Ligand based virtual screening using SVM on GPU

In silico methods play an essential role in modern drug discovery methods. Virtual screening, an in silico method, is used to filter out the chemical space on which actual wet lab experiments are need to be conducted. Ligand based virtual screening is a computational strategy using which one can build a model of the target protein based on the knowledge of the ligands that bind successfully to the target. This model is then used to predict if the new molecule is likely to bind to the target. Support vector machine, a supervised learning algorithm used for classification, can be utilized for virtual screening the ligand data. When used for virtual screening purpose, SVM could produce interesting results. But since we have a huge ligand data, the time taken for training the SVM model is quite high compared to other learning algorithms. By parallelizing these algorithms on multi-core processors, one can easily expedite these discoveries. In this paper, a GPU based ligand based virtual screening tool (GpuSVMScreen) which uses SVM have been proposed and bench-marked. This data parallel virtual screening tool provides high throughput by running in short time. The proposed GpuSVMScreen can successfully screen large number of molecules (billions) also. The source code of this tool is available at http://ccc.nitc.ac.in/project/GPUSVMSCREEN.     

Fully automatic assignment of small molecules' NMR spectra without relying on chemical shift predictions

We present a method for the automatic assignment of small molecules' NMR spectra. The method includes an automatic and novel self‐consistent peak‐picking routine that validates NMR peaks in each spectrum against peaks in the same or other spectra that are due to the same resonances. The auto‐assignment routine used is based on branch‐and‐bound optimization and relies predominantly on integration and correlation data; chemical shift information may be included when available to fasten the search and shorten the list of viable assignments, but in most cases tested, it is not required in order to find the correct assignment. This automatic assignment method is implemented as a web‐based tool that runs without any user input other than the acquired spectra. Copyright © 2015 John Wiley & Sons, Ltd.     

Automated assignment of charge states from resolved isotopic peaks for multiply charged ions

The recent proliferation of electrospray as an ionization method has greatly increased the ability to perform analyses of large biomolecules by using mass spectrometry. The major advantage of electrospray is the ability to produce multiply charged ions, which brings large molecules down to a mass-to-charge ratio range amenable to most instruments. Multiple charging is also a disadvantage because mass (m) becomes ambiguous unless charge (z) can be assigned. This is typically performed with simple algorithms that use multiple peaks of the same m and different z, but these methods are difficult to apply to complex mixtures and not applicable when only one z appears for each m. The use of mass analyzers with higher resolving powers, like the Fourier transform mass spectrometer, allows resolution of isotopic peaks, providing an internal 1-Da mass scale that can be used for unambiguous charge assignment. Manual assignment of charge state from the isotopic peaks is time consuming and becomes inaccurate when either the signal level or resolving power are low. For these cases, computer algorithms based on pattern recognition techniques have been developed to assist in assignment of charge states to isotopic clusters. These routines provide for more rapid analysis with higher accuracy than available manually.     

Structure verification through computer‐assisted spectral assignment of NMR spectra

The validation of a molecular organic structure on the basis of 1D and 2D HSQC, COSY and HMBC NMR spectra is proposed as an alternative to the methods that are mainly based on chemical shift prediction. The CCASA software was written for this purpose. It provides an updated and improved implementation of the preceding computer‐assisted spectral assignment software. CCASA can be downloaded freely from http://www.univ‐reims.fr/LSD/JmnSoft/CASA . Two bioactive natural products, a triterpene and a benzophenone, were selected from literature data as examples. The tentative matching between the structure and the NMR data interpretation of the triterpene unexpectedly leads to the hypothesis of an incorrect structure. The LSD software was used to find an alternative structure that improved the 2D NMR data interpretation and the carbon‐13 chemical shift matching between experimental values and those produced by the nmrshiftdb2 prediction tool. The benzophenone example showed that signal assignment by means of chemical shift prediction can be replaced by elementary user‐supplied chemical shift and multiplicity constraints. Copyright © 2012 John Wiley & Sons, Ltd.     

