Introduction: The aim of this study was to determine the potential genetic cause of retinal capillary hemangioblastoma (RCH) with symptoms of Von Hippel-Lindau (VHL) disease. Case Presentations: Three Iranian families (5 RCH patients) with novel variants are included in this study. The VHL variant analysis was performed by the Sanger sequencing technique. Molecular dynamics (MDs) simulations were conducted to analyze conformational changes resulting from variants in VHL protein structure and were compared with that of the native structure. Novel variant sites, including c.511A>C, c.511A>T, and c.514C>T in exon 3 of the VHL gene were identified. According to the American College of Medical Genetics (ACMG) classifications, c.514C>T (p.P172S) and c.511A>C (p.K171Q) are classified as variants of uncertain significance (VUS), and c.511A>T (p.K171*) is classified as a likely pathogenic variant. MD simulations demonstrated overall fluctuations of the proteins structure and a significantly lower degree of flexibility in the α-domain for the variant-encoded VHL protein structure compared to that of the native form. Conclusion: The structural information and computational analysis of the identified variants are predicted to induce conformational changes that limit the flexibility of protein VHL interaction interface with Elongin B/C, Elongin C/B, and Cullin-2, which are necessary for hypoxia-inducible factor 1-α binding. The genetic variants identified in Iranian patients with RCH may aid in the molecular confirmation of other patients diagnosed with VHL and their at-risk family members. These pioneering results that include detailed structural and functional analysis of a variant’s effect on the VHL protein may serve as a model for future studies.

Von Hippel-Lindau (VHL) syndrome is an autosomal dominant hereditary neoplastic disorder characterized by clinical findings that may include central nervous system hemangioblastoma (CHB), retinal capillary hemangioblastoma (RCH), renal cell carcinoma, pheochromocytoma (PCC) and other multiple tumors or cysts of the kidney, liver, pancreas (PC), and epididymis [1‒3]. VHL syndrome can be classified as type 1 or type 2 according to the presence or absence of PCC [4, 5].

RCH is one of the most common clinical manifestations of VHL, with a mean age of diagnosis of 24.8 years [6]. More than 500 different pathogenic variants have been identified and studied since the detection of the VHL gene in 1993 [3‒7]. Protein VHL (pVHL) forms a complex with Elongin C and B, Cullin-2, and Ring-box 1 protein (VCB-CR) which interacts with RBX1/ROC1 and regulates protein ubiquitination involved in the hypoxia gene response pathway [8]. Most variants are located in two regions of high functional importance in pVHL, including hypoxia-inducible factor 1-α (HIF-1α) binding site (amino acids 91–113) and Elongin C binding site (amino acids 157–171) [9]. To date, five different binding surfaces (A–E) have been reported in pVHL from which surfaces A to C are implicated in the pathogenesis of RCH [10, 11].

Genetic testing is recommended in the management of VHL patients and molecular confirmation is helpful in the diagnosis of VHL disease, especially in patients with subtle or mild symptoms and no clear family history [12]. Molecular diagnosis may also identify other family members at risk for disease and inform recurrence risk. With advances in computational analysis, a variant’s impact on the protein and target macromolecule’s overall structure can be modeled without the need for time-consuming and costly experimental efforts such as crystallography.

In this case series study, three probands presented to the Eye Clinic, Rasoul-Akram Hospital with reduced vision and were found to have RCH. Two of the probands had multiple members with other clinical manifestations of VHL syndrome. In silico prediction methods and molecular dynamics (MDs), simulations were employed to evaluate whether the novel variants could be implicated in disease.

Three families (5 RCH patients) with at least one individual diagnosed with RCH were enrolled for VHL gene sequencing. Ophthalmoscopic examination and systemic screening tests were used to rule out VHL disease in family members examined. A diagnosis of VHL was considered if one of the diagnostic criteria were present in a first-degree family member or if two VHL-related manifestations were present in a patient with no known family history of VHL. VHL-related manifestations included RCH, CHB or spinal cord, neuroendocrine tumors of the pancreas, PCC, or endolymphatic sac tumor [13].

The employed methodologies are fully described in our previous study [14]. PCR was carried out to amplify all 3 exons of VHL gene and then, all the amplified fragments were subjected to Sanger sequencing (Bioneer, South Korea). The study was approved by the Iran University of Medical Sciences with the Ethics code of IR.IUMS.REC.1402.735, and written informed consent was received from those individuals who participated in this study. The resulting sequences were submitted to the Gene Bank database (Accession numbers: ON506937, ON506938, ON506939).

