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Biophys J
Biophys J
Biophysical Journal
0006-3495
1542-0086
The Biophysical Society

S0006-3495(23)04176-0
10.1016/j.bpj.2023.12.024
Article
Bound ion effects: Using machine learning method to study the kinesin Ncd’s binding with microtubule
Guo Wenhan 12
Du Dan 2
Zhang Houfang 1
Sanchez Jason E. 2
Sun Shengjie 23
Xu Wang 1
Peng Yunhui yunhuipeng@ccnu.edu.cn
1∗
Li Lin lli5@utep.edu
24∗∗
1 College of Physical Science and Technology, Central China Normal University, Hubei, China
2 Computational Science Program, University of Texas at El Paso, El Paso, Texas
3 School of Life Sciences, Central South University, Hunan, China
4 Department of Physics, University of Texas at El Paso, El Paso, Texas
∗ Corresponding author yunhuipeng@ccnu.edu.cn
∗∗ Corresponding author lli5@utep.edu
30 12 2023
03 9 2024
30 12 2023
123 17 27402748
24 8 2023
27 12 2023
© 2023 Biophysical Society.
2023
Biophysical Society
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Drosophila Ncd proteins are motor proteins that play important roles in spindle organization. Ncd and the tubulin dimer are highly charged. Thus, it is crucial to investigate Ncd-tubulin dimer interactions in the presence of ions, especially ions that are bound or restricted at the Ncd-tubulin dimer binding interfaces. To consider the ion effects, widely used implicit solvent models treat ions implicitly in the continuous solvent environment without focusing on the individual ions’ effects. But highly charged biomolecules such as the Ncd and tubulin dimer may capture some ions at highly charged regions as bound ions. Such bound ions are restricted to their binding sites; thus, they can be treated as part of the biomolecules. By applying multiscale computational methods, including the machine-learning-based Hybridizing Ions Treatment-2 program, molecular dynamics simulations, DelPhi, and DelPhiForce, we studied the interaction between the Ncd motor domain and the tubulin dimer using a hybrid solvent model, which considers the bound ions explicitly and the other ions implicitly in the solvent environment. To identify the importance of treating bound ions explicitly, we also performed calculations using the implicit solvent model without considering the individual bound ions. We found that the calculations of the electrostatic features differ significantly between those of the hybrid solvent model and the pure implicit solvent model. The analyses show that treating bound ions at highly charged regions explicitly is crucial for electrostatic calculations. This work proposes a machine-learning-based approach to handle the bound ions using the hybrid solvent model. Such an approach is not only capable of handling kinesin-tubulin complexes but is also appropriate for other highly charged biomolecules, such as DNA/RNA, viral capsid proteins, etc.

Editor: Tamar Schlick.
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pmcSignificance

Ions are crucial for biomolecular interactions, especially for highly charged biomolecules. Bound ion effects are difficult to study in implicit solvent models. Based on the machine learning approach, we have developed a hybrid solvent method to combine the explicit solvent model with the implicit solvent model to study protein-protein interactions. Such a hybrid approach treats the bound ions explicitly and the free ions implicitly. This work applies the hybrid approach to a kinesin-tubulin complex, which demonstrates that the bound ions, especially the interfacial bound ions, play significant roles in kinesin-microtubule binding. This hybrid approach is not only capable of handling kinesin-tubulin complexes but is also appropriate for other highly charged biomolecules.

Introduction

Kinesin-14 is a motor protein belonging to the kinesin superfamily, which transports intracellular cargos along microtubules. The drosophila kinesin-14 (Ncd) is a minus-end-directed motor (1), with the Ncd motor domain located at the C-terminus of the peptide. Ncd proteins are nonprocessive motor proteins (2,3) and play important roles in spindle assembly, spindle pole organization, and chromosome dynamics. (4,5).

Due to their crucial biological functions, investigations into how Ncd works on microtubules have been enduring. Many studies have been carried out to investigate the mechanism of Ncd’s minus-end directionality on microtubules (6). The motion of Ncd is powered by ATP hydrolysis, similar to the mechanism in other molecular motors (7). The neck-motor interaction in the Ncd dimer plays a critical role in regulating the minus-end-directed movement (8,9,10). Some other studies demonstrated that conformational changes of the Ncd motor and microtubule are essential for Ncd’s movement and other functions (11,12,13).

