3DSDSCAR—a three dimensional structural database for sialic acid-containing carbohydrates through molecular dynamics simulation

Carbohydrate Research 345 (2010) 2030–2037

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Carbohydrate Research journal homepage: www.elsevier.com/locate/carres

3DSDSCAR—a three dimensional structural database for sialic acid-containing carbohydrates through molecular dynamics simulation Kasinadar Veluraja *, Jeyasigamani F. A. Selvin, Selvakumar Venkateshwari, Thanu R. K. Priyadarzini Department of Physics, Manonmaniam Sundaranar University, Tirunelveli 627 012, Tamilnadu, India

a r t i c l e

i n f o

Article history: Received 6 May 2010 Received in revised form 19 June 2010 Accepted 28 June 2010 Available online 8 July 2010 Keywords: Sialic acid Molecular dynamics simulation Three dimensional structure Conformational model Database

a b s t r a c t The inherent flexibility and lack of strong intramolecular interactions of oligosaccharides demand the use of theoretical methods for their structural elucidation. In spite of the developments of theoretical methods, not much research on glycoinformatics is done so far when compared to bioinformatics research on proteins and nucleic acids. We have developed three dimensional structural database for a sialic acidcontaining carbohydrates (3DSDSCAR). This is an open-access database that provides 3D structural models of a given sialic acid-containing carbohydrate. At present, 3DSDSCAR contains 60 conformational models, belonging to 14 different sialic acid-containing carbohydrates, deduced through 10 ns molecular dynamics (MD) simulations. The database is available at the URL: http://www.3dsdscar.org. Ó 2010 Elsevier Ltd. All rights reserved.

1. Introduction The ubiquitous presence and the structural versatility of carbohydrates make their role indispensable for numerous biological processes ranging from structural stabilisation to a variety of immunologically important molecular recognition events. Carbohydrates can occur in free form as oligosaccharides and in complexed form with other classes of biomolecules as glycoconjugates. Most of the oligosaccharide structures, including gangliosides which are recognised by toxins and viruses as receptors, invariably contain negatively charged sialic acid residues.1–16 Sialic acid-containing oligosaccharides act as good receptors for cholera toxin, heat labile enterotoxin, botulinum neurotoxin and simian virus.17–23 In order to understand the molecular mechanisms of carbohydrate-mediated recognition processes, it is necessary to understand the structural flexibility and solution dynamics of oligosaccharides. The dramatic increase in the computing power and computational software has led to significant progress in the conformational analysis and database development for biomolecular structure. There are a number of databases available for sequential and structural data of proteins and nucleic acids. UniProt and PDB (Protein Data Bank) are the two well-known examples for the sequential and structural databases of proteins.24,25 Genbank, DNA Data Bank of Japan (DDBJ) and EMBL-Bank are the major repositories for nucleic acid data. A lot of work has been done in the field of glycoinformatics regarding the structural elucidation and analysis of carbohydrate

* Corresponding author. Tel.: +91 462 2336768; fax: +91 462 2334363. E-mail address: [email protected] (K. Veluraja). 0008-6215/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.carres.2010.06.021

structures.26–29 GlycomeDB is an integration of open-access carbohydrate structural databases.30 W3-SWEET is a web-based tool which converts a given two dimensional sequence into a reliable three dimensional model.31 Complex Carbohydrate Structural Database (CCSD) was a sequential database for carbohydrates which existed until 1997. CCSD contained more than 50,000 carbohydrate sequences of which 3757 carbohydrates had sialic acids occurring at the terminal position.32 GLYCAN33 and GLYCAM34 are examples of a few existing databases for carbohydrate data. However, the databases available for 3D structural data of carbohydrates are very few when compared to proteins and nucleic acids. The inherent flexibility of glycosidic linkages makes the isolation and crystallisation of oligosaccharides a challenging task. The three dimensional structural data obtained through experimental methods like X-ray crystallography and NMR are inadequate to explain the different conformations of oligosaccharides in solution. Hence computational methods like molecular mechanics (MM), molecular dynamics (MD) and Monte Carlo (MC) calculations are required to have a complete understanding of the 3D structure and solution dynamics of oligosaccharides.35–42 MD simulations performed over an appropriate time scale in the order of nanoseconds showed the conformational flexibility of carbohydrates which is in good agreement with the experimental results.43–49 The conformation of the pentasaccharide in GM1 described by Merritt et al.50 was identified through MD simulations.51,52 Because of the biological importance of sialic acid-containing carbohydrates, 10 ns MD simulations of 14 different sialic acid-containing carbohydrates are carried out and the informations about the plausible conformers are derived from the trajectories. The derived 3D structural models are used in the development of 3DSDSCAR.

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trajectory by identifying and averaging the individual conformational states.

