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A robust method for multiplicative scatter correction (MSC) in infrared spectroscopy is presented. Using quantile regression, the outlier wavelengths (concentration‐dependent wavelengths) that are irrelevant to the regression are identified and therefore excluded from the regression model. This new MCS method, which could be implemented in its simple or extended form, is much simpler than the recently proposed methods and has only one hyperparameter (the quantile value) to be adjusted. To achieve this, a scoring function based on residual analysis can automatically determine the correct quantile value. The method is first explained using simulation data sets and then its validation is explained by analysing some experimental data sets. It was found that our new method can perform well in the presence of strong outlying variables. On the other hand, when the data sets are not associated outlying wavelengths, this method behaves similarly to the conventional MSC method. [ABSTRACT FROM AUTHOR]

The responses of the paper-based colorimetric sensor arrays are typically recorded by an imaging device. The color values of the images are subjected to chemometrics data analysis, with a view to extract the relevant information. As is the case with data extracted from other analytical instruments, these data must undergo pre-processing prior to undergoing further analysis. This study represents the first comprehensive and systematic investigation into the impact of data pre-processing techniques on the quality of subsequent data analysis methods applied to imaging data collected from paper-based colorimetric sensor arrays. The use of color difference data (calculated by subtracting the images of the sensors before exposure from those after exposure) revealed that pre-treatment of the data was not a critical factor, although it could reduce the complexity of the model. For example, the number of principal components in the principal component-linear discriminant analysis model was reduced from eight (for data that had not been pre-processed) to three (for pre-processed data) to achieve the same level of accuracy (92 %). Nevertheless, the pivotal role of data pre-processing was elucidated through the examination of data sets collected immediately following exposure to the samples' vapor. It was demonstrated that the use of an appropriate pre-processing method allows for the elimination or significant reduction of between-sensor variations, obviating the necessity for the inclusion of data from images taken prior to exposure. With regard to the objective of classification, the object pre-processing methods that demonstrated particular promise were mean (or median) centering, Pareto scaling and standard normal variate. To illustrate, in the analysis of volatile organic compounds by an array of metallic nanoparticles, the cross-validation classification accuracy of the unprocessed data, which was 70 %, increased to 95 % when unit variance scaling and range scaling were applied to objects and variables, respectively. In the calibration phase, the majority of pre-processing methods enhanced the quality of the regression models. Using suitable pre-processing methods for both objects and variables, eliminated the need for using the before exposing image of the CSAs. • Pre-processing can eliminate or significantly decrease the between sensor variations. • Mean-centering, Pareto scaling and standard normal variate showed to be more promising. • By choosing a suitable pre-processing, the need for capturing before exposing image is eliminated. • For classification, object scaling and for regression analysis, variable scaling played a more significant role. [ABSTRACT FROM AUTHOR]

The effect of bipolar and driving electrodes materials and also the electrolyte conductivity on the required potential for the beginning of the water electrolysis in the paper-based closed cell bipolar electrochemistry is investigated. The importance of the electrode material is studied by placement of various carbon paste mixtures as an electrode on the paper. Carbon paste mixtures are prepared with different carbon allotropes and various binders such as paraffin and ionic liquids. The effect of hydrophobicity, conductivity, and presence of common additives such as gold nanoparticle is discussed in detail. The role of electrolyte conductivity on the needed ∆E for water electrolysis initialization is investigated. It has been proved that even in the absence of ionic current in the closed bipolar setups, electrolyte conductivity can be effective. [ABSTRACT FROM AUTHOR]

In this investigation, a simple, green and facile fluorescence mrtod using carbon dots (CDs) of hazelnut kohl is described for selective detection of dopamine (DA). The sensing system is based on hazelnut kohl (the black soot of kohl) which is used as a carbon source. Generally, kohl is a traditional eye cosmetic that used in different parts of the world and synthesized by the combustion process like burning natural materials. Here, it has been proven that black soot (kohl) obtained from hazelnut has a carbon dot structure and can be used for sensory applications. Some characterization methods are carried out to reveal the kohl structure. Also, the photoluminescence properties of the prepared CDs of kohl are investigated. It is found that the size of CDs is 2–4 nm. Besides, under the optimal conditions, the fluorescence of CDs is used for DA determination. CDs fluorescence intensity is decreased linearly with the increase of DA concentration. By using the fluorescence dependency toward the DA concentration, DA can be determined in the range 0.5–30 μM with the limit of detection of 0.30 μM. Finally, this method is successfully applied to discriminate the DA in the real samples (healthy human serum and cerebrospinal fluid (CSF)) which shows acceptable efficiently for diagnostic purposes. [ABSTRACT FROM AUTHOR]

Wastewater treatment for lowering down the amount of antibiotic drugs in environment is essential for preventing their harmful effects in the ecosystem and for diminishing the growing bacterial resistance. Here, gold-decorated Fe3O4 nanoparticles (NPs) were used for efficient photocatalytic degradation of ampicillin, investigated by UV/Vis absorbance spectrometry. The absorbance data matrices recorded in the course of reactions were analyzed using multivariate curve resolution-alternative least squares as a power chemometrics method. The resolved concentration profiles were composed of three intermediate species and one final product. The concentration profiles were fitted to a first-order kinetics and for the photodegradation experiments run (1) in the absence of photocatalyst, (2) in the presence of Fe3O4 NPs and (3) in the presence of Au-decorated Fe3O4 NPs, the rate constants of 0.023, 0.041 and 0.055 min−1 were obtained, respectively. We found that ampicillin undergoes fast photocatalytic degradation reaction, so that, in the presence of Fe3O4 NPs and Au-decorated magnetic NPs, it was completely converted to its photodegradation product in a few min (35 and 25 min, respectively). The results obtained by chemometrics analysis of the absorbance data agreed with those obtained by capillary electrophoresis. [ABSTRACT FROM AUTHOR]