Computational methods have been widely used to study motor proteins (14,15,16,17,18). Electrostatic features are crucial when studying protein-protein interactions (19,20,21,22,23,24,25). One difficulty in studying the electrostatic interactions between kinesins and the microtubule is that kinesins are highly positively charged while the microtubules are highly negatively charged. Ions surrounding kinesins and microtubules serve to mitigate charge differences and are, therefore, essential to the binding process. Understanding ionic contributions to the binding mechanism can be achieved by calculating the electrostatic potential, electric field lines, and electrostatic forces on a given system. Explicit solvent models are widely used in molecular dynamics (MD) simulations. After the MD simulations, when calculating the electrostatic potential, electrostatic forces, electric field lines, and other electrostatic features, Poisson-Boltzmann (PB) solvers such as DelPhi (26) are commonly used. As an implicit solvent model, PB solvers naturally consider all the ions as free ions implicitly in a Boltzmann distribution without considering individual ions, even the bound ions (27). This approximation is efficient for free ions in solvent, but for ions bound to the highly charged regions of kinesins and microtubules, the implicit solvent model is not sufficiently accurate. In order to improve the PB solvers, we apply the hybrid method to add bound ions to the biomolecules before running PB solvers. Then, the PB solvers can consider such bound ions explicitly and all the free ions implicitly.

Instead, the explicit solvent model is good at simulating the individual ions, including bound ions. In this work, we have used a hybrid solvent model (28,29,30) to study the interactions between Ncd and the tubulin dimer. Based on MD simulations using the explicit solvent model, bound ions were identified and added to the Ncd-tubulin dimer structures for implicit solvent calculations, which significantly improved the accuracy of electrostatic calculations.

This hybrid method, Hybridizing Ions Treatment-2 (HIT-2) (28,29,30), was developed based on the machine learning algorithm to calculate and treat the bound ions. It has been proven to be successful at simulating the highly charged biomolecules (28,29,30). Using comprehensive analyses in our previous work, we have demonstrated that this hybrid method fits the explicit models very well. This hybrid method was trained to optimize the bound ions predicted from the explicit solvent model. One advantage that explicit solvent models have is that they treat the ions individually. Therefore, explicit solvent models treat the bound ions better than the implicit solvent models. Thus, HIT-2 yields more accurate electrostatic features than pure implicit solvent models, especially when there are bound ions in the biomolecules. However, we must admit the limitations of this hybrid method: 1) since the bound ions used by the hybrid method are predicted by the explicit solvent model, the performance of this hybrid method depends on the accuracy of the explicit solvent model, which is used to predict the bound ions. 2) The hybrid method performs better when there are bound ions. If no bound ions are found in the biomolecular system, the hybrid method should perform the same as the implicit solvent model.

Besides the hybrid method HIT-2 (28,29,30), we studied the interactions between Ncd and the tubulin dimer by using multiscale computational approaches, including AlphaFold2 (31,32), DelPhi (33), DelPhiForce (34,35), and NAMD (36). To compare the hybrid solvent model with the implicit solvent model, we also performed similar calculations using the implicit solvent model, which does not consider the individual bound ions. Instead, the implicit solvent model treats all the ions as a Boltzmann distribution.

The structure containing bound ions, as determined by the hybrid solvent model, exhibits a notable difference in electrostatic potential when compared to calculations performed with the implicit solvent model. To better elucidate these differences, the position of bound ions and the residues that capture the bound ions were identified and analyzed. Also, the electric field lines and electrostatic forces between the Ncd motor and the tubulin dimer using different solvent models were studied, further demonstrating that using the hybrid solvent model and treating bound ions at the highly charged regions explicitly is crucial for electrostatic calculations. The hybrid solvent approach used in this study can also be widely utilized with other highly charged biomolecules to enhance the accuracy of calculations, such as DNA/RNA, viral capsid proteins, etc.

