Insights into the mutation-induced HHH syndrome from modeling human mitochondrial ornithine transporter-1

Late onset hyperornithinemia, hyperammonemia, and homocitrullinuria syndrome, presenting as recurrent metabolic encephalopathy, A case report

Introduction

and importance: Hyperornithinemia, hyperammonemia, and homocitrullinuria (HHH) syndrome (OMIM 238970) seems to be an autosomal recessive disorder caused by a mitochondrial ornithine transporter 1 deficiency, which results in urea cycle dysfunction. HHH is the most uncommon of the urea cycle diseases, with less than 100 cases recorded.

Case presentation

A previously healthy 29 year old male presented to the emergency department complaining of decreased level of consciousness. CT scan, Cerebro-spinal-fluid analysis and toxicology screen were non-significant. Extended serum analysis showed elevated levels of ammonia. Urgent amino acid level analysis showed elevated ornithine. Follow up genetic testing showed that the patient is homozygous for the mutation c.44delG in exon 3 of SLC25A15 gene.

Clinical discussion

In this case, HHH syndrome presented as a late-onset metabolic encephalopathy. For diagnosis; elevated levels of ammonia, ornithine accompanied by the abovementioned genetic mutation confirms the diagnosis. Treatment focuses on reduction of the ammonia levels using sodium benzoat, citrulline or arginine, and low protein diet.

Conclusions

HHH syndrome, which is a urea cycle disorder, can present as a late-onset metabolic encephalopathy. High suspicion for genetic causes of metabolic encephalopathy should be maintained even for older patients without prior diagnosis in childhood/adolescence.

Successful liver transplantation in hyperornithinemia-hyperammonemia-homocitrullinuria syndrome: Case report

BACKGROUND

HHH syndrome is a rare autosomal recessive disorder of the urea cycle, caused by a deficient mitochondrial ornithine transporter. We report the first successful liver transplantation in HHH syndrome performed in a seven-year-old boy. The patient presented at 4 weeks of age with hyperammonemic coma. The plasma amino acid profile was suggestive of HHH syndrome, and the diagnosis was confirmed when sequencing of the SLC25A15 gene identified two mutations p.R275Q and p.A76D. Although immediate intervention resulted in normalization of plasma ammonia levels within 24 hours, he developed cerebral edema, coma, convulsions, and subsequent neurological sequelae. Metabolic control was difficult requiring severe protein restriction and continued treatment with sodium benzoate and L-arginine. Despite substantial developmental delay, he was referred to our center for liver transplantation because of poor metabolic control. Following cadaveric split liver transplantation, there was complete normalization of his plasma ammonia and plasma amino acid levels under a normal protein-containing diet. This excellent metabolic control was associated with a markedly improved general condition, mood and behavior, and small developmental achievements. Twelve years after liver transplantation, the patient has a stable cognitive impairment without progression of spastic diplegia.

CONCLUSION

This first case of liver transplantation in HHH syndrome demonstrates that this procedure is a therapeutic option for HHH patients with difficult metabolic control.

Molecular Docking and Dynamics Simulation Analysis of Thymoquinone and Thymol Compounds from Nigella sativa L. that Inhibit Cag A and Vac A Oncoprotein of Helicobacter pylori: Probable Treatment of H. pylori Infections

BACKGROUND

Helicobacter pylori infection is accountable for most of the peptic ulcer and intestinal cancers. Due to the uprising resistance towards H. pylori infection through the present and common proton pump inhibitors regimens, the investigation of novel candidates is the inevitable issue. Medicinal plants have always been a source of lead compounds for drug discovery. The research of the related effective enzymes linked with this gram-negative bacterium is critical for the discovery of novel drug targets.

OBJECTIVE

The aim of the study is to identify the best candidate to evaluate the inhibitory effect of thymoquinone and thymol against H. pylori oncoproteins, Cag A and Vac A in comparison to the standard drug, metronidazole by using a computational approach.

MATERIALS AND METHODS

The targeted oncoproteins, Cag A and Vac A were retrieved from RCSB PDB. Lipinski's rule and ADMET toxicity profiling were carried out on the phytoconstituents of the N. sativa. The two compounds of N. sativa were further analyzed by molecular docking and MD simulation studies. The reported phytoconstituents, thymoquinone and thymol present in N. sativa were docked with H. pylori Cag A and Vac A oncoproteins. Structures of ligands were prepared using ChemDraw Ultra 10 software and then changed into their 3D PDB structures using Molinspiration followed by energy minimization by using software Discovery Studio client 2.5.

RESULTS

The docking results revealed the promising inhibitory potential of thymoquinone against Cag A and Vac A with docking energy of -5.81 kcal/mole and -3.61kcal/mole, respectively. On the contrary, the inhibitory potential of thymol against Cag A and Vac A in terms of docking energy was -5.37 kcal/mole and -3.94kcal/mole as compared to the standard drug, metronidazole having docking energy of -4.87 kcal/mole and -3.20 kcal/mole, respectively. Further, molecular dynamic simulations were conducted for 5ns for optimization, flexibility prediction, and determination of folded Cag A and Vac A oncoproteins stability. The Cag A and Vac A oncoproteins-TQ complexes were found to be quite stable with the root mean square deviation value of 0.2nm.

CONCLUSION

The computational approaches suggested that thymoquinone and thymol may play an effective pharmacological role to treat H. pylori infection. Hence, it could be summarized that the ligands thymoquinone and thymol bound and interacted well with the proteins Cag A and Vac A as compared to the ligand MTZ. Our study showed that all lead compounds had good interaction with Cag A and Vac A proteins and suggested them to be a useful target to inhibit H. pylori infection.

