Identification of human genes interacting with HIV attachment receptors and potentially involved in disease pathogenesis based on multi-network bioinformatics analysis

The aim of the study was to search for candidate genes interacting with HIV attachment receptors (CCR5, CXCR4, CCR2, CD4) and potentially involved in disease pathogenesis, based on complex in silico network algorithms. Materials and methods. A number of web applications were used to analyse genetic and protein-protein networks, the algorithms and databases of which are complementary. The CD4 receptor and chemokine co-receptor genes CCR5, CXCR4 and CCR2 were used as background/baseline genes in all cases, as their protein products play a key role in the process of virus attachment to the cell. The data were analysed, including a two-stage ranking of the identified candidate genes according to their interaction with background genes and their presence in the results of network analysis of different web resources. Results and discussion. According to the results, candidate genes were identified using three web resources: HumanNet — 451 candidate genes, GeneMania — 86, STRING — 61. Based on the results of crossing the three web resources, the total number of candidate genes associated with background genes was 511. The total number of genes with a rank above 4 points was 68. Of these, 31 genes (45.6%) encoding C-C/C-X-C family chemokine ligands, 12 genes (17.6%) encoding C-C/C-XC receptors, 8 genes (11.8%) encoding receptors of other types, and 17 genes (25%) encoding proteins of other types. The following receptors and proteins that are not members of the C-C/C/C-X-C families of the indicated groups have been identified: ARRB2, TLR2, ADRA1A, ARRB1, FPR1, FPR3, GNAI1, PF4, PIK3CG, PPIA, S1PR3, GNA11, GNAI2, GNG2, PTPRC, ADRA1B, ADRB1, AFP, CD164, DBN1, GNB1, ITCH, RNF113A, SLC1A1, USP14. Conclusion. Most of the identified candidate genes interacting with HIV attachment receptors and potentially involved in the pathogenesis of the disease were those encoding chemokine receptors and their C-C/C-X-C family ligands, the role of which in the progression of HIV infection is known or under active investigation. At the same time, genes whose products have never been considered as possible participants in the pathogenesis of the disease were identified, but the results suggest that they may play a role in the regulation of virus entry and/or in the modulation of the immune response of the organism. Further bioinformatic and experimental studies of the functions and polymorphic variants of these genes will help to improve the understanding of the genetic basis of HIV pathogenesis and identify new directions for therapeutic approaches.

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Publication Details

Journal
HIV Infection and Immunosuppressive Disorders
Published
2025-02-13
DOI
https://doi.org/10.22328/2077-9828-2024-16-4-28-44
Citations
3
Primary Topic
HIV Research and Treatment
Type
article
Field-Weighted Citation Impact
3.11
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article

Identification of human genes interacting with HIV attachment receptors and potentially involved in disease pathogenesis based on multi-network bioinformatics analysis

V. S. Davydenko, Арег А. Тотолян, А. N. Shchemelev, Yu. V. Ostankova et al.
3 citations
HIV Infection and Immunosuppressive Disorders
HIV Research and Treatment
3.11
article

Identification of human genes interacting with HIV attachment receptors and potentially involved in disease pathogenesis based on multi-network bioinformatics analysis

V. S. Davydenko, Арег А. Тотолян, А. N. Shchemelev, Yu. V. Ostankova, E. V. Anufrieva, Valeriya V. Kushnareva
article en
3 citations

Abstract

The aim of the study was to search for candidate genes interacting with HIV attachment receptors (CCR5, CXCR4, CCR2, CD4) and potentially involved in disease pathogenesis, based on complex in silico network algorithms. Materials and methods. A number of web applications were used to analyse genetic and protein-protein networks, the algorithms and databases of which are complementary. The CD4 receptor and chemokine co-receptor genes CCR5, CXCR4 and CCR2 were used as background/baseline genes in all cases, as their protein products play a key role in the process of virus attachment to the cell. The data were analysed, including a two-stage ranking of the identified candidate genes according to their interaction with background genes and their presence in the results of network analysis of different web resources. Results and discussion. According to the results, candidate genes were identified using three web resources: HumanNet — 451 candidate genes, GeneMania — 86, STRING — 61. Based on the results of crossing the three web resources, the total number of candidate genes associated with background genes was 511. The total number of genes with a rank above 4 points was 68. Of these, 31 genes (45.6%) encoding C-C/C-X-C family chemokine ligands, 12 genes (17.6%) encoding C-C/C-XC receptors, 8 genes (11.8%) encoding receptors of other types, and 17 genes (25%) encoding proteins of other types. The following receptors and proteins that are not members of the C-C/C/C-X-C families of the indicated groups have been identified: ARRB2, TLR2, ADRA1A, ARRB1, FPR1, FPR3, GNAI1, PF4, PIK3CG, PPIA, S1PR3, GNA11, GNAI2, GNG2, PTPRC, ADRA1B, ADRB1, AFP, CD164, DBN1, GNB1, ITCH, RNF113A, SLC1A1, USP14. Conclusion. Most of the identified candidate genes interacting with HIV attachment receptors and potentially involved in the pathogenesis of the disease were those encoding chemokine receptors and their C-C/C-X-C family ligands, the role of which in the progression of HIV infection is known or under active investigation. At the same time, genes whose products have never been considered as possible participants in the pathogenesis of the disease were identified, but the results suggest that they may play a role in the regulation of virus entry and/or in the modulation of the immune response of the organism. Further bioinformatic and experimental studies of the functions and polymorphic variants of these genes will help to improve the understanding of the genetic basis of HIV pathogenesis and identify new directions for therapeutic approaches.

HIV Infection and Immunosuppressive DisordersVol. 16(4)
Saint Petersburg Pasteur Institute (RU)
Openalex Percentile: Top 11%
HIV Research and Treatment
3.11
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