Journal of Structural Biology 186 (2014) 132–140

Contents lists available at ScienceDirect

Journal of Structural Biology journal homepage: www.elsevier.com/locate/yjsbi

Structural dynamics of V3 loop in a trimeric ambiance, a molecular dynamics study on gp120–CD4 trimeric mimic Balasubramanian Chandramouli a,1, Giovanni Chillemi b, Alessandro Desideri a,⇑ a b

Department of Biology, University of Rome Tor Vergata, Via Della Ricerca Scientifica, Rome 00133, Italy CASPUR Inter-universities Consortium for Supercomputing Applications, Via dei Tizii 6b, Rome 00185, Italy

a r t i c l e

i n f o

Article history: Received 15 October 2013 Received in revised form 3 January 2014 Accepted 20 February 2014 Available online 28 February 2014 Keywords: gp120 Molecular dynamics V3 loop Co-receptor recognition

a b s t r a c t Entry of HIV virus into the host cell is initiated by the interaction of its surface exposed gp120 protein with the cell surface CD4 receptor and a co-receptor that can be either CCR5 or CXCR4. The third variable region (V3 loop) of gp120 has an important role in co-receptor selection by gp120 and forms an epitope for neutralizing antibodies. In this work the dynamical behavior of the V3 loop in a trimeric environment has been investigated by generating an atomistic trimer model of gp120–CD4 complex and has been compared with the result of a monomeric gp120–CD4 complex. The main results coming from this work are that the three V3 loops belonging to the three subunits of the trimer display a different dynamical behavior in terms of its flexibility, spatial orientation, motion along the principal modes, conformations, solvent exposure and electrostatic potential distribution. We propose that the ability of the V3 loop to present, in the trimeric environment, simultaneous multiple alternative conformations that increase its capability of co-receptor recognition, is at least in part due to the effect of electrostatic potential generated by two subunits over the third one. Ó 2014 Elsevier Inc. All rights reserved.

1. Introduction Envelope spikes of HIV is made up of the heterodimer of a transmembrane gp41 and a surface exposed gp120. HIV’s entry into the host cell is initiated by gp120’s interactions firstly with the cell surface CD4 receptor and subsequently with a co-receptor. The major co-receptors that are associated with HIV entry are the chemokine receptors CCR5 and CXCR4, which belong to seven transmembrane GPCR family. The conformational changes accompanying these interactions result in gp41 mediated fusion of HIV and host cell membranes. HIV isolates are classified, based on their ability to use either or both of the co-receptors, as R5/X4/R5X4 tropic strains (Berger et al., 1998). Understanding the mechanistic principles that directs the gp120’s interaction with the host cell receptors has an implication on targeting HIV at the entry level. Comparative sequence analysis of gp120 isolates have shown the protein to consist of five conserved (C1–C5) and five variable (V1–V5) regions (Los Alamos National Laboratory, 1987; Starcich et al., 1986). Several X-ray crystallographic structures of gp120 in complex with a

⇑ Corresponding author. Fax: +39 06 2022798. E-mail address: [email protected] (A. Desideri). Present address: Scuola Normale Superiore di Pisa, P.zza dei Cavalieri 7, Pisa 56126, Italy. 1

http://dx.doi.org/10.1016/j.jsb.2014.02.014 1047-8477/Ó 2014 Elsevier Inc. All rights reserved.

bound CD4 and antibody have reported the three dimensional organization of these regions. In these complexes gp120 unanimously takes up a unique folding into two domains, namely the inner and outer ones (Fig. 1), that are interspersed by a four stranded bridging b sheet (Diskin et al., 2010; Huang et al., 2004, 2005, 2007; Kwong et al., 1998, 2000a; Zhou et al., 2007). The third variable region of gp120 encodes a surface exposed loop (referred as the V3 loop) of 35 residues, known for its high sequence variability and structural heterogeneity (Sharon et al., 2003; Stanfield et al., 1999). The V3 loop is the principal determinant of the co-receptor preference by gp120 and it also contains epitope for neutralizing antibodies (Chesebro et al., 1991; De Jong et al., 1992; Fouchier et al., 1992; Goudsmit et al., 1988; Modrow et al., 1987). The co-receptor preference of gp120 has an important consequence on HIV infection and disease progression. R5 specific strains cause majority of the HIV infection while the population of X4 specific strains becomes predominant at a later stage (Princen and Schols, 2005; Regoes and Bonhoeffer, 2005). Hence there has been a major focus to understand the V3 guided co-receptor recognition by gp120. X-ray and NMR studies of V3 derived peptides in free and complex form with antibodies have shown the conformational polymorphisms of the loop (Galanakis et al., 2005; Sirois et al., 2005). The V3 loop intact in gp120 revealed an extended structure, protruding up to 3 nm from the core towards the target membrane (Huang et al., 2005). Following the earlier work that

B. Chandramouli et al. / Journal of Structural Biology 186 (2014) 132–140

133

resolution model proposed by advanced electron microscopic and tomographic approach (Merk and Subramaniam, 2013). In the present work, we have attempted to investigate the structural dynamical features of the V3 loop in the trimeric environment, where each V3 loop can feel the presence of its oligomeric partners. Taking advantage of the available EM data and X-ray models, we have produced a trimeric atomistic model of the gp120–CD4 complex and performed multiple MD simulations in explicit solvent conditions for a total time of 65 ns. The dynamical behavior of the V3 loop in the trimeric environment has been analyzed and compared with the simulation results of the monomeric gp120–CD4 complex, previously reported by us (Chandramouli et al., 2013). Our work highlights the different structural features of the V3 loop in terms of its orientation, conformational variability and sampling that increases the probable space presented for co-receptor interaction/recognition in the trimeric environment. 2. Materials and methods 2.1. The trimeric atomistic model Fig.1. Three dimensional structure of gp120. Gp120 extracted from the X-ray crystallographic ternary complex with bound CD4 and X5 antibody (2b4c). The inner and outer domains are colored in purple and dark blue. The green region represents the bridging b sheet. The locations of variable regions are indicated for clarity. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