Plant systemic acquired resistance compound salicylic acid as a potent inhibitor against SCF (SKP1-CUL1-F-box protein) mediated complex in Fusarium oxysporum by homology modeling and molecular dynamics simulations

Fusarium oxysporum causes significant economic losses in many crop plants by causing root rot, necrosis, and wilting symptoms. Homology and molecular dynamics studies are promising tools for the detection in F. oxysporum of the systemic resistance compound, salicylic acid, for control of the SKP1-CUL1-F-box protein complex. The structure of SKP1-CUL1-F-box subunit Skp1 from F. oxysporum is produced by Modeler 9v7 for the conduct of docking studies. The Skp1 structure is based on the yeast Cdc4/Skp1 (PDB ID: 3MKS A) crystal structure collected by the Protein data bank. Applying molecular dynamic model simulation methods to the final predicted structure and further evaluated by 3D and PROCHECK test programmers, the final model is verified to be accurate. Applying GOLD 3.0.1, SCF Complex Skp1 is used to prevent stress-tolerant operation. The SKP1-CUL1-F-box model is predicted to be stabilized and tested as a stable docking structure. The predicted model of the SCF structure has been stabilized and confirmed to be a reliable structure for docking studies. The results indicated that GLN8, LYS9, VAL10, TRP11, GLU48, ASN49 in SCF complex are important determinant residues in binding as they have strong hydrogen bonding with salicylic acid, which showed best docking results with SKP1-CUL1-F-box complex subunit Skp1 with docking score 25.25KJ/mol. Insilco studies have been used to determine the mode of action of salicylic acid for Fusarium control. Salicylic acid hinders the SKP1-CUL1-F-box complex, which is important in protein-like interactions through hydrogen bodings. Results from docking studies have shown that the best energy for SKP1-CUL1-F-box was salicylic acid.Communicated by Ramaswamy H. Sarma.

In Silico Design, Synthesis and Evaluation of Novel Series of Benzothiazole- Based Pyrazolidinediones as Potent Hypoglycemic Agents

Background:

The discovery of novel ligand binding domain (LBD) of peroxisome proliferator- activated receptor γ (PPARγ) has recently attracted attention to few research groups in order to develop more potent and safer antidiabetic agents.

Objective:

This study is focused on docking-based design and synthesis of novel compounds combining benzothiazole and pyrazolidinedione scaffold as potential antidiabetic agents.

Methods:

Several benzothiazole-pyrazolidinedione hybrids were synthesized and tested for their in vivo anti-hyperglycemic activity. Interactions profile of title compounds against PPARγ was examined through molecular modelling approach.

Results:

All tested compounds exhibited anti-hyperglycemic activity similar or superior to the reference drug Rosiglitazone. Introducing chlorine atom and alkyl group at position-6 and -5 respectively on benzothiazole core resulted in enhancing the anti-hyperglycemic effect. Docking study revealed that such groups demonstrated favorable hydrophobic interactions with novel LBD Ω- pocket of PPARγ protein.

Conclusion:

Among the tested compounds, N-(6-chloro-5-methylbenzo[d]thiazol-2-yl-4-(4((3,5- dioxopyrazolidin-4-ylidene)methyl)phenoxy)butanamide 5b was found to be the most potent compound and provided valuable insights to further develop novel hybrids as anti-hyperglycemic agents.

Application of Machine Learning Approaches for the Design and Study of Anticancer Drugs

BACKGROUND

Globally the number of cancer patients and deaths are continuing to increase yearly, and cancer has, therefore, become one of the world's highest causes of morbidity and mortality. In recent years, the study of anticancer drugs has become one of the most popular medical topics.

OBJECTIVE

In this review, in order to study the application of machine learning in predicting anticancer drugs activity, some machine learning approaches such as Linear Discriminant Analysis (LDA), Principal components analysis (PCA), Support Vector Machine (SVM), Random forest (RF), k-Nearest Neighbor (kNN), and Naïve Bayes (NB) were selected, and the examples of their applications in anticancer drugs design are listed.

RESULTS

Machine learning contributes a lot to anticancer drugs design and helps researchers by saving time and is cost effective. However, it can only be an assisting tool for drug design.

CONCLUSION

This paper introduces the application of machine learning approaches in anticancer drug design. Many examples of success in identification and prediction in the area of anticancer drugs activity prediction are discussed, and the anticancer drugs research is still in active progress. Moreover, the merits of some web servers related to anticancer drugs are mentioned.

The Cooperative Effect between Polybasic Region (PBR) and Polysialyltransferase Domain (PSTD) within Tumor-Target Polysialyltranseferase ST8Sia II

ST8Sia II (STX) is a highly homologous mammalian polysialyltransferase (polyST), which is a validated tumor-target in the treatment of cancer metastasis reliant on tumor cell polysialylation. PolyST catalyzes the synthesis of α2,8-polysialic acid (polySia) glycans by carrying out the activated CMP-Neu5Ac (Sia) to N- and O-linked oligosaccharide chains on acceptor glycoproteins. In this review article, we summarized the recent studies about intrinsic correlation of two polybasic domains, Polysialyltransferase domain (PSTD) and Polybasic region (PBR) within ST8Sia II molecule, and suggested that the critical amino acid residues within the PSTD and PBR motifs of ST8Sia II for polysialylation of Neural cell adhesion molecules (NCAM) are related to ST8Sia II activity. In addition, the conformational changes of the PSTD domain due to point mutations in the PBR or PSTD domain verified an intramolecular interaction between the PBR and the PSTD. These findings have been incorporated into Zhou's NCAM polysialylation/cell migration model, which will provide new perspectives on drug research and development related to the tumor-target ST8Sia II.

A Possible Modulation Mechanism of Intramolecular and Intermolecular Interactions for NCAM Polysialylation and Cell Migration

Polysialic acid (polySia) is a novel glycan that posttranslationally modifies neural cell adhesion molecules (NCAMs) in mammalian cells. Up-regulation of polySia-NCAM expression or NCAM polysialylation is associated with tumor cell migration and progression in many metastatic cancers and neurocognition. It has been known that two highly homologous mammalian polysialyltransferases (polySTs), ST8Sia II (STX) and ST8Sia IV (PST), can catalyze polysialylation of NCAM, and two polybasic domains, polybasic region (PBR) and polysialyltransferase domain (PSTD) in polySTs play key roles in affecting polyST activity or NCAM polysialylation. However, the molecular mechanisms of NCAM polysialylation and cell migration are still not entirely clear. In this minireview, the recent research results about the intermolecular interactions between the PBR and NCAM, the PSTD and cytidine monophosphate-sialic acid (CMP-Sia), the PSTD and polySia, and as well as the intramolecular interaction between the PBR and the PSTD within the polyST, are summarized. Based on these cooperative interactions, we have built a novel model of NCAM polysialylation and cell migration mechanisms, which may be helpful to design and develop new polysialyltransferase inhibitors.

