Multiple modes of cholesterol translocation in the human Smoothened receptor

  1. Prateek D Bansal
  2. Maia Kinnebrew
  3. Rajat Rohatgi
  4. Diwakar Shukla  Is a corresponding author
  1. Department of Chemical and Biomolecular Engineering, University of Illinois Urbana-Champaign, United States
  2. Department of Biochemistry, Stanford University School of Medicine, United States
  3. Department of Medicine, Stanford University School of Medicine, United States
  4. Department of Chemistry, University of Illinois at Urbana-Champaign, United States
  5. Department of Bioengineering, University of Illinois Urbana-Champaign, United States
  6. Cancer Center at Illinois, University of Illinois at Urbana-Champaign, United States
14 figures, 5 tables and 1 additional file

Figures

Figure 1 with 1 supplement
Overview of existing structures and hypotheses supporting the cholesterol translocation mechanisms in Smoothened.

(a) The binding sites of the sterols along the hypothesized tunnel in SMO. Sterol binding sites have been identified deep in the TMD (6XBL) (Qi et al., 2020), at the interface of CRD and TMD (6XBM; Qi et al., 2020), at the CRD sterol-binding site (5L7D; Byrne et al., 2016), and in a dual-bound mode where cholesterol is bound to both the TMD and CRD (6O3C; Deshpande et al., 2019). (b) Example simulation system showing SMO (5L7D, cyan) embedded in a membrane (white/magenta). Water is shown as a white surface, while sodium (purple), and chloride (green) ions are shown as spheres. (c) Pathway 1 and Pathway 2 investigate the translocation of cholesterol from the membrane to SMO’s TMD. (d) The Common Pathway follows the translocation of cholesterol from the TMD to the CRD. Snapshots in (a) are made from structures in the PDB, while (b–d) are frames taken from MD simulations.

Figure 1—figure supplement 1
Comparison of TM6 length for SMO (A) and β2AR (B).

SMO shows an elongated TM6, which emerges into the extracellular space.

Figure 2 with 3 supplements
The molecular events as cholesterol enters the core of SMO’s TMD from the outer leaflet of the membrane.

(a) Free energy plot showing the angle of cholesterol with the x-y plane, the plane of the membrane, versus the z-coordinate of cholesterol for Pathway 1. The pathway followed by cholesterol is α. The experimental structures of SMO are shown as black polygons. (b) Free energy landscape of cholesterol’s y-coordinate plotted versus cholesterol’s x-coordinate. Cholesterol interacts with residues in TM2-TM3 while entering the core TMD of SMO. (c–f) Insets show cholesterol’s interactions with residues at the membrane-protein interface for Pathway 1. (c,e) show cholesterol outside the protein (α), while (d, f) show cholesterol entering the protein (β). All snapshots presented are frames taken from MD simulations.

Figure 2—figure supplement 1
Error in free energies for Figure 2 and Figure 4.

Errors were computed using a bootstrapping strategy, where the MSM probabilities were computed from 80% of the data 200 times. (a) Error in Figure 2(a). (b) Error in Figure 2(b). (c) Error in Fig. 4(a). (d) Error in Fig. 4(b).

Figure 2—figure supplement 2
TICA (time-lagged independent component analysis) plot for SMO cholesterol transport - Pathway 1.

(A) The entire data projected along the first two time-lagged independent components (tICs). Free energies were calculated for each datapoint and reweighed using the Markov State Model probabilities. (B) The same data as (A), except the z-coordinate of the cholesterol plotted against the first two tICs. The translocation of cholesterol is the slowest process observed, as shown by the gradient in the plot. (C) Same as (A), but for Pathway 2. (D) Same as (B), but for Pathway 2.

Figure 2—figure supplement 3
Minimum energy path taken by cholesterol for both pathways.

(a) Minimum energy pathway for Pathway 1 (black), marked on Figure 2(a). Note that the order of transitions is α. (b) Free energy profile as cholesterol moves along Pathway 1. The progress is mapped by the cholesterol translocation progress variable. (c) Minimum energy pathway for Pathway 2 (black), marked on Figure 4(a). Note that the order of transitions is η. (d) Free energy profile as cholesterol moves along Pathway 2. The progress is mapped by the cholesterol translocation progress variable.

Figure 3 with 5 supplements
Effects of mutations along Pathways 1 and 2 on the activation of SMO.

