Structure-function roles of four cysteine residues in the human arsenic (+3 oxidation state) methyltransferase (hAS3MT) by site-directed mutagenesis

Arsenic methylation - Lessons from three decades of research

Between 1990 and 2020, our understanding of the significance of arsenic biomethylation changed in remarkable ways. At the beginning of this period, the conversion of inorganic arsenic into mono- and di-methylated metabolites was viewed primarily as a process that altered the kinetic behavior of arsenic. By increasing the rate of clearance of arsenic, the formation of methylated metabolites reduced exposure to this toxin; that is, methylation was detoxification. By 2020, it was clear that at least some of the toxic effects associated with As exposure depended on formation of methylated metabolites containing trivalent arsenic. Because the trivalent oxidation state of arsenic is associated with increased potency as a cytotoxin and clastogen, these findings were consistent with methylation-related changes in the dynamic behavior of arsenic. That is, methylation was activation. Our current understanding of the role of methylation as a modifier of kinetic and dynamic behaviors of arsenic is the product of research at molecular, cellular, organismic, and population levels. This information provides a basis for refining our estimates of risk associated with long term exposure to inorganic arsenic in environmental media, food, and water. This report summarizes the growth of our knowledge of enzymatically catalyzed methylation of arsenic over this period and considers the prospects for new discoveries.

Origins, fate, and actions of methylated trivalent metabolites of inorganic arsenic: progress and prospects

The toxic metalloid inorganic arsenic (iAs) is widely distributed in the environment. Chronic exposure to iAs from environmental sources has been linked to a variety of human diseases. Methylation of iAs is the primary pathway for metabolism of iAs. In humans, methylation of iAs is catalyzed by arsenic (+ 3 oxidation state) methyltransferase (AS3MT). Conversion of iAs to mono- and di-methylated species (MAs and DMAs) detoxifies iAs by increasing the rate of whole body clearance of arsenic. Interindividual differences in iAs metabolism play key roles in pathogenesis of and susceptibility to a range of disease outcomes associated with iAs exposure. These adverse health effects are in part associated with the production of methylated trivalent arsenic species, methylarsonous acid (MAs^III) and dimethylarsinous acid (DMAs^III), during AS3MT-catalyzed methylation of iAs. The formation of these metabolites activates iAs to unique forms that cause disease initiation and progression. Taken together, the current evidence suggests that methylation of iAs is a pathway for detoxification and for activation of the metalloid. Beyond this general understanding of the consequences of iAs methylation, many questions remain unanswered. Our knowledge of metabolic targets for MAs^III and DMAs^III in human cells and mechanisms for interactions between these arsenicals and targets is incomplete. Development of novel analytical methods for quantitation of MAs^III and DMAs^III in biological samples promises to address some of these gaps. Here, we summarize current knowledge of the enzymatic basis of MAs^III and DMAs^III formation, the toxic actions of these metabolites, and methods available for their detection and quantification in biomatrices. Major knowledge gaps and future research directions are also discussed.

Hydrogen peroxide triggers a novel alternative splicing of arsenic (+3 oxidation state) methyltransferase gene

We previously reported that two splicing variants of human AS3MT mRNA, exon-3 skipping form (Δ3) and exons-4 and -5 skipping form (Δ4,5), were detected in HepG2 cells and that both variants lacked arsenic methylation activity (Sumi et al., 2011). Here we studied whether hydrogen peroxide (H₂O₂) triggers alternative splicing of AS3MT mRNA. The results showed that exposure of HepG2 cells to H₂O₂ resulted in increased levels of a novel spliced form skipping exon-3 to exon-10 (Δ3-10) in an H₂O₂-concentration-dependent manner, although no change was detected in the mRNA levels of Δ3 AS3MT. We found decreased protein levels of serine/arginine-rich 40 (SRp40), which we determined to be a candidate splice factor for controlling the splicing of AS3MT mRNA. We next compared the amounts of methylated arsenic metabolites between control and H₂O₂-exposed HepG2 cells after the addition of arsenite as a substance. The results showed lower levels of methylated arsenic metabolites in HepG2 cells exposed to H₂O₂. These data suggest that the splicing of AS3MT pre-mRNA was disconcerted by oxidative stress and that abnormal alternative splicing of AS3MT mRNA may affect arsenic methylation ability.