The variants identified were first interrogated for new information in the Human Gene Mutation Database (HGMD). The ClinVar database (https://www.ncbi.nlm.nih.gov/clinvar/) was used to search for known variants and their clinical significance. The pathogenicity impact of the identified variants were discriminated by employing Mutation Taster, to evaluate variants of DNA sequences in terms of their disease-causing potential (http://www.mutationtaster.org/), Sorting Intolerant from Tolerant (SIFT) to predict the effect of amino acid substitution on protein function (https://sift.bii.a-star.edu.sg/), MutPred to classify variants as disease-associated or neutral in humans and predict the molecular cause of the disease (http://mmb.irbbarcelona.org/PMut), PROVEAN to predict whether an insertion/deletions (indels) or amino acid substitution effects on the biological function of a protein (http://provean.jcvi.org/index.php), Varsome analysis to collect data from multiple databases of human genomic variations into a central location and share knowledge (https://doi.org/10.1093/bioinformatics/bty897) and CADD for scoring the deleteriousness of amino acid substitution as well as indels in the human genome (https://cadd.gs.washington.edu/). Deleterious thresholds were set as follow: SIFT <0.05, PMut >0.5, and PROVEAN <−2.5. For CADD (GRCh37-v1.6), the highest Phred-like score cutoff was used as recommended by the authors [15].

The X-ray crystallographic structure of pVHL (PDB ID: 1lm8) was obtained from the protein data bank (https://www.rcsb.org). BOVIA Discovery studio program (https://www.3ds.com/products-services/biovia/), a tool for observing and analyzing macromolecule/molecule structures, was used to model the protein structure after target residues were substituted based on the corresponding variant.

MDs simulation method was carried out using GROMACS v5.1.5 to analyze the physical movements of the constituent atoms of the native and variant structures of pVHL. The atoms were allowed to interact in a desired condition for a fixed period of time to observe a view of the dynamic “evolution” of the system and resultant conformational changes resulting from residue substitution in the protein structure [16].

GROMOS AMBER force field (amber99sb-ildn) on the individual native and variants was used to estimate the forces between atoms within the molecules [17]. First, the models were solvated in a dodecahedral box of TIP3P water molecules [18] with a minimum distance of 14 Å between the protein surface and the box wall. Next, the net charge of the system was neutralized by replacing water molecules with appropriate counter sodium and chloride ions. The van der Waals cutoff was set to 14 Å [19]. Periodic boundary conditions were assigned in all directions. The solvated system was then minimized through the steepest descent algorithm [20] with 1,000 KJ mol−1 nm−1 tolerance followed by a canonical ensemble (NVT) and isothermal-isobaric ensemble (NPT) for 100 ps. The temperature and pressure of the system were independently maintained using the Berendsen thermostat and Parrinello-Rahman barostat algorithm at a constant temperature and pressure of 303 K and 1 bar, respectively [21]. Subsequently, the Particle Mesh Ewald (PME) algorithm was employed to calculate the long-range electrostatic interactions [22]. The LINCS algorithm was applied to restrain all the bonds with an integration step of 1 fs [23]. The whole system was gradually heated, and finally, the whole system was subjected to 100 ns of MDs at constant pressure and temperature. The stability of the computed structures was investigated by calculating the root mean square deviations (RMSDs) and root mean square fluctuations (RMSFs) during the simulation. The coordinate files were finally extracted from the trajectories for further analysis.

The MDs results were analyzed and visualized employing VMD 1.9 and Pymol packages. The graphs were all visually represented using Microsoft Office Excel [24, 25].

Family A

The proband was a 31-year-old female who presented to our ophthalmology clinic in 2018. At the first visit, the best corrected visual acuity (BCVA) in both eyes was 10/10, and the intraocular pressure (IOP) was normal. She had grade I fatty liver. Additionally, she presented with blurry vision in the right (OD) eye. Her pulse rate and blood pressure were 100/min and 110/75 mm Hg, respectively. On ophthalmoscopy, a feeder vessels, associated hemorrhage and hard exudates were located in the pre-equatorial and inferior temporal regions of the retina. Fundoscopy of the OD revealed a RCH (Fig. 1a). Measurement of plasma catecholamines, catecholamine metabolites (metanephrines), and vanillylmandelic acid were normal.

Fig. 1.

First fundus photograph of the probands. Fundus photograph of the OD eye (a, II-6) shows the progression of the RCH, fundus photograph of the OS eye (b, III-1) indicated multiple RCH in the superior and inferior temporal peripheral retina. c (II-2) shows the enlargement of the RCH.

Fig. 1.