implied the association of V3 loop net charge with the co-receptor usage, a charge based 11/25 rule, correlating the presence of a basic residue at positions 11 or 25 to CXCR4 recognition was proposed (De Jong et al., 1992; Fouchier et al., 1992). Sophisticated computational algorithms utilizing mainly the V3 loop’s sequence and structural informations have been developed with the attempt to predict the co-receptor phenotype of gp120 with high sensitivity (Dybowski et al., 2010; Jensen et al., 2003, 2006; Pillai et al., 2003; Resch et al., 2001; Sander et al., 2007). The dynamical behavior of the V3 loop has been investigated by computational modeling studies. Earlier molecular dynamics (MD) simulations of the free and CD4 bound gp120 have highlighted the inherent flexibility of the V3 loop that is more enhanced in the presence of CD4 (Hsu and Bonvin, 2004; Liu et al., 2008a,b, 2007; Pan et al., 2005). Other simulation studies, combined with experimental evidences, elucidated the role of V3 loop’s net positive charge in (i) influencing the immunological escape of gp120 (ii) co-receptor phenotype evolution and (iii) the loop’s ability to modulate the interaction space presented for antibody recognition (Naganawa et al., 2008; Yokoyama et al., 2012). In a more recent work, via MD simulations on V3 loops with same net charge but different starting conformations, the authors have shown a conserved electrostatic potential profile around the loop that could dictate the interaction with the co-receptor (López de Victoria et al., 2012b). Through MD simulations on multiple of gp120– CD4 complexes, we have reported the importance of V3 loop electrostatics in the context of its three dimensional orientation and co-receptor recognition (Chandramouli et al., 2012, 2013). However the details concerning the recognition must still be elucidated and this can be in part due to the fact that the structural dynamics of the V3 loop in the trimeric environment still remains elusive and it has never been attempted. To date, atomic models of the complete trimeric structure has not been resolved by X-ray crystallographic methods, although some models have been proposed based on the data from the mutagenesis and biochemical investigations of monomeric gp120 (Chen et al., 2005; Kwong et al., 2000b). Previously insightful informations on the three dimensional organization of native HIV trimer have become available thanks to a low

The trimer structure was modeled by fitting the gp120 X-ray crystallographic ternary complex (pdb id:2b4c), containing the full structure of the V3 loop region into the density map of HIV-1 trimer derived by electron tomography (emdb id: 5020) that represents the native HIV-1 trimer in ternary complex with CD4 and 17b antibody (Huang et al., 2005; Liu et al., 2008a,b). The fitting of the X-ray model has been done using the Chimera program (Goddard et al., 2007). The procedure involved a global search through a random placement of the X-ray model over the density map, followed by a local optimization. This returned a list of fits that are ranked by the density cross-correlation coefficient as the fit score. The correlation coefficient ranges from 1 to +1 and indicates the agreement between the simulated map constructed from the atomic coordinates and the experimental density map (Pintilie et al., 2010). The presence of the bound CD4 and antibody permitted an unambiguous best fit (Supplementary Fig. S1) that was chosen by visual inspection and maximum fit score whose value was 0.853. The symmetric copies were built imposing the threefold symmetry of the experimental map. The starting gp120–CD4 trimeric model, after excluding the antibody (Fig. 2), was placed in a solvent box and two independent simulations have been performed (referred below as Sim A and B). The results of the trimer simulations are also compared with a previously studied gp120– CD4 monomer simulation (Sim M) (Chandramouli et al., 2013). 2.2. MD simulations The starting trimer structure, after excluding the antibody, was immersed in a cubic box of TIP3P water (Jorgensen et al., 1983) that extended up to 16 Å from the solutes and neutralized with counter ions. The simulations were done in periodic boundary condition using Amber package and ff99SB forcefield (Case et al., 2005; Hornak et al., 2006). The long-range electrostatics have been calculated with the PME method (Darden et al., 1993). Bond lengths involving bonds to hydrogen atom were constrained with SHAKE algorithm and an integration time step of 2 fs was used (Ryckaert et al., 1977). The sampling was done at NPT condition, with a constant pressure of 1 atm and a temperature of 303 K. Langevin coupling with a collision frequency of 1.0 ps-1 was used for temperature regulation (Izaguirre et al., 2001). Prior to production simulation, the system was equilibrated in multiple steps that involved (i) two rounds of minimization (3000 iterations) and dynamics (30 ps) of the solvent and counter ions in the bulk solvent, keeping the solute restrained using a force constants of 50, 100, 300, and

134

B. Chandramouli et al. / Journal of Structural Biology 186 (2014) 132–140

where Dri is the displacement from the mean position of the ith atom and the hi represent the time average over the whole analyzed portion of the trajectory. The principal component analysis was performed diagonalizing the covariance matrix, obtained from the atomic fluctuations (of Ca atoms) after the removal of the translational and rotational movement (Amadei et al., 1993). Clustering of conformations was performed using the single-linkage and Jarvis Patrick algorithms implemented in gromacs tools using a 2 Å rmsd cutoff. With the chosen cutoff, similar result was obtained with both algorithms. Here we describe the result of single-linkage method. Solvent accessible surface area calculation was performed with Naccess program (Hubbard and Thornton, 1993). The electrostatic potential was calculated with APBS software using 2.0 and 80 as the solute and solvent dielectrics at zero salt concentration (Baker et al., 2001). The figures were generated with UCSF chimera and the plots were generated using matplotlib library (Hunter, 2007; Pettersen et al., 2004). 3. Results 3.1. Structural deviation and flexibility