Materials and methods

Structure preparation

The 3D structure of the nonprocessive Drosophila Ncd motor is determined by x-ray diffraction with a resolution of 2.79 Å (PDB: 5W3D (37)). However, three flexible regions (amino acids 385–391, 540–547, and 588–598) are missing in the structure. Therefore, AlphaFold2 (31,32) was implemented to fix the missing regions. The pLDDT and pTM values of the AlphaFold2 model are 88.4 and 0.875, respectively. The root-mean-square deviation (RMSD) between the AlphaFold2-modeled structure and PDB: 5W3D (37) is 0.847 Å (Fig. S2), which demonstrates that the modeled structure is reliable.

After fixing the single structure of the Ncd motor domain, we then modeled the complex structure of Ncd and tubulins based on the template of a human kinesin motor-tubulin complex. Chimera was used to superimpose the Ncd structure to the complex of human kinesin-5/Eg5 motor-tubulins complex (PDB: 6TA4) (38). The RMSD between the Ncd structure and the human kinesin-5/Eg5 motor is 1.256 Å, and the sequence identity is 34% (Fig. S1). To optimize the modeled Ncd motor-tubulin dimer complex, a 40 ns MD simulation was performed using NAMD 2.12 (36) using the explicit solvent model. In the simulation, the pressure model followed Langevin dynamics. The pressure was set to 1 atm using a Nosé-Hoover Langevin piston barostat with a decay period of 50 fs. The temperature was set to 300 K using a Langevin thermostat with a damping coefficient of 1/ps. The force field applied was CHARMM36m (39). We used 150 mM KCl to ionize the system. Periodic boundary conditions and the long-range electrostatic interactions with particle mesh Ewald were performed during the simulation. The simulation was performed after a 20,000 step minimization. Residues with any atom within 10 Å from the Ncd motor with tubulin dimer binding interfaces were treated as interfacial residues. All the interfacial residues were set free while noninterfacial residues were constrained during the MD simulation. The simulation was visualized by Visual MD (VMD) (40). Based on the RMSD plot (Fig. S3), the last 20 ns was suitable for analysis. The last frame from the MD simulation was abstracted to be further studied because the protein structure was well equilibrated by the end of the MD simulation.

Hybrid solvent model

Highly charged proteins tend to trap ions on their charged surfaces. Because the binding interfaces between Ncd and the tubulin dimer are highly charged, investigating Ncd-tubulin dimer interactions in the presence of ions is crucial. The hybrid solvent model should be more accurate in revealing the electrostatic features than the pure implicit solvent model.

To calculate the electrostatic features of the Ncd-tubulin dimer using the hybrid solvent model, the machine-learning-based HIT-2 program (28,29,30) was used to model the Ncd motor-tubulin dimer with bound ions. HIT-2 applies an efficient algorithm to calculate the position of bound ions from MD simulations. The relative positions of ions are calculated (the mass center of biomolecules) based on ionic cloud, which was the superposition of trajectories during the MD simulations. HIT-2 cuts the ionic cloud into several cubes and initializes the cube size to 3 Å. The filling ratio is calculated in each cube based on its ions. When the filling ratio of a cube is higher than a given filling ratio threshold, the mass center of the ions in this certain cube is calculated as the position of the bound ion. All the ions in such a cube will be removed from the ionic cloud before the next iteration. Then, the cube is removed, and the cube size will increase in the next iteration. The updated ionic cloud and cube size are further used in the iterations until the cube size is bigger than 10 Å. Finally, the positions of bound ions are aligned with the biomolecular structure. As a result, we finally get the absolute position of bound ions in the biomolecular structure. During the process as shown in Fig. 1, the filling ratio threshold, MD simulation time, and step size are important parameters to be optimized by machine learning methods. In our previous work (28,29,30), modeling parameters were optimized by machine learning methods from thousands of datasets. Logistic regression (41), classification and regression tree (42,43), random forest (44), and artificial neural networks (45) were utilized to address the binary classification problem (success/failure). Quantitative analysis was applied to understand the relationship between error and related parameters after the classification. After testing, the optimized parameters produced results with errors lower than 0.2 Å. Multiple tests demonstrate that the machine-learning-based HIT-2 method can effectively identify bound ion types, numbers, and positions for biomolecules.Figure 1 The flow chart and 3D illustration of the machine-learning-based HIT-2 algorithm. (A) is the flow chart of the machine-learning-based HIT-2 algorithm. (B) is the 3D illustration of the machine-learning-based HIT-2 algorithm.. To see this figure in color, go online.