First fundus photograph of the probands. Fundus photograph of the OD eye (a, II-6) shows the progression of the RCH, fundus photograph of the OS eye (b, III-1) indicated multiple RCH in the superior and inferior temporal peripheral retina. c (II-2) shows the enlargement of the RCH.

Close modal

Pathological lesions were found in the brain and kidney using computed tomography (CT) and magnetic resonance imaging (MRI). Genetic testing was also carried out for other family members (I-1, I-2, and II-1, II-2, II-3, II-4, II-5, and II-7) (Fig. 2, A).

Fig. 2.

Pedigree of the affected families. Color symbols represent the patients. The probands are indicated with arrows. Family A: The affected subject II-6 had retinal capillary hemangioblastoma (RCH) and was found to have variant of uncertain significance (VUS) (c.511A>C, p.K171Q). Family B: The proband III-1 had RCH and was found to have a VUS (c.514C>T, p.P172S). The deceased subject II-1 had RCH. The affected subject II-2 had central nervous system hemangioblastoma (CHB). The affected subject I-1 had RCH and kidney cysts (KC). Family C: The affected subject II-1 had RCH and CHB tumors. The proband II-2 had RCH. The affected subject II-3 had RCH, CHB, and pancreatic cysts (PC). A positive sign (+) denotes those individuals for which variants were identified.

Fig. 2.

Pedigree of the affected families. Color symbols represent the patients. The probands are indicated with arrows. Family A: The affected subject II-6 had retinal capillary hemangioblastoma (RCH) and was found to have variant of uncertain significance (VUS) (c.511A>C, p.K171Q). Family B: The proband III-1 had RCH and was found to have a VUS (c.514C>T, p.P172S). The deceased subject II-1 had RCH. The affected subject II-2 had central nervous system hemangioblastoma (CHB). The affected subject I-1 had RCH and kidney cysts (KC). Family C: The affected subject II-1 had RCH and CHB tumors. The proband II-2 had RCH. The affected subject II-3 had RCH, CHB, and pancreatic cysts (PC). A positive sign (+) denotes those individuals for which variants were identified.

Close modal

Family B

The proband was a 24-year-old male who presented in 2020 with blurry vision, a right kidney cyst of 16 mm and headache. He has a known history of VHL type 1 in his family members. The patient had no light perception in OD eye, but the BCVA in left eye (OS) was 2/10, and IOPs of 16 mm Hg in both eyes (OU). On examination, his pulse rate and blood pressure were 105/min and 155/90 mm Hg, respectively.

Fundoscopy of the OS revealed multiple RCH (Fig. 1b). Measurement of catecholamines was normal in plasma. computed tomography and MRI did not detect any pathological lesions in the brain or other organs.

His family history was positive for RCH (II-2), CHB (II-3), and both RCH and kidney cyst in I-I (Fig. 2, B). Only the proband’s was available for genetic testing, and we could not access his family’s clinical information further.

Family C

The proband was a 27-year-old female who presented in 2016 with palpitations, chest pain, and vision problems. On examination, her pulse rate and blood pressure were 100/min and 115/85 mm Hg, respectively. Enlargement of the RCH were revealed by fundoscopy of her OD eye (Fig. 1c). The BCVA of her OD and OS eyes were 10/10 and light perception, respectively, and her IOPs measured 16 mm Hg OD and 25 mm Hg OS.

In addition to the proband, genetic analysis was completed for unaffected family members of I-1, I-2, and affected family members of II-1, II-3, and II-4. The proband’s two sisters were found to have clinical findings of VHL such as RCH, CHB, and PC. However, her 31-year-old sister (II-1) presented with blurry vision, while her 21-year-old sister (II-3) presented with severe hypertension and blurry vision (Fig. 2, C). MRI revealed pathological lesions in the brain and pancreas of II-1 and II-3. Measurement of plasma metanephrine and normetanephrine in II-1 were 45 pg/mL (12–61 pg/mL) and 179 pg/m (18–112 pg/mL), respectively, while in II-3 were 38 pg/mL and 274 pg/m, respectively.

The sequencing results from Chromas software are shown in online supplementary Figure S1 (for all online suppl. material, see https://doi.org/10.1159/000543119). The results of the two-dimensional in silico characterizations of the native and variants are presented in Table 1. Accordingly, the target variants were categorized as inactivating (nonsense) and non-inactivating (missense variants). Given the novelty of the observed cases, an in silico analysis was conducted to monitor the alternations at the molecular level.

Table 1.