Metabolism of Oxalate in Humans: A Potential Role Kynurenine Aminotransferase/Glutamine Transaminase/Cysteine Conjugate Beta-lyase Plays in Hyperoxaluria

Hyperoxaluria, excessive urinary oxalate excretion, is a significant health problem worldwide. Disrupted oxalate metabolism has been implicated in hyperoxaluria and accordingly, an enzymatic disturbance in oxalate biosynthesis can result in the primary hyperoxaluria. Alanine glyoxylate aminotransferase-1 and glyoxylate reductase, the enzymes involving glyoxylate (precursor for oxalate) metabolism, have been related to primary hyperoxalurias. Some studies suggest that other enzymes such as glycolate oxidase and alanine glyoxylate aminotransferase-2 might be associated with primary hyperoxaluria as well, but evidence of a definitive link is not strong between the clinical cases and gene mutations. There are still some idiopathic hyperoxalurias, which require a further study for the etiologies. Some aminotransferases, particularly kynurenine aminotransferases, can convert glyoxylate to glycine. Based on biochemical and structural characteristics, expression level, subcellular localization of some aminotransferases, a number of them appear able to catalyze the transamination of glyoxylate to glycine more efficiently than alanine glyoxylate aminotransferase-1. The aim of this minireview is to explore other undermining causes of primary hyperoxaluria and stimulate research toward achieving a comprehensive understanding of underlying mechanisms leading to the disease. Herein, we reviewed all aminotransferases in the liver for their functions in glyoxylate metabolism. Particularly, kynurenine aminotransferase-I and III were carefully discussed regarding their biochemical and structural characteristics, cellular localization, and enzyme inhibition. Kynurenine aminotransferase-III is, so far, the most efficient putative mitochondrial enzyme to transaminate glyoxylate to glycine in mammalian livers, might be an interesting enzyme to look over in hyperoxaluria etiology of primary hyperoxaluria and should be carefully investigated for its involvement in oxalate metabolism.

Exploration of synthetic multifunctional amides as new therapeutic agents for Alzheimer's disease through enzyme inhibition, chemoinformatic properties, molecular docking and dynamic simulation insights

A new series of multifunctional amides has been synthesized having moderate enzyme inhibitory potentials and mild cytotoxicity. 2-Furyl(1-piperazinyl)methanone (1) was coupled with 3,5-dichloro-2-hydroxybenzenesulfonyl chloride (2) to form {4-[(3,5-dichloro-2-hydroxyphenyl)sulfonyl]-1-piperazinyl}(2-furyl)methanone (3). Different elecrophiles were synthesized by the reaction of various un/substituted anilines (4a-o) with 2-bromoacetylbromide (5), 2‑bromo‑N-(un/substituted-phenyl)acetamides (6a-o). Further, equimolar ratios of 3 and 6a-o were allowed to react in the presence of K₂CO₃ in acetonitrile to form desired multifunctional amides (7a-o). The structural confirmation of all the synthesized compounds was carried out by their EI-MS, IR, ¹H NMR and ¹³C NMR spectral data. Enzyme inhibition activity was performed against acetyl and butyrylcholinestrase enzymes, whereby 7e showed very good activity having IC₅₀ value of 5.54 ± 0.03 and 9.15 ± 0.01 μM, respectively, relative to eserine, a reference standard. Hemolytic activity of the molecules was checked to asertain their cytotoxicity towards red blood cell membrance and it was observed that most of the compounds were not toxic up to certain range. Moreover, chemoinformatic protepties and docking simulation results also showed the significance of 7e as compared to other compounds. Based on in vitro and in silico analysis 7e could be used as a template for the development of new drugs against Alzheimer's disease.

Electroactive Mg2+-Hydroxyapatite Nanostructured Networks against Drug-Resistant Bone Infection Strains

Surface colonization competition between bacteria and host cells is one of the critical factors involved in tissue/implant integration. Current biomaterials are evaluated for their ability both of withstanding favorable responses of host tissue cells and of resisting bacterial contamination. In this work, the antibacterial ability of biocompatible Mg²⁺-substituted nanostructured hydroxyapatite (HA) was investigated. The densities of Staphylococcus aureus, Pseudomonas aeruginosa, and Escherichia coli strains were significantly decreased after culture in the presence of Mg-substituted HA materials in direct correlation with Mg²⁺-Ca²⁺ switch in the HA lattice. It was noticed that this decrease was accompanied by a minimal alteration of bacterial environments; therefore, the Mg²⁺-HA antibacterial effect was associated with the material surface topography and it electroactive behavior. It was observed that 2.23 wt % Mg²⁺-HA samples exhibited the best antibacterial performance; it decreased 2-fold the initial population of E. coli, P. aeruginosa, and S. aureus at the intermediate concentration (50 mg mL^-1 of broth). Our results reinforce the potential of Mg-HA nanostructured materials to be used in antibacterial coatings for implantable devices and/or medicinal materials to prevent bone infection and to promote wound healing.

