Introduction

The ability to predict if genetic mutations cause disease or not has enormous potential to impact human health1, 2. Efforts to make these predictions to date have largely been done by assessing the effect of a genetic mutation on the coded protein’s stability and amino acid conservation3, 4. While these predictions have had some success based on genome-wide work5, when considering the disease-causing effects of mutations in particular protein families, other, more function specific, features may be more successful6, 7.

The kinesin superfamily of microtubule motor proteins is responsible for a diverse set of cell biological functions including intracellular transport, ciliary assembly, mitosis, meiosis, cytoskeletal morphology, and microtubule dynamics regulation8, 9. These functions depend on kinesin’s force generating and motile properties10, 11. Kinesins, for example, are particularly critical to the development of neurons due to their ability to transport intracellular cargos, including synaptic vesicles, mitochondria, and newly synthesized protein complexes from the endoplasmic reticulum near the nucleus in the cell body to the growing tips of axons and dendrites12. Kinesins enable elongated neurons, sometimes more than a meter long, to overcome physical limitations associated with long distance diffusion13.

To accomplish the diversity of functions that kinesins perform, there are 14 recognized and numbered families of kinesins8, 14, as well as numerous ungrouped, or orphan, kinesins8. Most members of the kinesin superfamily are microtubule plus end-directed motors12. Some notable exceptions include kinesin-13s, which are primarily involved in regulation of microtubule dynamics15 and move by diffusion16, and kinesin-14s, which are minus end-directed motors17, 18. Kinesin motor motility and pN-scale forces arise from structural changes in the neck linker subdomains19, 20 of kinesins upon hydrolysis of ATP21. However, these forces are not the only forces within kinesins that are critical to their function.

The forces of binding between a kinesin and the microtubule are additionally important to the motor’s processivity, which is a motility property determined by how far it moves along a microtubule before completely dissociating13. A single bound kinesin motor domain is in a state of force equilibrium in the absence of external loading, meaning that the sum of all forces between the microtubule and the kinesin must be zero. These forces are electrostatic and non-electrostatic forces, including hydrogen bonds and salt bridges, van der Waals forces, as well as others. However, because the charge of amino acids at the microtubule binding interface greatly affects the motility and microtubule-stimulated ATPase rate of kinesin22, the dominant force associated with binding is likely the electrostatic force. Electrostatic forces guide kinesin-1 to its binding site23 and allow it to follow a single protofilament24, 25. Electrostatic forces also likely underlie the diffusive motility of kinesin-826, 27 and kinesin-1316.

Kinesins are critical to cell biology, so they are also important to many aspects of life, particularly to cell division and the nervous system. Genetic defects in kinesin motor domains that cause errors in cell division are likely embryonic lethal. Somatic defects are found in and are distributed throughout many kinesins, including the motor domains28. These defects are prevalent in endometrial cancer, lung squamous cell carcinoma, and melanoma28. However, somatic defects are generally unique to single samples making it difficult to discern their significance to the cancer28. Multiple congenital disorders are caused by non-synonymous single nucleotide polymorphisms (nsSNPs) in kinesin motor domains, including nsSNPs in the kinesin-1 family member KIF5A that cause parkinsonism29, peripheral neuropathy29,30,31,32, Charcot–Marie–Tooth disease type 233, retinitis pigmentosa29, and spastic paraplegia33,34,35; nsSNPs in the kinesin-1 family member KIF5C and the kinesin-5 family member KIF11 that cause microcephaly36, 37; nsSNPs in the kinesin-10 family member KIF22 that cause lepto-spondyloepimetaphyseal dysplasia38; nsSNPs in the kinesin-3 family member KIF1A that cause spastic paraparesis and sensory and autonomic neuropathy type-239; and nsSNPs in the kinesin-5 family member KIF11 that cause primary lymphedema and chorioretinal dysplasia37.