In silico prediction of exonic variants observed in the VHL gene in the Iranian RCH patients

Family AFamily BFamily C
Tumors RCH RCH, CHB, KC RCH, CHB, PC 
VHL Type 
Variant Classes Non-inactivating Inactivating 
Variants c.511A>C, p.K171Q (NM_000551.4) c.514C>T, p.P172S (NM_000551.4) c.511A>T, p.K171* (NM_000551.4) 
Tools 
Mutation Taster Polymorphism Disease causing Disease causing 
SIFT Uncertain Damaging 
MutPred Uncertain Pathogenic 
PROVEAN Pathogenic Pathogenic 
PolyPhen 2 Benign Benign 
CADD GRCh37-v1.6 22.8 24.7 38 
ACMG Classification VUS VUS Likely pathogenic 
Family AFamily BFamily C
Tumors RCH RCH, CHB, KC RCH, CHB, PC 
VHL Type 
Variant Classes Non-inactivating Inactivating 
Variants c.511A>C, p.K171Q (NM_000551.4) c.514C>T, p.P172S (NM_000551.4) c.511A>T, p.K171* (NM_000551.4) 
Tools 
Mutation Taster Polymorphism Disease causing Disease causing 
SIFT Uncertain Damaging 
MutPred Uncertain Pathogenic 
PROVEAN Pathogenic Pathogenic 
PolyPhen 2 Benign Benign 
CADD GRCh37-v1.6 22.8 24.7 38 
ACMG Classification VUS VUS Likely pathogenic 

RCH, retinal capillary hemangioblastoma; CHB, central nervous system hemangioblastoma; KC, kidney cysts; PC, pancreas cysts; VUS, variants of uncertain significance.

Variant c.511A>C [ENST00000256474] with genomic coordinate chr3:10191518 [hg38 build] is predicted to lead to the substitution of amino acid lysine to glutamine at position 171 [p.L171Q] in surface A, Elongin B/C binding domain of pVHL (Family A) (Fig. 2). This variant was classified based on the ACMG classification as a variant of uncertain significance (VUS) with clinical manifestations of RCH in the proband (Table 1). Genetic testing other family members (I-1, I-2, and II-1, II-2, II-3, II-4, II-5, and II-7) showed that c.511A>C variant occurred sporadically and without systemic involvement.

The other variant of c.514C>T with genomic coordinate chr3:10191521 [hg38 build] leads to the substitution of the amino acid proline to serine at position 172 [p.P172S] and is also located within surface A, at Elongin B/C binding domain of pVHL (Family B). Likewise, this variant is classified as a VUS based on the ACMG classification. The proband, mother, maternal aunt, and maternal grandfather had clinical findings associated with VHL (Fig. 2).

The nonsense variant of c.511A>T [ENST00000256474, NM_000551] with genomic coordinate chr3:10191518 [hg38 build] generated, premature termination codon (PTC) at position 171 [p.K171*] within the Elongin B/C binding domain pVHL (Family C). This variant was also observed in the proband’s sisters with clinical features consistent with VHL type 1 phenotype. However, the variant was not detected in her parents and brother (I-1, I-2, and II-4).

According to the ACMG classification, the variant was classified as likely pathogenic. Clinical presentations of affected family members varied from isolated RCH in the proband to concurrent presentation of CHB and PC in the proband’s sisters.

To the best of our knowledge, the amino acid substitutions at position 171 (lysine to stop codon and lysine to glutamine) have not been reported previously in VHL patients. Recently, the c.514C>T (p.Pro172Ser) variant has been reported in ClinVar in VHL patients and Chuvash polycythemia patients (https://www.ncbi.nlm.nih.gov/clinvar/variation/2417858/).

The studied structures were submitted to a comprehensive set of atomistic MDs to compute the impact of the target variants on the native and variants pVHL structure. Basic MDs trajectory analysis was performed, including RMSD and RMSF, as the time evolution of target conformations using GROMACS software.

The backbone RMSD plots of the studied structures showed that the trajectories become stable after 60 ns, 75 ns, 35 ns, and 10 ns of MD simulations for the native, p.K171Q, p.P172S, and p.K171* structures, respectively (online suppl. Fig. S2). Accordingly, the RMSD plot of p.K171* structure shows that the omission of surfaces A and E dramatically decrease the deviations due to the presence of the rigid antiparallel β-sheets in surfaces B and C. Furthermore, p.K171Q variant stabilized the overall protein structure while p.P172S variant induced a structural rearrangement (like refolding of a loop into α-helix or vice versa) (online suppl. Table S1).

The per-residue RMSF of the native and the studied variants were also computed (online suppl. Fig. S2). As observed, the RMSF of the three variants have significantly decreased in comparison with the native structure. The number of hydrogen bonds formed with the overall studied structures as well as the surface accessible areas were computed and graphed (online suppl. Fig. S3).