Fig.2. Trimer model obtained by the fitting of X-ray coordinates. Starting trimer model from the top (A) and side (B) views. The yellow sphere represents the axis of rotation. Gp120 and CD4 are shown in blue and cyan. The V3 loop is colored in red. The green arrow indicates the direction towards the target membrane. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

50 kcal/(mol Å2), (ii) three rounds of minimization of whole system where the solute restraint was kept as 25, 10 and 5 kcal/(mol Å2), (iii) an unrestrained minimization of the whole system, (iv) Finally the system was heated to 303 K at constant volume and equilibrated for 650 ps at constant pressure. The production phase was initiated at this stage. During the production phase a low force constant of 1.0 kcal/(mol Å2) was applied on the CD4 receptor to restrain its position closer to the equilibrated configuration, whilst the gp120 protein is left free to move. The snapshots were collected in the trajectories at an interval of 2 ps. 2.3. Trajectory analysis The rmsd analysis was performed with the starting conformation as the reference. All the other analyses were performed on the last 25 ns of the trajectory. The rmsf calculation was done after a least square root mean square fitting to the average structure from the simulation. The DCC matrix was computed considering the coordinates of the Ca atoms as follows,

Cij ¼ hDri Drj i=

qffiffiffiffiffiffiffiffiffiffiffiffiqffiffiffiffiffiffiffiffiffiffiffiffi hDr2i i hDr2j i

Plot of rmsd Vs time is depicted in Fig. S2 (Supplementary) for the two trimeric simulations. The figure reveals that the rmsd values are similar and lower upon omitting the V3 loop, indicating the large contribution of the loop to the overall structural deviation of the protein. This is also confirmed by the average rmsd value with and without the V3 loop summarized in Table 1. A large flexibility of the V3 loop has been also reported in previous simulation studies on monomeric gp120 bound to the CD4 (Chandramouli et al., 2012; Hsu and Bonvin, 2004). The average rmsd values also evidentiate a different degree of structural deviation of the loop in the three subunits of the trimer with respect to the starting configuration. The comparison of the gp120 conformations obtained from the trimer and the monomer simulation indicates that the rmsd values when the V3 loop is omitted are low, demonstrating that the gp120 core is highly stable and compact in both the trimeric and monomeric simulations (Table 1). On the other hand, the rmsd of the V3 loop alone indicates that only in a single subunit (T3A, T3B) the V3 loop reaches in the trimeric simulations, a value comparable to the one observed for the monomeric simulation. Plot of the averaged per-residue backbone root mean square fluctuation (rmsf), calculated by fitting the conformations over the respective average structures (Fig. S3) shows large values around the variable regions, that are more enhanced at the level of the V3 loop. The flexibility of each residue can be better visualized in a 3D representation of the average structures, where the residues having large or low values are represented with a color scale from red to blue, respectively (Fig. S4). The 3D representation also shows that the V3 loop has different orientations in each of the three subunits of the trimer. However, in both trimer simulations one subunit displays a V3 loop orientation similar to the one observed in the monomer simulation, where the loop is located close to the bridging b sheet. In line the rmsd values of the V3 loop of these subunits (T3A, T3B) from the average V3 loop structure observed in the monomer simulation is low (Table 1, panel II). 3.2. Correlated and concerted protein motion The global inter protein communication during the dynamics are inferred from the dynamic residue cross correlation and principal component analyses (Chillemi et al., 2008; Mancini et al., 2012). Dynamic cross correlation analysis has been carried out on the Ca atoms to estimate the overall correlated motion between the protein residues. Positive values of the cross-correlation

135

B. Chandramouli et al. / Journal of Structural Biology 186 (2014) 132–140 Table 1 Summary of the average root mean square deviation (in Å) over last 10 ns. Sim. A

Sim. B

M

Tl

T2

T3

Tl

T2

T3

I Gp120 Without V3 V3 loop

6.02 (0.20) 1.89(0.11) 10.28(0.55)

3.85(0.22) 2.18(0.15) 7.19(0.47)

4.96 (0.24) 2.33 (0.27) 8.69 (0.49)

5.14(0.33) 3.12(0.17) 5.57 (0.49)

4.20 (0.24) 2.31 (0.12) 6.11 (0.49)

3.20(0.22) 2.00(0.11) 4.43 (0.68)

II Gp120 Without V3 V3 loop

5.79(0.14) 2.40(0.11) 9.38(0.30)

4.97(0.18) 2.24(0.11) 8.44 (0.33)

4.23 (0.27) 2.47(0.13) 4.92 (0.54)

6.08 (0.36) 2.77(0.13) 7.12(0.35)

4.91 (0.16) 2.55 (0.09) 6.26 (0.34)

2.96(0.12) 2.56 (0.08) 2.92 (0.27)

3.79(0.20) 2.32(0.11) 4.73 (0.23)

(Panel I) Average backbone rmsd and std. deviations (in parenthesis) for the trimeric (Sim. A, B) and monomeric (M) simulations. (Panel II) average backbone rmsd with respect to the average gp120 structure from the monomer simulation.

