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However, over the past fifty years the rapid growth in the development of harder, tougher and stronger work piece materials. The 4340 steel is a medium carbon, low alloy steel (Heat-treatable). It has excellent toughness, superior strength in the heat treated condition, good fatigue resistance, admirable hardness and wear resistance. The 4340 steel is widely used in different applications as: Automotive system, Aircraft landing gears, transmission, Gas & oil sectors, forged hydraulic and structural areas. A WEDM is a non-contact erosion cutting process. It has a capability of machining parts with varying hardness, intricate shapes, contours and complex shapes. The WEDM is a competitive and economical machining option fulfilling the demanding machining requirements. In WEDM the electric sparks is generated between the tool and workpiece and it used to cut the various types of electrical conductive as well as non-conductive materials. The machining process is controlled by various process parameters such as pulse on time, pulse off time and servo voltage. It was found that servo-voltage and pulse on time are the significant factors affecting the SR. While increases the pulse off time and pulse duration affects the MRR, as the reason of pulse off time limits the spark energy and interrupting the discharge energies. From the experimental result, increases the pulse duration, wire speed, open circuit voltage causes the increases in material removal rate. The wire speed and wire tension play the dominant role in the machining of 4340 steel. Machining with zinc coated brass is found to be the best alternative to the 4340 alloy steel.

In recent days, moulding of thermoplastic is difficult process. Injection moulding is one of the most imperative plastic processing technologies. The melted plastics were passed to the closed die unit through thrust of the screw or plunger. In this experimental work, Thermoplastic Polyurethane (TPU) was used as the processing material of injection moulding. The different input factors were applied to operate the injection moulding such as moulding temperature, cooling time and injection pressure. The response of each specimen of tensile strength was measured with respect to the change of input factors. Taguchi optimization, regression model and variance analysis have been conducted.

Lysinuric protein intolerance (LPI) is a rare, yet inimical, genetic disorder characterized by the paucity of essential dibasic amino acids in the cells. Amino acid transporter y+LAT-1 interacts with 4F2 cell-surface antigen heavy chain to transport the required dibasic amino acids. Mutation in y+LAT-1 is rumored to cause LPI. However, the underlying pathological mechanism is unknown, and, in this analysis, we investigate the impact of point mutation in y+LAT-1's interaction with 4F2 cell-surface antigen heavy chain in causing LPI. Using an efficient and extensive computational pipeline, we have isolated M50K and L334R single-nucleotide polymorphisms to be the most deleterious mutations in y+LAT-1s. Docking of mutant y+LAT-1 with 4F2 cell-surface antigen heavy chain showed decreased interaction compared with native y+LAT-1. Further, molecular dynamic simulation analysis reveals that the protein molecules increase in size, become more flexible, and alter their secondary structure upon mutation. We believe that these conformational changes because of mutation could be the reason for decreased interaction with 4F2 cell-surface antigen heavy chain causing LPI. Our analysis gives pathological insights about LPI and helps researchers to better understand the disease mechanism and develop an effective treatment strategy.

An enhancer is a short (50–1500bp) region of DNA that plays an important role in gene expression and the production of RNA and proteins. Genetic variation in enhancers has been linked to many human diseases, such as cancer, disorder or inflammatory bowel disease. Due to the importance of enhancers in genomics, the classification of enhancers has become a popular area of research in computational biology. Despite the few computational tools employed to address this problem, their resulting performance still requires improvements. In this study, we treat enhancers by the word embeddings, including sub-word information of its biological words, which then serve as features to be fed into a support vector machine algorithm to classify them. We present iEnhancer-5Step, a web server containing two-layer classifiers to identify enhancers and their strength. We are able to attain an independent test accuracy of 79% and 63.5% in the two layers, respectively. Compared to current predictors on the same dataset, our proposed method is able to yield superior performance as compared to the other methods. Moreover, this study provides a basis for further research that can enrich the field of applying natural language processing techniques in biological sequences. iEnhancer-5Step is freely accessible via http://biologydeep.com/fastenc/. Nanyang Technological University This work has been supported by the Nanyang Technological University Start-Up Grant.