Dead-end elimination for multistate protein design

Multistate protein design is the task of predicting the amino acid sequence that is best suited to selectively and stably fold to one state out of a set of competing structures. Computationally, it entails solving a challenging optimization problem. Therefore, notwithstanding the increased interest in multistate design, the only implementations reported are based on either genetic algorithms or Monte Carlo methods. The dead-end elimination (DEE) theorem cannot be readily transfered to multistate design problems despite its successful application to single-state protein design. In this article we propose a variant of the standard DEE, called type-dependent DEE. Our method reduces the size of the conformational space of the multistate design problem, while provably preserving the minimal energy conformational assignment for any choice of amino acid sequence. Type-dependent DEE can therefore be used as a preprocessing step in any computational multistate design scheme. We demonstrate the applicability of type-dependent DEE on a set of multistate design problems and discuss its strength and limitations.     

PreSSAPro: a software for the prediction of secondary structure by amino acid properties

PreSSAPro is a software, available to the scientific community as a free web service designed to provide predictions of secondary structures starting from the amino acid sequence of a given protein. Predictions are based on our recently published work on the amino acid propensities for secondary structures in either large but not homogeneous protein data sets, as well as in smaller but homogeneous data sets corresponding to protein structural classes, i.e. all-alpha, all-beta, or alpha–beta proteins. Predictions result improved by the use of propensities evaluated for the right protein class. PreSSAPro predicts the secondary structure according to the right protein class, if known, or gives a multiple prediction with reference to the different structural classes. The comparison of these predictions represents a novel tool to evaluate what sequence regions can assume different secondary structures depending on the structural class assignment, in the perspective of identifying proteins able to fold in different conformations. The service is available at the URL http://bioinformatica.isa.cnr.it/PRESSAPRO/.     

Semiautomatic sequence-specific assignment of proteins based on the tertiary structure--the program st2nmr

The sequence-specific assignment of resonances is still the most time-consuming procedure that is necessary as the first step in high-resolution NMR studies of proteins. In many cases a reliable three-dimensional (3D) structure of the protein is available, for example, from X-ray spectroscopy or homology modeling. Here we introduce the st2nmr program that uses the 3D structure and Nuclear Overhauser Effect spectroscopy (NOESY) peak list(s) to evaluate and optimize trial sequence-specific assignments of spin systems derived from correlation spectra to residues of the protein. A distance-dependent target function that scores trial assignments based on the presence of expected NOESY crosspeaks is optimized in a Monte Carlo fashion. The performance of the program st2nmr is tested on real NMR data of an alpha-helical (cytochrome c) and beta-sheet (lipocalin) protein using homology models and/or X-ray structures; it succeeded in completely reproducing the correct sequence-specific assignments in most cases using 2D and/or 15N/13C Nuclear Overhauser Effect (NOE) data. Additionally to amino acid residues the program can also handle ligands that are bound to the protein, such as heme, and can be used as a complementary tool to fully automated assignment procedures.     

Multilocus consensus genetic maps (MCGM): formulation, algorithms, and results

In process of creating genetic maps different labs/research groups obtain overlapping parts of the map. Merging these parts into one integrative map is based on looking for maximum shared marker orders among the maps. Really, not all shared markers of such maps have consensus order that obstructs building of the integrative maps. In this paper we propose a new approach to build verified multilocus consensus genetic maps in which shared markers always are integrated in stable consensus order. The approach is based on combined analysis of initial mapping data rather than manipulating with previously constructed maps. We show that more effective and reliable solutions may be obtained based on "synchronized ordering" facilitated by cycles of "re-sampling-->ordering-->removing unstable markers". The proposed formulation of consensus genetic mapping can be considered as a version of traveling salesperson problem (TSP) that we refer to as synchronized-TSP. From the viewpoint of optimization, synchronized-TSP belongs to discrete constrained optimization problems. Earlier we developed new powerful and fast guided evolution strategy algorithms for some types of discrete constrained optimization. These algorithms were used here as a basis for solving more challenging problems of consensual marker ordering.     