CoagVDb: a comprehensive database for coagulation factors and their associated SAPs

The current state of the art in medical genetics is to identify and classify the functional (deleterious) or non-functional (neutral) single amino acid substitutions (SAPs), also known as non-synonymous SNPs (nsSNPs). The primary goal is to elucidate the mechanisms through which functional SAPs exert their effects, and ultimately interrogating this information for association with complex phenotypes. This work focuses on coagulation factors involved in the coagulation cascade pathway which plays a vital role in the maintenance of homeostasis in the human system. We developed an integrated coagulation variation database, CoagVDb, which makes use of the biological information from various public databases such as NCBI, OMIM, UniProt, PDB and SAPs (rsIDs/variant). CoagVDb enriched with computational prediction scores classify SAPs as either deleterious or tolerated. Also, various other properties are incorporated such as amino acid composition, secondary structure elements, solvent accessibility, ordered/disordered regions, conservation, and the presence of disulfide bonds. This specialized database provides integration of various prediction scores from different computational methods along with gene, protein, and disease information. We hope our database will act as a useful reference resource for hematologists to reveal protein structure–function relationship and disease genotype–phenotype correlation.

Identification and catalytic residues of the arsenite methyltransferase from a sulfate-reducing bacterium, Clostridium sp. BXM

Arsenic methylation is an important process frequently occurring in anaerobic environments. Anaerobic microorganisms have been implicated as the major contributors for As methylation. However, very little information is available regarding the enzymatic mechanism of As methylation by anaerobes. In this study, one novel sulfate-reducing bacterium isolate, Clostridium sp. BXM, which was isolated from a paddy soil in our laboratory, was demonstrated to have the ability of methylating As. One putative arsenite S-Adenosyl-Methionine methyltransferase (ArsM) gene, CsarsM was cloned from Clostridium sp. BXM. Heterologous expression of CsarsM conferred As resistance and the ability of methylating As to an As-sensitive strain of Escherichia coli. Purified methyltransferase CsArsM catalyzed the formation of methylated products from arsenite, further confirming its function of As methylation. Site-directed mutagenesis studies demonstrated that three conserved cysteine residues at positions 65, 153 and 203 in CsArsM are necessary for arsenite methylation, but only Cysteine 153 and Cysteine 203 are required for the methylation of monomethylarsenic to dimethylarsenic. These results provided the characterization of arsenic methyltransferase from anaerobic sulfate-reducing bacterium. Given that sulfate-reducing bacteria are ubiquitous in various wetlands including paddy soils, enzymatic methylation mediated by these anaerobes is proposed to contribute to the arsenic biogeochemical cycling.

Pathway of human AS3MT arsenic methylation

A synthetic gene encoding human As(III) S-adenosylmethionine (SAM) methyltransferase (hAS3MT) was expressed, and the purified enzyme was characterized. The synthetic enzyme is considerably more active than a cDNA-expressed enzyme using endogenous reductants thioredoxin (Trx), thioredoxin reductase (TR), NADPH, and reduced glutathione (GSH). Each of the seven cysteines (the four conserved residues, Cys32, Cys61, Cys156, and Cys206, and nonconserved, Cys72, Cys85, and Cys250) was individually changed to serine. The nonconserved cysteine derivates were still active. None of the individual C32S, C61S, C156S, and C206S derivates were able to methylate As(III). However, the C32S and C61S enzymes retained the ability to methylate MAs(III). These observations suggest that Cys156 and Cys206 play a different role in catalysis than that of Cys32 and Cys61. A homology model built on the structure of a thermophilic orthologue indicates that Cys156 and Cys206 form the As(III) binding site, whereas Cys32 and Cys61 form a disulfide bond. Two observations shed light on the pathway of methylation. First, binding assays using the fluorescence of a single-tryptophan derivative indicate that As(GS)₃ binds to the enzyme much faster than inorganic As(III). Second, the major product of the first round of methylation is MAs(III), not MAs(V), and remains enzyme-bound until it is methylated a second time. We propose a new pathway for hAS3MT catalysis that reconciles the hypothesis of Challenger ((1947) Sci. Prog., 35, 396–416) with the pathway proposed by Hayakawa et al. ((2005) Arch. Toxicol., 79, 183–191). The products are the more toxic and more carcinogenic trivalent methylarsenicals, but arsenic undergoes oxidation and reduction as enzyme-bound intermediates.