(a) Gli1 mRNA fold changes show the responsiveness of SMO mutants to SHH. Untreated Gli1 levels indicate low SMO activity, while SHH-treated values correspond to the level of SMO activation induced by SHH ligand. A t-test with Welch’s correction was used to compute statistical significance. (p values: untreated vs treated: WT: 1.327 × 10-3, G2.57f V: 9.212 × 10-3, IECL2 A: 4.2 × 10-5, A2.60f M: 7.1 × 100-5, R5.64f A: 2.062 × 10-3, R5.64f Q: 1.192 × 10-3, F6.36f I: 2.163 × 10-3, L5.62f A: 1.948 × 10-3, treated WT vs treated mutant: G2.57f V: 9.1 × 10-3, IECL2 A: 0.02734, A2.60f M: 0.7477, R5.64f A: 0.08858, R5.64f Q: 0.02766, F6.36f I: 1.923 × 10-3, L5.62f A: 2.306 × 10 key: Not significant (ns) p > 0.05, *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, and ****p ≤ 0.0001, All experimental data represent biological replicates, N=4.) (b) ΔGli1 mRNA fold change (SHH vs untreated) and Δ PMF (difference of peak PMF, calculated as PMFWT - PMFmutant) plotted for the mutants in Pathway 1. (c) Example mutant A2.60f M shows that cholesterol is able to enter SMO through Pathway 1 even on a bulky mutation. (d) Same as (b) but for Pathway 2 (e) Example mutant L5.62f A shows that cholesterol can enter SMO through Pathway 2 due to lesser steric hindrance. All snapshots presented are frames taken from MD simulations.

Figure 3—figure supplement 1
Experimental data for mutants along Pathway 1.

(a) Immunoblotting was used to measure abundance of mSMO and GLI1 proteins in SMO-/- cells stably expressing either mSMO-WT or Pathway 1 mutants after treatment with SHH. (b) Gli1 mRNA fold change plotted for SMO mutants, showing fold change when the mutants are untreated, treated with a low concentration of SHH, and treated with a saturating concentration of SHH.

Figure 3—figure supplement 1—source data 1

PDF file containing original western blots for Figure 3—figure supplement 1a, indicating the relevant bands and treatments.

https://cdn.elifesciences.org/articles/108030/elife-108030-fig3-figsupp1-data1-v1.zip
Figure 3—figure supplement 1—source data 2

Original files for western blot analysis displayed in Figure 3—figure supplement 1a.

https://cdn.elifesciences.org/articles/108030/elife-108030-fig3-figsupp1-data2-v1.zip
Figure 3—figure supplement 2
PMF data for mutants along Pathway 1.

(a) PMF for cholesterol translocation was computed for hSMO G280V and compared with WT hSMO using adaptive biasing force-based simulations. Representative figures showing the mutation for WT G280 (b) versus V280 (c). (d, g) - Same as (a) but for I389A and A283M, respectively. (e, h) same as (b) but for I389 and A283, respectively. (f, i) - same as (c) but for A389 and M283, respectively.

Figure 3—figure supplement 3
Tunnel diameter profile for WT versus mutant A283M.
Figure 3—figure supplement 4
Experimental data for mutants along Pathway 2.

(a) Immunoblotting was used to measure abundance of mSMO and GLI1 proteins in SMO-/- cells stably expressing either mSMO-WT or Pathway 2 mutants after treatment with SHH. (b) Gli1 mRNA fold change plotted for SMO mutants, showing fold change when the mutants are untreated, treated with a low concentration of SHH, and treated with a saturating concentration of SHH.

Figure 3—figure supplement 4—source data 1

PDF file containing original western blots for Figure 3—figure supplement 4a, indicating the relevant bands and treatments.

https://cdn.elifesciences.org/articles/108030/elife-108030-fig3-figsupp4-data1-v1.zip
Figure 3—figure supplement 4—source data 2

Original files for western blot analysis displayed in Figure 3—figure supplement 4a.

https://cdn.elifesciences.org/articles/108030/elife-108030-fig3-figsupp4-data2-v1.zip
Figure 3—figure supplement 5
PMF data for mutants along Pathway 2.