The purpose of this study was to report on new heterozygous single nucleotide base substitutions in Iranian patients with RCH. In the current study, the effect of each target variant was evaluated by observing the impact of the substituted amino acid on protein folding and stability for each variant with the aim of predicting pathogenic molecular mechanisms in VHL disease.

It is known that amino acid residues in the α-domain mainly interact with Elongin C/B and alternations may have a powerful pathogenic role and lead to PTC [26]. The inactivating variant c.511A>T (p.K171*) in exon 3, identified in Family C, encodes a stop codon and is predicted to lead to premature termination of the protein. The nonsense variant was found in family C with affected siblings, but not in their parents, which may be due to gonadal mosaicism or de novo variant phenomenon and needs further investigation.

In vitro residues scanning studies have clearly displayed that pVHL residues 157–171 constitute an Elongin C binding site and the residues are considered a hot spot for VHL-causing variants [8, 27]. Also, another study showed that this variant resides on surface A (154–189), which is involved in the pathogenesis of RCH development [11]. According to the present study, it is predicted that the omission of surfaces A and E increase the rigidity and may impact protein interactions within the VCB-CR complex.

P.K171* might escape the nonsense-mediated mRNA decay machinery because the PTC is located in the last exon of VHL, and the nonsense-mediated mRNA decay typically eliminates mRNA transcripts containing premature stop codons and the presence of at least one intron, similar to that of p.Tyr175X as described in other studies [27, 28]. Also, if this transcript is processed, it still produces a pVHL molecule that lacks the main part of the α-domain with highly predicted pathogenicity [26, 29].

The two novel variants (c.511A>C and c.511A>T) as well as the recently reported variant of c.514C>T structures were thoroughly studied using MDs simulation technique. The protein structure’s overall fluctuations show a significantly lower degree of flexibility in the variant structures compared to the native form. The per-residue fluctuation analysis reveals a considerably different pattern of fluctuations in the α-domain participant amino acids for the target variants (except for that of p.K171*, leading to stop codons). Dynamic modeling demonstrated that the variants dramatically affected the flexibility of the protein. Previous structural analysis of pVHL has emphasized the necessity of flexibility in the α-domain region, which is needed for conformational change upon binding an interacting molecule [10]. The positively charged motif contributed by K171 interacts with the acidic E173 residue as well as hydrogen bond formation with N174 through the lysine hydroxyl group. Substitution of K171 with Q results in the formation of amide-π interactions between Q171 carbamoyl group and Y175 that extends the electrostatic interactions between H1 and H3 to H2, which enhances the electrostatic interaction network between the helices (online suppl. Fig. S4), and eventually limits the participant residue fluctuations. Substitution of P172 with serine allows the region to adapt to a helical geometry through hydrogen bond formation with Y175 (Fig. 3). The substitution also enhances the electrostatic interactions network between the helices (online suppl. Fig. S4), as well as a hydrogen bond formation between S172 and D189 that further reduces flexibility in the region.

Fig. 3.

A The overall structure and regions of native pVHL. B, a The amino acid arrangement in BC box located in pVHL α-domain. B, b The amino acid arrangement in Cullin box, located in pVHL α-domain. B, c The amino acid arrangement of the BC box with the amino acid K171Q substitution within the α-domain as found in affected subject II-6 (Family A). B, d The amino acid arrangement of the Cullin box with the K171Q substitution within the α-domain. B, e The amino acid arrangement of the BC box with the amino acid P172S substitution within the α-domain as found in proband III-1 (Family B). B, f The protein structure of the Cullin box with the P172S substitution in the α-domain. B, g Superimposition of the amino acid in native pVHL BC box over the correspondence residues in variant K171Q α-domain. B, h Superimposition of the amino acid in native pVHL Cullin box over the corresponding residues in the α-domain of the K171Q substituted protein. B, i Superimposition of the amino acid in native pVHL BC box over the correspondence residues in variant P172S α-domain. B, j Superimposition of the amino acid in native pVHL Cullin box over the correspondence residues in variant P172S α-domain.

Fig. 3.

A The overall structure and regions of native pVHL. B, a The amino acid arrangement in BC box located in pVHL α-domain. B, b The amino acid arrangement in Cullin box, located in pVHL α-domain. B, c The amino acid arrangement of the BC box with the amino acid K171Q substitution within the α-domain as found in affected subject II-6 (Family A). B, d The amino acid arrangement of the Cullin box with the K171Q substitution within the α-domain. B, e The amino acid arrangement of the BC box with the amino acid P172S substitution within the α-domain as found in proband III-1 (Family B). B, f The protein structure of the Cullin box with the P172S substitution in the α-domain. B, g Superimposition of the amino acid in native pVHL BC box over the correspondence residues in variant K171Q α-domain. B, h Superimposition of the amino acid in native pVHL Cullin box over the corresponding residues in the α-domain of the K171Q substituted protein. B, i Superimposition of the amino acid in native pVHL BC box over the correspondence residues in variant P172S α-domain. B, j Superimposition of the amino acid in native pVHL Cullin box over the correspondence residues in variant P172S α-domain.