coefficients Cij indicate a correlated motion between the two residues i and j. Negative values of Cij indicate an anti-correlated motion. The 2D dcc matrix, depicted in Fig. 3 for the trimer simulation A and B shows a considerable degree of correlation between the residues within each gp120 subunit. The figure also indicates the lack of any strong correlated motion of the V3 loop with the other regions of the same protein, confirming that the loop behaves as an independent unit of gp120, as already observed in the monomer simulations (Chandramouli et al., 2012, 2013). However when we consider the inter-subunit correlation, the V3 loop displays some degree of correlation with residues in the other subunits, indicating that the loop is the region that is mainly feeling the presence of the oligomeric partners. In addition some inter-subunit correlations are also observed at the level of the V4 loop. Informations on the main direction of the protein motion has been obtained from the principal component analysis (pca) that extracts the eigen vectors (or subspace) in which the majority of the dominant motion occurs. The pca analysis performed on the trimer and monomer trajectories revealed a percentage contribution of the first three eigen vectors of 65 (Sim A), 63 (Sim B) and 75 (M), respectively over the total motion. Projection of the motion along the first eigenvector (Fig. 4) indicates that a large quantity of the motion is localized over the V3 loops although the direction is different for each subunit of the trimer. In both trimer simulations (A, B), one of the V3 loops (T3A, T3B) tends to move in a space close to the bridging b sheet similar to what observed in the monomer simulation (Fig. 4, M). This trend in the V3 loop motion was also observed along the second and third eigenvectors (Figs. S5 and S6). 3.3. Conformational clustering and solvent accessibility To pick up representative snapshots that can best explain the different conformations explored by the V3 loop in the trimeric and monomeric conditions, a single combined trajectory of gp120 has been created, extracting conformations from both the trimer and monomer simulations at an interval of 20 ps. Clustering has been performed on the combined artificial trajectory focusing on the V3 loop alone, using the single-linkage algorithm with different rmsd values as a measure of similarity for grouping the structures. The clustering, performed with a rmsd threshold of 2 Å results in five different clusters CL1–CL5 that are differently contributed by V3 loop conformations from monomer and trimer simulations (Fig. 5). The largest cluster CL1 is populated with V3 loop conformations coming from the monomer and from the subunits T3A and T3B of the two trimer simulations. The other four clusters are populated by V3 loops each coming from one of the two subunits of the trimer (T1A,T2A,T1B,T2B). This result confirms that the V3 loop of subunits T3A and T3B from the trimer simulations A and B samples conformations close to the V3 loop of the monomeric simulation. The superimposition of the cluster

representatives shows that the V3 loops belonging to the individual clusters differ noticeably from each other in terms of conformation and orientation respect to the outer domain of gp120 (Fig. 5), indicating the ability of the loop to simultaneously sample, in the trimeric environment, a multiple conformational space, offering a variable accessible surface area that can be taken as an important parameter for the interaction with the co-receptor. The distribution of the solvent accessible surface area (sasa) of the V3 loops belonging to the three subunits of the trimer have a different degrees of solvent exposure as a reflection of the difference in their conformational features (Suppl. Fig. S7). The distribution of the sasa values also shows a large overlap of the solvent accessibility of the V3 loop from the monomer to the one of the subunits T3A and T3B from the two trimer simulations, confirming that these subunits display a V3 loop conformation similar to the monomer simulation, in agreement with what has been observed through rmsd and clustering analyses. 3.4. Distribution of the electrostatic surface Several studies have previously demonstrated the importance of V3 loop electrostatics towards the co-receptor recognition (Chandramouli et al., 2013; López de Victoria et al., 2012a; Naganawa et al., 2008). The electrostatic potential has been calculated on the average trimer structure, obtained from two trimer simulations and the distribution of the positive and negative isosurfaces of the electrostatic potential is depicted in Suppl. Fig. S8. The figure qualitatively confirms that the spread of the positive isosurface of the three V3 loops is noticeably different in the trimeric structure as a reflection of their conformational variability. The co-receptor recognition by gp120 is a two step process that is initiated by the interaction of the V3 loop tip with the second extracellular loop of the co-receptor followed by a more specific binding of the co-receptor to a binding site formed by the V3 loop base and part of the bridging b sheet. The differential spread of the V3 loops electrostatic surface around the trimer could from one side facilitate the interaction with the co-receptor or permit a simultaneous recognition of multiple co-receptors by the three V3 loops. In agreement, the results obtained from pca analysis indicate the differential motion of the three V3 loops along the principal modes that can facilitates the individual recognition of the co-receptor. 3.5. Inter subunit interactions The distribution of the positive and negative electrostatic potential iso-surfaces, additively produced by two subunits or by a single subunit, have been evaluated in order to guess the factor that could influence the different conformational behavior of the V3 loop in a trimeric environment. The distribution of the electrostatic iso-surfaces, depicted in Fig. 6, shows that the additive

136

B. Chandramouli et al. / Journal of Structural Biology 186 (2014) 132–140

Fig.3. Dynamic residue cross correlation matrix. DCC map of gp120 for trimer Sim A (top) and B (bottom). The correlated values in range 0.25 < Cij < 0.5, 0.50 < Cij < 0.75 and 0.75 < Cij < 1.0 are represented in green, yellow and red, respectively. The anti-correlated values in range 0.75 < Cij < 0.5 and 1.0 < Cij < 0.75 are represented in cyan and blue. Shaded portion indicates the V3 loop. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

contribution of two subunits is able to reach the surface of the third one, whilst the distribution generated by an individual subunit does not (Fig. S9), indicating that each subunit can feel the combined influence of the other two. As a matter of fact the electrostatic potential coming from two subunits can actually reach

and overlap the V3 loop. This can be appreciated coloring the surface of each subunit using the additive electrostatic potential produced by the other two subunits (Fig. S10), providing an explanation for the different behavior shown in each subunit by the V3 loop in a trimeric environment. The fluctuation of the

B. Chandramouli et al. / Journal of Structural Biology 186 (2014) 132–140

137

Fig.4. Motion along the first principal component. Motion of Ca of gp120 along the first eigenvector generated by interpolating structures between the extreme conformations sampled during the simulation along the eigenvector. V3 loop is depicted with a range of colors between the extreme conformations (cyan and red), while other regions are shown in khaki. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

system makes the electrostatic potential produced by two subunits over the third one different for each subunit, forcing the V3 loop to move in a different way.