The test of sweat chloride is routinely performed as a worldwide newborn screening (NBS) to the diagnosis of cystic fibrosis (CF) in infants. However, the available methods for measurement of chloride in sweat suffer from such limitations as either low selectivity and/or requiring relatively large sample size. In this work, we have designed an analytical ruler that can measure chloride ion in sweat and hence can be used for the diagnosis of cystic fibrosis. This micro-pad (μ-PAD) device is fabricated by making hydrophilic micro-channel on a filter paper impregnated with silver dichromate. After addition of chloride ion-containing sweat sample, it moves through the channel, leading to the formation of an AgCl sediment, which deposits as a white color stain, the length of which in the channel being proportional to the amount of chloride ion in sweat. A well-defined linear relation was observed between the length of white color stain and the concentration of chloride ion in the sample solutions with a relative standard deviation of 3.6% (n = 3) for an artificial sweat sample containing 100 mM chloride ion. The possible interfering effects of several different cations and anions on the detection of chloride ion were investigated and the results well-confirmed the selectivity of the proposed method. With the use of only 2.0 μL of the sample solution, the μPAD was able to measure the chloride content of sweat over a concentration range of 20.0–100.0 mM, which covers both the healthy range (˂ 40 mM) and the risky range (˃60 mM) of chloride ion. Analysis of chloride content of sweat samples by the μPAD agreed well with those obtained by a standard electrochemical method (with relative errors of lower than 10%). Image 1 • A novel strategy based on lab on a paper is developed for detection of cystic fibrosis. • Needing low amount of samples, high selectivity, fast response time and of course very low cost. • Analysis is completed within 1 min by dropping 2.0 μL of a sample solution. • The biocompatible colorimetry sensor for determination of chloride ions does not need any electrical based readout. • The μ-PAD sensor offers CF diagnosis in the developing countries and low-resource regions. [ABSTRACT FROM AUTHOR]

We present a detailed investigation of the effect of the crystallographic structure of the HIV-1 protease (PR) on the binding energy of different classes of inhibitors obtained from docking simulations. The crystal structures of 222 HIV-1 proteases (in wild-type and mutant forms) and 202 inhibitors were downloaded from appropriate databases. A cross-docking approach (docking of all 202 inhibitors to all 222 PR structures) using Autodock Vina was implemented. The protease structures were clustered using a Kohonen self-organization map analysis of the data matrix of docking energies. The obtained clusters of PRs were correlated with the x-y-z coordinates of the PR structures to identify structural segments underlying this clustering. The PR structures were clustered into 4 classes. One of these classes exhibits rather strong binding with almost all inhibitors, while another class exhibits rather weak binding. The remaining two classes are intermediate in binding strength. The selectivity ratio indices for the carbon-alpha atoms of the PR structures indicate that conformational motion of residues outside the binding pocket contributes significantly to the discrimination of the 4 classes. Image 1 • A cross-docking approach (docking of all 202 inhibitors to all 222 PR structures) using Autodock Vina was implemented. • The PR structures were clustered into 4 classes based on docking scores. • These classes could be discriminated based on their crystal structures, too. • We found motion of residues outside the binding pocket of PR contributes significantly to this discrimination. [ABSTRACT FROM AUTHOR]

Zataria multiflora (ZM), also known as Shirazi thyme is a popular culinary spice and medicinal plant, which is known by its thyme-like properties. Despite its wide usage in food, phenolic composition of this plant has remained uninvestigated. In this study, for the first time, several polyphenols including hydroxycinnamic acids, phenolic terpenes, and flavonoids were identified in the hydroalcoholic extract of Z. multiflora. Furthermore, HPLC–PDA fingerprints of the samples were established and antioxidant activity, total phenolic content (TPC) and total flavonoid content (TFC) of ZM samples were also evaluated. Potential quality markers of Zataria multiflora were then determined by chemometric evaluation of chromatographic fingerprints, which were subsequently quantified. Our results revealed that four major compounds including rosmarinic acid (6.53–42.39 mg/g E), naringenin (4.95–11.36 mg/g E), carvacrol (3.15–48.36 mg/g E), and thymol (1.63–19.14 mg/g E) are the principal compounds appertaining to antioxidant activity, TPC and TFC properties in ZM extracts, which are worth considering as potential markers of ZM quality. The obtained results not only could be informative for pharmaceutical and food industries but also can be applied for quality-control purposes. [ABSTRACT FROM AUTHOR]

Up to now, numerous peptides/hydrolysates derived from casein and whey protein have shown angiotensin-I-converting enzyme (ACE) inhibitory. In this research, quantum topological molecular similarity (QTMS) indices of amino acids were utilized in quantitative sequence-activity modeling (QSAM) to predict the activity of a set of milk-driven peptides with ACE inhibition. Since the derived peptides have not the same number of residues, we overcame this issue by auto cross covariance (ACC) methodology. Then, some QSAMs were built to predict the pIC50 value of ACE peptides derived from Bovine Casein and Whey. The model established an acceptable relationship between the selected variables and the pIC50 of the peptides. To estimate the performance of the developed models, casein and whey proteins from human, goat, bovine and sheep were virtually broken by trypsin and chymotrypsin enzymes and the ACE activity of the resultant virtual peptides were predicted and some new ACE peptides were proposed. [ABSTRACT FROM AUTHOR]

A new, simple and low‐cost method for patterning hydrophobic barriers in porous support such as paper by Parafilm® has been introduced. This method is then used for electrochemical paper‐based ammonia sensor construction. Ammonia sensor is based on electrochemical concentration cell which ammonia reaction with electrolyte in halves cell caused in concentration gradient and therefore potential difference dependent on ammonia concentration. The effect of concentrations of the involved chemicals, time periods of the required processes, the presence of Faraday cage as well as the effects of different salts used in the salt bridge on the response of the sensor, were investigated in order to find the optimized conditions. [ABSTRACT FROM AUTHOR]

[Display omitted] • Monitoring the food safety by using the intelligent packages in markets can improve the public health. • A colorimetric sensor array was developed using pH indicators immobilized on triacetyl cellulose (TAC) membrane to monitor the chicken meat freshness in referigrator. • Color change due to chicken meat spoilage was sharp and could be read even by untrained people. A new transparent colorimetric sensor array is presented for naked eye monitoring of the chicken meat freshness. This sensor array consists of four sensors fabricated by using pH indicators, immobilized on triacetyl cellulose (TAC) membrane. The sensor array represented obvious color change when it was exposed to the volatile organic compounds emitted from the chicken meat after 20 h keeping at room temperature or after four days of storage in the refrigerator. Therefore, it could easily identify spoiled meat from the fresh one assisted by chemometrics data analysis. Also, the color change of sensors due to the spoilage was sharp enough that could be read even by untrained people, providing naked eye monitoring the chicken meat freshness. The TAC polymer represented high physical stability for industrial scale-up. In addition, the immobilized indicators represented good stability against color change in humid condition. This offered the potential for continuous monitoring of the meat spoilage as smart labeling in the markets. [ABSTRACT FROM AUTHOR]

