Effect of naturally occurring polymorphisms on HIV-1 integrase structure and dolutegravir binding in subtypes A1 and D

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However, emerging evidence of reduced DTG efficacy in absence of major DTG resistance mutations among non-subtype B populations requires investigation into alternative resistance mechanisms. This study investigated the impact of naturally occurring polymorphisms (NOPs) on integrase stability and DTG binding in HIV-1 subtypes A1 and D, which are predominant in East Africa. Methods We analyzed sequences from ART-naïve individuals derived from the Los Alamos HIV sequence database for subtypes A1 and D. Consensus integrase sequences for subtypes A1 and D were generated, and stability effects of identified NOPs were assessed using the mutation scanning matrix (mCSM). Three-dimensional structures of HIV-1 A1 and D integrase were predicted using SWISS-MODEL. Molecular docking of HIV-1 integrase and DTG was performed with AutoDock Vina, and interaction profiles were analyzed using Protein-Ligand Interaction Profile (PLIP). Results We identified 15 NOPs in subtype A1 and 14 NOPs in subtype D consensus sequences relative to the HIV reference genome (HXB2). All NOPs showed destabilizing effects (ΔΔG: -1.617 to -0.011 kcal/mol), with I151V and S17N having the highest destabilization effect. Docking analyses showed preserved DTG coordination with the D64 and E152 residues across subtypes. However, subtype A1 showed an altered hydrophobic contact (Y143 vs P145) while subtype D lacked interaction with D116 and showed additional polar contacts with H67, K156, N155, and T66. Conclusion The NOPs identified in subtypes A1 and D do not completely disrupt DTG binding but induce thermodynamic destabilization, structural and interaction changes that may influence integrase stability and consequently drug susceptibility. These findings highlight the importance of subtype-specific structural analyses in exploring alternative drug resistance mechanisms. HIV-1 integrase dolutegravir naturally occurring polymorphisms molecular docking drug resistance Figures Figure 1 Figure 2 Figure 3 Figure 3 Introduction The integrase (IN) enzyme of Human Immunodeficiency Virus type 1 (HIV-1) plays an important role in HIV-1 replication by catalysing the process of virus integration into the host DNA (Kirchhoff, 2016 ). Integrase strand transfer inhibitors (INSTIs) were developed to block viral DNA integration and therefore suppress HIV replication (Li et al., 2023 ). INSTIs are categorised into two; (i) first-generation inhibitors which include raltegravir (RAL) and elvitegravir (EVG), (ii) second-generation inhibitors which have superior efficacy and higher genetic barriers to resistance including dolutegravir (DTG), bictegravir (BIC), and cabotegravir (CBT) (Ndashimye et al., 2022 ). Currently, DTG is recommended by the World Health Organization for first-line antiretroviral therapy (ART) due to its potency and safety profile (Wagner et al., 2024 ). DTG has shown high levels of viral suppression (Bwire et al., 2023 ; Namayanja et al., 2024 ). However, there is increasing evidence for the emergency of DTG resistance among non-subtype B populations (Kamori & Barabona, 2023 ). Specifically, major INSTI drug resistance mutations such as N115H, G118R, R263K, E138A, G140R among others, have been identified across sub-Saharan Africa and south America (Abdullahi et al., 2023 ; Chu et al., 2024 ; Diaz et al., 2023 ; Xiao et al., 2023 ). In addition to known major and accessory drug resistance mutations, other polymorphisms in HIV-1 integrase such as G123S, V72I and R127K have been linked to virological failure among patients receiving DTG regimens (Celotti et al., 2020 ). Several studies exploring the effect of HIV-1 integrase polymorphisms on drug binding are mainly based on homology-based methods for three-dimensional structure prediction, molecular docking and interaction analysis with particular focus on the catalytic triad which consists of the DDE motif (D64, D116, and E152) and two magnesium ions (Karim et al., 2023 ). For instance, in silico analysis of naturally occurring polymorphisms (NOPs) such as T124V which is highly enriched in diverse HIV-1 subtypes, has shown significant impact on the binding of raltegravir (RAL) as compared to DTG (Rogers et al., 2018 ). Moreover, polymorphisms that are subtype-specific have been shown to affect the binding affinity of IN and DNA in presence of known INSTI drug resistance mutations (Mikasi et al., 2021 ). The structural effect of naturally occurring polymorphisms (NOPs) of HIV-1 integrase on the binding affinity of DTG and other second generation INSTIs has been investigated in HIV-1 subtype C and CRF02-AG in South Africa and Cameroon respectively (Chitongo et al., 2020 ; Isaacs et al., 2020 ; Mikasi et al., 2021 ). These studies have shown a significant effect of major INSTI mutation G140S on HIV-1 subtype C integrase and DTG binding affinity (Chitongo et al., 2020 ). Similar analyses showed a change in the number and type of interactions induced by accessory INSTI mutation E157Q (Mikasi et al., 2021 ). There has been no significant changes in the structure of HIV-1 IN and binding affinity of second generation INSTIs by NOPs in Subtype C and CRF02-AG in comparison to Subtype B (Isaacs et al., 2020 ). There is limited data on the 3D structure of HIV-1 integrase for subtypes A1 and D, the effect of NOPs on the protein structure as well the binding affinity to different INSTIs. For this study, we set out to investigate the impact of NOPs on the stability of HIV-1 IN for subtypes A1 and D and the effect of NOPs on DTG-HIV-1 integrase binding. Methods Generation of consensus HIV-1 A1 and HIV-1 D integrase sequences We searched the Los Alamos HIV database (Foley et al., 2018 ) for HIV-1 sequences containing integrase sequences for subtypes A1 and D, from ART-naïve. The sequences spanned a period of 1986 to 2019 from different countries namely: Sweden, Kenya, Australia, Spain, Uganda, Rwanda, South Africa, Pakistan, and Tanzania. Sequences were analyzed using the Stanford HIV drug resistance algorithm to identify drug resistance mutations and other mutations that are not associated with drug resistance. Sequences without known drug resistance mutations in the integrase region were retained for further analysis. Multiple sequence alignments of the sequences were generated for the subtypes A1 and D using MAFFT sequence alignment tool (Katoh et al., 2002 ), and consensus sequences generated using JALVIEW. To extract the integrase region, we made a pairwise alignment of each consensus sequence and the HXB2 integrase sequence using BLAST and overlapping regions of the consensus sequences were extracted. The nucleotide sequences were translated to obtain corresponding amino acid sequences for subtype A1 and D. Prediction of the three-dimensional structure and quality assessment SWISSMODEL (Schwede et al., 2003 ) was used to predict the three-dimensional structures of HIV-1 integrase of subtypes A1and D. The template used to generate these models was the experimental structure of the Wild type of HIV-1 subtype B (PDB ID: 8W34), given the high sequence identity with the consensus sequences of HIV-1 integrase A1 and D. To assess the quality of the generated models, we used inbuilt quality metrics of SWISS MODEL including; the global model quality estimate (QMQE) and the qualitative mean energy analysis (QMEAN). In