2. Materials and methods The initial models of sialic acid-containing disaccharides and sialic acid-containing carbohydrates are generated using the standard geometry.53,54 The input parameters for MD simulations are prepared with gaff and ff99 force field parameters of AMBER9, which includes the assignment of partial charges to the individual atoms.55,56 The molecule is placed at the centre of a TIP3P box and water molecules from the solvent library are added. Sodium ions are positioned inside the solvent box to maintain the ensemble in neutral charge. The size of the box and the number of solvent molecules differ from structure to structure. The size of the chosen box is big enough to facilitate the free movement of the carbohydrate molecule during dynamics in aqueous environment. Periodic boundary conditions are used to treat the boundary of the system so as to minimise the edge effects. The resulting system is simulated using the molecular dynamics software NAMD.57 During simulation, the temperature, pressure and the number of particles are kept constant. The temperature is maintained at 300 K throughout the simulation. The whole ensemble is subjected to MD simulation for a period of 10 ns with the time step of one femto second. The information about the ensemble is recorded over every pico second. Totally, 10,000 structures are collected and analysed to arrive at the three dimensional structural models (conformational models) for the selected oligosaccharide structure. The conformational models for a particular oligosaccharide are deduced from the

3. Results 3.1. Deducing conformational models from trajectories The sequences of 14 different sialic acid-containing oligosaccharides which are subjected to 10 ns MD simulations are given in Table 1. In oligosaccharide structures, the glycosidic conformational flexibility and the freedom of flexibility depend upon the number of sugar residues in the sequence and the torsional angle parameters [(Ui, Wi)i = 1,n1] where n is the number of sugar residues in the sequence. The glycosidic torsional angles are defined with respect to anomeric hydrogen atom and the hydrogen atom attached to the linking carbon atom. In the case of sialic acid linkages, C-1 carbon atom of sialic acid is considered instead of anomeric hydrogen. The procedure for deducing three dimensional structures for a particular oligosaccharide is described by taking the monosialo ganglioside GM3 as an example. The GM3 oligosaccharide (a-D-Neu5Acp-(2?3)-b-D-Galp-(1?4)-b-D-Glcp) has three sugar residues in the sequence and two pairs of glycosidic torsions, [(U1, W1)] and [(U2, W2)]. The conformational map of the glycosidic linkage b-D-Galp-(1?4)-b-D-Glcp [(U1, W1)] of GM3 deduced from the 10 ns simulation (10,000 structures) clearly shows that it can exist in a single conformation (Fig. 1a) with the favoured glycosidic

Table 1 Sequential structure and number of possible conformers for sialic acid-containing carbohydrates S. No.

Molecular ID

Sequence

No. of conformers

1 2 3 4 5 6 7 8 9 10 11 12

SA23GAL SA26GAL SA28SA SA29SA GM3 GM2 GM1 GA2 GD3 GD1a GD1b GT1b

a-D-Neu5Acp-(2M3)-b-D-Galp a-D-Neu5Acp-(2M6)-b-D-Galp a-D-Neu5Acp-(2M8)-a-D-Neu5Acp a-D-Neu5Acp-(2M9)-a-D-Neu5Acp a-D-Neu5Acp-(2?3)-b-D-Galp-(1?4)-b-D-Glcp-(1?1)-Cer b-D-GalNAcp-(1?4)-[a-Neu5Acp-(2?3)]-b-D-Galp-(1?4)-b-D-Glcp-(1?1)-Cer b-D-Galp-(1?3)-b-D-GalNAcp-(1?4)-[a-D-Neu5Acp-(2?3)]-b-D-Galp-(1?4)-b-D-Glcp-(1?1)-Cer

13 14

SLEX LEX

a-D-Neu5Acp-(2?3)-b-D-Galp-(1?4)-b-D-GlcNAcp(3 1)-a-D-Fuc b-D-Galp-(1?4)-b-D-GlcNAcp-(3 1)-a-D-Fuc

b-D-GalNAcp-(1?4)-b-D-Galp(1?4)-b-D-Glcp(1?1)-Cer

a-D-Neu5Acp-(2?8)-a-D-Neu5Acp-(2?3)-b-D-Galp-(1?4)-b-D-Glcp-(1?1)-Cer a-D-Neu5Acp-(2?3)-b-D-Galp-(1?3)-b-D-GalNAcp-(1?4)-[a-D-Neu5Acp-(2?3)]-b-D-Galp-(1?4)-b-D-Glcp-(1?1)-Cer b-D-Galp-(1?3)-b-D-GalNAcp-(1?4)-[a-D-Neu5Acp-(2?8)-a-D-Neu5Acp-(2?3)]-b-D-Galp-(1?4)-b-D-Glcp-(1?1)-Cer a-D-Neu5Acp-(2?3)-b-D-Galp-(1?3)-b-D-GalNAcp-(1?4)-[a-D-Neu5Acp-(2?8)-a-D-Neu5Acp-(2?3)]-b-D-Galp-(1?4)-

3 4 4 8 3 4 4 3 6 3 1 4

b-D-Glcp-(1?1)-Cer

Figure 1a. The glycosidic torsional map for b-D-Galp-(1?4)-b-D-Glcp.

