molecular modeling and docking of mannose-binding lectin from lycoris radiata

Chem. Res. Chin. Univ. 2013, 29(6), 1153—1158 doi: 10.1007/s40242-013-3259-4

——————————— *Corresponding author. E-mail: [email protected] Received June 17, 2013; accepted July 9, 2013. Supported by the National Natural Science Foundation of China(No.31271302). © Jilin University, The Editorial Department of Chemical Research in Chinese Universities and Springer-Verlag GmbH

Molecular Modeling and Docking of Mannose-binding Lectin from Lycoris radiata

ZHU Qian-kun, ZHU Meng-li, ZOU Jia-xin, FENG Pei-chun, FAN Gao-tao, LIU Zu-bi and WANG Wan-jun*

School of Life Science and Engineering, Southwest Jiaotong University, Chengdu 610031, P. R. China

Abstract Lycoris radiata mannose-binding lectin(LRL) is a protein which binds mannose residues specifically. The maturation peptide and three mannose-binding domains(residues 49―57, 80―88 and 113―121) of LRL were identi-fied by sequence analysis. The 3D structure of LRL constructed by homology modeling shaped a fistular triangular prism. Three flanks of the prism are mainly composed of β-sheets and each flank has a mannose-binding domain. According to the docking and dynamics simulation, the bindings of residues 49―57 and 80―88 with mannose are more stable than that of residues 113―121 with it. The key residues for binding mannose are Gln80, Asp82, Asn84 and Tyr88. The study preliminarily analyzed the interaction sites and mechanism of LRL with mannoses, which could be useful for the study on insect-resistance and related drug discovery of LRL. Keywords Mannose-binding lectin; Lycoris radiata; Molecular modeling; Molecular docking; Dynamics simulation

1 Introduction

Plant lectins are carbohydrate-binding proteins that are highly specific for sugar moieties and foreign glycoconju-gates[1]. Monocot mannose-binding lectins(MBLs) are able to bind mannose residues specifically to form a big protein family of plant lectins[2]. MBLs are relatively rare in plant but abun-dant in insects, viruses, bacterias and fungals[3]. MBLs are able to bind the mannose-protein receptor in insects to interfere in the growth and development of insects[4]. MBLs can also bind the mannose residues on the surface of microorganisms so as to interfere with the metabolism of microorganisms. Therefore, MBLs play important roles in the defense of the destructive insects, pathogenic microorganism and phytophagy animals. Some exogenous genes of MBLs have been transferred into rice, tobacco, cotton, sugarcane, rape, and so on to develop insect-resistant varieties[5]. Some MBLs(such as Galanthus nivalis MBL and Narcissus pseudonarcissus MBL) have inhi-bitory activity to the human immunodeficiency viruses and feline immunodeficiency viruses[6].

Lycoris radiata, with a high ornamental value, is an im-portant medicinal plant. It contains many alkaloids and other medicinal active ingredients. Galantamine in Lycoris radiata is able to inhibit the activity of cholinesterase that has been used to cure the moderate Alzheimer’s disease[7]. Narcissine, dihy-drogalanthamine, haemanthidine, lycorenine, and so on from Lycoris radiata show the effects of antitumor, antivirus and antimalarial[8]. Lycoris radiata lectin(LRL)[9] belongs to the MBLs with similar structures and functions. Narcissus pseu-donarcissus MBL(NPL)[10] and Galanthus nivalis MBL(GNL)[11], the early discovered MBLs, show the activity

of antivirus and insect-resistance. Lycoris radiata, Narcissus pseudonarcissus and Galanthus nivalis belong to amaryllida-ceae plants. The antivirus activity and insect-resistance of LRL are worthy of in-depth study. In order to study that, one of the prerequisites is the knowledge of the structure and function of LRL. To date, the crystal structure of LRL has not been re-solved. In the study, the LRL protein sequence was subjected to molecular modeling, docking and dynamics simulations in order to analyze the structure features and the interaction me-chanism with mannose residues. The work could provide useful information for the further pharmacology study of LRL and development of transgenic insect-resistant crops.