Structural insights of dipeptidyl peptidase-IV inhibitors through molecular dynamics-guided receptor-dependent 4D-QSAR studies

Dipeptidyl peptidase-IV (DPP-IV) inhibitors are promising antidiabetic agents. Currently, several DPP-IV inhibitors have been approved for therapeutic use in diabetes mellitus. Receptor-dependent 4D-QSAR is comparatively a new approach which uses molecular dynamics simulations to generate conformational ensemble profiles of compounds representing a dynamic state of compounds at a target's binding site. This work describes a receptor-dependent 4D-QSAR study on triazolopiperazine derivatives. QSARINS multiple linear regression method was adopted to generate 4D-QSAR models. A model with 9 variables was found to have better predictive accuracy with [Formula: see text], [Formula: see text] (leave-one-out) = 0.592 and [Formula: see text] predicted = 0.597. The location of these 9 variables at the binding site of DPP-IV revealed the importance of the residues Val711, Tyr662, Tyr666, Val202, Asp200 and Thr199 in making critical interactions with DPP-IV inhibitors. The study of these critical interactions revealed the structural features required in DPP-IV inhibitors. Thus, in this study the importance of a halogen substituent on a phenyl ring, the extent of substitution on the triazolopiperazine ring, the presence of an ionizable amino group and the presence of a hydrophobic substituent that can bind deeper in binding pocket of DPP-IV were revealed.

Small molecular floribundiquinone B derived from medicinal plants inhibits acetylcholinesterase activity

Being a neurodegenerative disorder, Alzheimer's disease (AD) is the one of the most terrible diseases. And acetylcholinesterase (AChE) is considered as an important target for treating AD. Acetylcholinesterase inhibitors (AChEI) are considered to be one of the effective drugs for the treatment of AD. The aim of this study is to find a novel potential AChEI as a drug for the treatment of AD. In this study, instead of using the synthetic compounds, we used those extracted from plants to investigate the interaction between floribundiquinone B (FB) and AChE by means of both the experimental approach such as fluorescence spectra, ultraviolet-visible (UV-vis) absorption spectrometry, circular dichroism (CD) and the theoretical approaches such as molecular docking. The findings reported here have provided many useful clues and hints for designing more effective and less toxic drugs against Alzheimer's disease.

Ornithine and its role in metabolic diseases: An appraisal

Ornithine is a non-essential amino acid produced as an intermediate molecule in urea cycle. It is a key substrate for the synthesis of proline, polyamines and citrulline. Ornithine also plays an important role in the regulation of several metabolic processes leading to diseases like hyperorithinemia, hyperammonemia, gyrate atrophy and cancer in humans. However, the mechanism of action behind the multi-faceted roles of ornithine is yet to be unraveled completely. Several types of cancers are also characterized by excessive polyamine synthesis from ornithine by different rate limiting enzymes. Hence, in this review we aim to provide extensive insights on potential roles of ornithine in many of the disease related cellular processes and also on the structural features of ornithine interacting proteins, enabling development of therapeutic modalities.

Molecular dynamics and protein interaction studies of lipopeptide (Iturin A) on α- amylase of Spodoptera litura

The small mottled willow moth (Spodoptera litura) is one of the best-known agricultural pest insects. To understand the insecticidal activity, we have selected iturin A compound produced by Bacillus amyloliquefaciens RHNK22 which showed the strongest and most common inhibitory effect on the Spodoptera litura protein. In this work we have identified the action of iturin A on α- amylase is a major digestive enzyme of Spodoptera litura using docking studies. A 3D model of α- amylase from Spodoptera litura was generated using 2HPH as a template with the help of Modeller7v7. With the aid of the molecular mechanics and molecular dynamics methods, the final model is obtained and is further checked by Procheck and Verify 3D graph programs, which showed that the final refined model is reliable. With this model, a adjustable docking study was performed with iturin A using GOLD software. The results indicated that ARG 18, THR15, LEU42 in α- amylase are important determinant residues in binding as they have strong hydrogen bonding interactions with iturin A. These hydrogen binding interactions play an important role for the stability of the complex.

3D pharmacophore-based virtual screening, docking and density functional theory approach towards the discovery of novel human epidermal growth factor receptor-2 (HER2) inhibitors

Human epidermal growth factor receptor 2 (HER2) is one of the four members of the epidermal growth factor receptor (EGFR) family and is expressed to facilitate cellular proliferation across various tissue types. Therapies targeting HER2, which is a transmembrane glycoprotein with tyrosine kinase activity, offer promising prospects especially in breast and gastric/gastroesophageal cancer patients. Persistence of both primary and acquired resistance to various routine drugs/antibodies is a disappointing outcome in the treatment of many HER2 positive cancer patients and is a challenge that requires formulation of new and improved strategies to overcome the same. Identification of novel HER2 inhibitors with improved therapeutics index was performed with a highly correlating (r=0.975) ligand-based pharmacophore model (Hypo1) in this study. Hypo1 was generated from a training set of 22 compounds with HER2 inhibitory activity and this well-validated hypothesis was subsequently used as a 3D query to screen compounds in a total of four databases of which two were natural product databases. Further, these compounds were analyzed for compliance with Veber's drug-likeness rule and optimum ADMET parameters. The selected compounds were then subjected to molecular docking and Density Functional Theory (DFT) analysis to discern their molecular interactions at the active site of HER2. The findings thus presented would be an important starting point towards the development of novel HER2 inhibitors using well-validated computational techniques.

The effect of glycosylation on the transferrin structure: A molecular dynamic simulation analysis

Transferrins have been defined by the highly cooperative binding of iron and a carbonate anion to form a Fe-CO3-Tf ternary complex. As such, the layout of the binding site residues affects transferrin function significantly; In contrast to N-lobe, C-lobe binding site of the transferrin structure has been less characterized and little research which surveyed the interaction of carbonate with transferrin in the C-lobe binding site has been found. In the present work, molecular dynamic simulation was employed to gain access into the molecular level understanding of carbonate binding site and their interactions in each lobe. Residues responsible for carbonate binding of transferrin structure were pointed out. In addition, native human transferrin is a glycoprotein that two N-linked complex glycan chains located in the C-lobe. Usually, in the molecular dynamic simulation for simplifying, glycan is removed from the protein structure. Here, we explore the effect of glycosylation on the transferrin structure. Glycosylation appears to have an effect on the layout of the binding site residue and transferrin structure. On the other hand, sometimes the entire transferrin formed by separated lobes that it allows the results to be interpreted in a straightforward manner rather than more parameters required for full length protein. But, it should be noted that there are differences between the separated lobe and full length transferrin, hence, a comparative analysis by the molecular dynamic simulation was performed to investigate such structural variations. Results revealed that separation in C-lobe caused a significant structural variation in comparison to N-lobe. Consequently, the separated lobes and the full length one are different, showing the importance of the interlobe communication and the impact of the lobes on each other in the transferrin structure.