After obtaining the complex structure with bound ions, electrostatic features of the Ncd motor-tubulin dimer with bound ions were calculated via the DelPhi package. To identify the importance of treating bound ions explicitly, we also calculated the same electrostatic features with the implicit solvent model, in which DelPhi was performed without considering the individual bound ions from HIT-2.

Electrostatic potential comparison

To study the interaction of the Ncd motor with the tubulin dimer, DelPhi (33) was utilized to calculate electrostatic potential. DelPhi is a widely used computational tool for calculating the electrostatic potential of biomolecules, which solves the PB equation as shown in Eq. (1) using the finite-difference method:(1) ∇·[ϵ(r)∇φ(r)]=−4πρ(r)+ϵ(r)κ2(r)sinh(φ(r)/kBT)

where φ(r) is the electrostatic potential, ρ(r) is the permanent charge density, ε(r) is the dielectric permittivity, κ is the Debye-Huckel parameter, kB is the Boltzmann constant, and T is temperature.

During the calculation, the protein-filling percentage of the Delphi calculation box was set to 70.0, the boundary condition for the Poisson Boltzmann equation was set to the dipolar boundary condition, the probe radius for the molecular structure was 1.4 Å, and the salt concentration was 150 mM. The calculated electrostatic surface potentials were visualized with USCF Chimera (46), with the color scale ranging from −2.0 to 2.0 kT/e as shown in Fig. 2.Figure 2 Structures and electrostatic potentials of the Ncd motor-tubulin dimer using implicit/hybrid solvent models. (A) The structures of the Ncd motor-tubulin dimer without bound ions. The α-tubulin, β-tubulin, and Ncd motor are shown in blue, yellow, and purple, respectively. (B) The front view of the electrostatic potential for the Ncd motor-tubulin dimer using implicit solvent model. (C) The electrostatic potential of the Ncd motor binding interface using implicit solvent model. (D) The electrostatic potential of the tubulin dimer binding interface using implicit solvent model. (E) The structure of the Ncd motor-tubulin dimer with bound ions. The α-tubulin, β-tubulin, and Ncd motor are shown in blue, yellow, and purple, respectively. The Na+ and Cl− ions are shown as blue and red spheres, respectively. (F) The front view of the electrostatic potential for Ncd motor-tubulin dimer using hybrid solvent model. (G) The electrostatic potential of the tubulin dimer binding interface using the hybrid solvent model. (H) The electrostatic potential of the tubulin dimer binding interface using the hybrid solvent model. Positively and negatively charged regions are colored in blue and red, respectively. The color scale range is from −2.0 to 2.0 kT/e. To see this figure in color, go online.

The electrostatic potential of the Ncd motor-tubulin dimer was calculated via two models: the implicit solvent model and the hybrid solvent model. Each method generated a 3D potential map surrounding the complex. To compare the difference between the two models, we calculated the difference between the two potential maps and mapped the potential difference on the surface of the complex with bound ions shown (Fig. 3).Figure 3 Electrostatic potential difference mapped on the Ncd motor-tubulin dimer structure with bound ions. The α-tubulin, β-tubulin, and Ncd motor are shown in blue, yellow, and purple, respectively. The Na+ and Cl− ions are shown as blue and red spheres, respectively. (A) and (C) are the front view and back view of the Ncd motor-tubulin dimer with bound ions, respectively. (B) and (D) are the front view and back view of the electrostatic potential difference, respectively. To see this figure in color, go online.

Electric field lines comparison

Electric field lines between the Ncd motor and the tubulin dimer in the complexes calculated by the implicit solvent model and the hybrid solvent model were shown with VMD (40) to observe the electrostatic interaction difference in detail. The color scale ranges from −2.0 to 2.0 kT/e. The Ncd motor was separated by 20 Å from the tubulin dimer to get a better visualization. Densities of field lines represent the strengths of electrostatic interactions.