12 1

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Figure 1b. The glycosidic torsional map for a-D-Neu5Acp-(2?3)-b-D-Galp.

Figure 2a. Conformer I of GM3.

torsion of [(80°, 0°)]. The conformational map of the other glycosidic linkage a-D-Neu5Acp-(2?3)-b-D-Galp [(U2, W2)] indicates that this linkage can exist in three different conformational regions (Fig. 1b) with the favoured torsional angles [(150°, 50°)], [(100°, 50°)] and [(70°, 0°)]. Based on the combinatorial combination of the conformations around the two glycosidic linkages of GM3 (1  3), three structural models (three conformers) are plausible. These three conformers thus obtained for GM3 are given in Figure 2. In the projection diagram, hydrogen atoms with the exception of the anomeric hydrogen and the hydrogen atom attached to the linking carbon are not shown in order to increase the clarity of glycosidic torsions and the ring structures. A similar methodology is adopted for deducing conformational models for all the oligosaccharides under study. The numbers of plausible conformers for each of the simulated sialic acid-containing carbohydrates are given in Table 1. 3.2. Validation of theoretically derived models with experimental results

Figure 2b. Conformer II of GM3.

Figure 2c. Conformer III of GM3.

The similarity between the oligosaccharide conformations obtained through NMR experiments and MD simulations ensures the validity of the conformational models generated through MD simulations. The solution conformations of mannose pentasaccharide and oligomannosides determined through MD simulations are capable of explaining the experimental data obtained through NMR.58,59 The proposed value of the dihedral angles for the linkages a-D-Neu5Acp-(2?3)-b-D-Galp, b-D-Galp-(1?4)-b-D-GlcNAcp and b-D-GlcNAcp(3 1)-a-D-Fuc of the bound state of tetrasaccharide SLEX (a-D-Neu5Acp-(2?3)-b-D-Galp-(1?4)-b-D-GlcNAcp(3 1)-aD-Fuc) with Selectin P are [(85°, 4°), (45°, 18°) and (61°, 26°)], respectively, as deduced by NMR.60 Our MD simulations carried out for the same oligosaccharide reveal that the oligosaccharide can adopt a conformation [(70°, 0°), (65°, 15°), (65°, 40°)] which is very close to the NMR observation. The existence of the various conformers in the solution state is also confirmed by NMR and MD simulations.61,62 The bound state conformation of the GM1 pentasaccharide in the complex of the cholera toxin and GM1 is characterised by NMR and X-ray crystallographic techniques and the torsional angles around the glycosidic linkages of the GM1 pentasaccharide (b-D-Galp-(1?3)-b-D-GalNAcp-(1?4)-[a-D-Neu5Acp-(2?3)]-b-DGalp-(1?4)-b-D-Glcp) are found to be b-D-Galp-(1?3)-b-D-GalNAcp (58°, 3°), b-D-GalNAcp-(1?4)-b-D-Galp (48°, 7°), b-D-Galp-(1?4)b-D-Glcp (49°, 7°) and a-D-Neu5Acp-(2?3)-b-D-Galp (169°,

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K. Veluraja et al. / Carbohydrate Research 345 (2010) 2030–2037 Table 2 Torsional angle values and relative energies of the plausible conformational models of GM1 oligosaccharide GM1 conformers Conformer Conformer Conformer Conformer

Glycosidic torsional angles [(U, W)] in degrees

I II III IV

b-D-Galp-(1?3)-b-D-GalNAcp

b-D-GalNAcp-(1?4)-b-D-Galp

b-D-Galp-(1?4)-b-D-Glcp

a-D-Neu5Acp-(2?3)-b-D-Galp

70, 30 70, 30 70, 30 70, 30

30, 20 30, 20 30, 20 30, 20

80, 0 30, 30 80, 0 30, 30

70, 0 70, 0 150, 30 150, 30

Relative energy (kcal/mol) 0.00 4.91 5.45 6.33

Figure 3. Model data structure of the coordinate file for a particular conformer.

31°). The NMR experiments also show similar results to the X-ray experiment results.50 Similar conformation with the respective dihedral values (50°, 6°), (23°, 34°), (31°, 30°) and (158°, 29°) for GM1 is observed through MD simulation by Bernardi

and Raimondi.60 One of the conformational models of GM1 predicted through 10 ns MD simulations matches with the above said conformation (Conformer 4 in Table 2). In the case of another oligosaccharide GM3, the three conformational models obtained

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Figure 4a. The web interface of 3DSDSCAR.