Biosynthetic phage display: a novel protein engineering tool combining chemical and genetic diversity

BACKGROUND: Molecular diversity in nature is developed through a combination of genetic and chemical elements. We have developed a method that permits selective manipulation of both these elements in one protein engineering tool. It combines the ability to introduce non-natural amino acids into a protein using native chemical ligation with exhaustive targeted mutagenesis of the protein via phage-display mutagenesis. RESULTS: A fully functional biosynthetic version of the protease inhibitor eglin c was constructed. The amino-terminal fragment (residues 8-40) was chemically synthesized with a non-natural amino acid at position 25. The remaining carboxy-terminal fragment was expressed as a 30-residue peptide extension of gIIIp or gVIIIp on filamentous phage in a phage-display mutagenesis format. Native chemical ligation was used to couple the two fragments and produced a protein that refolded to its active form. To facilitate the packing of the introduced non-natural amino acid, residues 52 and 54 in the carboxy-terminal fragment were fully randomized by phage-display mutagenesis. Although the majority of the observed solutions for residues 52 and 54 were hydrophobic - complementing the stereochemistry of the introduced non-natural amino acid - a significant number of residues (unexpected because of stereochemical and charge criteria) were observed in these positions. CONCLUSIONS: Peptide synthesis and phage-display mutagenesis can be combined to produce a very powerful protein engineering tool. The physical properties of the environment surrounding the introduced non-natural residue can be selected for by evaluating all possible combinations of amino acid types at a targeted set of sites using phage-display mutagenesis.     

Assignment of the absolute configuration of hydroxy- and aminophosphonates by NMR spectroscopy

Phosphonate analogues of amino- and hydroxy acids have received considerable attention in bioorganic and medicinal chemistry due to their unique activities as peptidomimetics, being known as inhibitors of such enzymes as human renin, HIV protease and polymerase, leucine aminopeptidase and serine proteases. They have also been exploited as haptens for catalytic antibody research, herbicides, antibiotics, antiviral and anticancer agents and neuromodulators. Therefore, the demand for the asymmetric synthesis of hydroxy- and aminophosphonates should be accompanied by reliable methods for their absolute configuration assignment. NMR spectroscopy is one of the most commonly used techniques for the assignment of absolute configuration of different classes of compounds. This report describes the principles and practical aspects of applying chiral discriminating agents for the assignment of absolute configuration of 1- and 2-hydroxyphosphonates and 1- and 2-aminophosphonates by NMR spectroscopy. The report is organized in sections discussing the types of the chiral discriminating agents (including the models used for configuration assignment, if this was proposed) and the scope of their applications (with the list of all the examples of hydroxy- and aminophosphonates examined by this method). The application of the chiral derivatizing agents (CDA) and chiral solvating agents (CSA) used for these purposes, such as α-methoxy-α-(trifluoromethyl)phenylacetic acid (MTPA), α-methoxyphenylacetic acid (MPA), amino acids, diazaphospholidine, camphanic acid, naproxen, quinine and t-butylphenylphosphinothioic acid is discussed. Easy access to the selected values of the NMR chemical shifts observed for the diastereomeric species of the tested hydroxy- and aminophosphonates examined, will enable the reader to compare trends observed in spectra and subsequent absolute configuration assignment. In addition, any available complementary data confirming the configuration established by NMR (X-ray, chemical correlations, optical rotation) is also provided.     

A combinatorial selective labeling method for the assignment of backbone amide NMR resonances

A combinatorial selective labeling (CSL) method is presented for the assignment of backbone amide NMR resonances, which has a particular application in the identification of protein-ligand interaction sites. The method builds on the dual amino acid selective labeling technique. In the CSL method a number of different samples are produced, each with a different pattern of labeled amino acids. By analyzing peak intensities in HSQC and 2D HNCO spectra of these samples, a large number of combinations of amino acid pairs can be simultaneously assigned. We demonstrate the method on the 27 kDa protein GFP. The samples can be produced rapidly and cost-effectively in a commercially available in vitro translation system. The method greatly simplifies the process of backbone assignment and would be very straightforward to automate.     