Monitoring the secondary structure of proteins is surely important in different biochemical and biophysical interactions. In this study, estimation of changes in secondary structure motifs of bovine serum albumin were done by means of fluorescence spectroscopy coupled by parallel factor analysis (PARAFAC) method. Different parameters such as core consistency, number of iteration and residual sum of squares were used to estimate optimum number of components in PARAFAC of fluorescence spectra and finally three components were utilized for resolving spectra. After curve resolution based on PARAFAC using suitable constrains such as nonnegativity and unimodality, concentration profiles of the resolved components were compared by the results of the secondary structure analysis based on circular dichroism (CD). An interesting agreement was detected between the concentration profiles of two components with variation of α-helix and random coil during chemical denaturation. [ABSTRACT FROM AUTHOR]

Deep eutectic solvents (DESs) are a new generation of solvents. To consider them as green solvents, investigation of their toxicity is essential. In this work, the cytotoxicity of a number of natural deep eutectic solvents (NADESs) against HEK-293 human embryonic kidney cells was evaluated by MTT assay. The NADESs were prepared with choline chloride (ChCl) as hydrogen-bond acceptor (HBA) and different sugar alcohols as hydrogen-bond donor (HBD) constituents. They showed IC 50 values in the range of 3.52–75.46 mM. These results were used to evaluate the effect of structural parameters on the cytotoxicity of the studied NADESs by using quantitative structure activity relationship (QSAR) analysis. A three-parameter linear model was obtained between - log(IC 50 ) as a dependent variable and structural descriptors as independent variables. Rotatable bond number (RBN), mean atomic van der Waals volume (Mv) and the interaction of second power carbon numbers with the molar ratio of HBA to HBD in each NADES (C 2 Ratio), were three major parameters. The statistical model covered about 76.4% and 69.8% variance of data in training and leave-one-out cross-validation, respectively. This work, as the first study on the QSAR analysis of DESs, can provide a good perspective for designing greener novel DESs. [ABSTRACT FROM AUTHOR]

In this investigation a new non-separative kinetic-spectroflourimetric method is proposed for the determination of lysine (lys), leucine (leu) and phenylalanine (phe) enantiomers as their o -phthaldialdehyde (OPA) derivatives in the presence of an optically active chiral thiol compound, 1-mercapto-2-propanol (MP). At ambient temperature and in the borate buffer media of pH 9.6, MP, OPA, as highly selective fluorogenic reagents, and amino acid (AA) enantiomers reacts with each other to yield two fluorescent diasteriomers of D and L-AA with maximum difference in fluorescence intensity at about 450 nm. To achieve information from the small spectral changes, the data are analyzed by Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) method. Linear calibration curves are achieved to distinct D and L-lys, leu and phe in different mole ratios by applying appropriate constraints in MCR-ALS procedures. This is the first application of MCR-ALS in determination of enantiomeric excess (ee) using OPA/MP adduct as chiral reagent, which benefits from direct time dependent-fluorescence spectral analysis and does not require prior separation of chiral analytes. Both the cross-validated correlation coefficient ( Q 2 ) and root mean squares error of prediction (RMSEP) indicated satisfactory prediction ability of this method. [ABSTRACT FROM AUTHOR]

Abstract: For a long time, feature selection has been a hot topic in the statistical‐related literature and has become increasingly frequent and important in various research fields. Feature screening methods using marginal correlation show potential problems. Another issue that hinders to select an important variable is the shading effect of a highly influential variable on the variables of lower importance. Feature selection can be even more complex in the presence of nonlinear relations. To overcome these limitations, an innovative method for selecting linearly and nonlineary correlated variables is presented. It works based on the hyphenation of nonparametric variable ranking methods with nonparametric regression methods through an iterative regression based on residuals. Here, maximal information coefficient and distance correlation are used to rank the variables. The algorithm starts with modeling the relationship between response and the top‐ranking variable by using multivariate adaptive regression splines method. In the next iterations, the top‐ranking variables are selected based on relationship with subsequent residuals. The validation of the method is discussed by using 2 nonlinear simulated data. The method is further validated by analysis of 2 real cheminformatic data sets including toxicity of 1571 industrial chemicals and aqueous solubility of a diverse set of 1708 organic molecules. [ABSTRACT FROM AUTHOR]

Many diseases are detected through blood tests. Currently, most blood tests are done on plasma instead of whole blood because of the interference of blood cells on detection results. Here, we developed a laminated microfluidic paper-based analytical device (L-μPAD) for the separation of plasma from whole blood without using plasma separation membrane (PSM). A lateral flow design consisting of a circular sampling zone and rectangular detection zone was patterned on the paper substrate using laser printing technology. The μPAD was then laminated after impregnation with KCl solution. Lamination and electrolyte addition represented synergistic effects on the separation by controlling the pore size of the paper. In addition, by preventing evaporation on one hand and squeezing paper pores on the other hand, lamination caused longer movement of the separated plasma, the longest plasma path reported so far. The separation process was monitored using colorimetric reagent bromocresol green and scanning electron microscopy. The process of separation was completed in less than 90s without significant hemolysis and the separated plasma was far from the interfering effect of red blood cells. We used the device for the determination of serum albumin. However, it represents the potential for point-of-care testing in multi-assay experiments too. [Display omitted] • A laminated microfluidic paper-based analytical device for separation of plasma from whole blood. • No need to use plasma separation membrane. • Lamination represented significant effects on the separation by preventing evaporation. • Lamination caused longer movement of the separated plasma, the longest plasma path reported so far. • We used the device for determination of serum albumin. [ABSTRACT FROM AUTHOR]

Responses in colorimetric sensor arrays are based on the monitoring color changes of chemical transducers by multichannel spectrophotometers or imaging recorders such as scanners, digital camera and smartphones. The images are then digitized using different image analysis algorithms. The array based methods provide a multi-dimensional data containing analytical, noise and outlier information. The inconsistent data can be removed or decreased by data pre-processing methods. Based on the goal of researches, the refined data can be processed by the pattern recognition methods for qualitative analysis or a by the multivariate regression models for quantitative analysis. This article explains (i) the mechanism of data collection using different types of readers, (ii) introduces the types and applications of algorithms and software for image digitalization, (iii) represents information about data preprocessing, variable selection and multivariate statistical methods and (iv) evaluates their applications in processing of colorimetric sensor array data published during the last decade. • Fundamental basis of colorimetric sensor arrays (CSAs). • How to collect the response of the CSAs by spectroscopic or imaging methods. • Methods to analyze the images from CSAs. • Multivariate data analysis (chemometrics) methods are essential for CSAs. [ABSTRACT FROM AUTHOR]