(a) PMF for cholesterol translocation was computed for hSMO R421A/R421Q and compared with WT hSMO using adaptive biasing force-based simulations. Representative figures showing the mutation for WT R421 (b) versus A421 (c) and Q421 (d). (e, h) - Same as (a) but for F455I and L419A, respectively. (f, i) same as (b) but for F455 and L419, respectively. (g, j) - same as (c, d) but for I455 and A419, respectively.

Figure 4 with 1 supplement
The molecular events as cholesterol enters the TMD from the inner leaflet in Pathway 2.

(a) Free energy plot showing the angle of cholesterol with the x-y plane, the plane of the membrane, versus the z-coordinate of cholesterol for Pathway 2. The pathway followed by cholesterol is η. The experimental structures of SMO are shown as black polygons. (b) Free energy landscape of cholesterol’s y-coordinate plotted versus cholesterol’s x-coordinate for Pathway 2. Cholesterol interacts with residues in TM5-TM6 for Pathway 2 while entering the SMO core TMD. (e–h) Insets show cholesterol’s interactions with residues at the membrane-protein interface for Pathway 2. (c, e) show cholesterol outside the protein (η), while (d, f) show cholesterol entering the protein (θ) for Pathway 2. All snapshots presented are frames taken from MD simulations.

Figure 4—figure supplement 1
Comparison of cholesterol entry with existing resolved structure.

Frame from MD simulation showing cholesterol entry (cyan-blue), and resolved structure (PDB 8CXO, Zhang et al., 2022, orange). Cholesterol from the MD simulation frame is magenta, cholesterol from the resolved structure is white.

Figure 5 with 2 supplements
Multiple positions of cholesterol as it translocates through the Common Pathway, including the off-pathway intermediate.

(a) upright (δ), (b) tilted (γ), (c) the overtilted off-pathway intermediate (ϵ), and (d) cholesterol at the CRD binding site (ζ). All snapshots presented are frames taken from MD simulations.

Figure 5—figure supplement 1
Hydrophobic tunnel inside SMO core TMD.

Cholesterol interacts with the hydrophobic core of the TMD along the transport pathway. Figure corresponds to pose δ in Figure 4.

Figure 5—figure supplement 2
Cholesterol (purple) forms a tilted pose to enter the CRD binding site.

This is due to the presence of the Linker Domain (yellow).

Figure 6 with 3 supplements
The effects of mutations along the translocation pathway connecting the TMD and CRD binding sites on the activation of SMO.

(a) Gli1 mRNA fold changes show the responsiveness of SMO mutants to SHH. Untreated Gli1 levels indicate low SMO activity, while SHH-treated values correspond to the level of SMO activation induced by SHH ligand. A t-test with Welch’s correction was used to compute statistical significance. (p values: untreated vs treated: WT: 3 × 10-6, YLD A: 2.46 × 10-4, F6.65f A: 1.08 × 10-3, IECL3 A: 1.12 × 10-4, treated WT vs treated mutant: F6.65f A: 1.6 × 10-5, IECL3 A: 1.6 × 10-5, YLD A: 1.4 × 10-5, key: Not significant (ns) p > 0.05, *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, and ****p ≤ 0.0001, All experimental data represent biological replicates, N=4.) (b) ΔGli1 mRNA fold change (SHH vs untreated) and Δ PMF (difference of peak PMF, calculated as PMFWT - PMFmutant) are plotted for mutants along the TMD-CRD pathway. (c, d) Example mutants YLD A and F6.65f A show that cholesterol is unable to translocate through this pathway because of the loss of crucial hydrophobic contacts provided by Y207 and F484 and along the solvent-exposed pathway.

Figure 6—figure supplement 1
Experimental data for mutants along the Common Pathway between the TMD and the CRD.

(a) Immunoblotting was used to measure the abundance of mSMO and GLI1 proteins in SMO−⁄− cells stably expressing either mSMO-WT or Common Pathway mutants after treatment with SHH. (b) Gli1 mRNA fold change plotted for SMO mutants, showing fold change when the mutants are untreated, treated with a low concentration of SHH, and treated with a saturating concentration of SHH.

Figure 6—figure supplement 1—source data 1

PDF file containing original western blots for Figure 6—figure supplement 1a, indicating the relevant bands and treatments.

https://cdn.elifesciences.org/articles/108030/elife-108030-fig6-figsupp1-data1-v1.zip
Figure 6—figure supplement 1—source data 2

Original files for western blot analysis displayed in Figure 6—figure supplement 1a.

https://cdn.elifesciences.org/articles/108030/elife-108030-fig6-figsupp1-data2-v1.zip
Figure 6—figure supplement 2
PMF data for mutants along the Common Pathway between the TMD and the CRD.