The functions of crucial cysteine residues in the arsenite methylation catalyzed by recombinant human arsenic (III) methyltransferase

Arsenic (III) methyltransferase (AS3MT) is a cysteine (Cys)-rich enzyme that catalyzes the biomethylation of arsenic. To investigate how these crucial Cys residues promote catalysis, we used matrix-assisted laser desorption ionization-time of flight-mass spectrometry (MALDI-TOF-MS) to analyze Cys residues in recombinant human arsenic (III) methyltransferase (hAS3MT). We detected two disulfide bonds, Cys250-Cys32 and Cys368-Cys369, in hAS3MT. The Cys250-Cys32 disulfide bond was reduced by glutathione (GSH) or other disulfide bond reductants before the enzymatic methylation of arsenite (iAs3+). In addition to exposing residues around the active sites, cleavage of the Cys250-Cys32 pair modulated the conformation of hAS3MT. This adjustment may stabilize the binding of S-Adenosyl-L-methionine (AdoMet) and favor iAs3+ binding to hAS3MT. Additionally, we observed the intermediate of Cys250-S-adenosylhomocysteine (AdoHcy), suggesting that Cys250 is involved in the transmethylation. In recovery experiments, we confirmed that trivalent arsenicals were substrates for hAS3MT, methylation of arsenic occurred on the enzyme, and an intramolecular disulfide bond might be formed after iAs3+ was methylated to dimethylarsinous acid (DMA3+). In this work, we clarified both the functional roles of GSH and the crucial Cys residues in iAs3+ methylation catalyzed by hAS3MT.

Inhibitory mechanism of dimercaptopropanesulfonic acid (DMPS) in the cellular biomethylation of arsenic

Dimercaptopropanesulfonic acid (DMPS) has been approved for the treatment of arsenic poisoning through promoting arsenic excretion and modulating arsenic species. To clarify how DMPS regulates the excretion of arsenic species, we investigated the effects of DMPS on the biomethylation of arsenite (As(3+)) in HepG2 cells. In the experiments, we found that DMPS at low concentrations dramatically decreased the content of arsenic in HepG2 cells and inhibited the cellular methylation of As(3+). Three aspects, the expression of human arsenic (III) methyltransferase (hAS3MT), the accumulation of cellular reactive oxygen species (ROS) and the in vitro enzymatic methylation of arsenic, were considered to explain the reasons for the inhibition of DMPS in arsenic metabolism. The results suggested that DMPS competitively coordinated with As(3+) and monomethylarsonous acid (MMA(3+)) to inhibit the up-regulation of arsenic on the expression of hAS3MT and block arsenic involving in the enzymatic methylation. Moreover, DMPS eliminated arsenic-induced accumulation of ROS, which might contribute to the antidotal effects of DMPS on arsenic posing.

Evolution- and structure-based computational strategy reveals the impact of deleterious missense mutations on MODY 2 (maturity-onset diabetes of the young, type 2)

Heterozygous mutations in the central glycolytic enzyme glucokinase (GCK) can result in an autosomal dominant inherited disease, namely maturity-onset diabetes of the young, type 2 (MODY 2). MODY 2 is characterised by early onset: it usually appears before 25 years of age and presents as a mild form of hyperglycaemia. In recent years, the number of known GCK mutations has markedly increased. As a result, interpreting which mutations cause a disease or confer susceptibility to a disease and characterising these deleterious mutations can be a difficult task in large-scale analyses and may be impossible when using a structural perspective. The laborious and time-consuming nature of the experimental analysis led us to attempt to develop a cost-effective computational pipeline for diabetic research that is based on the fundamentals of protein biophysics and that facilitates our understanding of the relationship between phenotypic effects and evolutionary processes. In this study, we investigate missense mutations in the GCK gene by using a wide array of evolution- and structure-based computational methods, such as SIFT, PolyPhen2, PhD-SNP, SNAP, SNPs&GO, fathmm, and Align GVGD. Based on the computational prediction scores obtained using these methods, three mutations, namely E70K, A188T, and W257R, were identified as highly deleterious on the basis of their effects on protein structure and function. Using the evolutionary conservation predictors Consurf and Scorecons, we further demonstrated that most of the predicted deleterious mutations, including E70K, A188T, and W257R, occur in highly conserved regions of GCK. The effects of the mutations on protein stability were computed using PoPMusic 2.1, I-mutant 3.0, and Dmutant. We also conducted molecular dynamics (MD) simulation analysis through in silico modelling to investigate the conformational differences between the native and the mutant proteins and found that the identified deleterious mutations alter the stability, flexibility, and solvent-accessible surface area of the protein. Furthermore, the functional role of each SNP in GCK was identified and characterised using SNPeffect 4.0, F-SNP, and FASTSNP. We hope that the observed results aid in the identification of disease-associated mutations that affect protein structure and function. Our in silico findings provide a new perspective on the role of GCK mutations in MODY2 from an evolution-based structure-centric point of view. The computational architecture described in this paper can be used to predict the most appropriate disease phenotypes for large-genome sequencing projects and to provide individualised drug therapy for complex diseases such as diabetes.