Close modal

Although the target variants result in both BC box and Cullin box refolding, the rearrangement in the BC box changes the region conformation drastically, while the induced changes resulting from P172S are more significant than that of K171Q (Fig. 3). According to the obtained results, it is inferred that the observed variants restrain the α-domain region flexibility, resulting in the enhanced stability of variant structures RMSD plots. Likewise, no significant difference is observed in the number of amino acids formed between the constructed amino acids in the native and variants (except for that of K171*).

As previously shown, any conformational changes pVHL α-domain is induced through an allosteric pathway (online suppl. Fig. S5) that initiates interactions between P564 residue of HIF-1α with residue S111 in the β-domain of pVHL and extends to S168 in the α-domain. The pathway enhances the interactions between β-domain and α-domain to restrain the α-domain flexibility, which favors Elongin C binding. The impact of the observed variants over the allosteric pathway was also computed. Accordingly, the variants alter the localization of residues Q164 and S168 in the BC box α-helix, ultimately disturbing the hydrogen bond network in the pathway and affecting interactions with Elongin C and, in turn, a host of other molecules [30].

Further, hydrogen bond analyses of the native and variant proteins with respect to the simulation time were performed (online suppl. Fig. S3). No significant difference was observed between the numbers of hydrogen bonds formed during the simulation (except for variant K171*, in which the smaller number of hydrogen bonds is severely reduced due to the loss of the whole α-domain). Therefore, it seems that the region’s flexibility is altered more through electrostatic interactions (online suppl. Fig. S5). The solvent-accessible area (SASA) of the native and variant protein trajectory values was calculated (online suppl. Fig. S6). Accordingly, the SASA value is lower in variants K171Q and P172S in comparison with the native structure. Furthermore, the variant residues and their adjacent amino acids accessibility have decreased significantly, showing that the variants could affect the tertiary structure of the proteins, and the variant structures’ interactions with Elongin B/C may be affected. In conclusion, based on the in silico characterizations, both K171Q and P172S variants induce conformational rearrangement in the protein structure in such a way that the α-domain participating residue fluctuations are limited, and the rigidity increases.

Since majority of identified variants are classified as VUSs due to lack of evidence to determine their pathogenicity, and performing functional studies are limited and may not be feasible due to ethical restraints. Although gold standard is functional studies, computational methods are definitely useful assets to assay the molecular effects of VUSs and improve the prioritization of the observed mutations [31‒33].

Results of genotype analysis of Iranian patients with RCH along with in silico prediction strategies provide potential evidence for the effect of three variants on protein structure and function and may elucidate pathogenesis. All of the variants identified were predicted to impact protein structure and function. The three variants identified lead to an altered protein with significantly decreased fluctuation in comparison with the native structure of pVHL and increased rigidity. The results of this pilot study will provide a basis for future comprehensive studies (e.g., in vivo/in vitro functional studies) for pathogenicity assessment.

The authors thank all those who provided support during this research. We also that Fanavaran-e Imen Aria Company for their technical support of the in silico simulation machines. The CARE Checklist has been completed by the authors for this case report, attached as online supplementary material (for all online suppl. material, see https://doi.org/10.1159/000543119).

The study was approved by the Iran University of Medical Sciences with the Ethics code of IR.IUMS.REC.1402.735, and written informed consent was obtained from the patients for publication of the details of their medical case and any accompanying images. The report does not include personal information that could identify the patient directly or indirectly. The subjects received a detailed explanation of the study procedures and performed them in accordance with the Declaration of Helsinki.

No conflicting relationship exists for any author.

This work supported by Iran Eye Research Center, Tehran, Iran.

F.A.: wrote the initial draft of the manuscript, samples collection and genetic analysis, and genetic tests interpretation; K.B. performed MD and 3D structure and revised the manuscript text; G.K. and S.T.: genetic consultation; A.S.: introduced the patients; R.M.: wrote the clinical findings; H.K. and R.A.K.: collected clinical findings; M.N.: introduced and treated the patients and revised the final draft of the manuscript.

All data generated or analyzed during this study are included in this article and its online supplementary material files. Further inquiries can be directed to the corresponding author.