Local names are not reliable sources for identification of plants, because they differ significantly from one region to another. Apart from confusing nomenclature, the similar appearance and fragrance of Shirazi thyme and Thymus species cause misidentification. In order to prevent the adverse events in relation to the use of improper herbal products, easy-to-use quality control (QC) methodology was developed to classify these culinary plants. Fourier transform infrared (FT-IR) fingerprinting technique was applied for classification of these plants on the basis of their biochemical compositions. Powerful PLS-DA classification model with classification accuracy of 100% was obtained. For the first time in the present study, it was revealed that Shirazi thyme samples have higher antioxidant activity [average IC of 37.03 (µg/ml)] compared to different Thymus species [average IC of 148.35 (µg/ml)]. FT-IR fingerprint profiles were also used to construct a predictive model for antioxidant activity of the plants based on a reliable PLSR model. The developed PLSR model revealed that IR wavenumbers of 1000-1200, 1700, and 3200-3500 cm are important for antioxidant activity prediction of the analyzed plants. The applied approach has the potential for being used in QC programs not only for fraud mitigation and detection, but also for estimation of antioxidant activity of the culinary plants. [ABSTRACT FROM AUTHOR]

In order to design novel non-peptidic inhibitors of BACE1, many research groups have attempted using computational studies including docking analyses. Since there are too many 3D structures for BACE1 in the protein database, the selection of suitable crystal structures is a key prerequisite for the successful application of molecular docking. We employed a multi-structure docking protocol. In which 615 ligands’ structures were docked into 150 BACE1 structures. The large number of the resultant docking scores were post-processed by different data analysis methods including exploratory data analysis, regression analysis and discriminant analysis. It was found that using one crystal structure for docking did not result in high accuracy for predicting activity of the BACE1 inhibitors. Instead, using of the multi-structural docking scores, post-processed by chemometrics methods arrived to highly accurate predictive models. In this regards, the PDB accession codes of 4B70, 4DVF and 2WEZ could discriminate between active and inactive compounds, with higher accuracy. Clustering of the BACE1 structures based on principal component analysis of the crystallographic structures the revealed that the discriminant structures are in the center of the clusters. Thus, these structures can be selected as predominant crystal structures for docking studies of non-peptidic BACE1 inhibitors. [ABSTRACT FROM AUTHOR]

Identification of oil type and its QC are important concerns in food control laboratories. Classifying edible oils that have not been used (i.e., unheated) with the aid of vibrational spectroscopy has previously been reported. However, the classification of used (i.e., heat-treated) oils needs special attention. The effect of long heating times on the classification of four kinds of edible oils (canola, corn, frying, and sunflower) based on attenuated total reflectance (ATR)-FTIR spectra was surveyed. The sampling was done on the oils during a 36 h heating process (at 170°C). The ATR-FTIR spectra of the samples were collected in the range of 4000-550 cm-1. Interval extended canonical variates analysis (ECVA), as a variable selection and classification tool, was used to determine the best intervals during the heating procedure for classification. Principal component analysis discriminate analysis, partial least-squares discriminate analysis, and ECVA were performed on the selected intervals and on the total heating time. The effect of autoscaling and mean-centering, as data preprocessing methods, was also investigated. The ECVA method resulted in the best performances for classification, with a 94% cross-validated nonerror rate (one misclassification) for the heating process times of 24-27 and 33-36 h. [ABSTRACT FROM AUTHOR]

Today, traditional systems of medicines (such as herbal distillates) become important resources for providing healthcare benefits. The ability to discriminate among closely similar herbal products is critical to ensure their efficacy. This article proposes a pattern-based recognition approach for the rapid discrimination of herbal distillates using a low-cost and sensitive colorimetric sensor array composed of 25 indicators. The color changes of the sensor exposed to the vapor of the herbal distillates can be monitored easily with an ordinary flatbed scanner. The digital representation of the array response was analyzed with hierarchical clustering analysis (HCA) and principal component analysis (PCA). Using new variable selection strategy, 6 indicators among the 25 employed indicators were selected as discriminant elements of the array. So, a complete discrimination (with 100% accuracy) of 46 herbal distillates was achieved. The proposed sensor represented a better resolution when analytes were placed in an oven at 85 °C for 45 min. This colorimetric sensor array demonstrates excellent potential for quality assurance/control applications of herbal distillates. [ABSTRACT FROM AUTHOR]

• Recent advances in paper/thread-based zone and capillary electrophoresis techniques. • Various sample pretreatment methods using electrophoresis on wicking substrates. • Review of unmodified and modified microfluidic paper/threat -based chromatography. • Application of paper/threat -based chromatography in blood separation. Paper and thread are widely used as the substrates for fabricating low-cost, disposable, and portable microfluidic analytical devices used in clinical, environmental, and food safety monitoring. Concerning separation methods including chromatography and electrophoresis, these substrates provide unique platforms for developing portable devices. This review focuses on summarizing recent research on the miniaturization of the separation techniques using paper and thread. Preconcentration, purification, desalination, and separation of various analytes are achievable using electrophoresis and chromatography methods integrated with modified or unmodified paper/thread wicking channels. A variety of 2D and 3D designs of paper/thread platforms for zone electrophoresis, capillary electrophoresis, and modified/unmodified chromatography are discussed with emphasis on their limitation and improvements. The current progress in the signal amplification strategies such as isoelectric focusing, isotachophoresis, ion concentration polarization, isoelectric focusing, and stacking methods in paper-based devices are reviewed. Different strategies for chromatographic separations based on paper/thread will be explained. The separation of target species from complex samples and their determination by integration with other analytical methods like spectroscopy and electrochemistry are well-listed. Furthermore, the innovations for plasma and cell separation from blood as an important human biofluid are presented, and the related paper/thread modification methods are explored. [ABSTRACT FROM AUTHOR]

A new merocyanine dye was synthesized, and its acidity constant was determined by spectrophotometric and chemometrics methods. The interactions of the new cyanine dye with bovine serum albumin (BSA) have been studied by fluorescence and UV absorption spectroscopy at pH 7.40. A visual color change from red to blue was observed by addition of BSA to aqueous solution of the dye. The quenching constants and binding parameters (binding constants and number of binding sites) were determined at different temperatures. The calculated thermodynamic parameters confirmed that the binding reaction is mainly entropy-driven, whereas electrostatic interaction plays major role in the reaction. The displacement experiment confirmed binding of the dye to the subdomain IIA (site 1) of albumin. Moreover, synchronous fluorescence spectroscopy studies revealed the dye induces some local conformational change in BSA. The binding distance, r, between donor (serum albumin) and acceptor (dye) was obtained according to Förster's theory. [ABSTRACT FROM AUTHOR]