Because nsSNPs in kinesins tend to cause neurological genetic disorders and electrostatic forces between the kinesin motor domain and the microtubule are critical to multiple physiological properties of kinesins that could be particularly important in neurons, we hypothesized that the nsSNPs found in kinesin motor domains that greatly affect the electrostatic forces acting between kinesin and microtubules would strongly correlate to the nsSNPs causing human disease. To probe this hypothesis, we investigated the effect of known kinesin motor domain nsSNPs on the electrostatic force between kinesin and tubulin dimers using computational techniques. This study is based on 50 nsSNPs causing missense mutations in the motor domains of 10 different genes coding for proteins from 8 different kinesin families identified from dbNSFP40 and annotated as disease-causing using the Human Gene Mutation Database41 and ClinVar42 complemented with 11 nsSNPs that do not cause disease taken from 1000 genomes project43. The goal is to determine whether the changes in the electrostatic forces caused by mutations can be used to discriminate disease-causing mutations from those that do not cause human disease.

Materials and Methods

Selection of kinesin nsSNPs

The kinesin nsSNPs were downloaded from dbNSFP40 and missense mutations located in the coding regions of the kinesin motors domains with structures available in the PDB44 were selected. The Human Gene Mutation Database (HGMD)41 and ClinVar42 were used to identify disease-causing mutations. This resulted in the selection of 50 mutations in various kinesins.

A total of 11 nsSNPs with the allele frequency greater than 1% in the 1000 Genomes Project45 were identified and used as common, non-disease causing polymorphisms in the healthy individuals.

Note that significantly more disease-causing mutations were identified than non-disease-causing mutations, but the inclusion of mutations with allele frequency smaller than 1% may result in mutations with unknown physiological importance. The list of all the mutations for this study is provided in Supplementary Materials Table S1.

Preparation of kinesin-tubulin structures

The 61 selected mutants come from 10 kinesin proteins representing 8 kinesin families (Table 1). High resolution structures, those with better than 5 Å resolution and having no mutation, were downloaded from the Protein Data Bank (PDB)46 for 5 of the 10 kinesin proteins. If multiple structures were available for the same kinesin in PDB, the structure with the highest resolution was selected for this work.

Table 1 Details of the 10 wild type kinesin structures used.
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High resolution structures were not available in the PDB for the other 5 kinesin proteins. Note that for some proteins, including KIF1A and KIF5A, structures were available, however, either the resolution was too low or the structure had mutations introduced into it. In the cases without structure, SWISS-MODEL47 was used to build protein homology models from templates with high sequence similarities. The top model from SWISS-MODEL was selected to model the corresponding kinesin motor structures.

Some of the structures had missing heavy atoms. Profix48 was used to fix these structures.

NAMD49 was used to perform a 10,000-step energy minimization for each structure. In NAMD minimizations, the CHARMM50 force field and the Generalized Born (GB) implicit solvent model were used.

There were no structures of the human kinesin-human tubulin complex available in PDB. However, there were many other kinesin-tubulin complex structures available, and kinesins share the same microtubule binding site22, 51. Therefore, kinesin-tubulin complex structures were made using Chimera52 to align each kinesin (Table 1) to the human α1A/β3 tubulin dimer structure (PDB ID 5JCO)53, using a model of human kinesin-5 and a mammalian tubulin dimer docked into a 9.5- Å cryo-EM map (PDB ID 4AQW)54 as a template. The C-termini (E-hooks) were not modeled since their structures are not available in the corresponding PDB files.

Building complex structure via structural alignment of the backbone atoms resulted in atomic clashes at the binding interface. To remove these structural clashes introduced during the modeling process, the kinesin-tubulin complex structures underwent 2000 steps of energy minimization using the CHARMM3655 force field in CHARMM56 software in which only amino acid side chains were free to move because a 10 kcal·mol−1·Å−1 harmonic constraint was placed on all backbone atoms.

The nsSNP structures were generated based on the wild type structure for each kinesin using PDB2PQR57. The protonation states of titratable group were assumed to be standard, roughly corresponding to pH = 7.0. Since the kinesins considered in this work are cytoplasmic kinesins, the physiological pH is 7.0. Only the mutated residue was energy optimized; all other atoms were kept in the same position as in the wild type structure to isolate the direct effects of electrostatic forces.

