Automated discrimination of polymerase chain reaction products with closely related sequences by software-based detection of characteristic peaks in product ion spectra

A computer-based method is described for automated detection of peaks in product ion spectra that allows discrimination of structurally related polymerase chain reaction (PCR) products. PCR products of K-ras mutants having single nucleotide substitutions and isomeric sequence changes in positions 1 and 2 of codon 12 (e.g. TGT and GTT) were used as a model system. SpecDiff, a tool for differentiating pairs of mass spectra by identifying peaks that either differ in relative intensity between spectra or only appear in one of a pair of spectra, was created to help automate detection. This program was demonstrated to have great utility in detection of mutations and could also be useful as a general tool for differentiating other molecules of closely related structure.     

Direct glycan structure determination of intact N-linked glycopeptides by low-energy collision-induced dissociation tandem mass spectrometry and predicted spectral library searching

Intact glycopeptide MS analysis to reveal site-specific protein glycosylation is an important frontier of proteomics. However, computational tools for analyzing MS/MS spectra of intact glycopeptides are still limited and not well-integrated into existing workflows. In this work, a new computational tool which combines the spectral library building/searching tool, SpectraST (Lam et al. Nat. Methods2008, 5, 873–875), and the glycopeptide fragmentation prediction tool, MassAnalyzer (Zhang et al. Anal. Chem.2010, 82, 10194–10202) for intact glycopeptide analysis has been developed. Specifically, this tool enables the determination of the glycan structure directly from low-energy collision-induced dissociation (CID) spectra of intact glycopeptides. Given a list of possible glycopeptide sequences as input, a sample-specific spectral library of MassAnalyzer-predicted spectra is built using SpectraST. Glycan identification from CID spectra is achieved by spectral library searching against this library, in which both m/z and intensity information of the possible fragmentation ions are taken into consideration for improved accuracy. We validated our method using a standard glycoprotein, human transferrin, and evaluated its potential to be used in site-specific glycosylation profiling of glycoprotein datasets from LC-MS/MS. In addition, we further applied our method to reveal, for the first time, the site-specific N-glycosylation profile of recombinant human acetylcholinesterase expressed in HEK293 cells. For maximum usability, SpectraST is developed as part of the Trans-Proteomic Pipeline (TPP), a freely available and open-source software suite for MS data analysis.     

Lessons learned in induced fit docking and metadynamics in the Drug Design Data Resource Grand Challenge 2

Two of the major ongoing challenges in computational drug discovery are predicting the binding pose and affinity of a compound to a protein. The Drug Design Data Resource Grand Challenge 2 was developed to address these problems and to drive development of new methods. The challenge provided the 2D structures of compounds for which the organizers help blinded data in the form of 35 X-ray crystal structures and 102 binding affinity measurements and challenged participants to predict the binding pose and affinity of the compounds. We tested a number of pose prediction methods as part of the challenge; we found that docking methods that incorporate protein flexibility (Induced Fit Docking) outperformed methods that treated the protein as rigid. We also found that using binding pose metadynamics, a molecular dynamics based method, to score docked poses provided the best predictions of our methods with an average RMSD of 2.01 Å. We tested both structure-based (e.g. docking) and ligand-based methods (e.g. QSAR) in the affinity prediction portion of the competition. We found that our structure-based methods based on docking with Smina (Spearman ρ?=?0.614), performed slightly better than our ligand-based methods (ρ?=?0.543), and had equivalent performance with the other top methods in the competition. Despite the overall good performance of our methods in comparison to other participants in the challenge, there exists significant room for improvement especially in cases such as these where protein flexibility plays such a large role.     