2 Materials and Methods

2.1 Sequence Analysis and Molecular Modeling

The protein sequence of LRL[9](Accession number: AAP20877) and the homologous protein sequences[Clivia miniata lectin[12](CML), Accession number: AAA19913; Narcissus Pseudonarcissus lectin[10](NPL), Accession number: 1NPL_A; Zephyranthes candida lectin[13](ZCL), Accession number: AAM94381; Galanthus Nivalis lectin[14](GNL), Accession number: 1MSA_A; Amaryllis minuta lectin[15] (AML), Accession number: AAP37975; Gastrodia Elata lectin[16](GEL), Accession number: 1XD5_A] were retrieved from NCBI protein sequence database (http://www.ncbi.nlm.nih.gov/Proteins/). The homologous protein sequences were aligned with LRL sequence via ClustalW[17].

For homology modeling of LRL, the crystal structure of template NPL[10](PDB ID: 1NPL) was identified from

1154 Chem. Res. Chin. Univ. Vol.29

Protein Data Bank(PDB, http://www.rcsb.org/pdb) by NCBI BLAST (Basic Local Alignment Search Tool; http://www.ncbi.nlm.nih.gov/Blast). MODELER module in-cluded in Discovery Studio(DS) 2.1(Accelrys, San Diego, USA)[18] was used for homology modeling of LRL. MODELER is an automated homology modeling program that performs automated protein homology modeling and loop modeling by the satisfaction of spatial restraints[19]. The sequence of the template protein(NPL) was extracted and aligned with the target protein(LRL) by Align Multiple Se-quences module of DS. Based on the sequences alignment, the structure of conserved regions(SCRs) was determined. The loops and the variable regions not to be included in SCRs and the conformations of side chains were built automatically by MODELER.

2.2 Molecular Dynamics Simulations

The initial model from MODELER was optimized by energy minimization(EM) and subsequent molecular dynamics(MD) simulation with the force field of CHARMm[20] provided in DS. Firstly, the initial model was solvated with the TIP3P[21] model of water via the orthorhombic box at a mini-mum distance of, at least, 0.7 nm from any edge of the box to any protein atom. The solvated protein system was subse-quently subjected to a thorough EM before MD simulations by 1000 steps of the steepest descent algorithm minimization[22] of the water molecules on holding the solute frozen and followed by 2000 steps of the conjugate gradient minimization[22] of the whole system to remove close contacts and to relax the system.

The system was then subjected to 100 ps of heating from 50 K to 300 K with a Harmonic constraint[23] imposed on the solute to allow the relaxation of water molecules. The follo- wing 100 ps equilibrium run for the system was performed with distance Harmonic constraints. The production run was next carried out without any constraints in the NPT ensemble[23] under periodic boundary conditions for 2000 ps at 101 kPa and 300 K. During the simulations, all covalent bonds involving hydrogen were constrained via the SHAKE algorithm[22] so that a time step was set to 2 fs. Long-range electrostatic interactions were treated with the particle mesh Ewald(PME) method[24,25]. Finally, the output conformers were collected at 4 ps intervals and the optimized model was saved for further validation.

2.3 Validation of Model

The stereo chemical quality of LRL structure was firstly inspected by the Psi/Phi Ramachandran plot obtained from PROCHECK[26]. Secondly, ERRAT[27], the so-called “overall quality factor”, was used to check non-bonded atomic interac-tions, i. e., higher scores indicating higher quality. The PROSA test[28] was applied to the final model to check energy criteria with the potential of mean force derived from a large set of known protein structures. Further, the compatibility of the model with its sequence was measured by Verify-3D graph[29] obtained from Profile-3D module of DS. Finally, the root mean square deviation(RMSD) between the backbone atoms of LRL

on the one hand and those of the template(NPL) on the other hand was calculated by the Proteins Superimposing module of DS.