Electrostatic force comparison

To further investigate the interaction differences between the Ncd motor and the tubulin dimer using the hybrid or implicit solvent model, DelPhiForce (34,35) was used to calculate the electrostatic binding forces between the Ncd motor-tubulin dimer without/with bound ions. DelPhiForce calculates electrostatic forces by solving the PB equation as shown in Eq. (1).

In this study, the Ncd motor without/with bound ions was separated from 10 to 40 Å with a step size of 2 Å from the tubulin dimer without/with bound ions using StructureMan (47), separately. Finally, the directions and strengths of the net forces were displayed with VMD (40).

Results and discussion

To investigate the effect of bound ions when Ncd binds with microtubules, the electrostatic potential of the Ncd motor and the tubulin dimer was first calculated. Furthermore, the electric field lines were shown to see the strength of the interaction between the Ncd motor and the tubulin dimer using the implicit solvent model and the hybrid solvent model. Finally, the directions and magnitudes of electrostatic forces of the Ncd motor and the tubulin dimer were calculated to compare the accuracies between the implicit solvent model and the hybrid solvent model.

Electrostatic potential comparison

The electrostatic potentials on the surface of the Ncd motor and tubulin dimer were calculated using the implicit solvent and hybrid solvent models as shown in Fig. 2. The structures are rotated at certain angles to show the electrostatic potential on the Ncd motor-tubulin dimer binding interface. The Ncd motor and tubulin dimer are attractive if their interfaces have opposite net charges.

As shown in the front view (Fig. 2 B), the structure of the Ncd motor-tubulin dimer without explicit treated bound ions is predominantly negatively charged. When the bound ions are treated explicitly (Fig. 2 F), the neutral-charged region increases. The electrostatic potential on the binding interface of the tubulin dimer is also calculated with the implicit solvent model (Fig. 2 D) and the hybrid solvent model (Fig. 2 H). We found that the hybrid solvent model results in more neutrally charged regions than the implicit solvent model. Similar calculations were also performed on the binding interface of Ncd. The hybrid solvent model (Fig. 2 G) results in more positively charged regions than the implicit solvent model (Fig. 2 C).

In conclusion, the electrostatic potential calculated with the hybrid solvent model has a larger surface area of interacting opposite charges compared to that of the implicit solvent model. This demonstrates that, compared with the implicit solvent model, the hybrid solvent model describes a stronger binding interaction between the Ncd motor and the tubulin dimer. Such a stronger interaction may enhance the stability of the complex and imply tighter binding between the Ncd motor and tubulin dimer. Thus, treating bound ions explicitly at highly charged regions is crucial for performing electrostatic calculations.

To compare the implicit and hybrid solvent models clearly, the difference between the electrostatic potentials produced by the hybrid solvent and implicit models was analyzed and is shown in Fig. 3. The approach to calculating the potential difference is described in the materials and methods section. As shown in Fig. 3, two negatively charged regions are caused by two corresponding Cl− ions. Meanwhile, positively charged areas are related to corresponding Na+ ions. This means that bound ions significantly changed the electrostatic potential of the binding surface, which may affect the binding site of the Ncd motor with the tubulin dimer. The electric field lines and electrostatic forces will be discussed in the following sections.

To analyze the bound ions in detail, their positions are shown in Fig. 4. Among all the bound ions, the binding interfacial bound ions are shown in the close-up view to visualize the ion attractive residues, which are the oppositely charged residues within 8 Å distance from the ions. As shown in Fig. 4, all the bound ions on the binding interface are Na+ ions. Most of the bound ions (4 out of 5) on the binding surfaces are on β-tubulin. To recognize the key residues that are important for the bound ions, the residue or the group of residues was identified for each individual bound ion. For example, the Na+2 ion is bound to the Ncd motor because it is attracted by residues ASP203 and GLU 213, as shown in Fig. 4 A and Table 1. Each bound ion and its corresponding key residues are listed in Table 1. Such key residues are responsible for those bound ions in this Ncd-tubulin complex. This analysis is useful for future researchers who need to make mutations to remove any of the bound ions.Figure 4 Positions of bound ions. The α-tubulin, β-tubulin, and Ncd motor are shown in blue, yellow, and purple, respectively. The Na+ and Cl− ions are shown as blue and red spheres, respectively. The binding interfacial bound ions are shown in the close-up view to visualize the ion attractive residues. (A) The front view of the Ncd motor-tubulin dimer with bound ions. (B) The back view of the Ncd motor-tubulin dimer with bound ions. To see this figure in color, go online.