addition, tools including VERIFY3D, ERRAT and PROCHECK were used to further assess the quality of the predicted three-dimensional structures. We computed the root mean square deviation (RMSD) between the homologous template structure and the predicted structure to assess the deviation in the backbone of the predicted structures. Structure preparation and energy minimization The predicted three-dimensional structures of HIV-1 integrase (IN) were aligned to the 8W34 template using PyMOL (DeLano & others, 2002) to extract magnesium (Mg²⁺) ions and the ligand, dolutegravir (DTG). The DTG molecule was saved as an individual PDB file, while the predicted HIV-1 integrase structures and Mg²⁺ ions were saved together as a receptor complex for each subtype. Both ligand and receptor structures were imported into UCSF Chimera (Meng et al., 2023 ), hydrogen ions were added and Gasteiger charges were assigned using the AMBER ff14SB force field. The energy minimization stage involved 100 steps of steepest descent followed by 100 steps of conjugate gradient. Changes in Gibbs free energy by individual NOPs To determine the change induced by introduction of each mutation to the Gibbs free energy of the energy minimized wild-type structure, we uploaded a list of NOPs and the 3D structure of the WT subtype B structure to the mutation scanning matrix (mCSM) server (Pires et al., 2014 ). Molecular docking Molecular docking was performed using AutoDock Vina (Eberhardt et al., 2021 ) through the UCSF Chimera interface (Meng et al., 2023 ), utilizing a local installation of the docking engine. For each subtype, structures of both the receptor and the ligand were imported into UCSF Chimera, and the docking grid was defined to enclose the catalytic DDE triad and the magnesium ions. Docking parameters were set to generate nine binding modes, with an exhaustiveness value of eight and a maximum energy difference of 3 Kcal/Mol. Binding poses were ranked according to predicted binding affinity, and the pose with the lowest binding energy was selected for further analysis. Interaction analysis The Protein-Ligand interaction Profile (PLIP) tool was used to explore the interaction between DTG and the HIV-1 IN of subtypes B, A1 and D. PLIP detects hydrogen bonds, hydrophobic contacts, pi-stacking, pi-cation interactions, salt bridges, water bridges, metal complexes, and halogen bonds. The identified ionic contacts were depicted using USCF chimera and proteinplus for three-dimensional and two-dimensional visualisations respectively. Results Generation of consensus sequences and identification of polymorphisms Consensus sequences for subtype A1 and D were respectively generated from multiple sequence alignments of 366 and 107 HIV-1 sequences. These were aligned to HIV-1 integrase HXB2 reference (NCBI accession: K03455) to identify NOPs in subtype A1 and D. For subtype A1, we identified 15 NOPs, three of these (D10E, K14R, V31I) belong to the N-terminal domain. Nine (T112V, I113V, G123S, T125A, R127K, G134N, K136Q, D167E and V201I) belong to the catalytic core domain. Three belong to the C-terminal domain (N232D, L234I, S283G). For subtype D, we identified 14 NOPs, two of which belong to the N-terminal domain (D10E, S17N), one which belongs to the loop connecting the NTD to the CCD (M50L), six in the CCD (T112V, I113V, G123S, T125A, R127K, V201I) and five in the CTD (T218I, N232D, L234I, D256E, A265). Structure analysis and quality assessment The predicted three-dimensional structures of HIV-1 integrase for subtypes A1 and D are shown in Fig. 1 . The homologous template identified for the two subtypes was an experimental structure of HIV-1 subtype B integrase in complex with DTG, DNA, MG, and ZN (PDBID: 8W34). The sequence identity between the subtype A1 integrase consensus sequence and the sequence of the homologous template structure was 95.83% with a sequence similarity of 61%. With respect to the sequence of 8W34, we identified twelve mutations, including two in the NTD (K14R and V31I), eight in the CCD (T112V, T124A, T125A, G134N, K136Q, I151V, D167E and V201I) and two in the CTD (V234I and S283G) as shown in Fig. 1 a. Structural quality assessment showed a GMQE score of 0.83 and a QMEANDisCo global score of 0.78 ± 0.05. Ramachandran analysis showed that 90.9% of residues were in favored regions and additional 8.9% of residues were in allowed regions, and ERRAT reported an overall quality factor of 95.73. Structural alignment between the predicted model and template 8W34 showed a root-mean-square deviation (RMSD) of 0.094 Å for all chains and 0.093 Å for chain A (Fig. 2 a). Subtype D consensus sequence has a sequence identify of 96.18% and a sequence similarity of 61% with the sequence of homologous template structure (8W34). We identified 11 NOPs in the consensus sequence of subtype D relative to the sequence of 8W34. Amongst these, one belongs to the NTD (S17N), one belongs to the loop connecting the NTD to the CCD (M50L), five in the CCD (T112V, T124A, T125A, I151V, V201I) and four in the CTD (T218I, V234I, D256E, A265V) as shown in Fig. 1 a. Structural assessment showed a GMQE score of 0.83 and GMEANDisCo global score of 0.7 ± 0.05. Ramachandran analysis via PROCHECK showed that 90.8% and 8.8% of residues were in favored and allowed regions respectively and ERRAT reported an overall quality factor of 97.43. Alignment of the predicted model and the homologous template structure showed an RMSD of 0.146 Å for all chains and 0.142 Å for chain A (Fig. 2 b.) Effect of NOPs on the stability of the wild type of HIV-1 integrase protein The predicted stability changes in energy of the 3D structure of wild-type of subtype B HIV-1 integrase showed destabilizing effects on the 8W34 complex with energy changes ranging between − 1.617 and − 0.011 Kcal/Mol. Notably, CCD mutation I151V and NTD mutation S17N were the most destabilizing, causing respective energy changes of -1.617 and − 1.338 Kcal/Mol. Specific energy changes for other NOPs were − 0.878, -0.418, -0.413, -0.379, -0.339, -0.674, -0.61, -0.092, -0.209, -0.504, -0.011, -0.38, -0.316 Kcal/Mol for K14R, V31I, M50L, T112V, T124A, T125A, G134N, K136Q, D167E, V201I, T218L, D256E and A265V respectively. Molecular docking and interaction analysis The best pause docked complexes for subtypes A1 and D were analyzed relative to the subtype B homologous structure (8W34) to identify residues involved in the binding of DTG to HIV-1 integrase in subtypes A1 and D. For subtype A1, we observed interactions between DTG and the residues of the integrase catalytic triad (D64, D116, E152) mediated by the two MG ions and direct hydrophobic interaction with Y143. Similarly for 8W34, we observed interactions between DTG, and the residues of the integrase catalytic DDE motif mediated by MG ions in addition to a direct hydrophobic interaction with P145. However, for subtype D, the interactions between DTG and MG ions were only limited to two residues of the catalytic motif (D64 and E152) and there was no interaction with D116 either with DTG or any of the MG ions. Additional polar contacts were observed exclusively for subtype D including N155, H67, T66 and K156. Generally, there were slight changes in the distances between interacting atoms of DTG, MG ions and interacting atoms of the DDE residues (Table 1 ). Discussion This study investigates the potential impact of naturally occurring polymorphisms (NOPs) on Dolutegravir (DTG) susceptibility in HIV-1 subtypes A1 and D, with a focus on