to each other by 59.96 (10)° and by 36.74 (9)° to the central benzene ring. The corresponding dihedral angles in (II) are 0.0 and 89.87 (12)°. In the crystal of (I), mol-ecules are linked by C-H⋯O hydrogen bonds and C-H⋯π inter-actions, forming ribbons propagating along the [10] direction. In the crystal of (II), mol-ecules are linked by C-H⋯O hydrogen bonds, forming a supra-molecular framework. The Hirshfeld surface analyses indicate that for both compounds the H⋯H contacts are the most significant, followed by O⋯H/H⋯O and C⋯H/H⋯C contacts.

Molecular insights into substrate binding mechanism of undecaprenyl pyrophosphate with membrane integrated phosphatidyl glycerophosphate phosphatase B (PgpB) using molecular dynamics simulation approach.

Undecaprenyl phosphate (C55-P) acts as carrier lipid in the synthesis of peptidoglycan, which is de novo synthesized from dephosphorylation of undecaprenyl pyrophosphate (C55-PP). The phosphatidylglycerol phosphate phosphatase B (PgpB) catalyzes the dephosphorylation of C55-PP and forms C55-P. As no structural study has been made regarding the binding of C55-PP to PgpB, in the current study, in silico molecular docking, followed by 150 ns molecular dynamics simulation of the putative binding complex in membrane/solvent environment has been performed to understand conformational dynamics. Results are compared with simulated apo form and PE inhibitor-bound form. Analysis of correlated residual fluctuation network in apo form, C55-PP bound and PE inhibitor-bound form suggests that difference in dynamic coupling between TM domain and α2 and α3 helix of periplasmic domain provides ligand binding to facilitate catalysis or to show inhibitory activity. Distance distribution in catalytic residual pair, H207-R104; H207-R201 and H207-D211 which stabilizes phosphate-enzyme intermediate shows a narrow peak in 2.4-3.6 Å in substrate-bound compared to apo form. Binding interactions and binding free energy analyses complement the partial inhibition of PE where PE has less binding free energy compared to the C55-PP substrate as well as the difference in binding interaction with catalytic pocket. Thus, the present study provides how substrate binding couples the movement in TM domain and periplasmic domain which might help in the understanding of active site communication in PgpB. C55-PP phosphatase interactions with a catalytic pocket of PgpB provide new insight for designing drugs against bacterial infection.

Inhibitory effects of ascorbic acid toward snake venom metalloproteinase (SVMP) from Indian Echis carinatus venom: Insights from molecular modeling and binding studies.

Classical antivenom therapy is unable to shield complications of viper bite and has limitations such as anaphylaxis and serum sickness. Snake venom metalloproteinases are responsible for local tissue damage and hemorrhage at the bitten site in viper envenomation, and this has led to a persistent search for metalloproteinase inhibitors. Here, we report the inhibitory effects of ascorbic acid against metalloproteinase from Echis carinatus venom both in-silico and in-vitro. Ascorbic acid effectively inhibited the proteolytic activity of E. carinatus venom in a dose-dependent manner. Interaction studies of ascorbic acid with purified ecarin using isothermal titration calorimetry showed favorable binding energy and energetics. The molecular docking of ascorbic acid with ecarin revealed important interactions with residues at the active site pocket of ecarin. It was observed that the ligand behaves as a chelating inhibitor. Thus, the backbone structural scaffold of ascorbic acid can find potential use as building blocks in designing drug-like molecules for viper bite management.