Identification of the third binding site of arsenic in human arsenic (III) methyltransferase

Arsenic (III) methyltransferase (AS3MT) catalyzes the process of arsenic methylation. Each arsenite (iAs³⁺) binds to three cysteine residues, methylarsenite (MMA³⁺) binds to two, and dimethylarsenite (DMA³⁺) binds to one. However, only two As-binding sites (Cys156 and Cys206) have been confirmed on human AS3MT (hAS3MT). The third As-binding site is still undefined. Residue Cys72 in Cyanidioschyzon merolae arsenite S-adenosylmethyltransferase (CmArsM) may be the third As-binding site. The corresponding residue in hAS3MT is Cys61. Functions of Cys32, Cys61, and Cys85 in hAS3MT are unclear though Cys32, Cys61, and Cys85 in rat AS3MT have no effect on the enzyme activity. This is why the functions of Cys32, Cys61, and Cys85 in hAS3MT merit investigation. Here, three mutants were designed, C32S, C61S, and C85S. Their catalytic activities and conformations were determined, and the catalytic capacities of C156S and C206S were studied. Unlike C85S, mutants C32S and C61S were completely inactive in the methylation of iAs³⁺ and active in the methylation of MMA³⁺. The catalytic activity of C85S was also less pronounced than that of WT-hAS3MT. All these findings suggest that Cys32 and Cys61 markedly influence the catalytic activity of hAS3MT. Cys32 and Cys61 are necessary to the first step of methylation but not to the second. Cys156 and Cys206 are required for both the first and second steps of methylation. The S^C32 is located far from arsenic in the WT-hAS3MT-SAM-As model. The distances between S^C61 and arsenic in WT-hAS3MT-As and WT-hAS3MT-SAM-As models are 7.5 Å and 4.1 Å, respectively. This indicates that SAM-binding to hAS3MT shortens the distance between S^C61 and arsenic and promotes As-binding to hAS3MT. This is consistent with the fact that SAM is the first substrate to bind to hAS3MT and iAs is the second. Model of WT-hAS3MT-SAM-As and the experimental results indicate that Cys61 is the third As-binding site.

Residues in human arsenic (+3 oxidation state) methyltransferase forming potential hydrogen bond network around S-adenosylmethionine

Residues Tyr59, Gly78, Ser79, Met103, Gln107, Ile136 and Glu137 in human arsenic (+3 oxidation state) methyltransferase (hAS3MT) were deduced to form a potential hydrogen bond network around S-adenosylmethionine (SAM) from the sequence alignment between Cyanidioschyzon merolae arsenite S-adenosylmethyltransferase (CmArsM) and hAS3MT. Herein, seven mutants Y59A, G78A, S79A, M103A, Q107A, I136A and E137A were obtained. Their catalytic activities and conformations were characterized and models were built. Y59A and G78A were completely inactive. Only 7.0%, 10.6% and 13.8% inorganic arsenic (iAs) was transformed to monomethylated arsenicals (MMA) when M103A, Q107A and I136A were used as the enzyme. The V_max (the maximal velocity of the reaction) values of M103A, Q107A, I136A and E137A were decreased to 8%, 22%, 15% and 50% of that of WT-hAS3MT, respectively. The K_M(SAM) (the Michaelis constant for SAM) values of mutants M103A, I136A and E137A were 15.7, 8.9 and 5.1 fold higher than that of WT-hAS3MT, respectively, indicating that their affinities for SAM were weakened. The altered microenvironment of SAM and the reduced capacity of binding arsenic deduced from K_M(As) (the Michaelis constant for iAs) value probably synergetically reduced the catalytic activity of Q107A. The catalytic activity of S79A was higher than that of WT despite of the higher K_M(SAM), suggesting that Ser79 did not impact the catalytic activity of hAS3MT. In short, residues Tyr59 and Gly78 significantly influenced the catalytic activity of hAS3MT as well as Met103, Ile136 and Glu137 because they were closely associated with SAM-binding, while residue Gln107 did not affect SAM-binding regardless of affecting the catalytic activity of hAS3MT. Modeling and our experimental results suggest that the adenine ring of SAM is sandwiched between Ile136 and Met103, the amide group of SAM is hydrogen bonded to Gly78 in hAS3MT and SAM is bonded to Tyr59 with van der Waals, cation-π and hydrogen bonding contacts.