2.4 Docking of Ligands into the Protein

As mentioned above, the ligands of LRL are mannoses. The structure of mannose(Compound ID: 185698) was obtained from NCBI PubChem(http://pubchem.ncbi.nlm.nih.gov/). The binding sites between the protein and the ligand were ob-tained by the analysis of sequence and structure. After deter-mining the binding sites, the docking restraint spheres were used to cover the binding sites by Binding Site tools of DS and mannose was docked into the protein via CDOCKER[18] module of DS. The reasonable docking conformations were cho-sen according structural clustering analysis and binding energy. The final docking model(the complex of protein and ligands) with the minimum interaction energy and reasonable spatial conformation was chosen and then subjected to EM and MD simulation with the same methods as that used for the initial model of LRL. The structural models generated in this study were viewed in DS and Ligplot[30].

3 Results and Discussion

3.1 Sequence Analysis of LRL

Precursor protein sequence of LRL, which contained 350 amino acid residues, was used as query sequence to search the NCBI protein sequence database. As the result of that, three homologous precursor sequences(CML, ZCL and AML) and three homologous maturation sequences(NPL, GNL and GEL) of LRL were obtained. CML, ZCL and AML showed 73%, 67% and 69% identities with LRL, while NPL, GNL and GEL showed 83%, 82% and 54% identities with LRL.

The six homologous protein sequences were aligned with LRL sequence(Fig.1). Like other MBLs, LRL has a signal pep-tide(residues 1―23), a maturation peptide region(residues 24―133) and C-terminal cutting peptide(residues 134―158). The maturation peptide region contains three mannose-binding domains(MBDs, MBD1: residues 49―57, MBD2: residues 80―88, MBD3: residues 113―121). The mannose-binding domains have a common characteristic motif QXDXNXVXY. Mannose binding residues of three MBDs are residues 49, 51, 53, 55, 57, residues 80, 82, 84, 86, 88 and residues 113, 115, 117, 119, 121, respectively.

3.2 Molecular Modeling of LRL

Based on the results above, the maturation peptide of LRL was subjected to homology modeling with the crystal structure of NPL maturation protein as the template. The obtained struc-ture of LRL is shown in Fig.2. The constructed structure of LRL contained 60.39% β-sheet residues and 39.61% loop resi-dues. The sequences and structures of LRL and NPL were con-served due to their similar biological functions. Like that of NPL, the 3D structure of LRL shaped a fistular triangular prism consisting of 11 β-sheets and 12 loops. Three flanks of the prism are mainly composed of β-sheets(sheet 3―6; sheet

No.6 ZHU Qian-kun et al. 1155

Fig.1 Multiple sequence alignment between LRL and each of six MBLs from different plants CML, ZCL and AML were precursor sequences; NPL, GNL and GEL were maturation proteins and their crystal structures were resolved. • The less conserva-tive residue; * the same residue; : the highly conserved seidue.

Fig.2 Superimposition between the monomer struc-ture of LRL and that of template NPL S indicates sheet and L indicates loop.

2/7―9; sheet 1/10―11) and each flank has a MBD. MBD1 was located in loop 5 and sheet 5. MBD2 was located in loop 8 and sheet 8. MBD3 was located in loop 11 and sheet 11. The superimposition of the monomer structure of LRL predicted by its model with that of its template NPL resulted in a RMSD value of 0.075 nm, indicating that the 3D structure of LRL predicted by its model was similar to that of NPL(Fig.2). The high similarities of the relative locations of their putative active domains and their secondary structures attested to the high precision of the proposed model.

3.3 Refinement of LRL Model by MD Simulation

The constructed model was subjected to MD simulation in order to assess the stability of the model and to find the ener-getically favorable structure for further docking study. The MD simulation trajectory-based analysis shows that the potential energy of the model was decreased by 2474.532 kJ/mol, which indicates that the model was energetically stable during MD simulation. Structural stability of the constructed model during

the MD simulation was examined via RMSD. Fig.3(A) shows the RMSD plot for the protein backbone atoms with reference to the initial structure, as a function of time. The first 800 ps was considered as an equilibration period after which the model became stable in a RMSD range of 0.2―0.25 nm.

