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Influencia de los iones [Mg.sup.+2] sobre la interaccion entre el acido 3,5-dicafeoilquinico y la integrasa del HTLV-I.

Influence of [Mg.sup.2+] ions on the interaction between 3,5-dicaffeoylquinic acid and HTLV-I integrase

Influencia dos ions [Mg.sup.2+] sobre a interacao entre o acido 3,5-dicafeoilquinico e a integrase do HTLV-I.

Introduction

Human T-Lymphotropic Virus Type 1 (HTLV-I) infection is currently a serious problem of public health in several areas of the world including Japan, some regions of Africa, the Caribbean coast and some South American countries, affecting more than 20 million of inhabitants worldwide (1-3). Therefore, HTLV-I infection is regarded as a global epidemic problem (4, 5). Although most of the infected individuals remain asymptomatic for long periods of time, 2-3 % develop adult T-cell leukemia (ATL) (6) and about 1-2 % of the infected individuals display an evolution towards a neurodegenerative chronic condition termed HTLV-I Associated Myelopathy Tropical Spastic Paraparesis (HAM/ TSP) (7, 8). Several studies aiming to discover replication inhibitors have bee reported. However, up-to-date, there are no reports on the successful control of infection (9). HTLV-I Integrase (IN) is the enzyme responsible for the integration of reversely transcribed viral DNA (cDNA) into host cell DNA through two-step metal dependent reactions (10). In addition, IN plays an important role in HTLV-I genome replication, and it has been considered as one of the most promising targets for development of effective antiretroviral drugs.

Up-to-date, it has been reported that all known retroviral integrases present three domains: i) the zinc binding N-terminal (His12, His16, Cys40 and Cys43), ii) the catalytic core (Asp64, Asp116 and Glu152), and iii) the dsDNA-binding C-terminal domain (11, 12). There are available IN structural information on human immunodeficiency virus type 1 (HIV-1) (13-15), avian sarcoma virus (ASV) (16), prototype foamy virus (PFV) (17) and HIV-1 with orthologous genes close to Lentivirus and Alpharetrovirus (18-20). Additionally, the high similarity of the tridimensional structure among all solved retroviral INs allows determining the structure of unsolved IN through homology modeling (21, 22).

Dicaffeoylquinic Acids (DCQAs) have been previously reported as potent and irreversible inhibitors of HIV-1 (22-25). DCQAs have low cytotoxicity, present low molecular weight, have drug-like properties and are considered as promising inhibitors towards HIV-1 and HTLV-I integrases (23, 24). Despite the fact that its potent inhibitory activity is known, the underpinnings behind the inhibition mechanism remain to be elucidated.

Molecular Docking (MD) is a computational method capable of predicting the most probable topology during the formation of protein-ligand complexes (26) along with quantitative measurements of the affinity such as Binding Free Energy (BFE). This tool has been widely used to evaluate the potential of ligands as competitors which can abolish the infections (27, 28). MD coupled with other calculations, such as BFE (29), enables insights into biological systems and helps a more guided drug design.

In the present study, we evaluate the 3-5-DCQA interaction (IUPAC name: (S)-2-((1R,3R,4R,5R)-3,5-bis((E)-3-(3,4-dihydroxyphenyl)acryloyloxy)- 4hydroxycyclohexyl)-2-hydroxyacetic acid) with the catalytic domain of Human T-Lymphotropic (HTLV-I) type I Integrase in the presence of [Mg.sup.2+] ions. In this sense, a homology model of HTLV-I IN was proposed and docking analysis were performed between HTLV-I IN and 3,5-DCQA, considering the magnesium ([Mg.sup.2+]) ions influence. This modeling corroborated that the presence of one coordinated [Mg.sup.2+] ion decreases the binding free energy between 3,5-DCQA and HTLV-I IN. Thus, we propose 3,5-DCQA as a pharmacophore for HTLV-I integration process inhibition.

Materials and methods

HTLV-I Integrase homology modeling

Simple Modular Architecture Research Tool (SMART) software (http://smart.embl-heidelberg.de/) was used to identify the catalytic site. HTLV-I IN core domain was located between amino acids 492 and 631, confirmed from information of Pfam Data Base (http://pfam.sanger.ac.uk/) (30). HTLV-1 Pol amino acids sequence (accession number BAH85786), available at National Center for Biotechnology Information, NCBI (http://www.ncbi.nlm.nih.gov/), was the basis for determining the catalytic domain of HTLV-I IN. Protein Data Bank (PDB) Non Redundant Database searches using matrix similarity BLOSUM62 with Basic Local Alignment Search Tool (BLAST) software (http:// blast.ncbi.nlm.nih.gov/Blast.cgi) were used to obtain the homology template for HTLV-I IN. The catalytic domain of Avian Sarcoma Virus (ASV) Integrase (PDB: 1VSD) (16) showed the highest homology score.