Functional evaluation of Asp76, 84, 102 and 150 in human arsenic(III) methyltransferase (hAS3MT) interacting with S-adenosylmethionine

We prepared eight mutants (D76P, D76N, D84P, D84N, D102P, D102N, D150P and D150N) to investigate the functions of residues Asp76, 84, 102 and 150 in human arsenic(III) methyltransferase (hAS3MT) interacting with the S-adenosylmethionine (SAM)-binding. The affinity of all the mutants for SAM were weakened. All the mutants except for D150N completely lost their methylation activities. Residues Asp76, 84, 102 and 150 greatly influenced hAS3MT catalytic activity via affecting SAM-binding or methyl transfer. Asp76 and 84 were located in the SAM-binding pocket, and Asp102 significantly affected SAM-binding via forming hydrogen bonds with SAM.

Comparative oxidation state specific analysis of arsenic species by high-performance liquid chromatography-inductively coupled plasma-mass spectrometry and hydride generation-cryotrapping-atomic absorption spectrometry

The formation of methylarsonous acid (MAs^III) and dimethylarsinous acid (DMAs^III) in the course of inorganic arsenic (iAs) metabolism plays an important role in the adverse effects of chronic exposure to iAs. High-performance liquid chromatography-inductively coupled plasma-mass spectrometry (HPLC-ICP-MS) and hydride generation-cryotrapping-atomic absorption spectrometry (HG-CT-AAS) have been frequently used for the analysis of MAs^III and DMAs^III in biological samples. While HG-CT-AAS has consistently detected MAs^III and DMAs^III, HPLC-ICP-MS analyses have provided inconsistent and contradictory results. This study compares the capacities of both methods to detect and quantify MAs^III and DMAs^III in an in vitro methylation system consisting of recombinant human arsenic (+3 oxidation state) methyltransferase (AS3MT), S-adenosylmethionine as a methyl donor, a non-thiol reductant tris(2-carboxyethyl)phosphine, and arsenite (iAs^III) or MAs^III as substrate. The results show that reversed-phase HPLC-ICP-MS can identify and quantify MAs^III and DMAs^III in aqueous mixtures of biologically relevant arsenical standards. However, HPLC separation of the in vitro methylation mixture resulted in significant losses of MAs^III, and particularly DMAs^III with total arsenic recoveries below 25%. Further analyses showed that MAs^III and DMAs^III bind to AS3MT or interact with other components of the methylation mixture, forming complexes that do not elute from the column. Oxidation of the mixture with H₂O₂ which converted trivalent arsenicals to their pentavalent analogs prior to HPLC separation increased total arsenic recoveries to ~95%. In contrast, HG-CT-AAS analysis found large quantities of methylated trivalent arsenicals in mixtures incubated with either iAs^III or MAs^III and provided high (>72%) arsenic recoveries. These data suggest that an HPLC-based analysis of biological samples can underestimate MAs^III and DMAs^III concentrations and that controlling for arsenic species recovery is essential to avoid artifacts.

Methylation of arsenic by recombinant human wild-type arsenic (+3 oxidation state) methyltransferase and its methionine 287 threonine (M287T) polymorph: Role of glutathione