1.
Gossage
L
,
Eisen
T
,
Maher
ER
.
VHL, the story of a tumour suppressor gene
.
Nat Rev Cancer
.
2015
;
15
(
1
):
55
64
.
2.
Maher
ER
,
Neumann
HP
,
Richard
S
.
von Hippel–Lindau disease: a clinical and scientific review
.
Eur J Hum Genet
.
2011
;
19
(
6
):
617
23
.
3.
Nordstrom-O’Brien
M
,
van der Luijt
RB
,
van Rooijen
E
,
van den Ouweland
AM
,
Majoor-Krakauer
DF
,
Lolkema
MP
, et al
.
Genetic analysis of von Hippel-Lindau disease
.
Hum Mutat
.
2010
;
31
(
5
):
521
37
.
4.
Ruppert
MD
,
Gavin
M
,
Mitchell
KT
,
Peiris
AN
.
Ocular manifestations of von Hippel-Lindau disease
.
Cureus
.
2019
;
11
(
8
):
e5319
.
5.
Shuin
T
,
Yao
M
,
Shinohara
N
,
Yamasaki
I
,
Tamura
K
.
Clinical status of Von Hippel-Lindau disease associated pheochromocytoma in Japan: a national epidemiologic survey
.
Jpn J Urol
.
2012
;
103
(
3
):
557
61
.
6.
Dollfus
H
,
Massin
P
,
Taupin
P
,
Nemeth
C
,
Amara
S
,
Giraud
S
, et al
.
Retinal hemangioblastoma in von Hippel-Lindau disease: a clinical and molecular study
.
Invest Ophthalmol Vis Sci
.
2002
;
43
(
9
):
3067
74
.
7.
Béroud
C
,
Joly
D
,
Gallou
C
,
Staroz
F
,
Orfanelli
MT
,
Junien
C
.
Software and database for the analysis of mutations in the VHL gene
.
Nucleic Acids Res
.
1998
;
26
(
1
):
256
8
.
8.
Ohh
M
,
Takagi
Y
,
Aso
T
,
Stebbins
CE
,
Pavletich
NP
,
Zbar
B
, et al
.
Synthetic peptides define critical contacts between elongin C, elongin B, and the von Hippel-Lindau protein
.
J Clin Invest
.
1999
;
104
(
11
):
1583
91
.
9.
Maxwell
PH
,
Wiesener
MS
,
Chang
G-W
,
Clifford
SC
,
Vaux
EC
,
Cockman
ME
, et al
.
The tumour suppressor protein VHL targets hypoxia-inducible factors for oxygen-dependent proteolysis
.
Nature
.
1999
;
399
(
6733
):
271
5
.
10.
Leonardi
E
,
Murgia
A
,
Tosatto
S
.
Adding structural information to the von Hippel–Lindau (VHL) tumor suppressor interaction network
.
FEBS Lett
.
2009
;
583
(
22
):
3704
10
.
11.
Minervini
G
,
Quaglia
F
,
Tabaro
F
,
Tosatto
SC
.
Genotype-phenotype relations of the von Hippel-Lindau tumor suppressor inferred from a large-scale analysis of disease mutations and interactors
.
PLoS Comput Biol
.
2019
;
15
(
4
):
e1006478
.
12.
Albiges
L
,
Choueiri
T
,
Escudier
B
,
Galsky
M
,
George
D
,
Hofmann
F
, et al
.
A systematic review of sequencing and combinations of systemic therapy in metastatic renal cancer
.
Eur Urol
.
2015
;
67
(
1
):
100
10
.
13.
Wolters
WP
,
Dreijerink
KM
,
Giles
RH
,
van der Horst-Schrivers
ANA
,
van NesselrooijZandee
BWT
,
Timmers
HJLM
, et al
.
Multidisciplinary integrated care pathway for von Hippel–Lindau disease
.
Cancer
.
2022
;
128
(
15
):
2871
9
.
14.
Naseripour
M
,
Azimi
F
,
Talebi
S
,
Mirshahi
R
,
Kiaee
R
,
Sedaghat
A
, et al
.
Investigation of germline VHL variants in Iranian patients with retinal capillary hemangioblastoma and genotype-phenotype analysis
.
Ophthalmic Genet
.
2023
;
44
(
3
):
211
7
.
15.
Kircher
M
,
Witten
DM
,
Jain
P
,
O’Roak
BJ
,
Cooper
GM
,
Shendure
J
.
A general framework for estimating the relative pathogenicity of human genetic variants
.
Nat Genet
.
2014
;
46
(
3
):
310
5
.
16.
Pronk
S
,
Páll
S
,
Schulz
R
,
Larsson
P
,
Bjelkmar
P
,
Apostolov
R
, et al
.
GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit
.
Bioinformatics
.
2013
;
29
(
7
):
845
54
.
17.
Aliev
AE
,
Kulke
M
,
