Biology subjects

Sahoo, A. K.

Publications and source records attributed to Sahoo, A. K..

17 recordsLinked to original sources

bioRxiv2025

sCentInDB: A database of essential oil chemical profiles of Indian medicinal plants

Essential oils are complex mixtures of volatile compounds produced by aromatic plants. Due to their odor and therapeutic properties, essential oils are used in personal care, food flavoring and pharmaceutical industries. As a high-value and low-volume organic product, optimizing plant yield and modifying composition by leveraging knowledge on chemical profiles of essential oils can lead to enhanced bioproducts. To this end, we present sCentInDB, a manually curated DataBase of Essential oil Chemical profiles of Medicinal plants of India, which has been built based on information in published literature. sCentInDB is a FAIR-compliant database which compiles information on 554 Indian medicinal plants at the plant part level, encompassing 2170 essential oil profiles, 3420 chemicals, 471 plant-part-therapeutic use associations, 120 plant-part-odor associations, and 218 plant-part-color associations. For the documented essential oils, sCentInDB also compiles extensive metadata including sample location, isolation and analysis methods. Subsequently, an extensive analysis of the chemical space of essential oils documented in sCentInDB was performed. By constructing a chemical similarity network, the chemical space was found to be structurally diverse with terpenoids distributed across the network. Moreover, a comparison of the scaffold diversity in sCentInDB was performed against three other aroma libraries using cyclic system retrieval curves. Altogether, sCentInDB will serve as a valuable resource for researchers working on plant volatiles and employing genetic engineering to enhance oil yield and composition. Further, sCentInDB will aid in establishment of quality standards for essential oils and provide vital insights for therapeutic and perfumery applications. sCentInDB is accessible at https://cb.imsc.res.in/scentindb/.

pharmacology and toxicology↗

bioRxiv2024

Computational prediction of cyclotides from Viola odorata as potential inhibitors against the neuraminidase of Streptococcus pneumoniae

Cyclotides are naturally occurring peptides characterized by a cyclic cystine knot, which provides them with exceptional structural stability. In addition to their stability, cyclotides exhibit diverse therapeutic activities including antimicrobial, antiviral and antitumor activities, making them promising candidates in drug discovery. However, computational studies aimed at identifying cyclotide-based inhibitors for infectious diseases remain limited. To this end, we conducted a virtual screening of cyclotides from an Indian medicinal plant Viola odorata to identify potential inhibitors against a bacterial pathogen causing respiratory infections. We compiled a library of 93 cyclotides by retrieving their structures from public domain or predicting them using the AlphaFold server. We then docked these cyclotides against the neuraminidase protein of Streptococcus pneumoniae and analyzed the interacting residues and binding energies to identify top five potential inhibitors namely, kalata S, kalata B1, cycloviolacin O15, vodo L12, and cycloviolacin O36. Thereafter, we performed molecular dynamics simulations of the protein-cyclotide complexes, and observed that the cyclotides remained stable within the complex. Altogether, this study is the first computational effort to identify potential cyclotide inhibitors against bacterial pathogen causing respiratory diseases, which can be further pursued for experimental validation to develop novel therapeutic agents for respiratory infections.

pharmacology and toxicology↗

bioRxiv2024

Network-based investigation of petroleum hydrocarbons-induced ecotoxicological effects and their risk assessment

Petroleum hydrocarbons (PHs) are compounds composed mostly of carbon and hydrogen, originating from crude oil and its derivatives. PHs are primarily released into the environment through the diffusion of oils, resulting from anthropogenic activities like transportation and offshore drilling, and accidental incidents such as oil spills. Once released, these PHs can persist in different ecosystems and cause long-term detrimental ecological impacts. While the hazards associated with such PH contaminations are often assessed by the concentrations of total petroleum hydrocarbons in the environment, studies focusing on the risks associated with individual PHs are limited. Here, we leveraged different network-based frameworks to explore and understand the adverse ecological effects associated with PH exposure. First, we systematically curated a list of 320 PHs from published reports. Next, we integrated biological endpoint data from toxicological databases, and constructed a stressor-centric adverse outcome pathway (AOP) network linking 75 PHs with 177 ecotoxicologically-relevant high confidence AOPs within AOP-Wiki. Further, we relied on stressor-species network constructions, based on reported toxicity concentrations and bioconcentration factors data for 80 PHs and 28 PHs, respectively, and found that crustaceans are documented to be affected by many of these PHs. Finally, we utilized the aquatic toxicity data within ECOTOX to construct species sensitivity distributions for polycyclic aromatic hydrocarbons (PAHs) prioritized by the US EPA, and derived their corresponding hazard concentrations (HC05) that protect 95% of species in the aquatic ecosystem. Overall, this study highlights the importance of using network-based approaches and risk assessment methods to understand the PH-induced toxicities effectively.

pharmacology and toxicology↗

bioRxiv2024

Leveraging integrative toxicogenomic approach towards development of stressor-centric adverse outcome pathway networks for plastic additives