Unraveling solvent-driven equilibria between alpha- and 3(10)-helices through an integrated spin labeling and computational approach

In this work we present an effective and flexible computational approach, which is the result of an ongoing development in our groups, allowing the complete a priori simulation of the ESR spectra of complex systems in solution. The usefulness and reliability of the method are demonstrated on the very demanding playground represented by the tuning of the equilibrium between 3(10)- and alpha-helices of polypeptides by different solvents. The starting point is the good agreement between computed and X-ray diffraction structures for the 3(10)-helix adopted by the double spin-labelled heptapeptide Fmoc-(Aib-Aib-TOAC)2-Aib-OMe. Next, density functional computations, including dispersion interactions and bulk solvent effects, suggest another energy minimum corresponding to an alpha-helix in polar solvents, which, eventually, becomes the most stable structure. Computation of magnetic and diffusion tensors provides the basic ingredients for the building of complete spectra by methods rooted in the Stochastic Liouville Equation (SLE). The remarkable agreement between computed and experimental spectra at different temperatures allowed us to identify helical structures in the various solvents. The generality of the computational strategy and its implementation in effective and user-friendly computer codes pave the route toward systematic applications in the field of biomolecules and other complex systems.     

Integrating virtual screening and combinatorial chemistry for accelerated drug discovery

Virtual screening is increasingly being used in drug discovery programs with a growing number of successful applications. Experimental methodologies developed to speed up the drug discovery processes include high-throughput screening and combinatorial chemistry. The complementarities between computational and experimental screenings have been recognized and reviewed in the literature. Computational methods have also been used in the combinatorial chemistry field, in particular in library design. However, the integration of computational and combinatorial chemistry screenings has been attempted only recently. Combinatorial libraries (experimental or virtual) represent a notable source of chemically related compounds. Advances in combinatorial chemistry and deconvolution strategies, have enabled the rapid exploration of novel and dense regions in the chemical space. The present review is focused on the integration of virtual and experimental screening of combinatorial libraries. Applications of virtual screening to discover novel anticancer agents and our ongoing efforts towards the integration of virtual screening and combinatorial chemistry are also discussed.     

Computational prediction of ionic liquid 1-octanol/water partition coefficients

Wet 1-octanol/water partition coefficients (log?K(ow)) predicted for imidazolium-based ionic liquids using adaptive bias force-molecular dynamics (ABF-MD) simulations lie in excellent agreement with experimental values. These encouraging results suggest prospects for this computational tool in the a priori prediction of log?K(ow) values of ionic liquids broadly with possible screening implications as well (e.g., prediction of CO(2)-philic ionic liquids).     

Development of an on-site screening system for amphetamine-type stimulant tablets with a portable attenuated total reflection Fourier transform infrared spectrometer

We tried to develop a library search system using a portable, attenuated total reflection Fourier transform infrared (ATR-FT-IR) spectrometer for on-site identification of 3,4-methylenedioxymethamphetamine (MDMA) and 3,4-methylenedioxyamphetamine (MDA) tablets. The library consisted of the spectra from mixtures of controlled drugs (e.g. MDMA and ketamine), adulterants (e.g. caffeine), and diluents (e.g. lactose). In the seven library search algorithms, the derivative correlation coefficient showed the best discriminant capability. This was enhanced by segmentation of the search area. The optimized search algorithm was validated by the positive (n = 154, e.g. the standard mixtures containing the controlled drug, and the MDMA/MDA tablets confiscated) and negative samples (n = 56, e.g. medicinal tablets). All validation samples except for four were judged truly. Final criteria for positive identification were decided on the basis of the results of the validation. In conclusion, a portable ATR-FT-IR spectrometer with our library search system would be a useful tool for on-site identification of amphetamine-type stimulant tablets.     

Analyses of three-way data from equilibrium and kinetic investigations

In kinetic or equilibrium investigations it is common to measure two-way multiwavelength data, e.g. absorption spectra as a function of time or reagent addition. Often it is advantageous to acquire experimental data at various initial conditions or even on different instruments. A collection of these measurements can be arranged in three-dimensional arrays, which can be analysed as a whole under the assumption of a superimposed function, e.g. a kinetic model, and/or common properties of the subsets, such as molar absorptivity. As we show on selected formation equilibria (Zn²⁺/phen) and kinetic studies (Cu²⁺/cyclam) from our own research, an appropriate combination of multivariate data can lead to an improved analysis of the investigated systems.     