Identification of Glucose-Binding Pockets in Human Serum Albumin Using Support Vector Machine and Molecular Dynamics Simulations

Human Serum Albumin (HSA) has been suggested to be an alternate biomarker to the existing Hemoglobin-A1c (HbA1c) marker for glycemic monitoring. Development and usage of HSA as an alternate biomarker requires the identification of glycation sites, or equivalently, glucose-binding pockets. In this work, we combine molecular dynamics simulations of HSA and the state-of-art machine learning method Support Vector Machine (SVM) to predict glucose-binding pockets in HSA. SVM uses the three dimensional arrangement of atoms and their chemical properties to predict glucose-binding ability of a pocket. Feature selection reveals that the arrangement of atoms and their chemical properties within the first 4Å from the centroid of the pocket play an important role in the binding of glucose. With a 10-fold cross validation accuracy of 84 percent, our SVM model reveals seven new potential glucose-binding sites in HSA of which two are exposed only during the dynamics of HSA. The predictions are further corroborated using docking studies. These findings can complement studies directed towards the development of HSA as an alternate biomarker for glycemic monitoring.

Heterologous Expression in Yeast of Human Ornithine Carriers ORNT1 and ORNT2 and of ORNT1 Alleles Implicated in HHH Syndrome in Humans

Hyperornithinemia-hyperammonemia-homocitrullinuria (HHH) syndrome is an autosomal recessive metabolic disorder usually presenting in the neonatal period with intermittent episodes of hyperammonemia, psychomotor delay, and progressive encephalopathy. Adult cases usually evolve into frank spastic paraparesis. The syndrome is caused by mutations in SLC25A15/ORNT1 encoding the mitochondrial ornithine transporter; a second ornithine transporter, ORNT2 of unknown function, is also present in most placental mammals. ORNT2 is believed to originate from an ancient retro-transposition event. In yeast Saccharomyces cerevisiae the major function of the transporter (encoded by Arg11) is to shuttle ornithine from the mitochondrial matrix to the cytosol. Its inactivation abolishes growth in the absence of arginine.In this work, we used functional complementation in S. cerevisiae to characterize the function of human ORNT2 and to test the pathogenicity of ORNT1 mutations found in HHH patients. Notably, we found that human ORNT1 but not ORNT2 complements the deletion of the yeast gene, despite their high level of homology. However, we identified some key residues in ORNT2, which may recover its functional competence when replaced with the corresponding residues of ORNT1, suggesting that roles of the two transporters are different. Moreover, we used this system to test a series of missense mutations of ORNT1 identified in patients with HHH syndrome. All mutations had a detrimental effect on the functionality of the human gene, without however clear genotype-phenotype correlations. Our data support yeast as a simple and effective model to validate missense mutations occurring in patients with HHH.

Modelling the molecular mechanism of protein-protein interactions and their inhibition: CypD-p53 case study

Cyclophilin D (CypD) is an important regulatory protein involved in mitochondrial membrane permeability transition and cell death. Further, the mitochondrial CypD-p53 axis is an important contributor to necroptosis, a form of programmed necrosis, involved in various cardiovascular and neurological disorders. The CypD ligand, Cyclosporin A (CsA), was identified as an inhibitor of this interaction. In this study, using computational methods, we have attempted to model the CypD-p53 interaction in order to delineate their mode of binding and also to disclose the molecular mechanism, by means of which CsA interferes with this interaction. It was observed that p53 binds at the CsA-binding site of CypD. The knowledge obtained from this modelling was employed to identify novel CypD inhibitors through structure-based methods. Further, the identified compounds were tested by a similar strategy, adopted during the modelling process. This strategy could be applied to study the mechanism of protein-protein interaction (PPI) inhibition and to identify novel PPI inhibitors.

Pathogenic potential of SLC25A15 mutations assessed by transport assays and complementation of Saccharomyces cerevisiae ORT1 null mutant

HHH syndrome is an autosomal recessive urea cycle disorder caused by alterations in the SLC25A15 gene encoding the mitochondrial ornithine carrier 1, which catalyzes the transport of cytosolic ornithine into the mitochondria in exchange for intramitochondrial citrulline. In this study the functional effects of several SLC25A15 missense mutations p.G27R, p.M37R, p.N74A, p.F188L, p.F188Y, p.S200K, p.R275Q and p.R275K have been tested by transport assays in reconstituted liposomes and complementation of Saccharomyces cerevisiae ORT1 null mutant in arginine-less synthetic complete medium. The HHH syndrome-causing mutations p.G27R, p.M37R, p.F188L and p.R275Q had impaired transport and did not complement ORT1∆ cells (except p.M37R slightly after 5 days in solid medium). The experimentally produced mutations p.N74A, p.S200K and p.R275K exhibited normal or considerable transport activity and complemented ORT1∆ cells after 3 days (p.N74A, p.S200K) or 5 days (p.R275K) incubation. Furthermore, the experimentally produced p.F188Y mutation displayed a substantial transport activity but did not complement the ORT1∆ cells in both liquid and solid media. In view of the disagreement in the results obtained between the two methods, it is recommended that the method of complementing the S. cerevisiae ORT1 knockout strain is used complimentary with the measurement of the catalytic activity, in order to distinguish HHH syndrome-causing mutations from isomorphisms.