DTIC or dacarbazine is a photosensitive drug which is analyzed by chromatography methods. In this study, chemometric methods were applied to resolve the UV-Vis absorbance spectra recorded during irradiation of DTIC by an artificial lighting source. The photo-degradation reaction was monitored at different pH media (between 2 and 12). Multivariate curve resolution-alternative least square was then employed to simultaneously analyze the absorbance data matrices obtained at various pH media. Factor analysis revealed the presence of five chemical species co-existing in the reaction media. Regarding the analysis of concentration profiles of the detected species at different pH values, three species were attributed to the different acid-base states of DTIC, while the remaining components were considered as acid-base states of the photoproduct. Eventually, the presence of major photoproduct (2-azahypoxanthine) was confirmed by the HPLC method. [ABSTRACT FROM AUTHOR]

Nanospheres of Ag-coated Fe3O4 were successfully synthesized and characterized. Photocatalytic properties of Fe3O4@Ag composites have been investigated using steady-state studies and laser pulse excitations. Accumulation of the electrons in the Ag shell was detected from the shift in the surface plasmon band from 430 to 405 nm, which was discharged when an electron acceptor such as O2, Thionine ( TH) or C60 was introduced into the system. Charge equilibration with redox couple such as C60●-/C60 indicated the ability of these core-shell structures to carry out photocatalytic reduction reactions. As well, outer Ag layer could boost charge separation in magnetic core through dual effects of Schottky junction and localized surface plasmonic resonance ( LSPR)-powered band gap breaking effect under sunlight irradiation; resulted in higher photocatalytic degradation of diphenylamine ( DPA). The maximum photocatalytic degradation rate was achieved at optimum amount of Ag- NP loading to products. Adsorption studies confirmed that degradation of DPA dominantly occurred in solution. Moderately renewability of the nanocatalysts under sunlight was due to oxidation and dissolution of the outer Ag layer. [ABSTRACT FROM AUTHOR]

The present study reports on the extraction of antioxidant compounds from Iranian Ocimum basilicum . Central composite design (CCD) was used to investigate the effect of extraction variables on the ultrasound-assisted extraction (UAE). Three independent variables including temperature, methanol to water ratio percent, and sonication time were studied for simultaneous optimization of antioxidant capacity, total phenolic content and extraction yield. Both quantitative modeling and response surface methodology suggested that methanol to water ratio percent and extraction temperature were the most effective parameters of UAE process. However, sonication time was found out to be an insignificant factor in ultrasound-assisted extraction of antioxidant and total phenolic compounds of O. basilicum . The optimum conditions were determined as temperature of 59 °C, methanol to water ratio of 65.2% (v/v), and extraction time of 20 min. [ABSTRACT FROM AUTHOR]

One of the most extended subfields of chemometrics, at least by considering the number of publications and interested researchers, is QSAR/QSPR. During the time, various improved and/or alternative methods have been developed in different principal steps of QSAR/QSPR including (i) variable selection, (ii) model construction and (iii) validation evaluation. In the current manuscript, it is tried to represent a short overview on critical and bold developments of chemometrics tools utilized in QSAR/QSPR studies. [ABSTRACT FROM AUTHOR]

Edible parts of date palm fruits (DPF) from Iran have been evaluated for their antioxidant activities (AA) and total phenolic content (TPC) using Trolox equivalent antioxidant capacity, TEAC, and Folin-Ciocalteu methods, respectively. Seven kinds of soft dates (SD), namely Berehi, Mordasang, Mazafati, Kabkab, Khanizi, Shahabi and Medjool dates; four types of semidry dates (SDD), namely Piarom, Zahedi, Halavi and Karoot dates; and one kind of dry date (DD), Rabbi date were used. The AA of the DPF were in the range of 21.31-29.94, 33.36-35.85 and 33.71 µmol Trolox equivalents/100 g fresh weight, while TPC contents were in the range of 250.75-328.57, 356.55-398.23, and 361.46 mg gallic acid equivalents (GAE)/100 g fresh weight for SD, SDD and DD, respectively. Results show that there was a linear relationship between AA and TPC. Finally, transmittance FT-IR spectra of the extracted methanolic date samples were used to develop classification model based on their TPC content. [ABSTRACT FROM AUTHOR]

In chronoamprometric methods, the current is usually measured at relatively long times, where the contribution of charging current is assumed to be negligible. Previously, we used a chemometric method to resolve numerically the total current which is composed of three pure currents namely net faradaic current, induced charging current and step charging current. In this work, we investigated the effect of analyte concentration on each current component to derive calibration curves for quantitative analyses. In potential step chronoamperometric method, a current data matrix is obtained for each concentration of the analyte. Simultaneous analysis of the data matrices obtained at different concentrations of the analyte by multivariate curve resolution–alternative least squares (MCR–ALS) analysis, produced the net contribution of three types of currents for each concentration of the analyte. Then, the calibration curves based on the faradaic and induced charging current contributions below five cell time constants were compared with the traditional calibration curve, which was based on the total current. In this manner, the linear range, limit of detection and analytical sensitivity of all kinds of calibration curves were compared with each other. The calibration curves obtained based on net faradaic current represented better analytical appraisals compared to those obtained by total current. In addition, we found that at low analyte concentrations, the induced charging currents have insignificant contribution in total current, whereas it represented very significant contribution (even larger than net faradaic current) at high analyte concentrations. Also, the obtained calibration curves were used for prediction of unknown concentrations. [ABSTRACT FROM AUTHOR]

Semiconductor nanoparticles (quantum dots) are promising fluorescent markers, but very little known is about interaction of quantum dots with biological molecules. In this study, interactions of ZnS quantum dots doped with different amounts of Mn (1, 2 and 3 %) with human serum albumin (HSA) were studied by fluorescence and UV-Vis spectroscopic techniques. It was observed that fluorescence of HSA was strongly quenched by ZnS QDs. The results of fluorescence quenching at different temperatures and UV-Vis absorption spectra experiments indicated that the quenching mechanism of serum albumin by QDs is static quenching through formation of the complex of QDs-HSA. According to the modified Stern-Volmer equations at different temperatures, the thermodynamic parameters, Δ H, Δ S and Δ G were determined. The number of binding sites ( n) was also obtained. It was found that hydrogen bonding and van der Waals interaction played a key role in the interaction process. [ABSTRACT FROM AUTHOR]