Arsenic (+3 oxidation state) methyltransferase (AS3MT) is the key enzyme in the pathway for methylation of arsenicals. A common polymorphism in the AS3MT gene that replaces a threonyl residue in position 287 with a methionyl residue (AS3MT/M287T) occurs at a frequency of about 10% among populations worldwide. Here, we compared catalytic properties of recombinant human wild-type (wt) AS3MT and AS3MT/M287T in reaction mixtures containing S-adenosylmethionine, arsenite (iAs(III)) or methylarsonous acid (MAs(III)) as substrates and endogenous or synthetic reductants, including glutathione (GSH), a thioredoxin reductase (TR)/thioredoxin (Trx)/NADPH reducing system, or tris (2-carboxyethyl) phosphine hydrochloride (TCEP). With either TR/Trx/NADPH or TCEP, wtAS3MT or AS3MT/M287T catalyzed conversion of iAs(III) to MAs(III), methylarsonic acid (MAs(V)), dimethylarsinous acid (DMAs(III)), and dimethylarsinic acid (DMAs(V)); MAs(III) was converted to DMAs(III) and DMAs(V). Although neither enzyme required GSH to support methylation of iAs(III) or MAs(III), addition of 1mM GSH decreased K(m) and increased V(max) estimates for either substrate in reaction mixtures containing TR/Trx/NADPH. Without GSH, V(max) and K(m) values were significantly lower for AS3MT/M287T than for wtAS3MT. In the presence of 1mM GSH, significantly more DMAs(III) was produced from iAs(III) in reactions catalyzed by the M287T variant than in wtAS3MT-catalyzed reactions. Thus, 1mM GSH modulates AS3MT activity, increasing both methylation rates and yield of DMAs(III). AS3MT genotype exemplified by differences in regulation of wtAS3MT and AS3MT/M287T-catalyzed reactions by GSH may contribute to differences in the phenotype for arsenic methylation and, ultimately, to differences in the disease susceptibility in individuals chronically exposed to inorganic arsenic.

Rapid equilibrium kinetic analysis of arsenite methylation catalyzed by recombinant human arsenic (+3 oxidation state) methyltransferase (hAS3MT)

In the human body, arsenic is metabolized by methylation. Understanding this process is important and provides insight into the relationship between arsenic and its related diseases. We used the rapid equilibrium kinetic model to study the reaction sequence of arsenite methylation. The results suggest that the mechanism for arsenite methylation is a completely ordered mechanism that is also of general interest in reaction systems with different reductants, such as tris(2-carboxyethyl)phosphine, cysteine, and glutathione. In the reaction, cysteine residues of recombinant human arsenic (+3 oxidation state) methyltransferase (hAS3MT) coordinate with arsenicals and involve the methyl transfer step. S-Adenosyl-l-methionine (AdoMet) is the first-order reactant, which modulates the conformation of hAS3MT to a best matched state by hydrophobic interaction. As the second-order reactant, reductant reduces the disulfide bond, most likely between Cys-250 and another cysteine residue of hAS3MT, and exposes the active site cysteine residues for binding trivalent inorganic arsenic (iAs(3+)) to give monomethylarsonic dicysteine (MADC(3+)). In addition, the reaction can be extended to further methylate MADC(3+) to dimethylarsinic cysteine (DAMC(3+)). In the methylation reaction, the β-pleated sheet content of hAS3MT is increased, and the hydrophobicity of the microenvironment around the active sites is decreased. Similarly, we confirm that both the high β-pleated sheet content of hAS3MT and the high dissociation ability of the enzyme-AdoMet-reductant improve the yield of dimethylated arsenicals.

In silico profiling of deleterious amino acid substitutions of potential pathological importance in haemophlia A and haemophlia B

Background

In this study, instead of current biochemical methods, the effects of deleterious amino acid substitutions in F8 and F9 gene upon protein structure and function were assayed by means of computational methods and information from the databases. Deleterious substitutions of F8 and F9 are responsible for Haemophilia A and Haemophilia B which is the most common genetic disease of coagulation disorders in blood. Yet, distinguishing deleterious variants of F8 and F9 from the massive amount of nonfunctional variants that occur within a single genome is a significant challenge.

Methods

We performed an in silico analysis of deleterious mutations and their protein structure changes in order to analyze the correlation between mutation and disease. Deleterious nsSNPs were categorized based on empirical based and support vector machine based methods to predict the impact on protein functions. Furthermore, we modeled mutant proteins and compared them with the native protein for analysis of protein structure stability.

Results

Out of 510 nsSNPs in F8, 378 nsSNPs (74%) were predicted to be 'intolerant' by SIFT, 371 nsSNPs (73%) were predicted to be 'damaging' by PolyPhen and 445 nsSNPs (87%) as 'less stable' by I-Mutant2.0. In F9, 129 nsSNPs (78%) were predicted to be intolerant by SIFT, 131 nsSNPs (79%) were predicted to be damaging by PolyPhen and 150 nsSNPs (90%) as less stable by I-Mutant2.0. Overall, we found that I-Mutant which emphasizes support vector machine based method outperformed SIFT and PolyPhen in prediction of deleterious nsSNPs in both F8 and F9.