QSAR prediction of HIV-1 protease inhibitory activities using docking derived molecular descriptors

In this study, application of a new hybrid docking-quantitative structure activity relationship (QSAR) methodology to model and predict the HIV-1 protease inhibitory activities of a series of newly synthesized chemicals is reported. This hybrid docking-QSAR approach can provide valuable information about the most important chemical and structural features of the ligands that affect their inhibitory activities. Docking studies were used to find the actual conformations of chemicals in active site of HIV-1 protease. Then the molecular descriptors were calculated from these conformations. Multiple linear regression (MLR) and least square support vector machine (LS-SVM) were used as QSAR models, respectively. The obtained results reveal that statistical parameters of the LS-SVM model are better than the MLR model, which indicate that there are some non-linear relations between selected molecular descriptors and anti-HIV activities of interested chemicals. The correlation coefficient (R), root mean square error (RMSE) and average absolute error (AAE) for LS-SVM are: R=0.988, RMSE=0.207 and AAE=0.145 for the training set, and R=0.965, RMSE=0.403 and AAE=0.338 for the test set. Leave one out cross validation test was used for assessment of the predictive power and validity of models which led to cross-validation correlation coefficient QUOTE of 0.864 and 0.850 and standardized predicted relative error sum of squares (SPRESS) of 0.553 and 0.581 for LS-SVM and MLR models, respectively.

Bioassay directed isolation and biological evaluation of compounds isolated from Rubus fairholmianus Gard

The in vitro and in silico analysis of Rubus fairholmianus acetone extract for antioxidant, antiproliferative, and anti-inflammatory activity led to the isolation of six compounds. Amongst all the six isolated compounds tested, 1-(2-hydroxyphenyl)-4-methylpentan-1-one (compound 1) and 2-[(3-methylbutoxy) carbonyl] benzoic acid (compound 2) were found to be more active in inhibiting BRCA and COX target proteins, which also showed the better results for DPPH and ABTS radical scavenging assays. The promising results of this investigation emphasize the importance of using R. fairholmianus in the treatment of radical generated disorders mainly cancer and other inflammatory diseases.

Insights from molecular dynamics simulations: structural basis for the V567D mutation-induced instability of zebrafish alpha-dystroglycan and comparison with the murine model

A missense amino acid mutation of valine to aspartic acid in 567 position of alpha-dystroglycan (DG), identified in dag1-mutated zebrafish, results in a reduced transcription and a complete absence of the protein. Lacking experimental structural data for zebrafish DG domains, the detailed mechanism for the observed mutation-induced destabilization of the DG complex and membrane damage, remained unclear. With the aim to contribute to a better clarification of the structure-function relationships featuring the DG complex, three-dimensional structural models of wild-type and mutant (V567D) C-terminal domain of alpha-DG from zebrafish were constructed by a template-based modelling approach. We then ran extensive molecular dynamics (MD) simulations to reveal the structural and dynamic properties of the C-terminal domain and to evaluate the effect of the single mutation on alpha-DG stability. A comparative study has been also carried out on our previously generated model of murine alpha-DG C-terminal domain including the I591D mutation, which is topologically equivalent to the V567D mutation found in zebrafish. Trajectories from MD simulations were analyzed in detail, revealing extensive structural disorder involving multiple beta-strands in the mutated variant of the zebrafish protein whereas local effects have been detected in the murine protein. A biochemical analysis of the murine alpha-DG mutant I591D confirmed a pronounced instability of the protein. Taken together, the computational and biochemical analysis suggest that the V567D/I591D mutation, belonging to the G beta-strand, plays a key role in inducing a destabilization of the alpha-DG C-terminal Ig-like domain that could possibly affect and propagate to the entire DG complex. The structural features herein identified may be of crucial help to understand the molecular basis of primary dystroglycanopathies.

iNR-Drug: predicting the interaction of drugs with nuclear receptors in cellular networking

Nuclear receptors (NRs) are closely associated with various major diseases such as cancer, diabetes, inflammatory disease, and osteoporosis. Therefore, NRs have become a frequent target for drug development. During the process of developing drugs against these diseases by targeting NRs, we are often facing a problem: Given a NR and chemical compound, can we identify whether they are really in interaction with each other in a cell? To address this problem, a predictor called “iNR-Drug” was developed. In the predictor, the drug compound concerned was formulated by a 256-D (dimensional) vector derived from its molecular fingerprint, and the NR by a 500-D vector formed by incorporating its sequential evolution information and physicochemical features into the general form of pseudo amino acid composition, and the prediction engine was operated by the SVM (support vector machine) algorithm. Compared with the existing prediction methods in this area, iNR-Drug not only can yield a higher success rate, but is also featured by a user-friendly web-server established at http://www.jci-bioinfo.cn/iNR-Drug/, which is particularly useful for most experimental scientists to obtain their desired data in a timely manner. It is anticipated that the iNR-Drug server may become a useful high throughput tool for both basic research and drug development, and that the current approach may be easily extended to study the interactions of drug with other targets as well.

Conformational instability of human prion protein upon residue modification: a molecular dynamics simulation study

Technical strategies like amino acid substitution and residue modification have been widely used to characterize the importance of key amino acids and the role that each residue plays in the structural and functional properties of protein molecules. However, there is no systematic approach to assess the impact of the substituted/modified amino acids on the conformational dynamics of proteins. In this investigation to clarify the effects of residue modifications on the structural dynamics of human prion protein (PrP), a comparative molecular dynamics simulation study on the native and the amino acid-substituted analog at position 208 of PrP has been performed. It is believed that Arginine to Histidine mutation at position 208 is responsible for the structural transition of the native form of human prion protein to the pathogenic isoform causing Creutzfeldt-Jakob disease (CJD). So, three 10 ns molecular dynamics simulations on three model constructs have been performed. Simulation results indicated considerable differences of conformational fluctuations for Alanine substituted construct (PrPALA) and the analog form (PrPSB) comprising the neutralized state of the Arginine residue at position 208 of the human prion protein. According to our data, substitution of the Arginine residue by the uncharged state of this residue induces some reversible structural alterations in the intrinsically flexible loop area including residues 167-171 of PrP. Thus, deprotonation of Arg(208) is a weak perturbation to the structural fluctuations of the protein backbone and the resulting construct behaves almost identical as its native form. Otherwise, Alanine substitution at position 208 imposed an irreversible impact on the secondary and tertiary structure of the protein, which leads to conformational instabilities in the remote hot region comprising residues 190-195 of the C-terminal part of helix 2. Based on the results, it could be deduced that the observed conformational transitions upon Arg(208) to His point mutation, which is the main reason for CJD, may be mainly related to the structural instabilities due to the induced-conformational changes that caused alterations in local/spatial arrangements of the force distributions in the backbone of the human prion protein.