Identification of Abnormal Urinary Organic Acids in Inherited Metabolic Diseases by Gas Chromatography-Mass Spectrometry

A gas chromatography/mass spectrometry (GC/MS) coupled system has been established for the confirmatory identification of abnormal urinary organic acids in inherited metabolic diseases. Samples of patient urines were extracted with an organic solvent and trimethylsilylated (TMS). A mass spectra of gas chromatographically separated TMS derivatives can be obtained using the GC/MS coupled system with a single analytical run. Those compounds with close methylene units (e.g., 4-hydroxyphenylacetaic acid and phenylpyruvic acid) in the gas chromatograph can be identified by their specific mass spectra. The results indicate that this GC/MS system is a powerful method for identifying abnormal urinary organic acids. These acids can be identified by comparison with authentic mass spectra established in our laboratories or with mass spectra files from other sources or they can be directly identified by analysis of the mass spectrum. By using this system, we were able to make positive identification of several inherited metabolic diseases found in Chinese patients, including phenylketonuria, propionic acidemia, and methylmalonic aciduria. This GC/MS system is a powerful tool for the diagnosis of inherited metabolic diseases.     

CCSfind: A tool for chemically informed LC-IM-MS database building

In addition to providing critical knowledge of the accurate mass of ions, ion mobility-mass spectrometry (IM-MS) delivers complementary data relating to the conformation and size of ions in the form of an ion mobility spectrum and derived parameters, namely, the ion's mobility (K) and the IM-derived collision cross section (CCS). However, the maximum amount of information obtained in IM-MS measurements is not currently transferred into analytical databases including the full mobility spectra (CCS distributions) as well as capturing of additional ion species (e.g., adducts) into the same compound entry. We introduce CCSfind, a new tool for building comprehensive databases from experimental IM-MS measurements of small molecules. CCSfind allows predicted ion species to be chosen for input chemical formulae, which are then targeted by CCSfind after parsing open source mzML input files to provide a unified set of results within a single data processing step. CCSfind can handle both chromatographically separated isomers and IM separation of isomeric ions (e.g., “protomers” or conformers of the same ion species) with simple user control over the output for new database entries in SQL format. Files of up to 1 GB can be processed in less than 2 min on a desktop computer with 32 GB RAM with computational time scaling linearly with the size of the input mzML file or the number of input molecular formulae. Results are manually reviewed, annotated with experimental settings, before committing the database where the full dataset can be retrieved.     

Fourier-transform infrared and Raman spectra,and ab initio calculations for cadmium-n-di-iso-propylphosphorylguanidine-di-chloride (CdDPGCl2) complex

Cadmium-n-di-isopropylphosphorylguanidine-di-chloride (CdDPGCl2) was synthesized in the solid phase and characterized previously. The Fourier transform infrared and Raman spectra of (CdDPGCl2) in the solid state were recorded and analyzed. Emphasis was placed on the vibrational assignment of the [(O2P=O-[CdCl2]-HN=C) fragment of the complete molecular structure. With the aim of assisting the vibrational assignment of the experimental spectra, a comparison with the spectra of N-di-isopropylphosphorylguanidine ligand was carried out and ab initio calculations have been performed with several effective core potentials and valence basis sets (Hay-Wadt (HW) and Stevens-Basch-Krauss (SBK)). Due to our limited computational resources, hydrogen atoms replaced the isopropyl groups. The calculated geometrical parameters showed excellent agreement with the experimental, as well as the RHF/MP2 calculated infrared wave numbers, when compared to the IR/Raman experimental wave numbers.     

Solvent viscosity dependence of the protein folding dynamics

Solvent viscosity has been frequently adopted as an adjustable parameter in various computational studies (e.g., protein folding simulations) with implicit solvent models. A common approach is to use low viscosities to expedite simulations. While using viscosities lower than that of aqueous is unphysical, such treatment is based on observations that the viscosity affects the kinetics (rates) in a well-defined manner as described by Kramers' theory. Here, we investigate the effect of viscosity on the detailed dynamics (mechanism) of protein folding. On the basis of a simple mathematical model, we first show that viscosity may indeed affect the dynamics in a complex way. By applying the model to the folding of a small protein, we demonstrate that the detailed dynamics is affected rather pronouncedly especially at unphysically low viscosities, cautioning against using such viscosities. In this regard, our model may also serve as a diagnostic tool for validating low-viscosity simulations. It is also suggested that the viscosity dependence can be further exploited to gain information about the protein folding mechanism.     