Distinguishing the flexible regions of the protein could help one with understanding the stability of the protein. To examine the flexible regions of monomer structure predicted by the model, we generated the average root-mean-square fluctua-tion(RMSF) plot for the Cα-atoms with respect to the residues.

Fig.3 RMSD plots of LRL, docking complex and mannoses(A) and RMSF plots of residues in LRL and those in complex(B)


The residues with RMSF values lower than 0.2 nm clearly show that the protein structural core was well-constructed. And the model was stable in the course of MD simulation[31]. The high fluctuations occurred in the loop regions and a low fluc- tuation occurred in the β-sheets regions. As shown in Fig.3(B), the most regions of LRL are relatively stable as the result of their RMSF values being less than 0.2 nm and only residues 19, 37, 80―82 and 92, 93 fluctuated slightly in root-mean-square value. The flexible region of LRL mainly consisted of the C-terminal residue 122―124[Fig.3(B)] because of the C-terminal region forming a loop sticking out from the trian-gular column(Fig.2).

3.4 Validation of LRL model

The internal consistency and reliability of the LRL model was checked by PROCHECK based on the inspection of Psi/Phi Ramachandran plot. The results, summarized in Fig.4(A), show 98.8% of the residues in the favored and al-lowed regions and only 1.2% of them in disallowed region. The Goodness factors(G-factors), indicating the quality of covalent distance and bond/angle, were 0.30 for covalent, –0.34 for dihedrals and –0.07 for overall. Then, the ERRAT score(overall quality factor) was calculated based on the non-bonded atomic interactions[22,30]. In this case, the ERRAT score for the model was 97.80, which is within the range of a high quality model.

Fig.4 Ramachandran plot(A) and verify-3D curve(B) of LRL model

(A) Symbols A, B and L indicate the most favored regions; symbols a, b, l and p indicate the substitute additional allowed regions; symbols ~a, ~b, ~l and ~p indicate the generously allowed regions; the white regions indicate the disallowed regions.

In order to investigate whether the interaction energy of each residue with the remainder of the protein is negative, a second test was done by means of PROSA[28] energy plot. PROSA energy Z-score of LRL was –7.28, which was within

the range of scores[32] found for all the experimentally deter-mined protein chains(Fig.S1, see the Electronic Supplementary Material of this paper). PROSA energy plot evaluating the in-teraction energy per residue with negative PROSA energies confirms the reliability of the model. The PROSA analysis of the model shows that all the residues had negative interaction energy and no residues displayed positive interaction energy (Fig.S2, see the Electronic Supplementary Material of this pa-per).

Subsequently, the environmental profile and packing quality of each residue were assessed by the profile-3D pro-gram[Fig.4(B)]. The compatibility score above zero in the ve-rify-3D graph corresponds to acceptability side-chain environ-ment[33]. Over 90% of the residues had an average score more than 0.2, which suggests that the side chain environments were acceptable. Hence, the predicted model was determined to be good enough for further docking studies.

3.5 Docking of Ligand into LRL

The docking restraint spheres were used to cover the three MBDs(MBD1: residue 49―57, MBD2: residue 80―88, MBD3: residue 113―121) by DS binding site tools and three mannoses were docked into the LRL. Even though mannose was docked into the protein, the 3D structures of LRL were not changed much. The comparisons of LRL before and after docking only gave a less RMSD value than 0.1 nm. The docked complex of LRL and mannose is shown in Fig.5. Three man-nose molecules(indicated by Man1, Man2 and Man3) bound to three MBDs(MBD1, MBD2 and MBD3) and their interaction energies were –180.659, –237.901 and –30.549 kJ/mol, respec-tively(Table 1). According to the interaction energies, the binding of MBD1 and MBD2 with mannose was stronger than that of MBD3 with it.