Force calculations

Electrostatic forces were calculated for each kinesin-tubulin complex using DelPhiForce58. The force reported is the net electrostatic force exerted on a kinesin by its tubulin dimer binding partner. The electrostatic force on each individual atom and residue, which is used to analyze the detailed force distribution on each kinesin, was also calculated with DelPhiForce.

The forces on each kinesin were calculated in two states: the bound state and the unbound state. The bound state was considered to be the equilibrium complex position, which was determined as described in “Preparation of kinesin-tubulin structures”. The unbound state was obtained by displacing the kinesin 5 Å from the tubulin in the direction along the line between the mass center of the kinesin and tubulin dimer. The dielectric constant for water and protein were set as 80 and 2, respectively; the resolution of the grid was set at 2 grids/Å; the perfil was set at 70; the ionic strength of the solvent was set at 0 (zero salt concentration was used to be consistent with our previous studies and to avoid the ambiguity associated with explicit ion binding). However, to check the sensitivity of results, parallel calculations were done at physiological salt concentration corresponding to ionic strength I = 0.15 M. The dipolar boundary condition was used in all cases. Information on these parameters is available in the DelPhi59, 60 manual (http://compbio.clemson.edu/downloadDir/delphi/delphi_manual.pdf).

The electrostatic force difference, \({\rm{\Delta }}\bar{F}\), was defined as the difference between the electrostatic forces exerted on wild type and the corresponding mutant kinesins.

$${\rm{\Delta }}\bar{F}={\bar{F}}_{{\rm{mut}}}-{\bar{F}}_{{\rm{wt}}}$$
(1)

where \({\rm{\Delta }}\bar{F}\) and are vector quantities with components ΔF lat (lateral direction), ΔF long (longitude direction), and ΔF bind (binding direction).

The relative force difference ΔF rel is defined as:

$${\rm{\Delta }}{F}_{{\rm{rel}}}=|{\bar{F}}_{{\rm{mut}}}-{\bar{F}}_{{\rm{wt}}}|/|{\bar{F}}_{{\rm{wt}}}|$$
(2)

The relative force difference in the binding direction ΔF bind,rel is defined as

$${\rm{\Delta }}{F}_{{\rm{b}}{\rm{i}}{\rm{n}}{\rm{d}},{\rm{r}}{\rm{e}}{\rm{l}}}=|{\bar{F}}_{{\rm{b}}{\rm{i}}{\rm{n}}{\rm{d}},{\rm{m}}{\rm{u}}{\rm{t}}}-{\bar{F}}_{{\rm{b}}{\rm{i}}{\rm{n}}{\rm{d}},{\rm{w}}{\rm{t}}}|/|{\bar{F}}_{{\rm{b}}{\rm{i}}{\rm{n}}{\rm{d}},{\rm{w}}{\rm{t}}}|$$
(3)

where \({\bar{F}}_{{\rm{bind}},{\rm{mut}}}\) and \({\bar{F}}_{{\rm{bind}},{\rm{wt}}}\) are the components of the electrostatic force between the microtubule and the mutant and wild type kinesin in the binding direction, respectively.

Results

Electrostatic forces act between kinesin and tubulin

In our previous work, we demonstrated that the electrostatic forces on kinesin-5 form a binding funnel around the tubulin dimer58. A similar binding funnel was also found for dynein around the tubulin binding pocket61. In this work, we found that the binding funnel is common to kinesins, as shown for kinesin-13 as an example (Fig. 1), and that the electrostatic force guides the kinesin to the binding pocket of the tubulin. We obtained similar results for the other kinesins (Supplementary Material Table S1).

Figure 1
figure 1

A funnel of electrostatic binding forces guides kinesin to the binding site on a tubulin dimer. The kinesin-13 structure (yellow) was shifted 20 Å away from its bound position and circled around the tubulin dimer (colored blue for positive surface charge and red for negative surface charge) along a circle with a radius of 40 Å. Every 30 degrees, the electrostatic force on the kinesin was calculated. These forces are represented by arrows (green) with their tail end located at the mass center of the kinesin in the 12 locations around the circle and their lengths proportional to the magnitude of the electrostatic force. (A) and (C) are the side views. (B) and (D) are the top views. In (A) and (B) the kinesin structure is shown at two positions for illustration of the range of displacement. In (C) and (D) the kinesin is hidden to provide clear view of the forces. In all frames, the total electrostatic forces were calculated using DelPhiForce and visualized with VMD76.