Gas chromatography of amino acids.

This review summarizes all papers that have appeared on the gas chromatography of amino acids (including the iodoamino acids) and their enantiomers in the period 1956-mid-1974. It has been found that the methods used for analysis of amino acids can be divided into three classes: (1) degradative procedures and techniques for converting the amino acid into another chemical compound; (2) procedures based on esterification of the carboxyl group and derivatization of the a-amino and other reactive groups in at least two steps; and (3) procedures based on a simultaneous derivatization of the carboxyl and a-amino groups in one reaction medium. For the treatment of the amino acid or its alkyl ester, three approaches can be distinguished for the two latter cases, i.e., acylation, alkylation (including silylation) and condensation. Of the procedures used for the resolution of optical antipodes, two methods are discussed, namely analysis of diastereoisomers on optically inactive stationary phases and separation of enantiomers on optically active stationary phases.     

Binding pose and affinity prediction in the 2016 D3R Grand Challenge 2 using the Wilma-SIE method

The Farnesoid X receptor (FXR) exhibits significant backbone movement in response to the binding of various ligands and can be a challenge for pose prediction algorithms. As part of the D3R Grand Challenge 2, we tested Wilma-SIE, a rigid-protein docking method, on a set of 36 FXR ligands for which the crystal structures had originally been blinded. These ligands covered several classes of compounds. To overcome the rigid protein limitations of the method, we used an ensemble of publicly available structures for FXR from the PDB. The use of the ensemble allowed Wilma-SIE to predict poses with average and median RMSDs of 2.3 and 1.4 Å, respectively. It was quite clear, however, that had we used a single structure for the receptor the success rate would have been much lower. The most successful predictions were obtained on chemical classes for which one or more crystal structures of the receptor bound to a molecule of the same class was available. In the absence of a crystal structure for the class, observing a consensus binding mode for the ligands of the class using one or more receptor structures of other classes seemed to be indicative of a reasonable pose prediction. Affinity prediction proved to be more challenging with generally poor correlation with experimental IC50s (Kendall tau?~?0.3). Even when the 36 crystal structures were used the accuracy of the predicted affinities was not appreciably improved. A possible cause of difficulty is the internal energy strain arising from conformational differences in the receptor across complexes, which may need to be properly estimated and incorporated into the SIE scoring function.     

Effects of amino acid phi,psi propensities and secondary structure interactions in modulating H alpha chemical shifts in peptide and protein beta-sheet.

H alpha chemical shifts are often used as indicators of secondary structure formation in protein structural analysis and peptide folding studies. On the basis of NMR analysis of model beta-sheet and alpha-helical peptides, together with a statistical analysis of protein structures for which NMR data are available, we show that although the gross pattern of H alpha chemical shifts reflects backbone torsion angles, longer range effects from distant amino acids are the dominant factor determining experimental chemical shifts in beta-sheets of peptides and proteins. These show context-dependent variations that aid structural assignment and highlight anomalous shifts that may be of structural significance and provide insights into beta-sheet stability.     

The correct molecular weight of myoglobin, a common calibrant for mass spectrometry.