(a) PMF for cholesterol translocation was computed for hSMO Y207A and compared with WT hSMO using adaptive biasing force-based simulations. Representative figures showing the mutation for WT Y207 (b) versus A207 (c). (d, g) - Same as (a) but for F484A and I509A, respectively. (e, h) same as (b) but for F484 and I509, respectively. (f, i) - same as (c) but for A484 and A509, respectively.

Figure 6—figure supplement 3
Cholesterol positions along the entire transport pathway from membrane to CRD.

Pathway 1 is shown as (α), while Pathway 2 is shown as (η) from the membrane to the TMD is shown separately in the left. The Common Pathway from the TMD to the CRD is α* with off-pathway intermediates ϵ and δ.

Figure 7 with 2 supplements
The tunnel profile during cholesterol translocation in SMO.

(a) Free energy plot of the z-coordinate versus the tunnel diameter when cholesterol is present in the core TMD. The tunnel shows a spike in the radius in the TMD domain, indicating the presence of a cholesterol-accommodating cavity. (b) Representative figure for the tunnel when a cholesterol molecule is in the TMD. (c) Same as (a), when cholesterol is at the TMD-CRD interface. (d) same as (b), when cholesterol is at the TMD-CRD interface. (e) same as (a), when cholesterol is at the CRD binding site. (f) same as (b), when cholesterol is at the CRD binding site. Tunnel diameters are shown as spheres. Cholesterol positions are marked on plots using dotted lines. All snapshots presented are frames taken from MD simulations.

Figure 7—figure supplement 1
Error in Free Energies for Figure 7.

Errors were computed using a bootstrapping strategy, where the MSM probabilities were computed from 80% of the data 200 times. (a) Plot showing error for Figure 7(a). (b) Plot showing error for Figure 7(b). (c) Plot showing error for Figure 7(c).

Figure 7—figure supplement 2
Average tunnel radius for Figure 7.

The different positions of the cholesterol are marked in bold, and the overall tunnel profile has been marked as translucent.

The timescales associated with the translocation of cholesterol through SMO.

Each major intermediate state has been marked (a–f). Timescales were obtained by calculating the mean first passage time (MFPT) using the Markov state model. Errors in timescales are shown as subscripts. The arrows represent the relative flux for the translocation between subsequent steps. The overall process occurs at a timescale of ∼1 ms.

Appendix 2—figure 1
Roundwise data collection for SMO Cholesterol transport as projected along the first two time-lagged independent components (tICs).

Round numbers are specified in the respective plots.

Appendix 2—figure 2
MSM Construction for SMO Cholesterol transport - Pathway 1.

(A) Implied Timescales versus MSM Lagtime plot shows the convergence of timescales. A lag time of 30 ns was chosen for the MSM construction. (B) VAMP2 score versus Number of Clusters used for clustering the TICA-reduced data at three different variational cutoffs. The final MSM was made using 200 clusters and a 95% cutoff (corresponding to 42 tIC dimensions).

Appendix 2—figure 3
MSM Construction for SMO Cholesterol transport - Pathway 2.

(A) The Implied Timescales versus MSM Lagtime plot shows the convergence of timescales. A lag time of 30 ns was chosen for the MSM construction. (B) VAMP2 score versus Number of Clusters used for clustering the TICA-reduced data at three different variational cutoffs. The final MSM was made using 400 clusters and a 65% cutoff (corresponding to 28 tIC dimensions).

Appendix 2—figure 4
Chapman Kolmogorov Test for MSM validation - Pathway 1.

Chapman-Kolmogorov test was performed using the deeptime library (Hoffmann et al., 2022).

Appendix 2—figure 5
Chapman-Kolmogorov Test for MSM validation - Pathway 2.

The Chapman-Kolmogorov test was performed using the deeptime library (Hoffmann et al., 2022).

Appendix 2—figure 6
Distance of the binding site of cholesterol (marked by D95) from the nearest lipid headgroups in the membrane.

Kernel density plotted for 2.1 ms of simulation data. The binding site is at least 20 Å away from the nearest lipid headgroup in simulations.