Table 1 Bound ions and their corresponding key residues

Protein	Ncd motor	α-Tubulin	β-Tubulin	
Bound ions	Cl−1	Na+1	Na+2	Cl−2	Na+3	Na+4	Na+5	Na+6	Na+7	Na+8	Na+9	Na+10		
Key residues	ARG178	ASP 111	ASP203	ARG308	GLU155	GLU196	ASP345	ASP199	ASP46	GLU343	ASP67	ASP88		
	ARG181		GLU213	LYS338	GLU196	ASP424	ASP438		ASP47		GLU108	ASP114		
				ARG339	GLU417				ASP245		GLU111	ASP118		

Electric field lines comparison

By using implicit/hybrid solvent models, the electric field lines between the Ncd motor and the tubulin dimer were calculated and are shown in Fig. 5 to investigate the electrostatic interactions. To better visualize the interactions, we separated the Ncd motor from the tubulin dimer by 20 Å. The density of the electrostatic field lines indicates the strength of the electrostatic interactions between the Ncd motor and the tubulin dimer. As shown in Fig. 5, the Ncd motor-tubulin dimer shows some repulsive field lines (highlighted with yellow circles) between the Ncd motor and tubulin dimer interfaces when the implicit solvent model is used. When using the hybrid solvent model instead, all the field lines between the Ncd motor and the tubulin dimer with bound ions are attractive and dense (highlighted with green circles). This means that when using the hybrid solvent model, the Ncd motor and the tubulin dimer show a stronger attractive force than when using the implicit solvent model.Figure 5 Electric field lines at the binding interfaces of Ncd motor-tubulin dimer using implicit/hybrid solvent models. (A) and (B) are the front view and the back view of the electric field lines between the Ncd motor and tubulin dimer using implicit solvent model, respectively. (C) and (D) are the front view and the back view of the electric field lines between the Ncd motor and tubulin dimer using hybrid solvent model, respectively. The repulsive forces between Ncd motor-tubulin dimer are highlighted with yellow circles, while the attractive forces between them are highlighted with green circles. To see this figure in color, go online.

Electrostatic forces comparison

DelPhiForce (34,35) was utilized to calculate the electrostatic forces for biomolecules. To compare the difference between the Ncd motor and the tubulin dimer using implicit/hybrid solvent models, the Ncd motors were separated from the tubulin dimer from 10 to 40 Å with a step size of 2 Å using StructureMan (47). Then, the electrostatic forces between the Ncd motor and the tubulin dimer were calculated at each position by DelPhiForce (34,35). The directions of the net forces between the Ncd motor and the tubulin dimer are shown in the form of blue arrows in Fig. 6. Note that the blue arrows only demonstrate the directions of net forces because the arrows are normalized to the same size. Fig. 6 reveals that both net forces using the implicit solvent model and the hybrid solvent model are attractive between the Ncd motors and the tubulin dimer.Figure 6 Electrostatic forces between the Ncd motor and tubulin dimer using implicit/hybrid solvent models. The α-tubulin, β-tubulin, and Ncd motor are shown in blue, yellow, and purple, respectively. (A) shows the directions of the electrostatic forces felt by the tubulin dimer at distances from 10 to 40 Å with a step size of 2 Å using the implicit solvent model. (B) shows the directions of the electrostatic forces of the Ncd motor-tubulin dimer at distances from 10 to 40 Å with a step size of 2 Å using the hybrid solvent model. To see this figure in color, go online.