The use of multivariate curve resolution-alternating least square (MCR-ALS) for determination of nanoparticles concentration is proposed. The concentration of nanoparticles based on its reaction with a reagent such as a biomolecule, nanoparticles and etc was calculated. The reagent can be considered as an aggregating agent, capping agent and so on. To do so, titration of nanoparticle was achieved by adding variable amounts of reagent to a nanoparticle solution of unknown concentration. A reverse titration was also performed. The UV–Vis spectra of the solutions at different titration steps were recorded. After data collection, chemometrics approach was employed for data analysis. To use MCR-ALS as a quantitative tool, rotational and intensity ambiguities were removed employing unimodality, non-negativity, closure and equality constraints and simultaneous analysis of four spectroscopic titrations: three titrations of reagent by nanoparticles with different concentrations of reagent, and one titration of nanoparticles by reagent. The proposed method was firstly evaluated by simulated data. Then, the concentration of the laboratory-synthesized silver nanoparticles was determined using human serum albumin as reagent. The estimated concentration by the suggested method (1.24 × 10 − 8 M) was very close to that obtained by analysis of TEM images (1.19 × 10 − 8 M) with a relative error of 4.2%. [ABSTRACT FROM AUTHOR]

Diphenylamine (DPA) photodegradation was studied by applying the optimal response surface design methodology to the chromatographic data from pollutant solutions exposed to stressing irradiation. The procedure consisted of data analysis of aliquots collected at different reaction times and injected to a high-performance liquid chromatography coupled to diode array detection-mass spectrometry (HPLC–DAD–MS). The variables considered for the process optimization were irradiation power, irradiation time and pH of solution, for a solution with DPA concentration of 100 mg L −1 . This methodology allowed assessing and identifying the effects of different factors studied and their interactions in the process response. An appropriate quadratic model was developed in order to plot the response surface and contour curves and to perform the process optimization. The results obtained revealed that DPA photodegradation is strongly dependent on the solution pH and irradiation power. Under the optimal conditions (i.e., pH of 10, irradiation power of 2 × 15 W lamp and irradiation time of 150 min), it was possible to achieve an almost complete photodegradation of DPA. The process was found to follow a pseudo-first-order kinetic model. Mass spectrometric analysis allowed the identification of carbazole (CB) as the major photodegradation product. A possible pathway for the photodegradation of DPA was suggested. The optimized methodology was applied to preparation and separation of CB, as an important mediator in fine chemistry and pharmacy, from DPA by thin layer chromatography. [ABSTRACT FROM AUTHOR]

This paper introduces a new application of multivariate image analysis-thin layer chromatography, as simple and inexpensive method, for semi-separation and simultaneous measurement of two isomeric amino acids leucine (Leu) and isoleucine (Ile). The images recorded by a digital camera were processed by home-made software and were converted to TLC chromatograms. Linear calibration graphs were obtained for individual analytes with detection limits of 0.60 and 0.48 μg for Leu and Ile, respectively. The mobile phase composition was optimized for maximum separation. However, complete separation of the spots of the analytes was not obtained. So, the chromatograms were processed by partial least square regression to resolve the overlapped chromatogram. This offered simultaneous determination of Leu and Ile in their binary mixtures. Suitable models were obtained with root mean square error of prediction of 0.008 and 0.009 μg for Leu and Ile, respectively. The prediction ability of the developed model was assessed by determination of the analytes in diluted serum plasma and the obtained percent of recoveries were in the range of 95-105 %. [ABSTRACT FROM AUTHOR]

Virtual bioactive molecular design is an important part of modern drug discovery projects. In this regard, molecular docking may be looked upon as a well established in silico approach in structure-based hit/lead development. Stereoelectronic complementary fit of a bioactive ligand with its receptor may be predicted by molecular docking. Generally docking simulations are compromised of two principal steps; search algorithm and a scoring function. Search algorithms explore the ligand-receptor configurational space while scoring functions apply molecular mechanic force fields to estimate the free binding energies of various ligand-enzyme poses. In the present contribution, a new probability factor (PF) was proposed that could successfully enhance the predictability of AutoDock4.2 scoring function with regard to FRET-based BACE-1 inhibitory activities of some organic small molecules. BACE-1 or beta site amyloid precursor protein cleaving enzyme is a major therapeutic target for Alzheimer disease due to its determinant role in pathogenesis of the disease. [ABSTRACT FROM AUTHOR]

Highlights: [•] A simple, rapid and novel method for determination of folic acid (FA) has been suggested. [•] FA quenches the fluorescence of BSA-modified gold nanoclusters. [•] In pH of 7.4, the fluorescence quenching was fitted to Stern–Volmer equation. [•] A linear range of 0.12–33.12μgmL−1 and detection limit of 18.3ngmL−1 was achieved. [Copyright &y& Elsevier]

Nystatin, one of the tetraene antifungal antibiotics, is very sensitive to light. Thus, when nystatin is exposed to natural daylight, it is photodegraded to products of lower biological activity. In this work, the photodegradation kinetics of nystatin was monitored by a UV-Vis spectrophotometry method. The absorbance spectra of the nystatin, exposed to a 366 nm UV lamp, were recorded at different periods of time. By application of factor analysis to the absorbance data matrix, three absorbing chemical species, coexisting in the reaction system, were detected. The soft-modeling multivariate curve resolution-alternating least squares analysis of the evolutionary absorbance data revealed that nystatin undergoes photodegradation in a two-step consecutive manner. Hard-modeling data analysis suggested that reaction has first-order kinetics in the first step and zero-order kinetics in the second step. The reaction rate constants of the first and second steps were estimated as 0.0929 (±0.0076) and 0.0052 (±0.0016)/min, respectively. Finally, the pure spectra of the resolved chemical species were calculated. [ABSTRACT FROM AUTHOR]

Highlights: [•] Two linear models were constructed to predict the dispersibility of graphene in liquid phases. [•] Involved solute–solvent interactions were discussed in these colloidal systems. [•] Dispersive interactions, in comparison with H-bonding and polar interactions, might be more significant. [•] Some new solvents were proposed for graphene synthesis. [ABSTRACT FROM AUTHOR]