Molecular dynamics studies on the conformational transitions of adenylate kinase: a computational evidence for the conformational selection mechanism

Escherichia coli adenylate kinase (ADK) is a monomeric phosphotransferase enzyme that catalyzes reversible transfer of phosphoryl group from ATP to AMP with a large-scale domain motion. The detailed mechanism for this conformational transition remains unknown. In the current study, we performed long time-scale molecular dynamics simulations on both open and closed states of ADK. Based on the structural analyses of the simulation trajectories, we detected over 20 times conformational transitions between the open and closed states of ADK and identified two novel conformations as intermediate states in the catalytic processes. With these findings, we proposed a possible mechanism for the large-scale domain motion of Escherichia coli ADK and its catalytic process: (1) the substrate free ADK adopted an open conformation; (2) ATP bound with LID domain closure; (3) AMP bound with NMP domain closure; (4) phosphoryl transfer occurred with ATP, and AMP converted into two ADPs, and no conformational transition was detected in the enzyme; (5) LID domain opened with one ADP released; (6) another ADP released with NMP domain open. As both open and closed states sampled a wide range of conformation transitions, our simulation strongly supported the conformational selection mechanism for Escherichia coli ADK.

Find novel dual-agonist drugs for treating type 2 diabetes by means of cheminformatics

The high prevalence of type 2 diabetes mellitus in the world as well as the increasing reports about the adverse side effects of the existing diabetes treatment drugs have made developing new and effective drugs against the disease a very high priority. In this study, we report ten novel compounds found by targeting peroxisome proliferator-activated receptors (PPARs) using virtual screening and core hopping approaches. PPARs have drawn increasing attention for developing novel drugs to treat diabetes due to their unique functions in regulating glucose, lipid, and cholesterol metabolism. The reported compounds are featured with dual functions, and hence belong to the category of dual agonists. Compared with the single PPAR agonists, the dual PPAR agonists, formed by combining the lipid benefit of PPARα agonists (such as fibrates) and the glycemic advantages of the PPARγ agonists (such as thiazolidinediones), are much more powerful in treating diabetes because they can enhance metabolic effects while minimizing the side effects. This was observed in the studies on molecular dynamics simulations, as well as on absorption, distribution, metabolism, and excretion, that these novel dual agonists not only possessed the same function as ragaglitazar (an investigational drug developed by Novo Nordisk for treating type 2 diabetes) did in activating PPARα and PPARγ, but they also had more favorable conformation for binding to the two receptors. Moreover, the residues involved in forming the binding pockets of PPARα and PPARγ among the top ten compounds are explicitly presented, and this will be very useful for the in-depth conduction of mutagenesis experiments. It is anticipated that the ten compounds may become potential drug candidates, or at the very least, the findings reported here may stimulate new strategies or provide useful insights for designing new and more powerful dual-agonist drugs for treating type 2 diabetes.

π-π Stacking mediated drug-drug interactions in human CYP2E1

Because of having many low molecular mass substrates, CYP2E1 is of particular interests to the pharmaceutical industry. Many evidences showed that this enzyme can adopt multiple substrates to significantly reduce the oxidation rate of the substrates. The detailed mechanism for this observation is still unclear. In the current study, we employed GPU-accelerated molecular dynamics simulations to study the multiple-binding mode of human CYP2E1, with an aim of offering a mechanistic explanation for the unexplained multiple-substrate binding. Our results showed that Thr303 and Phe478 were key factors for the substrate recognition and multiple-substrate binding. The former can form a significant hydrogen bond to recognize and position the substrate in the productive binding orientation in the active site. The latter acted as a mediator for the substrate communications via π-π stacking interactions. In the multiple-binding mode, the aforementioned π-π stacking interactions formed by the aromatic rings of both substrates and Phe478 drove the first substrate far away from the catalytic center, orienting in an additional binding position and going against the substrate metabolism. All these findings could give atomic insights into the detailed mechanism for the multiple-substrate binding in human CYP2E1, providing useful information for the drug metabolism mechanism and personalized use of clinical drugs.

Computational design of glutamate dehydrogenase in Bacillus subtilis natto

Bacillus subtilis natto is widely used in industry to produce natto, a traditional and popular Japanese soybean food. However, during its secondary fermentation, high amounts of ammonia are released to give a negative influence on the flavor of natto. Glutamate dehydrogenase (GDH) is a key enzyme for the ammonia produced and released, because it catalyzes the oxidative deamination of glutamate to alpha-ketoglutarate using NAD(+) or NADP(+) as co-factor during carbon and nitrogen metabolism processes. To solve this problem, we employed multiple computational methods model and re-design GDH from Bacillus subtilis natto. Firstly, a structure model of GDH with cofactor NADP(+) was constructed by threading and ab initio modeling. Then the substrate glutamate were flexibly docked into the structure model to form the substrate-binding mode. According to the structural analysis of the substrate-binding mode, Lys80, Lys116, Arg196, Thr200, and Ser351 in the active site were found could form a significant hydrogen bonding network with the substrate, which was thought to play a crucial role in the substrate recognition and position. Thus, these residues were then mutated into other amino acids, and the substrate binding affinities for each mutant were calculated. Finally, three single mutants (K80A, K116Q, and S351A) were found to have significant decrease in the substrate binding affinities, which was further supported by our biochemical experiments.