Figure 4b. Web page showing the list of the carbohydrates and an option to choose.

through the MD simulations are very similar to the conformations proposed by DeMarco and Woods.63 In a 10 ns simulation, the different conformational states of an oligosaccharide are visited many times and so, for a reasonable oligosaccharide structure (10 sugar residues in the sequence) 10 ns MD simulations can provide reliable structural models. In

addition to that, the conformational models can be delineated based on the relative energy obtained through energy averaging of the conformational states. For example, of the four conformers of GM1, the first conformer has the relative energy 0.00 kcal/mol which is the highest probable conformational state of GM1 in solution.

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Figure 4c. Web page displaying conformers of the selected carbohydrate and their relative energies.

Figure 4d. Web page with Jmol applet displaying the selected conformer and an option to download the data file.

4. Construction of 3DSDSCAR database The data set of 3DSDSCAR contains coordinate files of 60 conformers belonging to 14 different carbohydrate sequences. The main information stored in the coordinate files is the cartesian coordinates of every atom of the conformer. Besides the atomic coordi-

nates, annotations are included in the file under various record types corresponding to different sections. The ANNOTATION section contains the record types HEADER, TITLE, MOLEID, SEQSTR, GLYTOR, AUTHOR, METHOD, MDCONF and REMARK. HEADER, TITLE and MOLEID records contain the classification, name of the sequential structure and the molecular identity code used in the database.

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Molecular identity code is unique for each carbohydrate entry. The record SEQSTR gives the sequential structure with residue numbers marked on it and GLYTOR record shows the glycosidic torsional angle numbering at the corresponding glycosidic linkages. AUTHOR record contains the names of the authors who have carried out the MD simulation. METHOD record gives the details of the MD simulation. MDCONF record contains the information about the possible conformers, glycosidic torsions, relative energy and the conformational state. Additional informations are provided in the REMARK record. The COORDINATE section contains the record type ATOM and this record includes the unique atom number, atom name, residue name, residue ID and the X, Y, Z cartesian coordinates. A typical data file is given in Figure 3. This database 3DSDSCAR has been given a user-friendly interactive interface in which, on selection, the molecules are displayed via Jmol applet.64 The back-end database is MySQL65 and the front-end coding is done by PHP.66 The database 3DSDSCAR can be accessed at the URL: http:// www.3dsdscar.org. A step-wise access of the 3DSDSCAR database through web interface is given in Figure 4 which is self-explanatory.

for Senior Research Fellowship. All the authors acknowledge the use of Bioinformatics Centre in the Department of Physics, Manonmaniam Sundaranar University (BT/BI/25/001/2006), funded by DBT.

5. Discussion

16. 17.

In the field of glycobiology, 3DSDSCAR is the first and unique three dimensional structural database of carbohydrates developed based on the models generated through MD simulations. Most of the biological recognition phenomena are very much controlled and regulated by the three dimensional structure of the oligosaccharides. One of the best examples is the recognition of oligosaccharides by the unique class of sugar-binding proteins called lectins. It is well established that the conformations of the carbohydrates binding to the glycoconjugates obtained through NMR are accessed through the MD simulation of the oligosaccharides.67–70 The crystal structure of the proteins complexed with the sugar moieties gives insight about the protein–carbohydrates interactions. However, in experimental methods like X-ray crystallography, there is a possibility of occurrence of error in fixing up the atoms in the correct orientations. Carbohydrate moieties of many of the protein carbohydrate complexes that are available in PDB contain errors in their structures.71 For example, the 3D structure of Clostridium botulinum neurotoxin B complexed with sialyllactose is solved through X-ray crystallographic technique and is available in the Protein databank with the ID 1f31.72 A careful analysis of the carbohydrate moiety reveals that the orientation of hydroxyl groups at C-3 and C-6 positions of galactose is not correct. This difference in orientation will lead to the development of an incorrect structure. These kinds of erroneous structures can be avoided if they are checked against standard structural data of the oligosaccharides. Since the models derived from MD simulations are highly reliable, 3DSDSCAR can serve as standard database against which the experimentally obtained structures can be checked for errors. Biophysicists, glycobiologists, biochemists and biotechnologists will find this database helping them to address research problems regarding the conformational aspects of molecular recognition processes and many protein carbohydrate interactions. The database will be expanded further on deriving conformational models for other carbohydrates by researchers of our group and by others.

18.

Acknowledgements

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K.V. acknowledges the Department of Science and Technology, India (SR/S0/BB-53/2003), New Delhi, for funding this project. J.F.A.S. and T.R.K.P. acknowledge the Junior Research Fellowship from the Department of Science and Technology (SR/S0/BB-53/ 2003) and the Department of Biotechnology (BT/PR4251/BID/07/ 068/2003). S.V. acknowledges the Rajiv Gandhi National Fellowship

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