Tables

Key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Cell line (Mus musculus)Smo-/- MEFsRohatgi et al., 2007Mouse embryonic fibroblasts lacking Smoothened
AntibodyAnti-GLI1 (Mouse monoclonal, clone L42B10)Cell Signaling TechnologyCat# 2643; RRID:AB_2294746Western Blot, 1:1000 dilution
AntibodyAnti-SMO (Rabbit polyclonal)Rohatgi et al., 2007RRID:AB_3738384Western Blot, 1:2000 dilution
AntibodyAnti-GAPDH (Mouse monoclonal, clone 1E6D9)ProteinTechCat# 60004–1-Ig; RRID:AB_2107436Western Blot, 1:10,000 dilution
Chemical compound, drugHigh-glucose DMEMThermo Fisher ScientificCat# SH30081FS
Chemical compound, drugFetal Bovine Serum (FBS)Sigma-AldrichCat# S11150
Chemical compound, drugSodium pyruvateGibcoCat# 11-360-070
Chemical compound, drugL-glutamineGeminiBioCat# 400106
Chemical compound, drugMinimum essential medium NEAA solutionGibcoCat# 11140076
Chemical compound, drugPenicillin / StreptomycinGeminiBioCat# 400109
Chemical compound, drugSigmaFast Protease inhibitor cocktail, EDTA-freeSigma-AldrichCat# S8830
Appendix 1—table 1
Modeled residues in 5L7D-inactive-Apo-SMO starting structure.

The helical content of K440–I445 was modeled based on the structure of SANT1-bound SMO (PDB: 4N4W; Wang et al., 2014).

Modeled residues in 5L7D-inac-Apo-SMOConstraintsLocation
I429NoneICL3
K430NoneICL3
S431NoneICL3
N432NoneICL3
H433NoneICL3
P434NoneICL3
G435NoneICL3
L436NoneICL3
L437NoneICL3
S438NoneICL3
E439NoneICL3
K440α-helicalTM6
A441α-helicalTM6
A442α-helicalTM6
S443α-helicalTM6
K444α-helicalTM6
I445α-helicalTM6
Appendix 1—table 2
Composition of the membrane used for embedding the protein in simulations.
Lipid NameUpper LeafletLower Leaflet
Cholesterol (CHL1)2121
1-palmitoyl-2-oleoylphosphatidylcholine (POPC)7676
Palmitoylsphingomyelin (PSM)44
Total101101
Appendix 1—table 3
Adaptive Sampling metrics used for clustering during the iterative landscape exploration process.
W281M525V321M525W281V321
S278F526L325M525T241F274
D473E518D384S387D384Y394
Y322F391G277V321W281V321
V319Y323V276I320I316V319
N219P513L221I509Y487I509
S483N511Y207K395I215M301
N219W480W109Y130W109R161
E160R485I156E160L112I156
N114V210D209A492E208V488
CHLH470CHLN521CHLF391
CHLY394CHLS387CHLW281
CHLL522CHLN521CHLL325
CHLV404CHLT466CHLI408
CHLT528CHLV329CHLF462
CHLV463CHLF274CHLF332
CHLE518CHLD473CHLN521
CHLF391CHLY394CHLR400
CHLN521CHLL522CHLW281
CHLM525CHLP220CHLF484
CHLS387CHLH470CHLD384
CHLL515CHLV386CHLK395
CHLN219CHLF222CHLW480
CHLP513CHLL221CHLW109
CHLR161CHLI156CHLD95
CHLY130CHLI496CHLL112
CHLN114CHLK105CHLF166
CHLV210CHLL489CHLV157
CHLE160CHLL108CHLP164
Appendix 1—table 4
Round-wise data collection for Cholesterol transport of SMO.
Simulation RoundAmount of Data
Round 120.38 μS
Round 2460.15 μS
Round 371.12 μS
Round 482.17 μS
Round 543.26 μS
Round 626.70 μS
Round 7508.16 μS
Round 8184.63 μS
Round 9118.69 μS
Round 10550.59 μS
Total2066.227 μS

Additional files

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Prateek D Bansal
  2. Maia Kinnebrew
  3. Rajat Rohatgi
  4. Diwakar Shukla
(2026)
Multiple modes of cholesterol translocation in the human Smoothened receptor
eLife 14:RP108030.
https://doi.org/10.7554/eLife.108030.3