The World Health Organization declared Ebola virus disease (EVD) as the major outbreak in the 20th century. EVD was first identified in 1976 in South Sudan and the Democratic Republic of the Congo. EVD was transmitted from infected fruit bats to humans via contact with infected animal body fluids. The Ebola virus (EBOV) has a genome size of ∼18,959 bp. It encodes seven distinct proteins: nucleoprotein (NP), glycoprotein (GP), viral proteins VP24, VP30, VP35, matrix protein VP40, and polymerase L is considered a prime target for potential antiviral strategies. The current US FDA-approved anti-EVD vaccine, ERVERBO, and the other equally effective anti-EBOV combinations of three fully human monoclonal antibodies such as REGN-EB3, primarily target the envelope glycoprotein. This work elaborates on the EBOV's phylogenetic structure and the crucial mutations associated with viral pathogenicity.

A promoter is a short region of DNA (100-1,000 bp) where transcription of a gene by RNA polymerase begins. It is typically located directly upstream or at the 5' end of the transcription initiation site. DNA promoter has been proven to be the primary cause of many human diseases, especially diabetes, cancer, or Huntington's disease. Therefore, classifying promoters has become an interesting problem and it has attracted the attention of a lot of researchers in the bioinformatics field. There were a variety of studies conducted to resolve this problem, however, their performance results still require further improvement. In this study, we will present an innovative approach by interpreting DNA sequences as a combination of continuous FastText N-grams, which are then fed into a deep neural network in order to classify them. Our approach is able to attain a cross-validation accuracy of 85.41 and 73.1% in the two layers, respectively. Our results outperformed the state-of-the-art methods on the same dataset, especially in the second layer (strength classification). Throughout this study, promoter regions could be identified with high accuracy and it provides analysis for further biological research as well as precision medicine. In addition, this study opens new paths for the natural language processing application in omics data in general and DNA sequences in particular. Published version

Anaplastic lymphoma kinase (ALK) positive non-small cell lung cancer (NSCLC) patients are mostly treated with ALK tyrosine kinase inhibitors (TKIs). Crizotinib is the first generation ALK inhibitor practiced as a primary chemo to combat cancer cells followed by second generation inhibitor ceritinib which are effective against crizotinib resistant ALK mutations. However, patients treated with these drugs invariably relapsed because of the development of new drug resistance mutations. In this study we explored the crizotinib resistance in the presence of ALK mutations L1196M and G1269A through molecular dynamics simulation studies. Further mutation specific inhibitors CID 71748211 and CID 71728095 were identified to potentially inhibit ALK with mutations L1196M and G1269A, respectively. This computational investigation in-sighted the molecular factors involved in crizotinib resistance which enhanced in the identification of new ALK drugs that brings individualized medicine to treat ALK positive NSCLC patients with specific mutations. J. Cell. Biochem. 118: 3462-3471, 2017. © 2017 Wiley Periodicals, Inc.

Cancer is one of the leading causes of global death and there is an urgent need for the development of cancer treatment; targeting VEGFR2 could be one of the promising therapies. In the present study, previously isolated marine fungal metabolite monacolin X, suppresses in vitro angiogenic characteristics such as proliferation, migration, adhesion, invasion and tube formation of HUVECs when stimulated by VEGF, at a non-toxic concentration. Monacolin X downregulated VEGFR2, PKCα and PKCη mRNA expression. Further, monacolin X inhibited in vivo angiogenesis in CAM assay, vascular sprouting in aortic ring, decreased ISV and SIV length and diameter in Tg (Kdr:EGFP)/ko1 zebrafish embryos. Monacolin X showed reduced protein expression of pVEGFR2, pAKT1, pMAPKAPK2, pFAK and pERK1 in breast cancer lines and in DMBA induced mammary carcinoma in SD rats showed tumor regression and anti-angiogenesis ability via decrease pVEGFR2 and pAKT1 protein expression. In silico studies also revealed monacolin X ability to bind to crucial amino acid Cys 919 in the active site of VEGFR2 suggesting it to be a potent VEGFR2 inhibitor.