4. Discussion The third variable region of gp120, the V3 loop, is an important component of the protein that determines the co-receptor preference of gp120. The choice over specific co-receptor by gp120 has an important consequence on HIV infection and disease progression. The ability of HIV to switch the co-receptor is also being used as a resistance mechanism against CCR5 inhibitors. It has been shown that even a single amino acid changes in the V3 loop can switch the viral co-receptor usage (Hu et al., 2000; Verrier et al., 1999). Computational prediction algorithms, utilizing the V3 loop informations, have been proposed to distinguish co-receptor phenotypes of gp120 with good efficiency. The V3 loop has also been the subject of many studies that attempted to understand how its structural/dynamical features modulate its recognition properties (Hsu and Bonvin, 2004; López de Victoria et al., 2012b; Yokoyama et al., 2012). To this aim MD simulations have been widely used. However structural dynamics of the V3 loop in

a trimeric context has never been attempted and remains elusive. To this end, in this work a trimeric model of the gp120–CD4 complex has been modeled using the available data from the electron tomography and X-ray crystallography (Fig. 2). The trimer model has been subjected to two independent MD simulations and the trajectories have been examined to understand how the presence of the three subunits can influence their behavior with a major focus on the V3 loop. Analysis of the residue fluctuation indicates that the V3 loop is characterized by the largest flexibility in line with the previous MD simulations on monomeric gp120 in free and CD4 bound states (Chandramouli et al., 2012; Hsu and Bonvin, 2004) and through the lack of resolution of the V3 loop in most of the X-ray structures of gp120 in complex form with CD4 and antibody. In the trimeric simulations, the core of the individual gp120 remains compact and rigid while the V3 loop remains as the most flexible part of the protein. However the three V3 loops display a different degree of orientation with respect to the starting configuration likely due to the presence of the neighboring subunits (Fig. S2, Table 1). This can be well appreciated comparing the averaged structure colored on the basis of the rmsf values that not only reveals the large fluctuations on the V3 loop tip but also the different orientation with respect to the outer domain of gp120 (Fig. S4). MD studies on a

138

B. Chandramouli et al. / Journal of Structural Biology 186 (2014) 132–140

Fig.5. Conformational clusters and superimposition of representative structures. (A) Occupancy of the individual clusters in the combined trajectory, (B) Superimposition of cluster representatives. The outer domain of gp120 is shown in ribbon representation in gray while V3 loop belonging to the individual cluster are colored differently for clarity. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

set of monomeric gp120’s (bound with CD4) having different net V3 loop charge and co-receptor specificity have demonstrated that the V3 electrostatics largely dictates its orientation in the 3D space (Chandramouli et al., 2013). In detail, we observed that the V3 loop with a low net charge orients itself close to the bridging b sheet, while the loop with high net charge moves away from the bridging b sheet. In the trimer simulations, the three V3 loops display different orientation with respect to the core despite having the same net charge indicating that the trimeric environment may differently perturb the loops behavior permitting multiple simultaneous conformations for co-receptor recruitment. The correlated motion, examined via the dcc matrix reveals the lack of any strong intra-subunit correlated motion of the three V3 loops in the trimer (Fig. 3), indicating their tendency to behave like an independent part of protein as observed in the case of monomeric gp120 (Chandramouli et al., 2012; Hsu and Bonvin, 2004). However the V3 loop reaches a preferential different conformation in each subunit of the trimer and this can be likely due to the occurrence of the inter-subunit correlations that mainly involves the V3 loop. The inter-subunits center of mass distance, calculated over the gp120 core, is constant during the whole simulation time (data not shown) indicating that the relative positions of each subunit are

maintained, likely due to the strong interaction with the CD4 receptor. Considering this constant distance the electrostatic potential generated by individual subunits is unable to reach the surface of the neighboring subunits (Fig. S9), whilst the additive electrostatics generated by two subunits overlaps the surface of the third subunit (Fig. 6). In detail the V3 loop is well overlapped by the additive electrostatic potential of the neighboring subunits (Fig. S10) providing a possible explanation for the different dynamical behavior of the loop in each subunit. The presence of different V3 loop conformations confers the possibility of the recognition of multiple co-receptors. In support, the pca analysis shows difference of the three V3 loops motion along the principal modes (Fig. 4, Figs. S5 and S6). The clustering and sasa analyses reveal and confirm the ability of the V3 loop to adopt varying conformations and solvent exposure in the trimeric simulations (Fig 5, S7). It is interesting however that two loops belonging to the subunits T3A, T3B of the two trimer simulations sample conformations close to that obtained from the monomeric simulation. The tendency of the same V3 loop to adopt different conformations, as the electrostatic potential differences in the proximity of the V3 loops (Fig. S8), confer to the loop the ability to interact with multiple co-receptor conformations. In agreement, NMR and X ray studies of V3 peptides in complex with antibodies

B. Chandramouli et al. / Journal of Structural Biology 186 (2014) 132–140

139

Fig.6. Distribution of the additive electrostatic potential surface. Positive (blue) and negative (red) electrostatic surfaces at a contour level of ±0.5 KT/e. In each case, the surface of the third subunit is colored using the color of the additive electrostatic potential generated by the other two subunits. The yellow sphere indicates the trimer axis. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

have demonstrated the ability of the V3 loop to adopt alternative conformations to interact with different antibodies (Sharon et al., 2003; Stanfield et al., 1999).

the CXCR4 one. The conformational variability of the V3 loop may help in recognizing the CCR5 conformation bound with the antagonist and so in providing resistance.