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Because the electrostatic force is a vector, \(\bar{F}\), we examined its components in the longitudinal (F long), lateral (F lat), and binding (F bind) directions (Fig. 2) separately to further assess the role of electrostatic forces. We found that the magnitude of the mean electrostatic force, \(|{\bar{F}}_{{\rm{avg}}}|\), for the 10 wild type kinesins used in this study in the bound state was 1,450 ± 170 pN (results for each kinesin are shown in Supplemental Material Table S1). Preforming the same calculations for unbound kinesins (at a displacement of 5 Å from the tubulin) resulted in an 87% decrease in \(|{\bar{F}}_{{\rm{avg}}}|\) to 192 ± 56 pN. However, despite the large drop in magnitude, the direction of that mean force, and therefore the contribution of individual components, in the bound state was statistically indistinguishable from the unbound state (Table 2). The component of the mean electrostatic force in the binding direction, F bind,avg, contributed the most to the force magnitude (Table 2), and the components in the lateral, F lat,avg, and longitudinal, F long,avg, directions were not statistically different from zero (Table 2).

Figure 2
figure 2

Definition of forces components. As an illustrative example, kinesin-3 family member KIF1A (light blue) is shown in the bound state on a tubulin dimer with α-tubulin (red) on the left side and β-tubulin (orange) on the right side. The “longitudinal” direction is along the microtubule, shown (green arrow) positive pointing toward the plus end. The “binding” direction is normal to the surface of the microtubule, shown (green arrow) positive toward the microtubule lumen. The “lateral” direction is around the microtubule, shown (green indicator) coming out of the page toward the reader.

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Table 2 Mean electrostatic force magnitude and direction.
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Electrostatic forces and diseases

We calculated the electrostatic force differences, \({\rm{\Delta }}\bar{F}\) (Equation 1), of bound and unbound structures (Supplementary Material Table S1), where the force difference quantifies the difference in electrostatic force between the mutant and the corresponding wild type structure. Like the electrostatic force, force differences have three components in the longitudinal (ΔF long), lateral (ΔF lat), and binding (ΔF bind) directions (Fig. 2). Besides the force differences, we also calculated the relative force difference ΔF rel (Equation 2). We found that mutations with larger values of relative force differences, ΔF rel, are more likely to cause disease (Supplementary Material Table S1).

We quantified the result that large ΔF rel tends to cause disease using Receiver Operating Characteristic (ROC) plots (Fig. 3). The area under an ROC plot indicates how well a descriptor, in this case ΔF rel, discriminates between two states, in this case whether a mutation is disease-causing or non-disease-causing. The area under an ROC plot of 1 indicates the descriptor can always discriminate between the states, and the area under a ROC plot of 0.5 (corresponding to the red dotted line in Fig. 3) indicates the descriptor is no better than random chance.

Figure 3
figure 3

Magnitude of the electrostatic force difference, ΔF rel, can be used to predict whether a mutation is disease-causing. ROC plots are of ΔF rel calculated in the bound state (BS Mag, black line), the component of force difference in the binding direction, ΔF bind,rel, in the bound state (BS BC, blue line), ΔF rel in the unbound (UBS Mag, red line), and ΔF bind,rel in the unbound state (UBS BC, green line). The areas below these four ROC curves are: 0.79, 0.77, 0.84, 0.84, respectively.