integrase-DTG interactions. Using a high-resolution structural template (PDB: 8W34), our analyses suggest that although these NOPs are not directly linked to drug resistance, they may affect integrase stability and modulate its binding affinity for DTG. Structural alignment of predicted integrase models for subtypes A1 and D with the subtype B template showed high overall conservation, with RMSD values below 0.15 Å. However, several subtype-specific differences were observed. Notably, both subtypes A1 and D had a short helical element in the N-terminal domain (NTD) absent in subtype B, which may influence the spatial orientation of the catalytic core domain (CCD) or modulate MG-dependent active site conformation. Such alterations could modulate susceptibility when compounded with treatment-induced pressure or additional resistance mutations (Isaacs et al., 2020 ). We identified 15 polymorphisms and 14 polymorphisms in subtype A1 and subtype D respectively, distributed across the N-terminal, catalytic core and C-terminal domains of HIV-1 integrase. Previous studies have shown that polymorphisms in key structural regions of the CCD induce changes in conformational dynamics of the binding pocket. For instance, an in-silico study showed that the interaction of the inner subunit T124 residue with target DNA is lost with the T124A substitution. Moreover, these results suggested that T124A affects the binding of DTG but to a lesser extent as compared to raltegravir (Rogers et al., 2018 ). Other CCD polymorphisms, including G134N and K136Q, may similarly affect DTG binding stability in non-B subtypes, however, their specific effects remain to be investigated. In addition, other identified polymorphisms such as G123S and R127K have previously been associated with higher risk of virological failure for individuals on INSTI-based ART in s subtype B dominant population (Celotti et al., 2020 ). Using the mCSM server, we evaluated the thermodynamic consequences of introducing identified NOPs into the WT subtype B integrase. All tested mutations showed a destabilizing effect on the global protein structure, with the most destabilizing substitutions, I151V (A1) and S17N (D). Though not located within the active site, their positions suggest they could exert long-range allosteric effects. Previous studies on other INSTI-resistance mutations (e.g., L74M) support the idea that allosteric destabilization may contribute to compromised drug binding or integration efficiency (Djojosugito et al., 2023 ). Molecular docking studies had successful DTG binding in all subtypes, with preserved interactions with the catalytic triad D64, D116, and E152 via MG coordination. However, subtype-specific deviations were observed. Subtype A1 retained all canonical interactions but shifted peripheral hydrophobic contact from P145 (in subtype B) to Y143. This may suggest altered ligand orientation or pocket accommodation, which could affect DTG binding. In contrast, subtype D lacked interaction with D116, which is part of the catalytic triad. Moreover, subtype D gained polar interactions with H67, K156, N155, and T66 residues not typically involved in canonical DTG binding. These additional contacts may indicate a less tightly constrained binding mode, potentially lowering the binding specificity of DTG. From a public health perspective, our findings support sequencing of HIV-1 integrase as part of DTG resistance surveillance programs, especially in East Africa where subtypes A1 and D predominate (Bbosa et al., 2019 ; Ndashimye et al., 2022 ). While our structural models are built upon a high-resolution crystal structure and validated by quality metrics, our study remains an in-silico prediction. Functional validation using integration efficiency assays, viral replication capacity assessments, and long-term treatment outcome data are necessary to confirm the clinical relevance of identified NOPs. Future studies should incorporate population-level sequence diversity to explore the full landscape of NOP-mediated effects. Conclusion This study provides structural and thermodynamic assessment of how NOPs in HIV-1 subtypes A1 and D affect integrase stability and DTG binding. While none of the identified polymorphisms completely disrupted DTG interaction, several introduced destabilizing effects and altered binding patterns that may contribute to resistance development. In addition, these results highlight the importance of subtype-specific investigations to inform HIV-1 drug resistance mechanisms in diverse global populations. Table 1 Interactions between DTG and HIV-1 integrase for subtypes B, A1 and D. Subtype Polar contacts (distance) Ionic contacts (distance) MG-A-303 MG-A-304 B P145 (3.57) D64 (2.05), D116 (2.02) D64 (2.01), E152 (2.38), E152 (2.45) A1 Y143 (3.16) D64 (2.13), D116 (2.42) D64 (2.43), E152 (2.59), E152 (2.63) D N155 (3.93), K156 (3.76), H67, T66 (3.18) D64 (2.04) D64 (2.62), E152 (2.80), E152 (2.82) The numbers indicated in parenthesis are interaction distances given in angstroms (Å). Abbreviations: Proline (P), Aspartic acid (D), Glutamic acid (E), Tyrosine (Y), Asparagine (N), Lysine (K), Histidine (H), and Threonine (T) and magnesium ions (Mg²⁺; MG-A-303 and MG-A-304). Declarations Author Contributions A.S. and D.J. conceptualized and designed the study. D.J., D.S., and D.P.K. supervised the study. A.S., D.S., and D.J. developed the methodology. A.S. curated the data, obtained the required software, performed data analysis, and visualization. N.B. guided on the interpretation of analysis results. D.P.K., D.J., and D.S. acquired the funding and provided resources. A.S. and N.B. wrote the original manuscript. A.S., N.B., D.S., D.P.K., and D.J. reviewed the manuscript. All authors approved the final version of the manuscript. Funding This work was supported by the National Institutes of Health (NIH) Common Fund, through the OD/Office of Strategic Coordination (OSC) and the Fogarty International Center (FIC) [NIH award number U2RTW010672], its contents are solely the responsibility of the authors and do not necessarily represent the official views of the supporting office. Additional funding was provided by the Bill and Melinda Gates Foundation [Investment ID INV-031335], the UK Medical Research Council (MRC) and UK Department for International Development (DFID) that is under the MRC/DFID Concordat agreement and is also part of the European & Developing Countries Clinical Trials Partnership (EDCTP2) programme sup- ported by the European Union. Data Availability Statement The sequence data analysed in this study are available in the Los Alamos National Laboratory (LANL) HIV Sequence Database. The curated sequence datasets and the predicted three-dimensional structural models of HIV-1 subtype A1 and D integrase generated in this study were deposited in Zenodo and can be accessed at the following DOI: https://doi.org/10.5281/zenodo.18605359. Ethics approval and consent to participate Not applicable. Consent for publication Not applicable Competing interests The authors declare no competing interests. References Abdullahi A, Kida IM, Maina UA, Ibrahim AH, Mshelia J, Wisso H, Adamu A, Onyemata JE, Edun M, Yusuph H, Aliyu SH, Charurat M, Abimiku A, Abeler-Dorner L, Fraser C, Bonsall D, Kemp SA, Gupta RK. Limited emergence of resistance to integrase strand transfer inhibitors (INSTIs) in ART-experienced participants failing dolutegravir-based antiretroviral therapy: a cross-sectional analysis of a Northeast Nigerian cohort. J Antimicrob Chemother. 