Conclusions

The models built in this work would be appropriate for predicting the deleterious amino acid substitutions and their functions in gene regulation which would be useful for further genotype-phenotype researches as well as the pharmacogenetics studies. These in silico tools, despite being helpful in providing information about the nature of mutations, may also function as a first-pass filter to determine the substitutions worth pursuing for further experimental research in other coagulation disorder causing genes.

Functional and structural evaluation of cysteine residues in the human arsenic (+3 oxidation state) methyltransferase (hAS3MT)

Arsenic (+3 oxidation state) methyltransferase (AS3MT) catalyzes the methylation of inorganic arsenic (iAs) and plays important role in the detoxication of this metalloid. There are fourteen cysteine residues in the human AS3MT (hAS3MT), among which twelve are absolutely conserved; Cys334 and Cys360 are unique; Cys368 and Cys369 are identified as a CysCys pair. The roles of several conserved cysteine residues in rat AS3MT and hAS3MT have been reported. Herein, the other conserved cysteine residues (Cys72, Cys271, Cys375) and the unique ones (Cys334, Cys360) were systematically replaced by serine using site-directed mutagenesis to study their functions. The mutants were investigated for enzymatic activity, kinetics, thermal stability and secondary structures. Present results indicate that C72S is completely inactive in methylation of iAs and has distinct changes in the secondary structures; Cys72 might form a critical intramolecular disulfide bond with Cys250; Cys271 and Cys375 do not affect the activity and structure of the hAS3MT. However, the mutations of Cys334 and Cys360 can decrease the enzymatic turnovers and change the conformation of the hAS3MT. The kinetic data show that Cys271, Cys334, Cys360 and Cys375 are not involved in the SAM binding. Additionally, all these cysteine residues except Cys375 affect the thermotropic properties of the hAS3MT.

Candidate single nucleotide polymorphism markers for arsenic responsiveness of protein targets

Arsenic is a toxic metalloid that causes skin cancer and binds to cysteine residues—a property that could be used to infer arsenic responsiveness of a target protein. Non-synonymous Single Nucleotide Polymorphisms (nsSNPs) result in amino acid substitutions and may alter arsenic binding with cysteine residues. Thus, the objective of this investigation was to identify and analyze nsSNPs that lead to substitutions to or from cysteine residues as an indication of increased or decreased arsenic responsiveness. We hypothesize that integration of data on molecular impacts of nsSNPs and arsenic-gene relationships will identify nsSNPs that could serve as arsenic responsiveness markers. We have analyzed functional and structural impacts data for 5,811 nsSNPs linked to 1,224 arsenic-annotated genes. In addition to the identified candidate nsSNPs for increased or reduced arsenic responsiveness, we observed i) a nsSNP that results in the breakage of a disulfide bond, as candidate marker for reduced arsenic responsiveness of KLK7, a secreted serine protease participate in normal shedding of the skin; and ii) 6 pairs of vicinal cysteines in KLK7 protein that could be binding sites for arsenic. In summary, our analysis identified non-synonymous SNPs that could be used to evaluate responsiveness of a protein target to arsenic. In particular, an epidermal expressed serine protease with crucial function in normal skin physiology was prioritized on the basis of abundance of vicinal cysteines for further research on arsenic-induced keratinocyte carcinogenesis.

New insights into the mechanism of arsenite methylation with the recombinant human arsenic (+3) methyltransferase (hAS3MT)