Fig.5 Complex structure of LRL and mannose Table 1 van der Waal energy(Evdw), electrostatic

energy(Eele) and total energy(Etotal) between LRL and mannoses

Mannobiose Binding domain(residue)

Evdw/ (kJ·mol–1)

Eele/ (kJ·mol–1)

Etotal/ (kJ·mol–1)

Man1 MBD1(49―57) –18.987 –161.672 –180.659Man2 MBD2(80―88) –25.616 –212.285 –237.901Man3 MBD3(113―121) –10.159 –20.390 –30.549

3.6 MD Simulation of Ligand-bound Complex

In order to study the stability of ligand-bound complex, the obtained complex structure was subjected to 2000 ps of MD

No.6 ZHU Qian-kun et al. 1157

simulation. The RMSD plot of the complex is shown in Fig.3(A), the complex approached to equilibrium after about 700 ps and the RMSD values stay in a range of 0.12―0.16 nm. Compared to the results of MD simulation of LRL above, the RMSD value of complex was decreased. It was the result of the complex containing three ligand molecule and the bindings of the ligand molecule with LRL stabilized the complex structure. The maximum RMSD values of three mannose molecules (Man1, Man2 and Man3) were 0.092, 0.076 and 0.122 nm, while the average RMSD values were 0.068, 0.061 and 0.088 nm, respectively. It suggests that the three ligands were stable, which were maintained in the binding sites during the MD simulation[18]. The RMSD value of Man3 was more than those of MBD1 and MBD2, indicating that the MBD1 and MBD2 were more conducive to binding mannose than MBD3.

A comparison of structure of ligand-bound complex with that of LRL indicates that structural changes were in loops and binding site regions[Fig.3(B)]. These regions showed a lower RMSF value in the ligand-bound complex than in the LRL, suggesting that the presence of ligand increased the structural stability of these regions. Particularly, the flexibilities of MBD1(residues 49―57), MBD2(residues 80―88) and MBD3

(residues 113―121) were decreased essentially in the presence of mannose[Fig.3(B)]. This was not surprising because ligands bound with these regions in complex. In addition, the RMSF values of mannose binding residues Gln49, Asp51, Asn53, Tyr57 in MBD1, Gln80, Asp82, Asn84, Tyr88 in MBD2 and Gln113, Asp115, Asn117, Tyr121 in MBD3 were much lower in the ligand-bound complex than in LRL, mostly due to their hydrogen bonds with mannose.

3.7 Binding Mode of Ligands in LRL

Like other lectins, three MBDs of LRL had the similar structure and the mannose binding to the MBDs was mediated by an extensive network of van der Waals and hydrogen bonds interactions(Fig.6). In the three MBDs, the residues which had hydrogen bonds with mannose are Gln, Asp, Asn and Tyr, while the residue without hydrogen bonds is Val. It was evident that the key residues binding the mannose were Gln, Asp, Asn and Tyr. The binding mode of MBD1 with mannose and that of MBD2 with mannose are similar while the hydrogen bond lengths and the total binding energies are different as the result of the influence of other residues in the binding sites.

As shown in Fig.6 and Table 2, Gln49, Asp51, Asn53 and

Fig.6 Interactions between the MBD residue of LRL and mannose Only the key residues are shown in the figure. Hydrogen bond lengths are in nm.