Design of Experiments is employed to study the stimulus of cutting parameters such as feed rate, spindle speed, depth of cut in the turning operation of AISI-310 and optimizing the value of those parameters for getting the higher material removal rate (MRR) and minimal surface roughness. A prediction model has been developed by using the above influencing parameters. For the purpose of parameters optimization we investigate the parameters using Response Surface Methodology (RSM). It is shown that feed rate is the main parameter in influencing the surface roughness, which is being followed by spindle speed and depth of cut. It is found that surface roughness and feed rate were directly proportional to each other for some extent. The confirmation tests were carried out to with the optimum set of parameters and are verified with test results. The comparison of above two results were found to be good with maximum error within 5% on comparing it with the predicted model.

Fanconi anemia (FA) is an autosomal recessive human disease characterized by genomic instability and a marked increase in cancer risk. The importance of FANCD1 gene is manifested by the fact that deleterious amino acid substitutions were found to confer susceptibility to hereditary breast and ovarian cancers. Attaining experimental knowledge about the possible disease-associated substitutions is laborious and time consuming. The recent introduction of genome variation analyzing in silico tools have the capability to identify the deleterious variants in an efficient manner. In this study, we conducted in silico variation analysis of deleterious non-synonymous SNPs at both functional and structural level in the breast cancer and FA susceptibility gene BRCA2/FANCD1. To identify and characterize deleterious mutations in this study, five in silico tools based on two different prediction methods namely pathogenicity prediction (SIFT, PolyPhen, and PANTHER), and protein stability prediction (I-Mutant 2.0 and MuStab) were analyzed. Based on the deleterious scores that overlap in these in silico approaches, and the availability of three-dimensional structures, structure analysis was carried out with the major mutations that occurred in the native protein coded by FANCD1/BRCA2 gene. In this work, we report the results of the first molecular dynamics (MD) simulation study performed to analyze the structural level changes in time scale level with respect to the native and mutated protein complexes (G25R, W31C, W31R in FANCD1/BRCA2-PALB2, and F1524V, V1532F in FANCD1/BRCA2-RAD51). Analysis of the MD trajectories indicated that predicted deleterious variants alter the structural behavior of BRCA2-PALB2 and BRCA2-RAD51 protein complexes. In addition, statistical analysis was employed to test the significance of these in silico tool predictions. Based on these predictions, we conclude that the identification of disease-related SNPs by in silico methods, in combination with MD approach has the potential to create personalized tools for the diagnosis, prognosis, and treatment of diseases. The methods reviewed here generated a considerable amount of valuable data, but also the need for further validation.

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.

Understanding and predicting the significance of novel genetic variants revealed by DNA sequencing is a major challenge to integrate and interpret in medical genetics with medical practice. Recent studies have afforded significant advances in characterization and predicting the association of single nucleotide polymorphisms in human TERT with various disorders, but the results remain inconclusive. In this context, a comparative study between disease causing and novel mutations in hTERT gene was performed computationally. Out of 59 missense mutations, five variants were predicted to be less stable with the most deleterious effect on hTERT gene by in silico tools, in which two mutations (L584W and M970T) were not previously reported to be involved in any of the human disorders. To get insight into the structural and functional impact due to the mutation, docking study and interaction analysis was performed followed by 6 ns molecular dynamics simulation. These results may provide new perspectives for the targeted drug discovery in the coming future.