The catalytic mechanism of the recombinant human arsenic (+3) methyltransferase (hAS3MT) was studied using kinetics, initial velocity and spectroscopy. The production and the distribution of methylated arsenicals changed with various concentrations of arsenite/S-adenosyl-L-methionine (SAM)/thiols, enzyme contents, and incubation times. These results suggest a sequential methylation of arsenite to monomethylated arsenicals (MMA) and dimethylated arsenicals (DMA). In addition, competition exists between the two reactions. hAS3MT showed the greatest activity at pH 8.5 with glutathione (GSH) as the reductant. This might indicate that a balance between the deprotonation and protonation of sulfhydryl groups is required. Initial velocity studies illuminate an ordered sequence for the binding of SAM and arsenite to the hAS3MT; while GSH should probably be placed either as the first reactant or as a reactant combining with the enzyme only after products have been released. The interactions between substrate/cofactors and the hAS3MT were first monitored by UV-visible and circular dichroism spectroscopy. It revealed that arsenite and SAM combined with the hAS3MT before reaction started; whereas, no interactions between GSH and the hAS3MT were detected. Integrating the results from kinetics, initial velocity and spectroscopy studies, an ordered mechanism are originally attained, with the SAM as the first reactant that adds to the hAS3MT and arsenite as the second one. Arsenite is successively methylated reductively, rather than a stepwise oxidative methylation. GSH should combine with the hAS3MT after the methylation to reduce the disulfide bond formed during the catalytic cycle in the hAS3MT to resume the active form of the enzyme.

Interspecies differences in metabolism of arsenic by cultured primary hepatocytes

Biomethylation is the major pathway for the metabolism of inorganic arsenic (iAs) in many mammalian species, including the human. However, significant interspecies differences have been reported in the rate of in vivo metabolism of iAs and in yields of iAs metabolites found in urine. Liver is considered the primary site for the methylation of iAs and arsenic (+3 oxidation state) methyltransferase (As3mt) is the key enzyme in this pathway. Thus, the As3mt-catalyzed methylation of iAs in the liver determines in part the rate and the pattern of iAs metabolism in various species. We examined kinetics and concentration-response patterns for iAs methylation by cultured primary hepatocytes derived from human, rat, mice, dog, rabbit, and rhesus monkey. Hepatocytes were exposed to [(73)As]arsenite (iAs(III); 0.3, 0.9, 3.0, 9.0 or 30 nmol As/mg protein) for 24 h and radiolabeled metabolites were analyzed in cells and culture media. Hepatocytes from all six species methylated iAs(III) to methylarsenic (MAs) and dimethylarsenic (DMAs). Notably, dog, rat and monkey hepatocytes were considerably more efficient methylators of iAs(III) than mouse, rabbit or human hepatocytes. The low efficiency of mouse, rabbit and human hepatocytes to methylate iAs(III) was associated with inhibition of DMAs production by moderate concentrations of iAs(III) and with retention of iAs and MAs in cells. No significant correlations were found between the rate of iAs methylation and the thioredoxin reductase activity or glutathione concentration, two factors that modulate the activity of recombinant As3mt. No associations between the rates of iAs methylation and As3mt protein structures were found for the six species examined. Immunoblot analyses indicate that the superior arsenic methylation capacities of dog, rat and monkey hepatocytes examined in this study may be associated with a higher As3mt expression. However, factors other than As3mt expression may also contribute to the interspecies differences in the hepatocyte capacity to methylate iAs.

Transition metal ions and selenite modulate the methylation of arsenite by the recombinant human arsenic (+3 oxidation state) methyltransferase (hAS3MT)

This report demonstrates that transition metal ions and selenite affect the arsenite methylation by the recombinant human arsenic (+3 oxidation state) methyltransferase (hAS3MT) in vitro. Co(2+), Mn(2+), and Zn(2+) inhibited the arsenite methylation by hAS3MT in a concentration-dependent manner and the kinetics indicated Co(2+) and Mn(2+) to be mixed (competitive and non-competitive) inhibitors while Zn(2+) to be a competitive inhibitor. However, only a high concentration of Fe(2+) could restrain the methylation. UV-visible, CD and fluorescence spectroscopy were used to study the interactions between the metal ions above and hAS3MT. Further studies showed that neither superoxide anion nor hydrogen peroxide was involved in the transition metal ion or selenite inhibition of hAS3MT activity. The inhibition of arsenite methylating activity of hAS3MT by selenite was reversed by 2mM DTT (dithiothreitol) but neither by cysteine nor by beta-mercaptoethanol. Whereas, besides DTT, cysteine can also prevent the inhibition of hAS3MT activity by Co(2+), Mn(2+), and Zn(2+). Free Cys residues were involved in the interactions of transition metal ions or selenite with hAS3MT. It is proposed that the inhibitory effect of the ions (Co(2+), Mn(2+), and Zn(2+)) or selenite on hAS3MT activity might be via the interactions of them with free Cys residues in hAS3MT to form inactive protein adducts.