Myoglobins from horse heart muscle, horse skeletal muscle and sperm whale are widely used as calibration standards or test compounds for various mass spectrometric methodologies. In all such cases reported in the literature, a molecular weight value is used (16,950.5 and 17,199, respectively) which is based on the assumption that amino acid 122 in this 153 amino-acid-long protein is asparagine, overlooking a published suggestion that it is aspartic acid instead. Since the mass assignment accuracy for matrix-assisted laser desorption mass spectrometry is reported to be +/- 0.01% and for electrospray ionization +/- 0.0025%, and error of one mass unit in approximately 17,000 would be significant. The mass-to-charge ratio of ions of the tryptic peptide encompassing amino acid 122 derived from commercially available horse heart and horse skeletal myoglobins, the apomyoglobin of the latter, and the tryptic and chymotryptic peptide of sperm whale myoglobin proved that in both proteins amino acid 122 is indeed aspartic acid, rather than asparagine. This finding was further confirmed by the collision-induced dissociation spectra of the [M + H]+ ions of the tryptic peptides from the horse myoglobins and the chymotriptic peptide from sperm whale myoglobin. Thus, the correct molecular weight of horse myoglobin is 16,951.49 and that of the sperm whale protein is 17,199.91.     

Reduced dimensionality (3,2)D NMR experiments and their automated analysis: implications to high‐throughput structural studies on proteins

Protein NMR spectroscopy has expanded dramatically over the last decade into a powerful tool for the study of their structure, dynamics, and interactions. The primary requirement for all such investigations is sequence‐specific resonance assignment. The demand now is to obtain this information as rapidly as possible and in all types of protein systems, stable/unstable, soluble/insoluble, small/big, structured/unstructured, and so on. In this context, we introduce here two reduced dimensionality experiments – (3,2)D‐hNCO canH and (3,2)D‐hN coCA nH – which enhance the previously described 2D NMR‐based assignment methods quite significantly. Both the experiments can be recorded in just about 2–3 h each and hence would be of immense value for high‐throughput structural proteomics and drug discovery research. The applicability of the method has been demonstrated using alpha‐helical bovine apo calbindin‐D9k P43M mutant (75 aa) protein. Automated assignment of this data using AUTOBA has been presented, which enhances the utility of these experiments. The backbone resonance assignments so derived are utilized to estimate secondary structures and the backbone fold using Web‐based algorithms. Taken together, we believe that the method and the protocol proposed here can be used for routine high‐throughput structural studies of proteins. Copyright © 2014 John Wiley & Sons, Ltd.     

Synthesis of noval chiral tridentate amino alcohols as chiral solvating agents under ball-milling conditions

A new family of chiral solvating agents based on chiral didentate amino alcohols and chloromethyl pyridine derivatives were synthesized by ball milling in solvent free condition. The new chiral tridentate amino alcohols were tested as chiral NMR solvating agents for the Ts-derivatives of amino acids, other several acids and pyrazole drugs. For the Ts-derivatives of amino acids studied herein, chiral tridentate amino alcohol 3a could be used for the assignment of the absolute configurations of their racemes through the chemical shift non-equivalences of their CH₃ (Ts) protons with certain confidence.     

Determining secondary structure in spider dragline silk by carbon-carbon correlation solid-state NMR spectroscopy

Two-dimensional (2D) (13)C-(13)C NMR correlation spectra were collected on (13)C-enriched dragline silk fibers produced from Nephila clavipes spiders. The 2D NMR spectra were acquired under fast magic-angle spinning (MAS) and dipolar-assisted rotational resonance (DARR) recoupling to enhance magnetization transfer between (13)C spins. Spectra obtained with short (150 ms) recoupling periods were utilized to extract distinct chemical shifts for all carbon resonances of each labeled amino acid in the silk spectra, resulting in a complete resonance assignment. The NMR results presented here permit extraction of the precise chemical shift of the carbonyl environment for each (13)C-labeled amino acid in spider silk for the first time. Spectra collected with longer recoupling periods (1 s) were implemented to detect intermolecular magnetization exchange between neighboring amino acids. This information is used to ascribe NMR resonances to the specific repetitive amino acid motifs prevalent in spider silk proteins. These results indicate that glycine and alanine are both present in two distinct structural environments: a disordered 3(1)-helical conformation and an ordered beta-sheet structure. The former can be ascribed to the Gly-Gly-Ala motif while the latter is assigned to the poly(Ala) and poly(Gly-Ala) domains.