2023;78(8):2000–7. https://doi.org/10.1093/jac/dkad195 . Bbosa N, Kaleebu P, Ssemwanga D. HIV subtype diversity worldwide. 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High viral suppression rates among PLHIV on dolutegravir who had an initial episode of viral non-suppression in Uganda September 2020–July 2021. PLoS ONE. 2024;19(6 JUNE):1–13. https://doi.org/10.1371/journal.pone.0305129 . Ndashimye E, Reyes PS, Arts EJ. (2022). New antiretroviral inhibitors and HIV-1 drug resistance: more focus on 90% HIV-1 isolates ? September , 1–22. https://doi.org/10.1093/femsre/fuac040 Pires DEV, Ascher DB, Blundell TL. mCSM: predicting the effects of mutations in proteins using graph-based signatures. Bioinformatics. 2014;30(3):335–42. Rogers L, Obasa AE, Jacobs GB, Sarafianos SG, Sönnerborg A, Neogi U, Singh K. Structural Implications of Genotypic Variations in HIV-1 Integrase From Diverse Subtypes. Front Microbiol. 2018;9(August):1–9. https://doi.org/10.3389/fmicb.2018.01754 . Schwede T, Kopp J, Guex N, Peitsch MC. SWISS-MODEL: an automated protein homology-modeling server. Nucleic Acids Res. 2003;31(13):3381–5. Wagner Z, Wang Z, Stecher C, Karamagi Y, Odiit M, Haberer JE, Linnemayr S. The association between adherence to antiretroviral therapy and viral suppression under dolutegravir-based regimens: an observational cohort study from Uganda. J Int AIDS Soc. 2024;27(8):1–8. https://doi.org/10.1002/jia2.26350 . Xiao MA, Cleyle J, Yoo S, Forrest M, Krullaars Z, Pham HT, Mesplède T. The G118R plus R263K Combination of Integrase Mutations Associated with Dolutegravir-Based Treatment Failure Reduces HIV-1 Replicative Capacity and Integration. Antimicrob Agents Chemother. 2023;67(5). https://doi.org/10.1128/aac.01386-22 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 28 Apr, 2026 Reviews received at journal 28 Apr, 2026 Reviews received at journal 26 Apr, 2026 Reviewers agreed at journal 11 Apr, 2026 Reviewers agreed at journal 07 Apr, 2026 Reviews received at journal 25 Feb, 2026 Reviewers agreed at journal 24 Feb, 2026 Reviewers agreed at journal 24 Feb, 2026 Reviewers agreed at journal 23 Feb, 2026 Reviewers invited by journal 22 Feb, 2026 Editor assigned by journal 14 Feb, 2026 Submission checks completed at journal 13 Feb, 2026 First submitted to journal 12 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8861457","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":597294846,"identity":"bc02ad3b-d3a0-4a1a-9368-dc633a2d9673","order_by":0,"name":"Alfred Ssekagiri","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIie2PsQrCMBRFUwJxedI1haK/UClUwcFfceoU/6AWp7pIXfUvdHEuBNvRtaOloOCkCAWXYqJ7jZtgznDJcA8vFyGN5kcxZggBwjgRb2p/o5CxVEBZEYDzyo91c5kVxSqY2v053C95MADU4vtNk0Jz5vY2aQY2b++GLBUfA9/PG8/kQKwjSYHi9s5lRCgUvEale8jOj2MtFTi5rFZQnGTsGdsokAouJ5GC0hNbrHWcCIV4eBJTIJ+2dA5ZcVtU4YiavLyzKuyYLZ42z3/DZRD6SoW6JJSBr4ptjUaj+TOe141EU9VF4e4AAAAASUVORK5CYII=","orcid":"","institution":"Uganda Virus Research Institute","correspondingAuthor":true,"prefix":"","firstName":"Alfred","middleName":"","lastName":"Ssekagiri","suffix":""},{"id":597294849,"identity":"672277fc-a62a-4564-825d-7cce9e3a7e13","order_by":1,"name":"Deogratius Ssemwanga","email":"","orcid":"","institution":"Uganda Virus Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Deogratius","middleName":"","lastName":"Ssemwanga","suffix":""},{"id":597294851,"identity":"f235c3b2-ee98-4239-a1f4-737a1670cedf","order_by":2,"name":"Nicholas Bbosa","email":"","orcid":"","institution":"Uganda Virus Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Nicholas","middleName":"","lastName":"Bbosa","suffix":""},{"id":597294856,"identity":"f4727832-69d7-4d47-83fd-84bed290415c","order_by":3,"name":"David Patrick Kateete","email":"","orcid":"","institution":"Makerere University","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"Patrick","lastName":"Kateete","suffix":""},{"id":597294862,"identity":"b3f72891-8b56-4fae-adc6-0c12bee879b9","order_by":4,"name":"Daudi Jjingo","email":"","orcid":"","institution":"Makerere University","correspondingAuthor":false,"prefix":"","firstName":"Daudi","middleName":"","lastName":"Jjingo","suffix":""}],"badges":[],"createdAt":"2026-02-12 11:23:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8861457/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8861457/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103630536,"identity":"f5654638-ad1e-413c-8495-ccbae424a80f","added_by":"auto","created_at":"2026-02-28 01:40:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1625309,"visible":true,"origin":"","legend":"\u003cp\u003ePolymorphisms in HIV-1 integrase across subtypes A1 and D, using subtype B (HXB2) as reference. (A) Schematic representation of the HIV-1 integrase protein showing its functional domains N-terminal domain (NTD) in blue, Catalytic Core Domain (CCD) in red, and C-terminal domain (CTD) in green. Catalytic residues (D64, D116, E152) comprising the DDE motif are marked with red circles. Polymorphic residues specific to subtype A1 (orange bars), subtype D (green bars), and those shared between A1, and D (light blue bars) are mapped onto the integrase structure, showing their distribution across domains. (B) A multiple sequence alignment (MSA) of HIV-1 integrase amino acid sequences from subtypes B (HXB2 reference), A1, and D. Variations across subtypes are color-coded by residue to highlight conserved and polymorphic positions.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8861457/v1/d165a328bb0655d54183ff01.png"},{"id":103630535,"identity":"edbba2ec-5809-4737-9236-3f15d80e2443","added_by":"auto","created_at":"2026-02-28 01:40:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2251945,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStructural comparison of HIV-1 integrase subtypes A1 and D with the subtype B template.\u003c/strong\u003e (A) Structural alignment of the predicted HIV-1 integrase model for subtype A1 (blue) with the subtype B experimental structure (grey, PDB ID: 8W34). (B)Structural alignment of subtype D integrase (green) with the same subtype B template (grey). (C) Subtype B integrase structure (grey) with polymorphic sites identified in subtypes A1 and D highlighted in red and teal (catalytic DDE motif).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8861457/v1/4b43ed4586b59294e8e546a7.png"},{"id":104399314,"identity":"65bcd4cf-5759-4d18-9d6a-5d7820b5a473","added_by":"auto","created_at":"2026-03-11 12:05:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1589729,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular interactions between dolutegravir (DTG), catalytic residues, and magnesium ions in HIV-1 integrase subtypes B, A1, and D. Left panels: 3D representations of the DTG-binding pocket in subtype B (A), subtype A1 (C), and subtype D (E) showing interactions with the catalytic triad residues (D64, D116, E152) and coordination with two Mg²⁺ ions (green spheres). Right panels: Corresponding 2D interaction diagrams showing DTG contacts with the Mg²⁺ ions and surrounding residues in subtype B (B), subtype A1 (D) and subtype D (F).