Ammonium metabolism in humans

Free ammonium ions are produced and consumed during cell metabolism. Glutamine synthetase utilizes free ammonium ions to produce glutamine in the cytosol whereas glutaminase and glutamate dehydrogenase generate free ammonium ions in the mitochondria from glutamine and glutamate, respectively. Ammonia and bicarbonate are condensed in the liver mitochondria to yield carbamoylphosphate initiating the urea cycle, the major mechanism of ammonium removal in humans. Healthy kidney produces ammonium which may be released into the systemic circulation or excreted into the urine depending predominantly on acid-base status, so that metabolic acidosis increases urinary ammonium excretion while metabolic alkalosis induces the opposite effect. Brain and skeletal muscle neither remove nor produce ammonium in normal conditions, but they are able to seize ammonium during hyperammonemia, releasing glutamine. Ammonia in gas phase has been detected in exhaled breath and skin, denoting that these organs may participate in nitrogen elimination. Ammonium homeostasis is profoundly altered in liver failure resulting in hyperammonemia due to the deficient ammonium clearance by the diseased liver and to the development of portal collateral circulation that diverts portal blood with high ammonium content to the systemic blood stream. Although blood ammonium concentration is usually elevated in liver disease, a substantial role of ammonium causing hepatic encephalopathy has not been demonstrated in human clinical studies. Hyperammonemia is also produced in urea cycle disorders and other situations leading to either defective ammonium removal or overproduction of ammonium that overcomes liver clearance capacity. Most diseases resulting in hyperammonemia and cerebral edema are preceded by hyperventilation and respiratory alkalosis of unclear origin that may be caused by the intracellular acidosis occurring in these conditions.

Scaffold-based pan-agonist design for the PPARα, PPARβ and PPARγ receptors

As important members of nuclear receptor superfamily, Peroxisome proliferator-activated receptors (PPAR) play essential roles in regulating cellular differentiation, development, metabolism, and tumorigenesis of higher organisms. The PPAR receptors have 3 identified subtypes: PPARα, PPARβ and PPARγ, all of which have been treated as attractive targets for developing drugs to treat type 2 diabetes. Due to the undesirable side-effects, many PPAR agonists including PPARα/γ and PPARβ/γ dual agonists are stopped by US FDA in the clinical trials. An alternative strategy is to design novel pan-agonist that can simultaneously activate PPARα, PPARβ and PPARγ. Under such an idea, in the current study we adopted the core hopping algorithm and glide docking procedure to generate 7 novel compounds based on a typical PPAR pan-agonist LY465608. It was observed by the docking procedures and molecular dynamics simulations that the compounds generated by the core hopping and glide docking not only possessed the similar functions as the original LY465608 compound to activate PPARα, PPARβ and PPARγ receptors, but also had more favorable conformation for binding to the PPAR receptors. The additional absorption, distribution, metabolism and excretion (ADME) predictions showed that the 7 compounds (especially Cpd#1) hold high potential to be novel lead compounds for the PPAR pan-agonist. Our findings can provide a new strategy or useful insights for designing the effective pan-agonists against the type 2 diabetes.

Computational studies on the substrate interactions of influenza A virus PB2 subunit

Influenza virus, which spreads around the world in seasonal epidemics and leads to large numbers of deaths every year, has several ribonucleoproteins in the central core of the viral particle. These viral ribonucleoproteins can specifically bind the conserved 3' and 5' caps of the viral RNAs with responsibility for replication and transcription of the viral RNA in the nucleus of infected cells. A fundamental question of most importance is that how the cap-binding proteins in the influenza virus discriminates between capped RNAs and non-capped ones. To get an answer, we performed molecular dynamics simulations and free energy calculations on the influenza A virus PB2 subunit, an important component of the RNP complexes, with a cap analog m7GTP. Our calculations showed that some key residues in the active site, such as Arg355, His357, Glu361 as well as Gln406, could offer significant hydrogen bonding and hydrophobic interactions with the guanine ring of the cap analog m7GTP to form an aromatic sandwich mechanism for the cap recognition and positioning in the active site. Subsequently, we applied this idea to a virtual screening procedure and identified 5 potential candidates that might be inhibitors against the PB2 subunit. Interestingly, 2 candidates Cpd1 and Cpd2 have been already reported to have inhibitory activities to the influenza virus cap-binding proteins. Further calculation also showed that they had comparatively higher binding affinities to the PB2 subunit than that of m7GTP. We believed that our findings could give an atomic insight into the deeper understanding of the cap recognition and binding mechanism, providing useful information for searching or designing novel drugs against influenza viruses.

Autoinhibitory mechanism for the mutation-induced impaired FGF9 signaling

Fibroblast growth factor 9 (FGF9), an important member of the fibroblast growth factor (FGF) family, can bind with high affinity to FGFR3 in a heparin-dependent approach. In humans, the deletions and mutations resulting in dysfunction of the FGF9 signaling can cause human skeletal dysplasia and cancers. A mutation (S99N) in this protein has been identified to be associated with significantly impaired FGF signaling considered as a potential cause of synostoses syndrome. However, the detailed mechanism for this observation still remains unknown. In this study, we used molecular dynamics simulations and free energy calculations to study the interactions of FGF9(WT/S99N), FGFR3c, and heparin, with an aim of providing atomic sights into the detailed mechanism for the impaired FGF signaling caused by the S99N mutation. We found that the S99N mutation has a well-ordered C-terminal structure, which can reduce its homodimerization ability so as to break the monomer-dimer equilibrium in the FGF signaling, which is considered as a key factor to regulate extracellular matrix affinity and tissue diffusion in the FGF signaling pathway. The FGF9(WT) monomer can preferentially form a homodimer owing to its comparatively favorable binding free energy. In contrast, the FGF9(S99N) monomer is preferred to bind with the FGFR3c receptor to form an inactive complex, leading to impair FGF signaling. To support our computational findings, we also performed biochemical experiments, which confirm the computational results mentioned above. The impaired FGF signaling is believed to be a potential cause of human synostoses syndrome, implicating an important role for FGF9 in normal joint development.