Artemisinin resistance in Plasmodium falciparum threatens global efforts in the elimination or eradication of malaria. Several studies have associated mutations in the PfATP6 gene in conjunction with artemisinin resistance, but the underlying molecular mechanism of the resistance remains unexplored. Associated mutations act as a biomarker to measure the artemisinin efficacy. In the proposed work, we have analyzed the binding affinity and efficacy between PfATP6 and artemisinin in the presence of L263D, L263E and L263K mutations. Furthermore, we performed virtual screening to identify potential compounds to inhibit the PfATP6 mutant proteins. In this study, we observed that artemisinin binding affinity with PfATP6 gets affected by L263D, L263E and L263K mutations. This in silico elucidation of artemisinin resistance enhanced the identification of novel compounds (CID: 10595058 and 10625452) which showed good binding affinity and efficacy with L263D, L263E and L263K mutant proteins in molecular docking and molecular dynamics simulations studies. Owing to the high propensity of the parasite to drug resistance the need for new antimalarial drugs will persist until the malarial parasites are eventually eradicated. The two compounds identified in this study can be tested in in vitro and in vivo experiments as possible candidates for the designing of new potential antimalarial drugs.

Multilingual abstracts in the six official working languages of the United Nations. (PDF 373Â kb)

List of top 15 compounds from TCM database. Table S2. Top ranking TCM lead compounds obtained using iScreen against VP40. Table S3. Comparison of binding free energies of lead compounds using Autodock. Table S4. Energetic contribution of lead compounds and RNA with VP40. Table S5. Comparison of interacting residues of lead compounds. Table S6. ADME and Drug-likeness analysis. Table S7. Toxicity risks of lead compounds predicted by OSIRIS property explorer. Table S8. Prediction of oral toxicity (LD50). Figure S1. Overall flow chart of the present study. Figure S2. Crucial Hydrogen bond interaction formed between RNA and VP40. Figure S3. Crucial Hydrogen bond interaction formed between compound1 and VP40. Figure S4. Crucial Hydrogen bond interaction formed between compund2 and VP40. (DOC 8072Â kb)

Functional alteration in SMAD proteins leads to dis-regulation of its mechanism results in possibilities of high risk diseases like fibrosis, cancer, juvenile polyposis etc. Studying single nucleotide polymorphism (SNP) in SMAD genes helps understand the malfunction of these proteins. In this study, we focused on deleterious effects of nsSNPs in both structural and functional level using publically available bioinformatics tools. We have mainly focused on identifying deleterious nsSNPs in both structural and functional level in SMAD genes by using SIFT, PolyPhen, SNPs&GO, I-Mutant 3.0, MUpro and PANTHER. Structure analysis was carried out with the major mutation that occurred in the native protein coded by SMAD genes and its amino acid positions (R358W, K306S, R310G, S433R and R361C). SRide was used to check the stability of the native and mutant modelled proteins. In addition, we used MAPPER to identify SNPs present in transcription factor binding sites. These findings demonstrate that the in silico approaches can be used efficiently to identify potential candidate SNPs in large scale analysis.

Some individuals with non-small-cell lung cancer (NSCLC) benefit from therapies targeting epidermal growth factor receptor (EGFR), and the characterization of a new mechanism of resistance to the EGFR-specific antibody gefitinib will provide valuable insight into how therapeutic strategies might be designed to overcome this particular resistance mechanism. The G719S and T790M mutations and their combination were involved in causing different conformational redistribution of EGFR. In the present computational study, we analyzed the impact and structural influence of G719S/T790M double mutation (DM) in EGFR with ligand (gefitinib) through molecular dynamic simulation (50 ns) and docking analysis. We observed the escalation in distance between the functional loop and activation loop with respect to T790M mutation compared to the G719S mutation. Furthermore, we confirmed that the G719S mutation causes the ligand to move closer to the hinge region, whereas T790M makes the ligand escape from the binding pocket. Obtained results provide with an explanation for the resistance induced by T790M and a vital clue for the design of drugs to combat gefitinib resistance.