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8861457/v1/450a2f1d6584e480e5ede1d9.png"},{"id":103782234,"identity":"0b479952-acbd-46ac-a43c-7f6ffe9b4d51","added_by":"auto","created_at":"2026-03-02 21:09:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1589729,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular interactions between dolutegravir (DTG), catalytic residues, and magnesium ions in HIV-1 integrase subtypes B, A1, and D. Left panels: 3D representations of the DTG-binding pocket in subtype B (A), subtype A1 (C), and subtype D (E) showing interactions with the catalytic triad residues (D64, D116, E152) and coordination with two Mg²⁺ ions (green spheres). Right panels: Corresponding 2D interaction diagrams showing DTG contacts with the Mg²⁺ ions and surrounding residues in subtype B (B), subtype A1 (D) and subtype D (F).\u003c/p\u003e","description":"","filename":"31.png","url":"https://assets-eu.researchsquare.com/files/rs-8861457/v1/131558bc9016a466b418af4e.png"},{"id":104779312,"identity":"e9ee4532-d88c-48da-9eec-29b8a2890529","added_by":"auto","created_at":"2026-03-17 07:38:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9024995,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8861457/v1/abe3f0cc-9adc-41ba-9aa5-9c8ccac7d584.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effect of naturally occurring polymorphisms on HIV-1 integrase structure and dolutegravir binding in subtypes A1 and D","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe integrase (IN) enzyme of Human Immunodeficiency Virus type 1 (HIV-1) plays an important role in HIV-1 replication by catalysing the process of virus integration into the host DNA (Kirchhoff, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Integrase strand transfer inhibitors (INSTIs) were developed to block viral DNA integration and therefore suppress HIV replication (Li et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). INSTIs are categorised into two; (i) first-generation inhibitors which include raltegravir (RAL) and elvitegravir (EVG), (ii) second-generation inhibitors which have superior efficacy and higher genetic barriers to resistance including dolutegravir (DTG), bictegravir (BIC), and cabotegravir (CBT) (Ndashimye et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Currently, DTG is recommended by the World Health Organization for first-line antiretroviral therapy (ART) due to its potency and safety profile (Wagner et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDTG has shown high levels of viral suppression (Bwire et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Namayanja et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, there is increasing evidence for the emergency of DTG resistance among non-subtype B populations (Kamori \u0026amp; Barabona, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Specifically, major INSTI drug resistance mutations such as N115H, G118R, R263K, E138A, G140R among others, have been identified across sub-Saharan Africa and south America (Abdullahi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Chu et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Diaz et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Xiao et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In addition to known major and accessory drug resistance mutations, other polymorphisms in HIV-1 integrase such as G123S, V72I and R127K have been linked to virological failure among patients receiving DTG regimens (Celotti et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeveral studies exploring the effect of HIV-1 integrase polymorphisms on drug binding are mainly based on homology-based methods for three-dimensional structure prediction, molecular docking and interaction analysis with particular focus on the catalytic triad which consists of the DDE motif (D64, D116, and E152) and two magnesium ions (Karim et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). For instance, \u003cem\u003ein silico\u003c/em\u003e analysis of naturally occurring polymorphisms (NOPs) such as T124V which is highly enriched in diverse HIV-1 subtypes, has shown significant impact on the binding of raltegravir (RAL) as compared to DTG (Rogers et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Moreover, polymorphisms that are subtype-specific have been shown to affect the binding affinity of IN and DNA in presence of known INSTI drug resistance mutations (Mikasi et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe structural effect of naturally occurring polymorphisms (NOPs) of HIV-1 integrase on the binding affinity of DTG and other second generation INSTIs has been investigated in HIV-1 subtype C and CRF02-AG in South Africa and Cameroon respectively (Chitongo et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Isaacs et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mikasi et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These studies have shown a significant effect of major INSTI mutation G140S on HIV-1 subtype C integrase and DTG binding affinity (Chitongo et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Similar analyses showed a change in the number and type of interactions induced by accessory INSTI mutation E157Q (Mikasi et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). There has been no significant changes in the structure of HIV-1 IN and binding affinity of second generation INSTIs by NOPs in Subtype C and CRF02-AG in comparison to Subtype B (Isaacs et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThere is limited data on the 3D structure of HIV-1 integrase for subtypes A1 and D, the effect of NOPs on the protein structure as well the binding affinity to different INSTIs. For this study, we set out to investigate the impact of NOPs on the stability of HIV-1 IN for subtypes A1 and D and the effect of NOPs on DTG-HIV-1 integrase binding.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eGeneration of consensus HIV-1 A1 and HIV-1 D integrase sequences\u003c/h2\u003e \u003cp\u003eWe searched the Los Alamos HIV database (Foley et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) for HIV-1 sequences containing integrase sequences for subtypes A1 and D, from ART-na\u0026iuml;ve. The sequences spanned a period of 1986 to 2019 from different countries namely: Sweden, Kenya, Australia, Spain, Uganda, Rwanda, South Africa, Pakistan, and Tanzania. Sequences were analyzed using the Stanford HIV drug resistance algorithm to identify drug resistance mutations and other mutations that are not associated with drug resistance. Sequences without known drug resistance mutations in the integrase region were retained for further analysis. Multiple sequence alignments of the sequences were generated for the subtypes A1 and D using MAFFT sequence alignment tool (Katoh et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), and consensus sequences generated using JALVIEW. To extract the integrase region, we made a pairwise alignment of each consensus sequence and the HXB2 integrase sequence using BLAST and overlapping regions of the consensus sequences were extracted. The nucleotide sequences were translated to obtain corresponding amino acid sequences for subtype A1 and D.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePrediction of the three-dimensional structure and quality assessment\u003c/h3\u003e\n\u003cp\u003eSWISSMODEL (Schwede et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) was used to predict the three-dimensional structures of HIV-1 integrase of subtypes A1and D. The template used to generate these models was the experimental structure of the Wild type of HIV-1 subtype B (PDB ID: 8W34), given the high sequence identity with the consensus sequences of HIV-1 integrase A1 and D. To assess the quality of the generated models, we used inbuilt quality metrics of SWISS MODEL including; the global model quality estimate (QMQE) and the qualitative mean energy analysis (QMEAN). In addition, tools including VERIFY3D, ERRAT and PROCHECK were used to further assess the quality of the predicted three-dimensional structures. We computed the root mean square deviation (RMSD) between the homologous template structure and the predicted structure to assess the deviation in the backbone of the predicted structures.