The homology model was constructed using Prime software (Schrodinger, Inc). The HTLV-I IN secondary structure was determined by alignment of its core domain and ASV template sequences by means of Prime-Secondary Structure Prediction Module. The rotamers of the conserved amino acids were maintained during model building. Next, the side chains were optimized and the residues not derived from the template were minimized. Polak-Ribiere conjugate gradient, OPLS-2005 force field and GB/SA with implicit water-like solvent algorithms were used to optimize loops and complex minimization, using MacroModel (Schrodinger, Inc).

Three HTLV-I IN catalytic domain models, each one with different [Mg.sup.2+] number and position, were constructed: the first one without [Mg.sup.2+] ions (IN0[Mg.sup.2+]); the second one with one [Mg.sup.2+] ion coordinated at Asp15 and Asp72 (IN1[Mg.sup.2+]) and the third one with two [Mg.sup.2+] ions, one chelated at Asp15-Asp72 and the other one at Asp72-Glu108 (IN2[Mg.sup.2+]). The Asp 15, Asp72 and Glu108 are highly conserved amino acids of the catalytic domain of IN for HTLV-1, being homologous to Asp64, Asp116 and Glu152 of IN for HIV-1.

The coordinates to incorporate the [Mg.sup.2+] ions into the homology model of HTLV-I (models two and three), were obtained from 1QS4 (13) and 1VSH (16) crystal structure available in the Protein Data Bank (www.rcsb.org). Those models were achieved by modifying the PDB HTVL-1 model IN format and imported to Maestro file formats (Schrodinger, Inc) (31). Hydrogen atoms were added to IN with Protein Preparation Wizard workflow in Maestro (Schrodinger, Inc) and minimized using OPLS-2005 force field.

3,5-Dicaffeoylquinic acid modeling

The structure of 3,5-Dicaffeoylquinic Acid was constructed using the fragment dictionary of Maestro software 9.0 (Schrodinger, Inc). The ionization states were predicted with Epik (Application of MacroModel, Schrodinger, Inc) using water as solvent at a pH = 7.0 [+ o -] 2.0. ConfGen program (Schrodinger, Inc) was used to identify the most stable ligand conformation with full mode 0.5 [angstrom] as RMS and 120 kcal /mol energy window in order to eliminate redundant conformations. Finally, the structure was optimized with Jaguar software (Schrodinger, Inc) using Density Functional Theory method, with 6-31G** basis set.

Molecular docking

Glide 5.5 software (Schrodinger, Inc) was used for docking studies. To relax the ligand coupling at protein site, Glide uses a series of hierarchical filters to search possible locations of the receptor in the active site. The first filter localizes the ligand centre at various grid positions of a 1 [angstrom] grid and also rotates it around the three Euler angles. At this stage, crude score values and geometrical filters remove those unlikely binding modes. The next filter stage involves a grid-based force field evaluation and refinement of docking solutions including torsional and rigid body movements of the ligand. OPLS-2005 force field was used for this purpose. A small number of surviving docking solutions can then be subjected to a Monte Carlo procedure to minimize the energy score. The final energy evaluation with GlideScore was carried out and a single best pose was generated as output for a particular ligand (32).

The GlideScore scoring function is based on ChemScore, but includes a steric-clash term, adds buried polar terms devised by Schrodinger to penalize electrostatic mismatches, and has modifications to others terms. GlideScore modifies and extends the ChemScore as follow:

GScore = 0.065 * vdW + 0.130 * Coul + Lipo + Hbond + Metal + BuryP + RotB +Site

Where: vdW = van der Waals energy; Coul = Coulomb energy; Lipo = lipophilic contact term; HBond = hydrogen-bonding term; Metal = metal binding term; BuryP = penalty for buried polar groups; RotB = penalty for freezing rotatable bonds; Site = polar interactions at the active site.