Excision repair cross complementation group 1 (ERCC1) is an important protein in the nucleotide excision repair (NER) pathway, which is responsible for removing DNA adducts induced by platinum based compounds. The heterodimer ERCC1-XPF is one of two endonucleases required for NER. Genetic variations or polymorphisms in ERCC1 gene alter DNA repair capacity. Reduced DNA repair (NER) capacity may result in tumors and enhances cisplatin chemotherapy in cancer patients, which functions by causing DNA damage. Therefore, ERCC1 variants have the potential to be used as a strong candidate biomarker in cancer treatments. In this study we identified five variants V116M, R156Q, A199T, S267P, and R322C of ERCC1 gene as highly deleterious. Further structural and functional analysis has been conducted for ERCC1 protein in the presence of three variants V116M, R156Q, and A199T. Occurrence of theses variations adversely affected the regular interaction between ERCC1 and XPF protein. Analysis of 20 ns molecular dynamics simulation trajectories reveals that the predicted deleterious variants altered the ERCC1-XPF complex stability, flexibility, and surface area. Notably, the number of hydrogen bonds in ERCC1-XPF mutant complexes decreased in the molecular dynamic simulation periods. Overall, this study explores the link between the ERCC1 deleterious variants and cisplatin chemotherapy for various cancers with the help of molecular docking and molecular dynamic approaches.

Background Recent reports suggest the role of nonsynonymous single nucleotide polymorphisms (nsSNPs) in cyclin-dependent kinase 7 (CDK7) gene associated with defect in the DNA repair mechanism that may contribute to cancer risk. Among the various inhibitors developed so far, flavopiridol proved to be a potential antitumor drug in the phase-III clinical trial for chronic lymphocytic leukemia. Here, we described a theoretical assessment for the discovery of new drugs or drug targets in CDK7 protein owing to the changes caused by deleterious nsSNPs. Methods Three nsSNPs (I63R, H135R, and T285M) were predicted to have functional impact on protein function by SIFT, PolyPhen2, I-Mutant3, PANTHER, SNPs&GO, PhD-SNP, and screening for non-acceptable polymorphisms (SNAP). Furthermore, we analyzed the native and proposed mutant models in atomic level 10 ns simulation using the molecular dynamics (MD) approach. Finally, with the aid of Autodock 4.0 and PatchDock, we analyzed the binding efficacy of flavopiridol with CDK7 protein with respect to the deleterious mutations. Results By comparing the results of all seven prediction tools, three nsSNPs (I63R, H135R, and T285M) were predicted to have functional impact on the protein function. The results of protein stability analysis inferred that I63R and H135R exhibited less deviation in root mean square deviation in comparison with the native and T285M protein. The flexibility of all the three mutant models of CDK7 protein is diverse in comparison with the native protein. Following to that, docking study revealed the change in the active site residues and decrease in the binding affinity of flavopiridol with mutant proteins. Conclusion This theoretical approach is entirely based on computational methods, which has the ability to identify the disease-related SNPs in complex disorders by contrasting their costs and capabilities with those of the experimental methods. The identification of disease related SNPs by computational methods has the potential to create personalized tools for the diagnosis, prognosis, and treatment of diseases. Lay abstract Cell cycle regulatory protein, CDK7, is linked with DNA repair mechanism which can contribute to cancer risk. The main aim of this study is to extrapolate the relationship between the nsSNPs and their effects in drug-binding capability. In this work, we propose a new methodology which (1) efficiently identified the deleterious nsSNPs that tend to have functional effect on protein function upon mutation by computational tools, (2) analyze d the native protein and proposed mutant models in atomic level using MD approach, and (3) investigated the protein-ligand interactions to analyze the binding ability by docking analysis. This theoretical approach is entirely based on computational methods, which has the ability to identify the disease-related SNPs in complex disorders by contrasting their costs and capabilities with those of the experimental methods. Overall, this approach has the potential to create personalized tools for the diagnosis, prognosis, and treatment of diseases.

Cyclic-dependent kinase 2 (CDK2) is one of the primary protein kinases involved in the regulation of cell cycle progression. Flavopiridol is a flavonoid derived from an indigenous plant act as a potent antitumor drug showing increased inhibitory activity toward CDK2. The presence of deleterious variations in CDK2 may produce different effects in drug-binding adaptability. Studies on nsSNPs of CDK2 gene will provide information on the most likely variants associated with the disease. Furthermore, investigating the relationship between deleterious variants and its ripple effect in the inhibitory action with drug will provide fundamental information for the development of personalized therapies. In this study, we predicted four variants Y15S, V18L, P45L, and V69A of CDK2 as highly deleterious. Occurrence of these variations seriously affected the normal binding capacity of flavopiridol with CDK2. Analysis of 10-ns molecular dynamics (MD) simulation trajectories indicated that the predicted deleterious variants altered the CDK2 stability, flexibility, and surface area. Notably, we noticed the decrease in number of hydrogen bonds between CDK2 and flavopiridol mutant complexes in the whole dynamic period. Overall, this study explores the possible relationship between the CDK2 deleterious variants and the drug-binding ability with the help of molecular docking and MD approaches.