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We found that ΔF rel of unbound structures provided a better prediction of disease than ΔF rel of bound structures because the areas under the unbound state ROC plots were 0.84 and 0.84 for ΔF rel and ΔF bind,rel, respectively (Fig. 3) and the area under the bound state ROC plots were 0.79 and 0.77 for ΔF rel and ΔF bind,rel, respectively (Fig. 3). We also noted that ΔF rel performed slightly better than ΔF bind,rel for structures in bound states (Fig. 3). We obtained similar results from ROC plots (Supplementary Material Figure S1) of electrostatic force calculations at an ionic strength of 0.15 M, indicating that ionic strength does not play a role in discriminating disease-causing from non-disease-causing mutations. Thus, in the rest of the manuscript, we focus on results obtained with I = 0 M. Since disease can be caused by either decreasing or increasing the wild type force, we did ROC using the absolute values of \(|{\rm{\Delta }}\bar{F}|\) and |ΔF bind|, for both unbound and bound states, which resulted in similar as above performance; areas under ROC curve ranged from 0.72 to 0.75 (Supplementary Material Figure S2).

Statistical analysis of electrostatic force components and disease-causing mutations

We further investigated the unbound state’s \(|{\rm{\Delta }}\bar{F}|\,\,\)and its \({\rm{\Delta }}\bar{F}\)’s components as predictors of whether a mutation is disease-causing or non-disease-causing using histograms (Fig. 4). We found that all mutations in our study with \(|{\rm{\Delta }}\bar{F}| > 16\) pN led to disease and that only 9% of the non-disease causing mutations had \(|{\rm{\Delta }}\bar{F}| > 4\) pN (Fig. 4A).

Figure 4
figure 4

Whether a mutation causes a disease or not is correlated to the electrostatic force differences. Normalized histograms of disease-causing (black) and non-disease-causing (gray) mutations by electrostatic force difference when kinesin is in the unbound state for (A) \(|{\rm{\Delta }}\bar{F}|\), (B) ΔF bind, (C) ΔF lat, and (D) ΔF long. Total mutation counts are labeled on each bar. Note that our dataset included a total of 50 disease-causing mutants and 11 non-disease-causing mutants. The error bars indicate the standard deviation.

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We also found that kinesins had a higher tolerance to ΔF bind and ΔF long than to ΔF lat. We found that only 9% of the non-disease-causing mutants had ΔF lat > 1 pN while 36% had ΔF bind > 1 pN and 27% had ΔF long > 1 pN (Fig. 4B,C,D). We also noted that mutations causing ΔF lat between 1 pN and 4 pN did a much better job distinguishing disease state because this range in ΔF lat contains 35% of all disease-causing but only 9% of non-disease-causing mutants, which is statistically significantly different (p-value = 0.02), but this same range in ΔF bind and ΔF long had percentages of disease-causing and non-disease-causing that were statistically indistinguishable (Fig. 4B,C,D).

Analysis of additional features that may be used to discriminate disease-causing and non-disease-causing mutations

We performed a statistical analysis of 23 features potentially affecting the pathogenicity of kinesin mutations using standard techniques (see Supplementary Material). By comparing the p-values of an F-regression analysis, we found that electrostatic force was the best predictor (Table 3). The other good predictors were the secondary structure of mutation position, change in binding free energy, and the location of mutation site (Table 3). The buried surface area, residue polarity, residue charge, etc., were not identified as significant features in predicting pathogenicity (Table 3).

Table 3 Statistical analysis of 23 possible features.
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We found that 88% of the disease-causing mutations occur in α-helices, coils, and turns (Fig. 5A). Only 31% of mutations located on strands caused disease, which is significantly fewer than the 61% and 53% disease-causing rates for mutations on coils and turns, respectively (Fig. 5A). Our data had few instances of mutations on 3–10 helices or salt bridges, therefore these mutations are not taken into further analysis.

Figure 5
figure 5

Location of the mutation is correlated to its likelihood of causing disease. (A) Histograms indicating which secondary structure the mutated residue is on for disease-causing and non-disease-causing mutants. (B) Histograms indicating whether the mutated residue is on the microtubule binding interface or not for disease-causing and non-disease-causing mutants.

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Additionally, we noted that the disease-causing nature of a mutation was correlated to the function of the structure domain upon which it resides. 76% of mutations at the tubulin binding site were disease-causing (Fig. 5B), while mutations at other locations were disease-causing in only 46% of instances (Fig. 5B). Note that since this study focused on the kinesin-tubulin interaction, mutations on ATP binding site were not taken into further discussion.