After preparing and minimizing the three models (IN0[Mg.sup.2+], IN1[Mg.sup.2+] and IN2[Mg.sup.2+]) and the 3,5-DCQA, we used the receptor grid generation application of Glide to construct the receptor-grid files. To soften the potential non-polar regions of each IN models we scaled van der Waals radius of the receptor atoms by 1.00 A with a partial atomic charge of 0.25. The size outcome of grid box was 13 x 13 x 13 [angstrom] in each dimension, with coordinates: X = 49.9592, Y = 35.3464 and Z = 60.5208 and centered at the active site delimited at residues Asp15, Asp72 and Glu108. To define the spherical region position that should be occupied by the ligand during docking, [Mg.sup.2+] ions were used as constraints in the second and third models. The [Mg.sup.2+] ions and the ligand were selected from workspace.

To perform the docking calculations, we used the "Extra Precision" Glide algorithm. XP GlideScore is a function that severely penalizes poses that violate established physical and chemistry principles, e.g. charged and strong polar groups forming H-bonds or adequately being exposed to the solvent (33). This algorithm is broadly used to minimize positive falses and is highly useful for studies in which the number of structures is limited and pursue the highest possible computational quality.

Re-docking

Re-docking procedure for the three integrases models were performed afterwards to obtain the GlideScore data. The procedure was carried out using the workflow QM-Polarized Ligand Docking by recalculating charges using quantum mechanics at the site. The best scores were used to recalculate the charges of 3,5-DCQA and also to perform the Re-docking by using Qsite and Jaguar (Schrodinger Inc). The 3,5-DCQA charges were obtained from the electrostatic potential energy surface which was evaluated from calculations in a single point using density functional theory (DFT) under 6-31G*/LACVP* basis set, B3LYP functional, Ultrafine SCF accuracy level parameters. Once the charges were calculated, a new docking was performed in XP mode, excluding those poses that were duplicated (Root Mean Square deviation value is less than 5 [angstrom] and the atomic displacement is less than 1.3 [angstrom]). The final pose was selected based on Coulomb-vdW energy.

Binding free energy calculations

In order to select which complex pose displays the best affinity, we evaluated the binding free energy (BFE). The best re-docking scoring pose was taken for BFE calculations. Energy difference mode framed in eMBrAcE software (Schrodinger Inc.) was used for calculating receptor, ligand and complex energies, and the energy change was evaluated based on the following equation:

[DELTA]E = [E.sub.complex] - [E.sub.ligand] - [E.sub.protein] [1]

The values of free energy for the three complexes were subjected to energy minimization in implicit solvent (water) using OPLS-2005 force field with dielectric constant of one. PRCG method was used to calculate solvation energy of electrostatic component. A conjugate gradient minimization protocol with 10,000 maximum steps of iterations and convergence threshold of 0.05 was used to determine the minimum energy.

Results

Homology modeling

The HTLV-I Integrase model that was obtained by homology modeling (homology 44%, identity 34% and positivity 44%) (Figure 1), presented well structured regions of five beta sheets and four alpha helices. The well- structured regions displayed high similarity with other integrases that have been analyzed by X-Ray diffraction, which include the Avian Sarcoma Virus (ASV, pdb: 1VSD and pdb: 1VSH); Human Immunodeficiency Virus (HIV-1, pdb: 1BIZ) and Prototype of Human Foamy Virus (PFV, pdb: 3DLR) (Figure 2).

Docking and re-docking

Docking and re-docking were performed in order to analyze the main physicochemical and thermodynamically issues of the interaction of 3,5 DCQA with the catalytic domain of HTLV-I IN (Figure 3).

The presence of one [Mg.sup.2+] ion (IN1[Mg.sup.2+]) showed the best affinity interaction characterized by a low score value in GlideScore (-12,363 kcal/mol). These results were corroborated with quantum mechanics calculations (Table 1). The complex 3,5-DCQA-HTLV-I IN interactions were analyzed in major dock score. Interestingly, we identified interactions between 3,5-DCQA and the functional domain amino acids (Asp15-Asp72-Glu108); for all the cases thirteen interactions for IN0[Mg.sup.2+] were observed, four of them corresponding to hydrogen bonds (Figure 4a). Similarly, thirteen interactions were observed for IN1[Mg.sup.2], with two electrostatic types between ligand, caffeic acid group and [Mg.sup.2+] ion, and six hydrogen bonds (Figure 4b). In this model, Glu108 and Asp72 established H-bonds with 3,5-DCQA. Finally, IN2[Mg.sup.2+] presented the highest number of interactions (23 in total); six H-bonds and six electrostatic bonds connected with [Mg.sup.2+] ions. In this model, Asp15 and Glu108 bound through H-bonds to 3,5-DCQA (Figure 4c).