BackgroundElucidating the molecular dynamic behavior of Protein-DNA complex upon mutation is crucial in current genomics. Molecular dynamics approach reveals the changes on incorporation of variants that dictate the structure and function of Protein-DNA complexes. Deleterious mutations in APE1 protein modify the physicochemical property of amino acids that affect the protein stability and dynamic behavior. Further, these mutations disrupt the binding sites and prohibit the protein to form complexes with its interacting DNA.Principal findingsIn this study, we developed a rapid and cost-effective method to analyze variants in APE1 gene that are associated with disease susceptibility and evaluated their impacts on APE1-DNA complex dynamic behavior. Initially, two different in silico approaches were used to identify deleterious variants in APE1 gene. Deleterious scores that overlap in these approaches were taken in concern and based on it, two nsSNPs with IDs rs61730854 (I64T) and rs1803120 (P311S) were taken further for structural analysis.SignificanceDifferent parameters such as RMSD, RMSF, salt bridge, H-bonds and SASA applied in Molecular dynamic study reveals that predicted deleterious variants I64T and P311S alters the structure as well as affect the stability of APE1-DNA interacting functions. This study addresses such new methods for validating functional polymorphisms of human APE1 which is critically involved in causing deficit in repair capacity, which in turn leads to genetic instability and carcinogenesis.

We report the structures of Mnt_~Bi2+yS4 (0

The transition metal chalcogenides, M, P2S1 (M = divalcnt transition metal cation), are lamellar materials that undergo an unusual cation exchange process when their crystals are placed in contact with a solution of a transition metal salt. EPR spectroscopy has been used to examine the exchange of paramagnetic Co2 + for Cd*+ in diamagnetic CdrP,S,. It has been possible to study the uptake of ions by the lamellar lattice and to examine the cation coordination environment through its effect on the parameters of the spin-Hamiltonian. In order to extract details of the Co2+ coordination from the observed EPR spectra, theoretical values of the g-value have been computed as a function of several crystal field parameters. The results for Co'+ are compared with previous results for the insertion of Mn'+ into Cd,P2S6 by cation exchange. The relative occupancy of the inter- and intra-lamcllar sites is a function of the cation type and the solvent employed. INTRODUCT ION The transition metal phosphorus chalcogenides (M1P2SL, M = transition metal) form a class of lamellar materials with crystal structures of the CdCI, type (l). The layers are composed of arrays of (p2Ssj'- units coordinated to the M*+ cations through M-S bonds, so that the transition metal ions are in a trigonally distorted octahedral environment. The transition metal layers are separated by two planes of chalcogenide atoms, bound together by relatively weak van der Waals interactions. Because of the weak nature of these interactions, various chemical species may be intercalcated into the van der Waals gap (VWG) between the adjacent chalcogenide layers (2). An unusual ion exchange process occurs in crystalline M,P,S, lattices in which the lattice cations are exchanged with intercalate cations (3). The pro- cess is surprising in terms of the conventional view of transition metal chalcogenide lattices as covalently bonded, extended networks. In Mn2P2Ss, the Mn*+ can be exchanged at room temperature with mono- or dipositive guest cations (G+ or G*+) to form com- pounds with the composition Mn2_,G",;,P2S,. EXAFS studies (4) have demonstrated that Ni*+ guest cations enter the intralamellar Mn*+ vacancies in Mn2P2S6. Recently, Clement et al. (5) studied the exchange process by systematically exchanging the lattice cation in several of the M,P,S, lattice5 with