Table 2 Potential hydrogen bonds interactions between LRL and mannose

MBD residue atom Man atom Hydrogen bond distance/nm

Interaction energy/(kJ·mol–1)

MBD1 Gln49 NE2 Man1 O4 0.324 –3.552 MBD1 Gln49 NE2 Man1 O10 0.317 –4.348 MBD1 Asp51 OD2 Man1 O10 0.277 –5.014 MBD1 Asn53 ND2 Man1 O10 0.313 –4.71 MBD1 Tyr57 OH Man1 O3 0.275 –5.014 MBD2 Gln80 NE2 Man2 O4 0.321 –3.944 MBD2 Gln80 NE2 Man2 O10 0.294 –5.006 MBD2 Asp82 OD2 Man2 O10 0.254 –4.036 MBD2 Asn84 ND2 Man2 O2 0.314 –4.646 MBD2 Asn84 ND2 Man2 O10 0.332 –2.764 MBD2 Tyr88 OH Man2 O3 0.288 –5.01 MBD3 Gln113 NE2 Man3 O8 0.306 –5.002 MBD3 Asp115 OD2 Man3 O9 0.267 –5.016 MBD3 Asn117 ND2 Man3 O9 0.306 –5.002 MBD3 Tyr121 OH Man3 O3 0.284 –5.012

Tyr57 in MBD1 had potential hydrogen bonds with O3, O4, and O10 of Man1; the interaction energy was –22.638 kJ/mol. Gln80, Asp82, Asn84, Tyr88 in MBD2 had potential hydrogen bonds with O2, O3, O4 and O10 of Man2; the interaction energy was –25.406 kJ/mol. In addition, Gly101 in MBD2 had hydrophobic interaction with O1 of Man2. Gln113, Asp115, Asn117 and Tyr121 in MBD3 had potential hydrogen bonds with O3, O8, and O9 of Man3; the interaction energy was –20.032 kJ/mol. As mentioned above, the binding of MBD2 with mannose was stronger than those of MDB1 and MBD3 with it as the result of the hydrogen bonds of Gln80, Asp82, Asn84, Tyr88 with Man2 and hydrophobic interaction of Asp101 with Man2. The binding of MBD3 with mannose was weaker than those of MBD1 and MBD2 with it.

4 Conclusions LRL had a signal peptide(residues 1―23), a maturation


peptide region(residues 24―133) and C-terminal cutting peptide(residues 134―158). The maturation peptide region contained three mannose-binding domains(residues 49―57, residues 80―88 and residues 113―121). The structure of LRL constructed by homology modeling based on NPL as a template shaped a fistular triangular prism. Three flanks of the prism was mainly composed of β-sheets and each flank had a man-nose-binding domain. According the docking and dynamics simulation, the bindings of MBD residues 49―57 and 80―88 with mannose were more stable than that of MBD residues 113―121 with it. The key residues for binding mannose were Gln80, Asp82, Asn84 and Tyr88. Considering the binding of MBD residues 80―88 with mannose was stronger than those of the other two with it, we could try to mutate the modes of the other two MBDs to that of MBD residues 80―88 so as to fur-ther construct the transgenic plant in order to study the in-sect-resistance and pharmacologic actions of mutein. The in-sect-resistance of some MBLs was applied to agriculture and some were found to have inhibitory activity to retrovirus[6]. The study preliminarily analyzed the interaction sites and mechanism of LRL with mannoses, which could be useful for the further site-directed mutagenesis experiments to study insect- resistance and related drug discovery of LRL. Electronic Supplementary Material

Supplernentary material is available in the online version of this article at http://dx.dol.ory/10.1007/s40242-013-3259-4.

Reference

[1] Chrispeels M. J., Raikhel N. V., Plant Cell, 1991, 3, 1 [2] Peumans W. J., van Damme E. J., Histochem. J., 1995, 27, 253 [3] Peumans W. J., van Damme E., Plant Physiol., 1995, 109, 347 [4] Vandenborre G., Smagghe G., van Damme E. J., Phytochemistry,

2011, 72, 1538 [5] Chang T., Zhu Z., Hereditas, 2002, 24, 493 [6] Lopez S., Armand-Ugon M., Bastida J., Viladomat F., Este J. A.,