\u003c/p\u003e\n\u003ch3\u003eStructure preparation and energy minimization\u003c/h3\u003e\n\u003cp\u003eThe predicted three-dimensional structures of HIV-1 integrase (IN) were aligned to the 8W34 template using PyMOL (DeLano \u0026amp; others, 2002) to extract magnesium (Mg\u0026sup2;⁺) ions and the ligand, dolutegravir (DTG). The DTG molecule was saved as an individual PDB file, while the predicted HIV-1 integrase structures and Mg\u0026sup2;⁺ ions were saved together as a receptor complex for each subtype. Both ligand and receptor structures were imported into UCSF Chimera (Meng et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), hydrogen ions were added and Gasteiger charges were assigned using the AMBER ff14SB force field. The energy minimization stage involved 100 steps of steepest descent followed by 100 steps of conjugate gradient.\u003c/p\u003e\n\u003ch3\u003eChanges in Gibbs free energy by individual NOPs\u003c/h3\u003e\n\u003cp\u003eTo determine the change induced by introduction of each mutation to the Gibbs free energy of the energy minimized wild-type structure, we uploaded a list of NOPs and the 3D structure of the WT subtype B structure to the mutation scanning matrix (mCSM) server (Pires et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eMolecular docking\u003c/h3\u003e\n\u003cp\u003eMolecular docking was performed using AutoDock Vina (Eberhardt et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) through the UCSF Chimera interface (Meng et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), utilizing a local installation of the docking engine. For each subtype, structures of both the receptor and the ligand were imported into UCSF Chimera, and the docking grid was defined to enclose the catalytic DDE triad and the magnesium ions. Docking parameters were set to generate nine binding modes, with an exhaustiveness value of eight and a maximum energy difference of 3 Kcal/Mol. Binding poses were ranked according to predicted binding affinity, and the pose with the lowest binding energy was selected for further analysis.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eInteraction analysis\u003c/h2\u003e \u003cp\u003eThe Protein-Ligand interaction Profile (PLIP) tool was used to explore the interaction between DTG and the HIV-1 IN of subtypes B, A1 and D. PLIP detects hydrogen bonds, hydrophobic contacts, pi-stacking, pi-cation interactions, salt bridges, water bridges, metal complexes, and halogen bonds. The identified ionic contacts were depicted using USCF chimera and \u003cem\u003eproteinplus\u003c/em\u003e for three-dimensional and two-dimensional visualisations respectively.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eGeneration of consensus sequences and identification of polymorphisms\u003c/h2\u003e \u003cp\u003eConsensus sequences for subtype A1 and D were respectively generated from multiple sequence alignments of 366 and 107 HIV-1 sequences. These were aligned to HIV-1 integrase HXB2 reference (NCBI accession: K03455) to identify NOPs in subtype A1 and D. For subtype A1, we identified 15 NOPs, three of these (D10E, K14R, V31I) belong to the N-terminal domain. Nine (T112V, I113V, G123S, T125A, R127K, G134N, K136Q, D167E and V201I) belong to the catalytic core domain. Three belong to the C-terminal domain (N232D, L234I, S283G). For subtype D, we identified 14 NOPs, two of which belong to the N-terminal domain (D10E, S17N), one which belongs to the loop connecting the NTD to the CCD (M50L), six in the CCD (T112V, I113V, G123S, T125A, R127K, V201I) and five in the CTD (T218I, N232D, L234I, D256E, A265).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStructure analysis and quality assessment\u003c/h2\u003e \u003cp\u003eThe predicted three-dimensional structures of HIV-1 integrase for subtypes A1 and D are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The homologous template identified for the two subtypes was an experimental structure of HIV-1 subtype B integrase in complex with DTG, DNA, MG, and ZN (PDBID: 8W34). The sequence identity between the subtype A1 integrase consensus sequence and the sequence of the homologous template structure was 95.83% with a sequence similarity of 61%. With respect to the sequence of 8W34, we identified twelve mutations, including two in the NTD (K14R and V31I), eight in the CCD (T112V, T124A, T125A, G134N, K136Q, I151V, D167E and V201I) and two in the CTD (V234I and S283G) as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea. Structural quality assessment showed a GMQE score of 0.83 and a QMEANDisCo global score of 0.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05. Ramachandran analysis showed that 90.9% of residues were in favored regions and additional 8.9% of residues were in allowed regions, and ERRAT reported an overall quality factor of 95.73. Structural alignment between the predicted model and template 8W34 showed a root-mean-square deviation (RMSD) of 0.094 \u0026Aring; for all chains and 0.093 \u0026Aring; for chain A (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Subtype D consensus sequence has a sequence identify of 96.18% and a sequence similarity of 61% with the sequence of homologous template structure (8W34). We identified 11 NOPs in the consensus sequence of subtype D relative to the sequence of 8W34. Amongst these, one belongs to the NTD (S17N), one belongs to the loop connecting the NTD to the CCD (M50L), five in the CCD (T112V, T124A, T125A, I151V, V201I) and four in the CTD (T218I, V234I, D256E, A265V) as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea. Structural assessment showed a GMQE score of 0.83 and GMEANDisCo global score of 0.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05. Ramachandran analysis via PROCHECK showed that 90.8% and 8.8% of residues were in favored and allowed regions respectively and ERRAT reported an overall quality factor of 97.43. Alignment of the predicted model and the homologous template structure showed an RMSD of 0.146 \u0026Aring; for all chains and 0.142 \u0026Aring; for chain A (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb.)