Background: Distinguishing the deleterious from the massive number of non-functional nsSNPs that occur within a single genome is a considerable challenge in mutation research. In this approach, we have used the existing in silico methods to explore the mutation-structure-function relationship in the XPA gene. Materials and Methods: We used the Sorting Intolerant From Tolerant (SIFT), Polymorphism Phenotyping (PolyPhen), I-Mutant 2.0, and the Protein Analysis THrough Evolutionary Relationships methods to predict the effects of deleterious nsSNPs on protein function and evaluated the impact of mutation on protein stability by Molecular Dynamics simulations. Results: By comparing the scores of all the four in silico methods, nsSNP with an ID rs104894131 at position C108F was predicted to be highly deleterious. We extended our Molecular dynamics approach to gain insight into the impact of this non-synonymous polymorphism on structural changes that may affect the activity of the XPA gene. Conclusion: Based on the in silico methods score, potential energy, root-mean-square deviation, and root-mean-square fluctuation, we predict that deleterious nsSNP at position C108F would play a significant role in causing disease by the XPA gene. Our approach would present the application of in silico tools in understanding the functional variation from the perspective of structure, evolution, and phenotype.

The FTIR electronic absorption spectra of single crystals of Fe,P,S,, Co,P,S, and their lithium intercalation compounds have been obtained. The spectrum of Fe, P2 S, exhibits a broad, weak absorption feature at 1885 cm-' and a second, stronger band at 8870 cm-'. These are assigned to transitions between the 'EC (ground state) and the 5A,, and 5E, trigonal crystal-field components of the Fez+ free-ion 5D ground term. The broad absorption bands in the spectrum of Co,P,S, are assigned to the transitions between the "A, (ground state) and the 4E, (1224 cm-') and 4A,, (7124 LXX-') trigonal crystal-field components of the Co2+ free-ion 4Fground term. A point-charge crystal-field model was used to relate the crystal-field splitting parameters (Dq and Cp) to the trigonal lattice distortion. Lithium intercalation completely suppresses the trigonal field transition in Co,P,S, and causes a dramatic shift of the absorption edge to lower frequencies. However, lithium intercalation has little effect upon the spectrum of Fe,P,S,.

The luminescence of microcrystalline samples of Cs[Au(CN)2] is reported and ascribed to planar AuAu interactions. Low-temperature measurements from 1.6 to 100 K of the luminescence decay rate of Cs[Au(CN)2] for the band centered at 458 nm reveal the presence of at least two emitting levels separated by 46 cm−1. A simple orbital model is proposed to account for the luminescence, and spin—orbit coupling is invoked to explain the splitting of the two lowest states. The analogies and differences between this luminescence and that observed for salts of Pt(CN)42− are briefly discussed.

The kinetics of oxidation of fluorene by alkaline hexacyanoferrate(III) is followed under pseudo-first-order conditions in 50% aqueous acetonitrile. The reaction is first-order both in the oxidant and substrate. The rate dependence on [NaOH] is unity. Hexacyanoferrate(II) retards the reaction. The product of oxidation is fluorenone and the stoichiometry between the substrate and the oxidation is 1:4. A large positive salt effect and specific cation effect are observed. A tentative mechanism accounting for all the observations is envisaged.

Studies aiming to explore the involvement of host genetic factors to determine susceptibility to develop disease and individual's response to the infection with Mycobacterium leprae have increased in recent years. To address this issue, we have developed a Leprosy Susceptible Human Gene Database (LSHGD) to integrate leprosy and human associated 45 genes by profound literature search. This will serve as a user-friendly and interactive platform to understand the involvement of human polymorphisms (SNPs) in leprosy, independent genetic control over both susceptibility to leprosy and its association with multi-drug resistance of M. leprae. As the first human genetic database in leprosy it aims to provide information about the associated genes, corresponding protein sequences, available three dimensional structures and polymorphism related to leprosy. In conclusion, this will serve as a multifunctional valuable tool and convenient information platform which is freely available at http://www.vit.ac.in/leprosy/leprosy.htm and enables the user to retrieve information of their interest.