The magnitudes of the net forces between the Ncd motor and the tubulin dimer were calculated by implicit and hybrid solvent models as presented in Fig. 7. The figure shows that when using either the implicit solvent model or the hybrid solvent model, the attractive force of the Ncd motor-tubulin dimer decreases as the distance between the Ncd motor and tubulin dimer is increased, which is expected to be due to Coulomb’s law. In addition, the Ncd-tubulin dimer experiences stronger net forces when using the hybrid solvent model instead of the implicit solvent model. This finding is consistent with the electrostatic potentials and electric field lines described previously.Figure 7 The magnitude of electrostatic forces of Ncd motor-tubulin dimer at distances from 10 to 40 Å with a step size of 2 Å using implicit/hybrid solvent models. To see this figure in color, go online.

Bound ions are important in biomolecules for their functions, but they are challenging to handle in implicit solvent models. This hybrid solvent method treats the bound ions explicitly to provide accurate analysis, which helps to reveal the electrostatic features of the Ncd motor. In this work, Ncd and the tubulins are highly charged and thus attract many bound ions. Therefore, the hybrid method is very effective for this Ncd-tubulin complex. Even though the hybrid method was applied to the Ncd-tubulin complex in this work, it can be widely used on many other biological molecules, especially highly charged biomolecules such as DNA/RNA, membrane proteins, molecular motors, viral capsid, etc.

Conclusions

Using the implicit and hybrid solvent models, the Drosophila Ncd motor binding to the tubulin dimer was studied. By using AlphaFold2, MD simulation, and the machine learning algorithm HIT-2, we modeled and obtained Ncd motor-tubulin dimer structures without/with bound ions. The differences between the electrostatic features of the Ncd motor-tubulin dimer were explored using multiscale computational approaches. The electrostatic potential on the surfaces indicates that, using the hybrid solvent model, the Ncd motor-tubulin dimer has a more attractive binding interface than when using the implicit solvent model. This means that the binding force is stronger when using the hybrid solvent model compared to using the implicit solvent model. The electrostatic potential difference also shows that the bound ions change the electrostatic surfaces significantly. The bound ions’ positions and the key residues that attract the bound ions were identified and analyzed in detail. Electric field line analysis shows that there are some repulsive electric field lines between the Ncd motor and the tubulin dimer when using the implicit solvent model. In contrast, there are more dense and attractive electric field lines in the Ncd motor-tubulin dimer when using the hybrid solvent model. This result corroborates the electrostatic potential result, which reveals that the Ncd motor has a stronger binding force to microtubules with bound ions. The electrostatic force analysis also supports this finding. The directions of electrostatic forces reveal that, using implicit/hybrid solvent models, the net forces between the Ncd motor and tubulin dimer are all attractive forces. The magnitudes of the electrostatic binding forces show that the net force between the Ncd motor and the tubulin dimer is stronger when using the hybrid solvent model than that when using the implicit solvent model.

The electrostatic interactions of Ncd motor-tubulin dimer using implicit/hybrid solvent models are significantly different, which indicates that treating bound ions at highly charged regions explicitly is crucial in the electrostatic calculations. Using the hybrid solvent model can significantly improve electrostatic calculations for biomolecules. This work proposes a machine-learning-based approach to handle bound ions using the hybrid solvent model. Such an approach is not only capable of handling kinesin-tubulin complexes but is also appropriate for other highly charged biomolecules.

Author contributions

Research design, W.G., Y.P., and L.L.; methodology, W.G. and D.D.; validation, W.G.; investigation, H.Z. and J.E.S.; writing – original draft, W.G.; writing – review & editing, W.G., D.D., H.Z., J.E.S., S.S., W.X., Y.P., and L.L.; visualization, W.G., Y.P., and L.L.; project administration, Y.P. and L.L.; funding acquisition, Y.P. All authors have read and agreed to the published version of the manuscript.

Supporting material

Document S1. Figures S1–S3

Document S2. Article plus supporting material

Acknowledgments

This work is supported by 10.13039/501100001809 National Natural Science Foundation of China 12205112 and the 10.13039/501100012226 Fundamental Research Funds for the Central Universities .

Declaration of interests

The authors declare no competing interests.

Supporting material can be found online at https://doi.org/10.1016/j.bpj.2023.12.024.
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