[FIGURE 1 OMITTED]

Binding free energy

Binding free energy calculations showed that the presence of one [Mg.sup.2+] ion presents the best affinity, confirming the docking and re-docking results (Table 2).

Discussion

In this in silico study we reported for the first time a homology model of the catalytic domain of integrase (IN) for HTLV-I. Comparison of our homology model with some crystallographic structures of IN for other viruses, such as: HIV-1 (1BIZ), VSA (1VSD, 1VSH) and PFV (3DLR) showed a high similarity structure, especially in the positions of the amino acid of the catalytic site, Asp15, Asp72 and Glu108, suggesting that these amino acids are very important for the enzymatic function of IN. Additionally, these results support our homology model of IN for HTLV-1.

We found that the presence of [Mg.sup.2+] ions as protein cofactor in vivo could affect the binding between the IN of HTLV-1 and the chemical compound 3,5-DCQA as well. A single [Mg.sup.2+] ion can stabilize the complex between IN and 3,5-DCQA, decreasing the interaction energy and showing a more specific binding. The same results were obtained using different mathematical models simulations, such as: Docking, Re-docking and BFE.

It is important to notice that a single [Mg.sup.2+] ion could increase the binding stability between 3,5-DCQA and IN of HTLV-1, the 3,5-DCQA itself can bind within or near to the catalytic domain of IN and set up interactions with at least two of the three amino acids of the catalytic domain (Asp15, Asp72 and Glu108). This result suggests that 3,5-DCQA is an important molecule with a high pharmaceutical potential against IN of HTLV-1, and therefore, further experimental studies are needed.

Regarding the interactions between IN, [Mg.sup.2+] ions and 3,5-DCQA generated in each model, the higher affinity was observed in the interaction between IN1[Mg.sup.2+] and 3,5-DCQA. However, the interactions in model IN2[Mg.sup.2+] were more frequent (24 interactions) compared with the interactions in IN1[Mg.sup.2+] and IN0[Mg.sup.2+] models (13 interactions each). One possible explanation for this result could be that the interactions in IN1[Mg.sup.2+] are stronger, such as hydrogen bonds, in comparison with the other two models, where the energy of the system increases and improves the affinity of interaction. This aspect was evident for the GlideScore value obtained in this study.

Similar studies have been performed in the IN of HIV-1 in order to evaluate the influence of [Mg.sup.2+] in molecules with a potential inhibitor to IN of HIV-1 via binding free energy calculations. Wang and coworkers (37) reported in an in silico study the influence of [Mg.sup.2+] ions on the binding between IN of HIV-1 and the inhibitor molecule Thiazolothiazepine (2H-benzo(f)thiazolo(2,3-c)(1,4)thiazepine-5,11(3H, 11aH)-dione) using computer simulation and methodologies such as docking and molecular dynamics. Results showed that the presence of [Mg.sup.2+] ions could effectively avoid or influence the binding between them. Also, that the presence of a single [Mg.sup.2+] ion coordinated by Asp 64 and Asp116 decreases the docking energy and determines a more specific binding. However, the presence of a second [Mg.sup.2+] ion coordinated by Asp64 and Glu152 is disadvantageous for the interaction, since it increases the range of energy and decreases the affinity of the coupling (34). Our results are in agreement with the results obtained by Wang et al. (34) for the interaction between 3,5-DCQA and IN of HTLV-1, although the ligand molecules showed a different structure.

[FIGURE 2 OMITTED]

[FIGURE 3 OMITTED]

Other authors have suggested that there is not enough countercharge in the catalytic domain of the enzyme to allow simultaneous coupling of two divalent cations in adjacent sites (35, 36). Additionally, it has been proposed that although there are two [Mg.sup.2+] ions in the catalytic site, in the presence of viral DNA only one would be available to interact with one incoming inhibitor molecule, because the second ion may be largely shielded, while the first ion could be much more exposed (37).

[FIGURE 4 OMITTED]

Based on experimental evidence of the crystal structure of the IN of Avian Sarcoma Virus (ASV), it has been suggested that there could be two [Mg.sup.2+] ions interacting in the catalytic domain of IN for HIV-1 (16). However, so far only the presence of one [Mg.sup.2+] ion of IN for HIV-1 has been experimentally characterized. Unlike what was initially expected, our studies showed greater affinity between the IN of HTLV-1 and 3,5-DCQA when one [Mg.sup.2+] ion is present. The experimental observation supports our proposed predictive results of IN for HTLV-1.