5. Conclusion and implications

Acknowledgment

In conclusion, the present work highlights how the trimeric arrangement of the gp120 may provide a simultaneous multiple conformations to the V3 loop. The V3 loop is an important element of gp120 for co-receptor recognition and antibody binding and its ability to present simultaneous multiple conformations has several implications in the HIV entry mechanism. The co-receptor binding is a two step process that involves (i) the interaction of the V3 loop tip with the ECL2 (second extracellular loop) of the co-receptor and (ii) the binding of a sulfated tyrosine localized at the co-receptor Nterminal domain to a region between the V3 loop base and the bridging b sheet. The ECL’s are flexible regions and the multiple V3 loop conformations may aid the loop-coreceptor recognition. The different motion and conformation of the V3 loops in the trimeric environment can also facilitate the independent recruitment of multiple co-receptors. Co-receptor antagonists that prevent the interaction with gp120 have been reported. Viral resistance to such compounds may occur either through a switch of the co-receptor choice or mutations in HIV envelope genomic regions that enables gp120 to bind to the inhibitor bound co-receptors. The available data for resistance against CCR5 antagonists suggest that the virus keeps interacting with the CCR5 receptor rather than shifting to

The authors acknowledge Caspur HPC facility for the resource time granted for carrying out the simulations. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.jsb.2014.02.014. References Amadei, A., Linssen, A.B.M., Berendsen, H.J.C., 1993. Essential dynamics of proteins. Proteins: Structure, Function, and Bioinformatics 17, 412–425. Baker, N.A., Sept, D., Joseph, S., Holst, M.J., McCammon, J.A., 2001. Electrostatics of nanosystems: application to microtubules and the ribosome. Proc. Natl. Acad. Sci. U.S.A. 98, 10037–10041. Berger, E.A., Doms, R.W., Fenyo, E.-M., Korber, B.T.M., Littman, D.R., Moore, J.P., Sattentau, Q.J., Schuitemaker, H., Sodroski, J., Weiss, R.A., 1998. A new classification for HIV-1. Nature 391, 240. Case, D.A., Cheatham 3rd, T.E., Darden, T., Gohlke, H., Luo, R., Merz Jr, K.M., Onufriev, A., Simmerling, C., Wang, B., Woods, R.J., 2005. The Amber biomolecular simulation programs. J. Comput. Chem. 26, 1668–1688. Chandramouli, B., Chillemi, G., Abbate, I., Capobianchi, M.R., Rozera, G., Desideri, A., 2012. Importance of V3 Loop Flexibility and Net Charge in the Context of CoReceptor Recognition. A Molecular Dynamics Study on HIV gp120. J. Biomol. Struct. Dyn. 29, 879–891.