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eEffect of NOPs on the stability of the wild type of HIV-1 integrase protein\u003c/h2\u003e \u003cp\u003eThe predicted stability changes in energy of the 3D structure of wild-type of subtype B HIV-1 integrase showed destabilizing effects on the 8W34 complex with energy changes ranging between \u0026minus;\u0026thinsp;1.617 and \u0026minus;\u0026thinsp;0.011 Kcal/Mol. Notably, CCD mutation I151V and NTD mutation S17N were the most destabilizing, causing respective energy changes of -1.617 and \u0026minus;\u0026thinsp;1.338 Kcal/Mol. Specific energy changes for other NOPs were \u0026minus;\u0026thinsp;0.878, -0.418, -0.413, -0.379, -0.339, -0.674, -0.61, -0.092, -0.209, -0.504, -0.011, -0.38, -0.316 Kcal/Mol for K14R, V31I, M50L, T112V, T124A, T125A, G134N, K136Q, D167E, V201I, T218L, D256E and A265V respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eMolecular docking and interaction analysis\u003c/h2\u003e \u003cp\u003eThe best pause docked complexes for subtypes A1 and D were analyzed relative to the subtype B homologous structure (8W34) to identify residues involved in the binding of DTG to HIV-1 integrase in subtypes A1 and D. For subtype A1, we observed interactions between DTG and the residues of the integrase catalytic triad (D64, D116, E152) mediated by the two MG ions and direct hydrophobic interaction with Y143. Similarly for 8W34, we observed interactions between DTG, and the residues of the integrase catalytic DDE motif mediated by MG ions in addition to a direct hydrophobic interaction with P145. However, for subtype D, the interactions between DTG and MG ions were only limited to two residues of the catalytic motif (D64 and E152) and there was no interaction with D116 either with DTG or any of the MG ions. Additional polar contacts were observed exclusively for subtype D including N155, H67, T66 and K156. Generally, there were slight changes in the distances between interacting atoms of DTG, MG ions and interacting atoms of the DDE residues (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study investigates the potential impact of naturally occurring polymorphisms (NOPs) on Dolutegravir (DTG) susceptibility in HIV-1 subtypes A1 and D, with a focus on integrase-DTG interactions. Using a high-resolution structural template (PDB: 8W34), our analyses suggest that although these NOPs are not directly linked to drug resistance, they may affect integrase stability and modulate its binding affinity for DTG.\u003c/p\u003e \u003cp\u003eStructural alignment of predicted integrase models for subtypes A1 and D with the subtype B template showed high overall conservation, with RMSD values below 0.15 \u0026Aring;. However, several subtype-specific differences were observed. Notably, both subtypes A1 and D had a short helical element in the N-terminal domain (NTD) absent in subtype B, which may influence the spatial orientation of the catalytic core domain (CCD) or modulate MG-dependent active site conformation. Such alterations could modulate susceptibility when compounded with treatment-induced pressure or additional resistance mutations (Isaacs et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe identified 15 polymorphisms and 14 polymorphisms in subtype A1 and subtype D respectively, distributed across the N-terminal, catalytic core and C-terminal domains of HIV-1 integrase. Previous studies have shown that polymorphisms in key structural regions of the CCD induce changes in conformational dynamics of the binding pocket. For instance, an \u003cem\u003ein-silico\u003c/em\u003e study showed that the interaction of the inner subunit T124 residue with target DNA is lost with the T124A substitution. Moreover, these results suggested that T124A affects the binding of DTG but to a lesser extent as compared to raltegravir (Rogers et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Other CCD polymorphisms, including G134N and K136Q, may similarly affect DTG binding stability in non-B subtypes, however, their specific effects remain to be investigated. In addition, other identified polymorphisms such as G123S and R127K have previously been associated with higher risk of virological failure for individuals on INSTI-based ART in s subtype B dominant population (Celotti et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUsing the mCSM server, we evaluated the thermodynamic consequences of introducing identified NOPs into the WT subtype B integrase. All tested mutations showed a destabilizing effect on the global protein structure, with the most destabilizing substitutions, I151V (A1) and S17N (D). Though not located within the active site, their positions suggest they could exert long-range allosteric effects. Previous studies on other INSTI-resistance mutations (e.g., L74M) support the idea that allosteric destabilization may contribute to compromised drug binding or integration efficiency (Djojosugito et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMolecular docking studies had successful DTG binding in all subtypes, with preserved interactions with the catalytic triad D64, D116, and E152 via MG coordination. However, subtype-specific deviations were observed. Subtype A1 retained all canonical interactions but shifted peripheral hydrophobic contact from P145 (in subtype B) to Y143. This may suggest altered ligand orientation or pocket accommodation, which could affect DTG binding. In contrast, subtype D lacked interaction with D116, which is part of the catalytic triad. Moreover, subtype D gained polar interactions with H67, K156, N155, and T66 residues not typically involved in canonical DTG binding. These additional contacts may indicate a less tightly constrained binding mode, potentially lowering the binding specificity of DTG.\u003c/p\u003e \u003cp\u003eFrom a public health perspective, our findings support sequencing of HIV-1 integrase as part of DTG resistance surveillance programs, especially in East Africa where subtypes A1 and D predominate (Bbosa et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Ndashimye et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). While our structural models are built upon a high-resolution crystal structure and validated by quality metrics, our study remains an \u003cem\u003ein-silico\u003c/em\u003e prediction. Functional validation using integration efficiency assays, viral replication capacity assessments, and long-term treatment outcome data are necessary to confirm the clinical relevance of identified NOPs. Future studies should incorporate population-level sequence diversity to explore the full landscape of NOP-mediated effects.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides structural and thermodynamic assessment of how NOPs in HIV-1 subtypes A1 and D affect integrase stability and DTG binding. While none of the identified polymorphisms completely disrupted DTG interaction, several introduced destabilizing effects and altered binding patterns that may contribute to resistance development. In addition, these results highlight the importance of subtype-specific investigations to inform HIV-1 drug resistance mechanisms in diverse global populations.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInteractions between DTG and HIV-1 integrase for subtypes B, A1 and D.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubtype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePolar contacts (distance)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eIonic contacts (distance)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMG-A-303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMG-A-304\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP145 (3.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD64 (2.05), D116 (2.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eD64 (2.01), E152 (2.38), E152 (2.45)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eY143 (3.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD64 (2.13), D116 (2.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eD64 (2.43), E152 (2.59), E152 (2.63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN155 (3.93), K156 (3.76), H67, T66 (3.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eD64 (2.