Orthogonal transformations for feature extraction in chemical pattern recognition

A crucial point in pattern recognition methods is the extraction of features to determine the pattern vectors. Orthogonal transformations, e.g., Fourier, Walsh and Haar, are investigated as preprocessing methods for feature extraction. The theoretical considerations and conclusions are compared with computational results obtained by applying different pattern recognition methods to two different but similar collections of low-resolution mass spectra.     

Using intrinsic X-ray absorption spectral differences to identify and map peptides and proteins

The intrinsic variation in the near-edge X-ray absorption fine structure (NEXAFS) spectra of peptides and proteins provide an opportunity to identify and map them in various biological environments, without additional labeling. In principle, with sufficiently accurate spectra, peptides (<50 amino acids) or proteins with unusual sequences (e.g., cysteine- or methionine-rich) should be differentiable from other proteins, since the NEXAFS spectrum of each amino acid is distinct. To evaluate the potential for this approach, we have developed X-SpecSim, a tool for quantitatively predicting the C, N, and O 1s NEXAFS spectra of peptides and proteins from their sequences. Here we present the methodology for predicting such spectra, along with tests of its precision using comparisons to the spectra of various proteins and peptides. The C 1s, N 1s, and O 1s spectra of two novel antimicrobial peptides, Indolicidin (ILPWKWPWWPWRR-NH2) and Sub6 (RWWKIWVIRWWR-NH2), as well as human serum albumin and fibrinogen are reported and interpreted. The ability to identify, differentiate, and quantitatively map an antimicrobial peptide against a background of protein is demonstrated by a scanning transmission X-ray microscopy study of a mixture of albumin and sub6.     

异硫氰酸荧光素-溶菌酶的制备及晶体生长预研究

迄今尚未有适用于光源为488 nm激光扫描共聚焦显微镜研究用的溶菌酶. 为此, 用异硫氰酸荧光素作为探针标记了溶菌酶, 测定了溶菌酶标记物的紫外-可见吸收光谱和荧光光谱, 摸索了其晶体的生长条件. 实验结果表明, 在标记过程中异硫氰酸荧光素没有影响溶菌酶的生化性质, 标记后的溶菌酶可用于激光扫描共聚焦显微镜进行后续研究.     

In silico-aided prediction of biological properties of chemicals: oestrogen receptor-mediated effects

In silico methods are a valid tool for analysing the properties of chemical compounds and interest in computational modelling techniques to predict the activity of chemicals is constantly growing. Many computational methods can be used to analyse the toxicity or biological activity of chemicals, particularly as regards their interactions with biological macromolecules (e.g. receptors) and other physico-chemical properties. An overview of these methods is provided in this tutorial review, with some examples of their application to predict oestrogen receptor (ER)-mediated effects. Nuclear receptors, particularly ER, have been studied with in silico tools since concern is growing about substances, called endocrine disrupters, that can interfere with hormone regulation. Molecular modelling techniques such as Quantitative Structure-Activity Relationships (QSAR), related methods like 3D-QSAR, and virtual docking have been used to investigate these phenomena and are described here. Implications about regulatory acceptance and use of these methods and the resulting models for identifying hazards and setting priorities are also addressed.     

Environmental Effects in Computational Spectroscopy: Accuracy and Interpretation

Spectroscopic techniques are valuable tools for understanding the structure and dynamics of complex systems, such as biomolecules or nanomaterials. Most of the current research is devoted to the development of new experimental techniques for improving the intrinsic resolution of different spectra. However, the subtle interplay of several different effects acting at different length and time scales still makes the interpretation and analysis of such spectra a very difficult task. In this respect, computational spectroscopy is becoming a needful and versatile tool for the assignment and interpretation of experimental spectra. It is in fact possible nowadays to model with relatively high accuracy the physical–chemical properties of complex molecules in different environments, and to link spectroscopic evidence directly to the structural and dynamical properties of optically or magnetically active solvated probes. In this Review, significant steps toward the simulation of entire spectra in condensed phases are presented together with some basic aspects of computational spectroscopy, which highlight how intramolecular and intermolecular degrees of freedom influence several spectroscopic parameters.