140

B. Chandramouli et al. / Journal of Structural Biology 186 (2014) 132–140

Chandramouli, B., Chillemi, G., Giombini, E., Capobianchi, M.R., Rozera, G., Desideri, A., 2013. Structural dynamics of V3 loop with different electrostatics: implications on co-receptor recognition: a molecular dynamics study of HIV gp120. J. Biomol. Struct. Dyn. 31, 403–413. Chen, B., Vogan, E.M., Gong, H., Skehel, J.J., Wiley, D.C., Harrison, S.C., 2005. Structure of an unliganded simian immunodeficiency virus gp120 core. Nature 433, 834– 841. Chesebro, B., Nishio, J., Perryman, S., Cann, A., O’Brien, W., Chen, I.S., Wehrly, K., 1991. Identification of human immunodeficiency virus envelope gene sequences influencing viral entry into CD4-positive HeLa cells, T-leukemia cells, and macrophages. J. Virol. 65, 5782–5789. Chillemi, G., D’Annessa, I., Fiorani, P., Losasso, C., Benedetti, P., Desideri, A., 2008. Thr729 in human topoisomerase I modulates anti-cancer drug resistance by altering protein domain communications as suggested by molecular dynamics simulations. Nucleic Acids Res. 36, 5645–5651. Darden, T., York, D., Pedersen, L., 1993. Particle mesh Ewald: An N [center-dot] log(N) method for Ewald sums in large systems. J. Chem. Phys. 98, 10089– 10092. De Jong, J.J., De Ronde, A., Keulen, W., Tersmette, M., Goudsmit, J., 1992. Minimal requirements for the human immunodeficiency virus type 1 V3 domain to support the syncytium-inducing phenotype: analysis by single amino acid substitution. J. Virol. 66, 6777–6780. Diskin, R., Marcovecchio, P.M., Bjorkman, P.J., 2010. Structure of a clade C HIV-1 gp120 bound to CD4 and CD4-induced antibody reveals anti-CD4 polyreactivity. Nat. Struct. Mol. Biol 17, 608–613. Dybowski, J.N., Heider, D., Hoffmann, D., 2010. Prediction of co-receptor usage of HIV-1 from genotype. PLoS Comput. Biol. 6, e1000743. Fouchier, R.A., Groenink, M., Kootstra, N.A., Tersmette, M., Huisman, H.G., Miedema, F., Schuitemaker, H., 1992a. Phenotype-associated sequence variation in the third variable domain of the human immunodeficiency virus type 1 gp120 molecule. J. Virol. 66, 3183–3187. Galanakis, P.A., Spyroulias, G.A., Rizos, A., Samolis, P., Krambovitis, E., 2005. Conformational properties of HIV-1 gp120/V3 immunogenic domains. Curr. Med. Chem. 12, 1551–1568. Goddard, T.D., Huang, C.C., Ferrin, T.E., 2007. Visualizing density maps with UCSF Chimera. J. Struct. Biol. 157, 281–287. Goudsmit, J., Debouck, C., Meloen, R.H., Smit, L., Bakker, M., Asher, D.M., Wolff, A.V., Gibbs Jr, C.J., Gajdusek, D.C., 1988. Human immunodeficiency virus type 1 neutralization epitope with conserved architecture elicits early type-specific antibodies in experimentally infected chimpanzees. Proc. Natl. Acad. Sci. U.S.A. 85, 4478–4482. Hornak, V., Abel, R., Okur, A., Strockbine, B., Roitberg, A., Simmerling, C., 2006. Comparison of multiple Amber force fields and development of improved protein backbone parameters. Proteins 65, 712–725. Hsu, S.-T.D., Bonvin, A.M.J.J., 2004. Atomic insight into the CD4 binding-induced conformational changes in HIV-1 gp120. Proteins 55, 582–593. Huang, C.-C., Lam, S.N., Acharya, P., Tang, M., Xiang, S.-H., Hussan, S.S.-U., Stanfield, R.L., Robinson, J., Sodroski, J., Wilson, I.A., Wyatt, R., Bewley, C.A., Kwong, P.D., 2007. Structures of the CCR5 N terminus and of a tyrosine-sulfated antibody with HIV-1 gp120 and CD4. Science 317, 1930–1934. Huang, C., Tang, M., Zhang, M.-Y., Majeed, S., Montabana, E., Stanfield, R.L., Dimitrov, D.S., Korber, B., Sodroski, J., Wilson, I.A., Wyatt, R., Kwong, P.D., 2005. Structure of a V3-containing HIV-1 gp120 core. Science 310, 1025–1028. Huang, C., Venturi, M., Majeed, S., Moore, M.J., Phogat, S., Zhang, M.-Y., Dimitrov, D.S., Hendrickson, W.A., Robinson, J., Sodroski, J., Wyatt, R., Choe, H., Farzan, M., Kwong, P.D., 2004. Structural basis of tyrosine sulfation and VH-gene usage in antibodies that recognize the HIV type 1 coreceptor-binding site on gp120. Proc. Natl. Acad. Sci. U.S.A. 101, 2706–2711. Hubbard, S., Thornton, J., 1993. ‘‘NACCESS’’, computer program. Hunter, J., 2007. Matplotlib: A 2D graphics environment. Comput. Sci. Eng. 9, 90–95. Hu, Q., Trent, J.O., Tomaras, G.D., Wang, Z., Murray, J.L., Conolly, S.M., Navenot, J.-M., Barry, A.P., Greenberg, M.L., Peiper, S.C., 2000. Identification of ENV determinants in V3 that influence the molecular anatomy of CCR5 utilization. J. Mol. Biol. 302, 359–375. Izaguirre, J.A., Catarello, D.P., Wozniak, J.M., Skeel, R.D., 2001. Langevin stabilization of molecular dynamics. J. Chem. Phys. 114, 2090. Jensen, M.A., Coetzer, M., van ’t Wout, A.B., Morris, L., Mullins, J.I., 2006. A reliable phenotype predictor for human immunodeficiency virus type 1 subtype C based on envelope V3 sequences. J. Virol. 80, 4698–4704. Jensen, M.A., Li, F.-S., van ’t Wout, A.B., Nickle, D.C., Shriner, D., He, H.-X., McLaughlin, S., Shankarappa, R., Margolick, J.B., Mullins, J.I., 2003. Improved coreceptor usage prediction and genotypic monitoring of R5-to-X4 transition by motif analysis of human immunodeficiency virus type 1 env V3 loop sequences. J. Virol. 77, 13376–13388. Jorgensen, W.L., Chandrasekhar, J., Madura, J.D., Impey, R.W., Klein, M.L., 1983. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 79, 926. Kwong, P.D., Wyatt, R., Majeed, S., Robinson, J., Sweet, R.W., Sodroski, J., Hendrickson, W.A., 2000a. Structures of HIV-1 gp120 envelope glycoproteins from laboratory-adapted and primary isolates. Structure 8, 1329–1339. Kwong, P.D., Wyatt, R., Robinson, J., Sweet, R.W., Sodroski, J., Hendrickson, W.A., 1998. Structure of an HIV gp120 envelope glycoprotein in complex with the CD4 receptor and a neutralizing human antibody. Nature 393, 648–659.