We have recently suggested using clustering of variables (CLoVA) based on unsupervised pattern recognition for partitioning variables into informative and redundant ones. Because data clustering plays a central role in CLoVA, in the present study, we compared the efficiency of different clustering methods including the Kohonen self-organizing map (SOM), principal component analysis, fuzzy c-means clustering, K-means clustering, and hierarchical cluster analysis for clustering spectroscopic data and molecular descriptors to build multivariate calibration and quantitative structure-activity (QSAR) models. To investigate which clustering methods are more efficient for CLoVA, four data sets (three spectroscopic and one QSAR) were analyzed. Most of the CLoVA-based models obtained by SOM resulted in the least root mean square errors of cross-validation and prediction, suggesting a higher efficiency of SOM for clustering variables. In all cases, the results obtained by the CLoVA-based method were compared with those obtained by conventional principal component regression as well as genetic algorithm and successive projection algorithm partial least square regression. Interestingly, models produced by the CLoVA-based method were more predictive with respect to that of the other methods, as indicated by the lowest root mean square error of prediction. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A simple pH-independent optical method for the sensing of heparin, as a biomedically important polyionic drug, based on aggregation of gold nanoparticles (AuNPs) is described. The polyanionic heparin induces the aggregation of positively charged ionic liquid stabilized AuNPs, which results in a shift in the surface plasmon band and a consequent color change of the AuNPs from red to blue. The color change was monitored using UV-vis spectrophotometry and image analysis methods. The aggregation was confirmed by transmission electron microscopic measurements. The degree of aggregation was found to be proportional to the concentration of the added heparin, allowing its quantitative detection. The change in the absorbance and color-value has been used to monitor the concentration of heparin. This optical method can quantify heparin as low as 0.010 μg mL−1 and the calibration is linear for a wide range of concentration. [ABSTRACT FROM AUTHOR]

We report the development of a simple and rapid colorimetric detection method for hydrazine in boiler feed water using label-free aggregation-based gold nanoparticles as probe. This assay relies upon the distance-dependent optical properties of gold nanoparticles. Hydrazine could rapidly induce the aggregation of gold nanoparticles, thereby resulting in visual color change from red to blue (or purple). The concentration of hydrazine can be determined by the naked eye or by a UV-vis spectrometer. Calibration curve was linear ranging from 1.0 × 10 to 1.0 × 10 M of hydrazine. The present limit of detection for hydrazine was 1.0 × 10 M. The method is rather simple, and the whole process including sample pretreatment takes only 15 min at room temperature. The merits (such as simplicity, rapidity, low cost and visual colorimetry) make the proposed method especially useful for on-site screening of hydrazine levels well in boiler feed water. [ABSTRACT FROM AUTHOR]

Abstract: A central question is how the conformational changes of proteins affect their function and the inhibition of this function by drug molecules. Many enzymes change from an open to a closed conformation upon binding of substrate or inhibitor molecules. These conformational changes have been suggested to follow an induced-fit mechanism in which the molecules first bind in the open conformation in those cases where binding in the closed conformation appears to be sterically obstructed such as for the HIV-1 protease. In this article, we present a general model for the catalysis and inhibition of enzymes with induced-fit binding mechanism. We derive general expressions that specify how the overall catalytic rate of the enzymes depends on the rates for binding, for the conformational changes, and for the chemical reaction. Based on these expressions, we analyze the effect of mutations that mainly shift the conformational equilibrium on catalysis and inhibition. If the overall catalytic rate is limited by product unbinding, we find that mutations that destabilize the closed conformation relative to the open conformation increase the catalytic rate in the presence of inhibitors by a factor exp(ΔΔG C /RT) where ΔΔG C is the mutation-induced shift of the free-energy difference between the conformations. This increase in the catalytic rate due to changes in the conformational equilibrium is independent of the inhibitor molecule and, thus, may help to understand how non-active-site mutations can contribute to the multi-drug-resistance that has been observed for the HIV-1 protease. A comparison to experimental data for the non-active-site mutation L90M of the HIV-1 protease indicates that the mutation slightly destabilizes the closed conformation of the enzyme. This article is part of a Special Issue entitled: The emerging dynamic view of proteins: Protein plasticity in allostery, evolution and self-assembly. [Copyright &y& Elsevier]

Abstract: The present work is designed to investigate the interaction of ZnS nanoparticles (NPs) with human serum albumin (HSA) using florescence spectroscopy. The results revealed the presence of static type of quenching mechanism in the binding of ZnS NPs to HSA. The association constant (Ka ) between ZnS NPs and HSA were obtained according to modified Stern–Volmer equation. Based on the thermodynamic parameters extracted from the fluorescence data, it was shown that the binding of ZnS NPs to HSA was driven mainly by van der Waals and hydrogen bonding interactions. Further, the competitive experiments using the site markers suggested that the binding site of ZnS NPs to HSA was located in the region of subdomain IIA (sudlow site I). Furthermore, synchronous fluorescence spectroscopy and temperature-induced denaturation study revealed the possibility of the change in the secondary structure of HSA molecules during the bonding and interaction with ZnS NPs. [Copyright &y& Elsevier]

Abstract: This article presents a data analysis method for biomarker discovery in proteomics data analysis. In factor analysis-based discriminate models, the latent variables (LV''s) are calculated from the response data measured at all employed instrument channels. Since some channels are irrelevant and their responses do not possess useful information, the extracted LV''s possess mixed information from both useful and irrelevant channels. In this work, clustering of variables (CLoVA) based on unsupervised pattern recognition is suggested as an efficient method to identify the most informative spectral region and then it is used to construct a more predictive multivariate classification model. In the suggested method, the instrument channels (m/z value) are clustered into different clusters via self-organization map. Subsequently, the spectral data of each cluster are separately used as the input variables of classification methods such as partial least square-discriminate analysis (PLS-DA) and extended canonical variate analysis (ECVA). The proposed method is evaluated by the analysis of two experimental data sets (ovarian and prostate cancer data set). It is found that our proposed method is able to detect cancerous from healthy samples with much higher sensitivity and selectivity than conventional PLS-DA and ECVA methods. [Copyright &y& Elsevier]

Abstract: Total current in the electroanalytical data is assumed to be consisting of three main constituents: faradaic current, step charging current and induced charging current. Both charging currents can cause an interfering effect on precise determination of faradaic currents, and hence insert direct effects on sensitivity and detection limit of the electroanalytical techniques. Despite the widespread techniques introduced until now, the extraction of the net faradaic current from total current still remains a challenge. In this work, by using multivariate curve resolution-alternating least square (MCR-ALS) as a powerful curve resolution-based chemometrics method, a straightforward method has been introduced for resolving faradaic current from the two types of charging currents (step charging current and induced charging current) in single potential step and staircase cyclic voltammetric methods. By simultaneous analyses of the current data matrices for different electrochemical systems, the three sources of current were successfully identified and their contributions in the total signal were easily calculated. Also, in this manner, the cell time constant can be obtained easily. Contrary to the previously reported methods, the present method does not need any pre-determined mathematical method; particularly there is no need to know the cell time constant. [Copyright &y& Elsevier]