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eD64 (2.62), E152 (2.80), E152 (2.82)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe numbers indicated in parenthesis are interaction distances given in angstroms (\u0026Aring;). Abbreviations: Proline (P), Aspartic acid (D), Glutamic acid (E), Tyrosine (Y), Asparagine (N), Lysine (K), Histidine (H), and Threonine (T) and magnesium ions (Mg\u0026sup2;⁺; MG-A-303 and MG-A-304).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA.S. and D.J. conceptualized and designed the study. D.J., D.S., and D.P.K. supervised the study. A.S., D.S., and D.J. developed the methodology. A.S. curated the data, obtained the required software, performed data analysis, and visualization. N.B. guided on the interpretation of analysis results. D.P.K., D.J., and D.S. acquired the funding and provided resources. A.S. and N.B. wrote the original manuscript. A.S., N.B., D.S., D.P.K., and D.J. reviewed the manuscript. All authors approved the final version of the manuscript. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Institutes of Health (NIH) Common Fund, through the OD/Office of Strategic Coordination (OSC) and the Fogarty International Center (FIC) [NIH award number U2RTW010672], its contents are solely the responsibility of the authors and do not necessarily represent the official views of the supporting office. Additional funding was provided by the Bill and Melinda Gates Foundation [Investment ID INV-031335], the UK Medical Research Council (MRC) and UK Department for International Development (DFID) that is under the MRC/DFID Concordat agreement and is also part of the European \u0026amp; Developing Countries Clinical Trials Partnership (EDCTP2) programme sup- ported by the European Union.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sequence data analysed in this study are available in the Los Alamos National Laboratory (LANL) HIV Sequence Database. The curated sequence datasets and the predicted three-dimensional structural models of HIV-1 subtype A1 and D integrase generated in this study were deposited in Zenodo and can be accessed at the following DOI: https://doi.org/10.5281/zenodo.18605359. \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbdullahi A, Kida IM, Maina UA, Ibrahim AH, Mshelia J, Wisso H, Adamu A, Onyemata JE, Edun M, Yusuph H, Aliyu SH, Charurat M, Abimiku A, Abeler-Dorner L, Fraser C, Bonsall D, Kemp SA, Gupta RK. 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Antimicrob Agents Chemother. 2023;67(5). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/aac.01386-22\u003c/span\u003e\u003cspan address=\"10.1128/aac.01386-22\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"virology-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"virj","sideBox":"Learn more about [Virology Journal](http://virologyj.biomedcentral.com/)","snPcode":"12985","submissionUrl":"https://submission.nature.com/new-submission/12985/3","title":"Virology Journal","twitterHandle":"@VirologyJ","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"HIV-1 integrase, dolutegravir, naturally occurring polymorphisms, molecular docking, drug resistance","lastPublishedDoi":"10.21203/rs.3.rs-8861457/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8861457/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eDolutegravir (DTG), a second-generation integrase strand transfer inhibitor (INSTI), is recommended for first-line antiretroviral therapy due to its high potency and genetic barrier to resistance. However, emerging evidence of reduced DTG efficacy in absence of major DTG resistance mutations among non-subtype B populations requires investigation into alternative resistance mechanisms. This study investigated the impact of naturally occurring polymorphisms (NOPs) on integrase stability and DTG binding in HIV-1 subtypes A1 and D, which are predominant in East Africa.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe analyzed sequences from ART-na\u0026iuml;ve individuals derived from the Los Alamos HIV sequence database for subtypes A1 and D. Consensus integrase sequences for subtypes A1 and D were generated, and stability effects of identified NOPs were assessed using the mutation scanning matrix (mCSM). Three-dimensional structures of HIV-1 A1 and D integrase were predicted using SWISS-MODEL. Molecular docking of HIV-1 integrase and DTG was performed with AutoDock Vina, and interaction profiles were analyzed using Protein-Ligand Interaction Profile (PLIP).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe identified 15 NOPs in subtype A1 and 14 NOPs in subtype D consensus sequences relative to the HIV reference genome (HXB2). All NOPs showed destabilizing effects (ΔΔG: -1.617 to -0.011 kcal/mol), with I151V and S17N having the highest destabilization effect. Docking analyses showed preserved DTG coordination with the D64 and E152 residues across subtypes. However, subtype A1 showed an altered hydrophobic contact (Y143 vs P145) while subtype D lacked interaction with D116 and showed additional polar contacts with H67, K156, N155, and T66.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe NOPs identified in subtypes A1 and D do not completely disrupt DTG binding but induce thermodynamic destabilization, structural and interaction changes that may influence integrase stability and consequently drug susceptibility. These findings highlight the importance of subtype-specific structural analyses in exploring alternative drug resistance mechanisms.\u003c/p\u003e","manuscriptTitle":"Effect of naturally occurring polymorphisms on HIV-1 integrase structure and dolutegravir binding in subtypes A1 and D","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-28 01:40:03","doi":"10.21203/rs.3.rs-8861457/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-28T09:23:25+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-28T08:54:24+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-26T18:12:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"232402870082200309056883784365893192388","date":"2026-04-11T22:23:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"105416920898573577908142365496347304016","date":"2026-04-07T13:09:01+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-25T14:58:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"238981925467267289960527637790128254896","date":"2026-02-24T15:46:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"217488032826577525363091017593422127108","date":"2026-02-24T12:24:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"125838328582337145781134772991334751332","date":"2026-02-23T07:45:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-22T12:11:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-14T09:57:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-13T15:34:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Virology Journal","date":"2026-02-12T11:14:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"virology-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"virj","sideBox":"Learn more about [Virology Journal](http://virologyj.biomedcentral.com/)","snPcode":"12985","submissionUrl":"https://submission.nature.com/new-submission/12985/3","title":"Virology Journal","twitterHandle":"@VirologyJ","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6f0ef841-97f0-4fa3-bbcb-f82ef4f73290","owner":[],"postedDate":"February 28th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-04-28T09:39:59+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-28 01:40:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8861457","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8861457","identity":"rs-8861457","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}