Stewart D., Codina C., Planta Med., 2003, 69, 109 [7] Heinrich M., Lee Teoh H., J. Ethnopharmacol., 2004, 92, 147 [8] Yuan J. H., J. Anhui Agr. Sci., 2010, 2, 053 [9] Zhao X., Yao J., Sun X., Tang K., Mitochondr. DNA, 2003, 14, 223

[10] Sauerborn M. K., Wright L. M., Reynolds C. D., Grossmann J. G., Rizkallah P. J., J. Mol. Biol., 1999, 290, 185

[11] Hester G., Kaku H., Goldstein I. J., Wright C. S., Nat. Struct. Mol. Biol., 1995, 2, 472

[12] van Damme E. J., Smeets K., van Leuven F., Peumans W. J., Plant Mol. Biol., 1994, 24, 825

[13] Pang Y. Z., Shen G. A., Liao Z. H., Yao J. H., Fei J., Sun X. F., Tan F., Tang K. X., Mitochondr. DNA, 2003, 14, 163

[14] Wright C. S., Kaku H., Goldstein I. J., J. Biol. Chem., 1990, 265, 1676

[15] Wu C. F., Li J., An J., Chang L. Q., Chen F., Bao J. K., J. Int. Plant Biol., 2006, 48, 223

[16] Liu W., Yang N., Ding J., Huang R. H., Hu Z., Wang D. C., J. Biol. Chem., 2005, 280, 14865

[17] Larkin M., Blackshields G., Brown N., Chenna R., McGettigan P., McWilliam H., Valentin F., Wallace I., Wilm A., Lopez R., Bioinfor-matics, 2007, 23, 2947

[18] Zhu Q., Zhou J., Zhang G., Liao H., Chin. J. Chem., 2012, 30, 2533 [19] Johnson M. S., Mol. Med. Today, 1995, 1, 188 [20] Brooks B. R., Bruccoleri R. E., Olafson B. D., Swaminathan S., Kar-

plus M., J. Comput. Chem., 1983, 4, 187 [21] Lan H. N., Wang Y. X., Zheng M. Z., Han W. W., Zheng X., Chem.

Res. Chinese Universities, 2013, 29(1), 139 [22] Li J. L., Wang J. P., Hu D. H., Shao C., Su Z. M., Chem. J. Chinese

Universities, 2010, 31(8), 1636 [23] Elumalai P., Liu H. L., Int. J. Biol. Macromol., 2011, 49, 134 [24] Wang Y., Zhou Y. H., Guo Y. J., Xu X. L., Si D. Y., Zhou H., Li Z. S.,

Chem. Res. Chinese Universities, 2009, 25(6), 904 [25] Xu X., Cannistraro S., Bizzarri A., Zeng Y., Wang C., Chem. Res.

Chinese Universities, 2013, 29(2), 299 [26] Zhou Y. H., Luo Q., Han W. W., Yao Y., Li Z. S., Chem. J. Chinese

Universities, 2009, 30(7), 1423 [27] Colovos C., Yeates T. O., Protein Sci., 1993, 2, 1511 [28] Wiederstein M., Sippl M. J., Nucleic Acids Res., 2007, 35, 407 [29] Yuan X. H., Qu Z. Y., Wu X. M., Wang Y. C., Wei F. X., Zhang H. Y.,

Liu L., Yang Z. W., Chem. J. Chinese Universities, 2009, 30(8), 1636 [30] Wallace A. C., Laskowski R. A., Thornton J. M., Protein Eng., 1995,

8, 127 [31] Gajendrarao P., Krishnamoorthy N., Sakkiah S., Lazar P., Lee K. W.,

J. Mol. Graph. Model., 2010, 28, 524 [32] Shan S., Xia L., Ding X., Zhang Y., Hu S., Sun Y., Yu Z., Han L.,

Chin. J. Chem., 2011, 29, 427 [33] Bodade R., Beedkar S., Manwar A., Khobragade C., Int. J. Biol. Ma-

cromol., 2010, 47, 298

molecular modeling and docking of mannose-binding lectin from lycoris radiata

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