Conclusion

We calculated the binding model between IN of HTLV-1 and the chemical compound 3,5-DCQA using molecular modeling, such as Docking, Re-docking and Binding Free Energy (BFE). The results confirmed that the presence of [Mg.sup.2+] ions could affect the binding between 3,5-DCQA and the IN enzyme of HTLV-1. Also, we found that the presence of a single [Mg.sup.2+] ion in the interface ligand-enzyme favors the interaction of the complex. Additionally, it was determined that regardless of the presence of [Mg.sup.2+] ions important for catalytic activity of the enzyme, 3,5-DCQA established interactions with any of the amino acids that are highly conserved in the IN enzyme catalytic site of HTLV-1. Therefore, we propose that the 3,5-DCQA is a molecule with an anti-integrase pharmaceutical potential.

Acknowledgments

We want to extend our appreciation to: Dr. Andres Gonzalez Barrios (Universidad de los Andes, Colombia) and Dr. Mihaela Delcea (University of Greifswald, Germany) for critical reading of the manuscript.

Financial support

This work was partially supported by grants of COLCIENCIAS (Young Researchers Program) and the Vice-Rectorate of the Pontificia Universidad Javeriana (PUJ 001648).

Conflict of interest

The authors declare that there are no conflicts of interest.

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Angela Pena [1] *, Juvenal Yosa [2] *, Yesid Cuesta-Astroz [1], Orlando Acevedo [3], Leonardo Lareo [dagger], Felipe Garcia-Vallejo [1]

[1] Laboratorio de biologia molecular y patogenesis. Departamento de ciencias fisiologicas. Escuela de ciencias basicas. Departamento de Salud. Universidad del Valle. Sede San Fernando. Cali, Colombia.

[2] Universidad Distrital Francisco Jose de Caldas. Facultad de ciencias ambientales. Ingenieria ambiental. Av. Circunvalar Venado de Oro., Bogota, Colombia.

[3] Laboratorio de bioquimica computacional y estructural y bioinformatica. Departamento de nutricion y Bioquimica. Facultad de ciencias. Pontificia Universidad Javeriana. Bogota, D.C. Colombia.

* viviana.pena@gmail.com; juvenal.yosa@unibas.ch

Received: 18-11-2011; Accepted: 23-03-2012
Table 1. Docking and re-docking energy results in Kcal/mol of the
interaction between 3, 5-Dicaffeoylquinic Acid and three models of
HTLV-I integrase, using Glide "Xtra Precision" algorithm.

Model *     Study        No. of      GlideScore **
                          poses          (XP)
                        generated

I         Docking           10          -5,414
          Re-docking                    -6,315
II        Docking           10          -12,363
          Re-docking                    -11,789
III       Docking           10          -8,622
          Re-docking                    -7,656

Model *   Emodel ***    CvdW ****

I          -57,688       -49,585
           -123,452      -87,301
II         -95,8287      -67,412
           -244,867     -142,170
III        -123,525      -91,190
           -502,784     -253,890

* Model I = IN0[Mg.sup.2+]; model II = IN1[Mg.sup.2+] and model III =
IN2[Mg.sup.2+]. ** GlideScore values correspond to best pose
generated with Glide of 10 poses generated. *** Emodel is a specific
combination of GScore, CvdW and the internal torsional energy of the
ligand conformer. **** CvdW = Coul + vdW is the non-bonded
interaction energy between ligand and receptor.

Table 2. Calculated energies and estimated values of Binding Free
Energy (BFE) of 3,5-Dicaffeoylquinic Acid coupled to three models of
HTLV-I integrase in kcal/mol.

Model *   3,5-DCQA    IN-HTLV    Complex 3,5-DCQA-IN   [DELTA]E **

I         -166,600   -6768,425        -6947,431          -12,406
II        -180,443   -1783,416        -7482,986          -76,415
III       -173,787   -2090,551        -7430,551          -32,412

* Model I = IN0[Mg.sup.2+]; model II = IN1[Mg.sup.2+] and model III =
IN2[Mg.sup.2+]

** [DELTA]E is calculated from [DELTA]E = [E.sub.complex] -
[E.sub.ligand] - [E.sub.protein]
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Title Annotation:Original paper
Author:Pena, Angela; Yosa, Juvenal; Cuesta-Astroz, Yesid; Acevedo, Orlando; Lareo, Leonardo; Garcia-Vallejo
Publication:Revista Universitas Scientarum
Article Type:Report
Date:Jan 1, 2012
Words:4730
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