Khaneja
HS
,
Chudasama
V
,
Sheppard
TD
,
Lanigan
RM
.
Motional timescale predictions by molecular dynamics simulations: case study using proline and hydroxyproline sidechain dynamics
.
Proteins
.
2014
;
82
(
2
):
195
215
.
18.
Price
DJ
,
Brooks
CL
3rd
.
A modified TIP3P water potential for simulation with Ewald summation
.
J Chem Phys
.
2004
;
121
(
20
):
10096
103
.
19.
Silva
TF
,
Vila-Viçosa
D
,
Reis
PB
,
Victor
BL
,
Diem
M
,
Oostenbrink
C
, et al
.
The impact of using single atomistic long-range cutoff schemes with the GROMOS 54A7 force field
.
J Chem Theory Comput
.
2018
;
14
(
11
):
5823
33
.
20.
Kiwiel
K
,
Murty
K
.
Convergence of the steepest descent method for minimizing quasiconvex functions
.
J Optim Theor Appl
.
1996
;
89
(
1
):
221
6
.
21.
Parrinello
M
,
Rahman
A
.
Polymorphic transitions in single crystals: a new molecular dynamics method
.
J Appl Phys
.
1981
;
52
(
12
):
7182
90
.
22.
York
DM
,
Darden
TA
,
Pedersen
LG
.
The effect of long-range electrostatic interactions in simulations of macromolecular crystals: a comparison of the Ewald and truncated list methods
.
J Chem Phys
.
1993
;
99
(
10
):
8345
8
.
23.
Hess
B
,
Bekker
H
,
Berendsen
HJ
,
Fraaije
JG
.
LINCS: a linear constraint solver for molecular simulations
.
J Comput Chem
.
1997
;
18
(
12
):
1463
72
.
24.
Humphrey
W
,
Dalke
A
,
Schulten
K
.
VMD: visual molecular dynamics
.
J Mol Graph
.
1996
;
14
(
1
):
33
28
.
25.
Makarewicz
T
,
Kazmierkiewicz
R
.
Molecular dynamics simulation by GROMACS using GUI plugin for PyMOL
.
J Am Chem Soc
.
2013
;
53
(
5
):
1229
34
.
26.
Sutovsky
H
,
Gazit
E
.
The von Hippel-Lindau tumor suppressor protein is a molten globule under native conditions: implications for its physiological activities
.
J Biol Chem
.
2004
;
279
(
17
):
17190
6
.
27.
Bangiyeva
V
,
Rosenbloom
A
,
Alexander
AE
,
Isanova
B
,
Popko
T
,
Schoenfeld
AR
.
Differences in regulation of tight junctions and cell morphology between VHL mutations from disease subtypes
.
BMC Cancer
.
2009
;
9
(
1
):
229
18
.
28.
Nagy
E
,
Maquat
LE
.
A rule for termination-codon position within intron-containing genes: when nonsense affects RNA abundance
.
Trends Biochem Sci
.
1998
;
23
(
6
):
198
9
.
29.
Leonardi
E
,
Martella
M
,
Tosatto
SC
,
Murgia
A
.
Identification and in silico analysis of novel von Hippel-Lindau (VHL) gene variants from a large population
.
Ann Hum Genet
.
2011
;
75
(
4
):
483
96
.
30.
Qian
H
,
Zou
Y
,
Tang
Y
,
Gong
Y
,
Qian
Z
,
Wei
G
, et al
.
Proline hydroxylation at different sites in hypoxia-inducible factor 1α modulates its interactions with the von Hippel–Lindau tumor suppressor protein
.
Phys Chem Chem Phys
.
2018
;
20
(
27
):
18756
65
.
31.
Spielmann
M
,
Kircher
M
.
Computational and experimental methods for classifying variants of unknown clinical significance
.
Mol Case Stud
.
2022
;
8
(
3
):
a006196
.
32.
Sultana
T
,
Mou
SI
,
Chatterjee
D
,
Faruk
MO
,
Hosen
MI
.
Computational exploration of SLC14A1 genetic variants through structure modeling, protein-ligand docking, and molecular dynamics simulation
.
Biochem Biophys Rep
.
2024
;
38
:
101703
.
33.
Bhattacharya
R
,
Rose
PW
,
Burley
SK
,
Prlić
A
.
Impact of genetic variation on three dimensional structure and function of proteins
.
PLoS One
.
2017
;
12
(
3
):
e0171355
.