The interaction of solvents with ultrasonic waves isof drasticimportance and has been the subject of many studies in recent years.In this study, the effect of solvent structural parameters on thespeed of sound in chemical solvents was investigated through a quantitativestructure–property relationship (QSPR). Genetic algorithm–multiplelinear regression (GA-MLR) analysis was employed to select the mostrelevant subset of descriptors and, then, to develop the model. Thevalidity of the obtained 10-parameter model was assessed by most widelyused validation techniques. The predictive power of the model wasevaluated by use of an external data set. The high level of accuracyof results approved the model. According to the model, those solventsthat have stronger solvent–solvent interactions can createa more appropriate medium for passing and propagating sound wavesand will result in higher speed of sounds. [ABSTRACT FROM AUTHOR]

The newly proposed hard–soft net analyte signal(HS-NAS)method was employed to determine the acidity constants of drugs. Thespectrophotometricdata obtained through monitoring of the pH-metric titrations of theacids (both experimental and simulated data) were analyzed by theHS-NAS method, and accurate results were obtained. As experimentaldata sets, tetracycline as a triprotic acid and p-aminobenzoic acid, m-aminobenzoic acid, and piroxicamas diprotic acids were studied. In addition, the acidity constantsof the drugs were determined in the presence of Triton X-100 as aninert light-absorbing interference. The data for such systems, whichare rank-deficient in nature, were successfully analyzed by the HS-NASmethod. This method is based on changing the acidity constants ofthe drugs to maximize the correlation coefficient between the NASvector obtained for one species of the reaction and the theoreticalconcentration profile of that species. Unlike existing methods, itneeds neither previous information on the pure spectra of the species(as required for rank annihilation factor analysis) nor the hard modelsof all species contributing to the absorbance of the solution (asneeded for the hard modeling method). [ABSTRACT FROM AUTHOR]

Abstract: The interaction between harmalol and human serum albumin (HSA) has been studied by fluorescence spectroscopy and molecular modeling methods. The intrinsic fluorescence of HSA was quenched by harmalol, which was rationalized in terms of the static quenching mechanism. The binding parameters, quenching constants and conformation changes were determined by fluorescence quenching method. The thermodynamic parameters, calculated from the temperature dependence of binding constants (i.e., ΔH°=−62.7kJmol−1 and ΔS°=−119.3Jmol−1 K−1), indicated the major role of van der Waals force and hydrogen bonding in binding process. Site marker competitive experiments revealed that harmalol binds to both the IIA and IIIA sub-domains of HSA with a slight preference toward sub-domain IIA. Finally, the binding of harmalol to HSA was modeled by molecular docking and molecular dynamic simulation methods. Excellent agreement was found between the experimental and theoretical results with respect to the mechanism of binding and binding constants. Molecular dynamic simulation revealed that HSA does not have a significant conformational change when it binds with harmalol. [Copyright &y& Elsevier]

Abstract: We employed segmented principal component analysis and regression, as a new methodology in quantitative structure–activity relationship (QSAR), to define new amino acid indices. The descriptors are first classified into different groups (based on the similarity in the information contents they are possessing) and then each group is subjected to principal component analysis (PCA), separately. The extracted principal components (PC) from the descriptor data matrix of each group can be considered as new sources of amino acid indices. These indices were used as input variables for QSAR study of two dipeptide data sets (58 angiotensin-converting enzyme (ACE) inhibitor activity, and 48 bitter tasting threshold (BTT) activity). Modeling between the indices and biological activity was achieved utilizing segmented principal component regression (SPCR) and segmented partial least squares (SPLS) methods. Both methods resulted in reliable QSAR models. In comparison with conventional principal component regression (PCR) and partial least square (PLS), the segmented ones produced more predictive models. In addition, the developed models showed better performances with respect to the previously reported models for the same data sets. It can be concluded that by segmentation of variables and partitioning of the information into informative and redundant parts, it is possible to discard the redundant part of variables and to obtain more appropriate models. [Copyright &y& Elsevier]

Abstract: A series of Schiff bases were studied for their delicate changes in absorption electronic spectra by changing substituents and solvents. UV/vis absorbance spectra of Schiff base derivatives of different substituents ranging from electron withdrawing to electron donating (Br, CF3, Cl, CN, CO2H, F, Me, NO2, OH, OMe, H) were studied in different solvents (acetonitrile, chloroform, cyclohexane, dioxane, dimethylsulfoxide and methanol). Linear relationships were established to investigate the effect of solute structure and solvatochromic parameters of solvents on the absorbance spectra. Meaningful chemical factors and then regression models were provided utilizing factor analysis (FA) and multiple linear regression (MLR). It was found that the frequency of maximum absorbance was mainly controlled by the solvent''s dipolarity/polarizability. The λ max of the ortho-nitro derivative represented the largest dependency on solvents’ polarity/polarizability so that it can be used as a solvatochromic probe. [Copyright &y& Elsevier]

The interactions of two organoplatinum complexes, [Pt(C^N)Cl(dppa)], 1, and [Pt(C^N)Cl(dppm)], 2 (C^N = N(1), C(2')-chelated, deprotonated 2-phenylpyridine,dppa = bis(diphenylphosphino)amine, dppm = bis(diphenylphosphino)methane), as antitumor agents, with bovine serum albumin (BSA) and human serum albumin (HSA) have been studied by fluorescence and UV-vis absorption spectroscopic techniques at pH 740. The quenching constants and binding parameters (binding constants and number of binding Sites) were determined by fluorescence quenching method. The obtained results revealed that there is a strong binding interaction between the ligands and proteins. The calculated thermodynamic parameters (ΔG, ΔH, and ΔS) confirmed that the binding reaction is mainly entropy-driven, and hydrophobic forces played a major role in the reaction. The displacement experiment shows that these Pt complexes can bind to the subdomain HA (site I) of albumin. Moreover, synchronous fluorescence spectroscopy studies revealed some changes in the local polarity around the tryptophan residues. Finally, the distance, r, between donor (serum albumin) and acceptor (Pt complexes) was obtained according to Förster theory of nonradiation energy transfer. [ABSTRACT FROM AUTHOR]