Discussion

We demonstrated that the changes of the electrostatic component of the force between kinesin and microtubule caused by amino acid mutations in the kinesin motor domain serve as a good discriminator between disease-causing and non-disease-causing mutations. 23 other features typically used by the computational community were also investigated, but we found them to be not as good predictors of disease state as the change of the electrostatic force. These results are remarkable because kinesin-related diseases may originate from nsSNPs causing effects within the motor domain not related to kinesin-microtubule binding. These effects may include disruption of nucleotide hydrolysis site because motility requires ATP hydrolysis62, proximity of the mutation to the location neck-linker-motor domain interaction site because motility requires neck linker docking63, 64, and motor domain structural stability because structure and function are closely correlated in structured proteins. Additionally, the kinesin family to which the mutated protein belongs could also be an important factor because certain families may have more critical cell or developmental biological function than others, and certain families may have fewer functional redundancies with other motors within the family than others65. Moreover, that our results show electrostatic force is a good discriminator between disease-causing and non-disease causing mutations suggests that there is steep electrostatic potential energy well about the kinesin docking location on the microtubule. Because the force is proportional to the spatial gradient of potential energy, small changes in the electrostatic energy potential result in large change in the force. Therefore, it is likely that electrostatic force is an even better discriminator than electrostatic energy potential.

We checked if our results were biased by the location of the mutations sites relative to the kinesin-microtubule binding interface by generating a representative kinesin motor domain-tubulin structure (Fig. 6). We note that the kinesin motor domains studied in this work have similar structures (Fig. 6A), and thus we use one (kinesin-3) to visualize the location of mutations sites (Fig. 6B). We found that there is no preference for disease-causing mutations to be at the binding interface while non-disease-causing mutations are away.

Figure 6
figure 6

Mutations distribution map. (A) The structural alignment for all the kinesin-tubulin dimer structures studied, each color representing a different kinesin structure. (B) Mutations sites mapped on a representative kinesin structure (kinesin-3 family member, KIF1A). Red residues indicate disease-causing mutation sites and yellow residues indicate non-disease-causing mutation sites. α-tubulin (red) is on the left and β-tubulin (orange) is on the right in both panels.

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Recent studies indicate that positively charged residues on the kinesin motor domain strengthens its interaction with the microtubule, while negatively charged residues have an opposite effect22, 23, 25, 66. Consistent with these previous studies, we have found that most of the disease-causing mutations we studied involve charged residues. Our findings provide additional evidence for the importance of charged residues and electrostatics to kinesin motor domain microtubule binding. Furthermore, we found that Y274 and L248, which were previously identified as the top two most important uncharged residues for kinesin-microtubule binding22, 66, were also associated with disease-causing mutations in kinesin-3 family member KIF1A (L249Q) and in kinesin-1 family member KIF5A (Y276C). The correspondence between important previously identified charged and uncharged residues22, 66 and disease-association allows us to speculate that mutations at other positions identified as important in previous studies22, 66 including R346, K44, and K261, which do not appear in our database, are likely to be disease-causing.

Our key result is that if a mutation causes a \(|{\rm{\Delta }}\bar{F}| > 4\) pN in the unbound state, then it is very likely to cause disease. Such a threshold roughly corresponds to 1 kcal/mol binding energy, an energy threshold that is widely used to discriminate disease-causing from non-disease-causing mutations67. Below we investigate a few particular mutants more closely, as illustrative examples, to understand our result a bit better.

First, we noted that kinesin-3 family member KIF1A E253K is charge reversal, from a negatively charged glutamic acid residue to a positively charged lysine residue, and it resulted in the largest \(|{\rm{\Delta }}\bar{F}|\) (Supplementary Material Table S1) in both the bound and unbound states. We looked carefully at the magnitude and direction of the force on each amino acid in this kinesin-3 (Fig. 7). We found that the mutated amino acid lies close to the tubulin interface: the distance between the CA atom of E253 and the closest CA atom on tubulin is 9.6 Å. Because the mutation flips the charge of the residue and it is so close to the highly-charged tubulin interface, the large change in force we calculated was likely do the negative-to-positive charge reversal. The negatively charged E253 in wild type kinesin-3 opposes binding (Fig. 7 red arrow), and the positively charged K253 in the mutant kinesin-3 favors binding (Fig. 7 blue arrow), to the net negatively charged tubulin dimer. It is therefore not surprising that the enhanced binding due to this mutation causes spastic paraparesis and sensory and autonomic neuropathy type-239 given that kinesin-3 drives long-distance transport in neuronal cells9.