Kwong, P.D., Wyatt, R., Sattentau, Q.J., Sodroski, J., Hendrickson, W.A., 2000b. Oligomeric modeling and electrostatic analysis of the gp120 envelope glycoprotein of human immunodeficiency virus. J. Virol. 74, 1961–1972. Liu, J., Bartesaghi, A., Borgnia, M.J., Sapiro, G., Subramaniam, S., 2008a. Molecular architecture of native HIV-1 gp120 trimers. Nature 455, 109–113. Liu, S.-Q., Liu, S.-X., Fu, Y.-X., 2007. Dynamic domains and geometrical properties of HIV-1 gp120 during conformational changes induced by CD4 binding. J. Mol. Model. 13, 411–424. Liu, S.-Q., Liu, S.-X., Fu, Y.-X., 2008b. Molecular motions of human HIV-1 gp120 envelope glycoproteins. J. Mol. Model. 14, 857–870. López de Victoria, A., Kieslich, C.A., Rizos, A.K., Krambovitis, E., Morikis, D., 2012a. Clustering of HIV-1 subtypes based on gp120 V3 loop electrostatic properties. BMC Biophys. 5, 3. López de Victoria, A., Tamamis, P., Kieslich, C.A., Morikis, D., 2012b. Insights into the structure, correlated motions, and electrostatic properties of two HIV-1 gp120 V3 loops. PLoS ONE 7, e49925. Los Alamos National Laboratory, 1987. Human retroviruses and AIDS: a compilation and analysis of nucleic acid and amino acid sequences. Theoretical Biology and Biophysics Group T-10, Los Alamos National Laboratory, Los Alamos, N.M. Mancini, G., D’Annessa, I., Coletta, A., Chillemi, G., Pommier, Y., Cushman, M., Desideri, A., 2012. Binding of an indenoisoquinoline to the topoisomerase-DNA complex induces reduction of linker mobility and strengthening of Protein-DNA interaction. PLoS ONE 7, e51354. Merk, A., Subramaniam, S., 2013. HIV-1 envelope glycoprotein structure. Curr. Opin. Struct. Biol. 23, 268–276. Modrow, S., Hahn, B.H., Shaw, G.M., Gallo, R.C., Wong-Staal, F., Wolf, H., 1987. Computer-assisted analysis of envelope protein sequences of seven human immunodeficiency virus isolates: prediction of antigenic epitopes in conserved and variable regions. J. Virol. 61, 570–578. Naganawa, S., Yokoyama, M., Shiino, T., Suzuki, T., Ishigatsubo, Y., Ueda, A., Shirai, A., Takeno, M., Hayakawa, S., Sato, S., Tochikubo, O., Kiyoura, S., Sawada, K., Ikegami, T., Kanda, T., Kitamura, K., Sato, H., 2008. Net positive charge of HIV-1 CRF01_AE V3 sequence regulates viral sensitivity to humoral immunity. PLoS ONE 3, e3206. Pan, Y., Ma, B., Nussinov, R., 2005. CD4 binding partially locks the bridging sheet in gp120 but leaves the beta2/3 strands flexible. J. Mol. Biol. 350, 514–527. Pettersen, E.F., Goddard, T.D., Huang, C.C., Couch, G.S., Greenblatt, D.M., Meng, E.C., Ferrin, T.E., 2004. UCSF Chimer—a visualization system for exploratory research and analysis. J. Comput. Chem. 25, 1605–1612. Pillai, S., Good, B., Richman, D., Corbeil, J., 2003. A new perspective on V3 phenotype prediction. AIDS Res. Hum. Retroviruses 19, 145–149. Pintilie, G.D., Zhang, J., Goddard, T.D., Chiu, W., Gossard, D.C., 2010. Quantitative analysis of cryo-EM density map segmentation by watershed and scale-space filtering, and fitting of structures by alignment to regions. J. Struct. Biol. 170, 427–438. Princen, K., Schols, D., 2005. HIV chemokine receptor inhibitors as novel anti-HIV drugs. Cytokine Growth Factor Rev. 16, 659–677. Regoes, R.R., Bonhoeffer, S., 2005. The HIV coreceptor switch: a population dynamical perspective. Trends Microbiol. 13, 269–277. Resch, W., Hoffman, N., Swanstrom, R., 2001. Improved success of phenotype prediction of the human immunodeficiency virus type 1 from envelope variable loop 3 sequence using neural networks. Virology 288, 51–62. Ryckaert, J., Ciccotti, G., Berendsen, H., 1977. Numerical integration of the cartesian equations of motion of a system with constraints: molecular dynamics of nalkanes. J. Comput. Phys. 23, 327–341. Sander, O., Sing, T., Sommer, I., Low, A.J., Cheung, P.K., Harrigan, P.R., Lengauer, T., Domingues, F.S., 2007. Structural descriptors of gp120 V3 loop for the prediction of HIV-1 coreceptor usage. PLoS Comput. Biol. 3, e58. Sharon, M., Kessler, N., Levy, R., Zolla-Pazner, S., Görlach, M., Anglister, J., 2003. Alternative conformations of HIV-1 V3 loops mimic beta hairpins in chemokines, suggesting a mechanism for coreceptor selectivity. Structure 11, 225–236. Sirois, S., Sing, T., Chou, K.-C., 2005. HIV-1 gp120 V3 loop for structure-based drug design. Curr. Protein Pept. Sci. 6, 413–422. Stanfield, R., Cabezas, E., Satterthwait, A., Stura, E., Profy, A., Wilson, I., 1999. Dual conformations for the HIV-1 gp120 V3 loop in complexes with different neutralizing fabs. Structure 7, 131–142. Starcich, B.R., Hahn, B.H., Shaw, G.M., McNeely, P.D., Modrow, S., Wolf, H., Parks, E.S., Parks, W.P., Josephs, S.F., Gallo, R.C., 1986. Identification and characterization of conserved and variable regions in the envelope gene of HTLV-III/LAV, the retrovirus of AIDS. Cell 45, 637–648. Verrier, F., Borman, A.M., Brand, D., Girard, M., 1999. Role of the HIV type 1 glycoprotein 120 V3 loop in determining coreceptor usage. AIDS Res. Hum. Retroviruses 15, 731–743. Yokoyama, M., Naganawa, S., Yoshimura, K., Matsushita, S., Sato, H., 2012. Structural dynamics of HIV-1 envelope Gp120 outer domain with V3 loop. PLoS ONE 7, e37530. Zhou, T., Xu, L., Dey, B., Hessell, A.J., Van Ryk, D., Xiang, S.-H., Yang, X., Zhang, M.-Y., Zwick, M.B., Arthos, J., Burton, D.R., Dimitrov, D.S., Sodroski, J., Wyatt, R., Nabel, G.J., Kwong, P.D., 2007. Structural definition of a conserved neutralization epitope on HIV-1 gp120. Nature 445, 732–737.