Figure 7
figure 7

Forces on each residue of kinesin-3 show the large change in relative force due to the mutation. Kinesin-3 family member KIF1A (light blue) with the E253K mutation is shown bound to a tubulin dimer with α-tubulin (red) on the left side and β-tubulin (orange) on the right side. Most electrostatic forces (yellow arrows) on each residue of the kinesin-3 remain unchanged, but the force on residue 253 changes with the mutation, with both the force on wild type (red arrow) and the force on the mutant (blue arrow) shown.

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Second, we noted that kinesin-8 family member KIF18A T273A mutant is the only non-disease causing mutant with a \(|{\rm{\Delta }}\bar{F}| > 4\) pN; it had \(|{\rm{\Delta }}\bar{F}|=4.92\) pN. We looked carefully at the location of this residue in the structure and found it to reside on an unstructured region (or at least one that is not in the PDB ID 3LRE structure)68 on the microtubule binding surface22, thus leading to a relatively large calculated \(|{\rm{\Delta }}\bar{F}|\). However, the T273 is not highly conserved and the T273A does not change the motility of the kinesin in in vitro motility assays22. This could explain how this mutation is non-disease-causing despite relatively large \(|{\rm{\Delta }}\bar{F}|\).

Third, we noted that the kinesin-1 family member KIF5A S203C mutant has a low \(|{\rm{\Delta }}\bar{F}|=1.27\) pN in the unbound state (Supplementary Material Table S1), well below the discrimination threshold of 4 pN, but is disease-causing. We looked carefully at the location of this mutation, and found it is located in close proximity (5.5 Å) to the Mg2+ ion in the nucleotide binding site69. Specifically, S203 resides within a highly conserved sequence (NXXSSR, residues 199–204 of KIF5A) in switch I30, and it is thought to be important in recognizing the hydrolysis state of bound the nucleotide70. This could explain how this mutation causes a disease despite low \(|{\rm{\Delta }}\bar{F}|\), highlighting our discrimination method’s limitation in finding all the true positive cases, particularly when mutations are unrelated to the kinesin-tubulin interaction.

While we did find that \(|{\rm{\Delta }}\bar{F}| > 4\) pN in the unbound state is an excellent discriminator, we also found that the three components of the relative force difference, ΔF long,rel, ΔF lat,rel, and ΔF bind,rel, are also successful predictors, in their own right. These results suggest that the individual components of the binding force, particularly the lateral and longitudinal components, may be of critical importance for kinesin motility. It should be additionally noted that the magnitude of the electrostatic force is significantly (least 5-fold) larger in the binding direction than the other two directions (Table 1). Thus, it is likely to be less sensitive to the changes in magnitude than the other directions. If a mutation changes the force in the binding direction a given amount, kinesin may still bind to tubulin properly, however if the force in the lateral or longitudinal direction were changed by that same amount, it may be significantly more sensitive to the difference. It should be noted that the absolute value of the electrostatic force change was found to be the best discriminator. Thus, mutations strengthening the binding are equally likely to be disease-causing as mutations weakening it. This is consistent with previous studies on other systems, indicating that these systems are optimized and any deviation away from the wild type properties could be disease-causing4, 67.

Finally, it should be noted that this study considers the electrostatic component of the force acting between the kinesin and tubulin, not the total force. A kinesin motor domain that is not subjected to other external force, e.g. a cargo load, is at equilibrium on the microtubule. Therefore, at equilibrium, non-electrostatic forces must be acting at the tubulin-kinesin interface to balance out the large magnitude electrostatic forces we have calculated.