Plastics are widespread pollutants found in atmospheric, terrestrial and aquatic ecosystems due to their extensive usage and environmental persistence. Plastic additives, that are utilized to achieve specific functionality in plastics, leach into the environment upon plastic degradation and pose considerable risk to ecological and human health. Limited knowledge concerning the presence of plastic additives throughout the plastic life cycle has hindered their effective regulation, thereby posing risks to product safety. In this study, we leveraged the adverse outcome pathway (AOP) framework to understand the mechanisms underlying plastic additives-induced toxicities. We first identified an exhaustive list of 6470 plastic additives from chemicals documented to be found in plastics. Next, we leveraged heterogenous toxicogenomics and biological endpoints data from five exposome-relevant resources, and identified associations between 1287 plastic additives and 322 complete and high quality AOPs within AOP-Wiki. Based on these plastic additive-AOP associations, we constructed a stressor-centric AOP network, wherein the stressors are categorized into 10 priority use sectors and AOPs are linked to 27 disease categories. We visualized the plastic additives-AOP network for each of the 1287 plastic additives and made them available in a dedicated website: https://cb.imsc.res.in/saopadditives/. Finally, we showed the utility of the constructed plastic additives-AOP network by identifying 28 highly relevant AOPs associated with benzo[a]pyrene, and thereafter, explored the associated toxicity pathways leading to respiratory and gastrointestinal system diseases in humans and developmental disorders in aquatic species. Overall, the constructed plastic additives-AOP network will enable regulatory risk assessment of plastic additives, thereby contributing towards a toxic-free circular economy for plastics.

pharmacology and toxicology↗

bioRxiv2023

An integrative data-centric approach to derivation and characterization of an adverse outcome pathway network for cadmium-induced toxicity

Cadmium is a prominent toxic heavy metal that contaminates both terrestrial and aquatic environments. Owing to its high biological half-life and low excretion rates, cadmium causes a variety of adverse biological outcomes. Adverse outcome pathway (AOP) networks were envisioned to systematically capture toxicological information to enable risk assessment and chemical regulation. Here, we leveraged AOP-Wiki and integrated heterogeneous data from four other exposome-relevant resources to build the first AOP network relevant for inorganic cadmium-induced toxicity. From AOP-Wiki, we filtered 309 high confidence AOPs, identified 312 key events (KEs) associated with inorganic cadmium, and thereafter, curated 30 cadmium relevant AOPs (cadmium-AOPs), using a data-centric approach. By constructing the undirected AOP network, we identified a large connected component of 18 cadmium-AOPs. Further, we analyzed the directed network of 59 KEs and 82 key event relationships (KERs) in the largest component using graph-theoretic approaches. Subsequently, we mined published literature using artificial intelligence-based tools to provide auxiliary evidence of cadmium association for all KEs in the largest component. Finally, we performed case studies to verify the rationality of cadmium-induced toxicity in humans and aquatic species. Overall, cadmium-AOP network constructed in this study will aid ongoing research in systems toxicology and chemical exposome.

pharmacology and toxicology↗

bioRxiv2023

First complete genome characterization of an Indian pigeon pox virus directly from a clinical sample

Avian pox disease is a highly contagious infection caused by pox virus and has serious consequences on avian species with regards to economic and conservation aspects. This viral genus named as Avipox virus (APV) that infects nearly 300 bird species and lack of enough complete genome information creates hindrance to infer this virus biology. Thus in this study, we have revealed the first complete genome of an Indian pigeon pox virus that belongs to the genus APV followed by comparative genomics analysis. The entire genome of present isolate (PPV/Pur-Od-4b/01/Ind) having 280058 bp nucleotide sequences with the GC content 29.51%. The unique feature of this complete genome revealed the presence of 270 open reading frames (ORFs) circumscribed by inverted terminal repeats (ITRs) of 4,689 bp at each end and lack of recombination events. The concatenated amino acid phylogenetic tree deciphered the present isolate closely related with Feral Pigeon pox virus derived from Africa. The molecular markers, such as microsatellites were ubiquitously distributed throughout the genome and more prevalent within the functional genes.

evolutionary biology↗

bioRxiv2023

ViCEKb: Vitiligo-linked Chemical Exposome Knowledgebase

Vitiligo is a complex disease wherein the environmental factors, in conjuction with the underlying genetic predispositions, trigger the autoimmune destruction of melanocytes, ultimately leading to depigmented patches on the skin. Apart from being susceptible to other autoimmune disorders, the affected patients may face social stigmatization leading to a decreased quality in life. While genetic factors have been extensively studied, the knowledge on environmental triggers remains sparse and less understood. Therefore, a comprehensive understanding of the environemental triggers will not only explain the complex etiology of the disease, it will also enable the prioritization of potential toxic chemicals in human chemcical exposome. Towards this, we present the first comprehensive knowledgbase of vitiligo triggering chemicals compiled from published literature namely, Vitiligo-linked Chemical Exposome Knowledgbase (ViCEKb). ViCEKb involved an extensive and systematic manual effort in curation of published literature and subsequent compilation of 113 unique chemical triggers of vitiligo. ViCEKb standardises various chemical information, and categorizes the chemicals based on their evidences and sources of exposure. Importantly, ViCEKb contains a wide range of metrics necessary for different toxicological evaluations. Moreover, our extensive cheminformatics-based analysis of the ViCEKb chemical space highlighted its diversity and uniqueness in comparison to other skin specific chemical regulatory lists. We also observed that ViCEKb chemicals are present in various consumer products and are not regulated. Additionally, a transcriptomics based analysis of ViCEKb chemical perturbations in skin cell samples highlighted the commonality in their linked biological processes. Overall, we present the first comprehensive effort in compilation and exploration of various chemical triggers of vitiligo. We believe such a resource will enable in deciphering the complex etiology of vitiligo and aid in the characterization of human chemical exposome. ViCEKb is freely available for academic research at: https://cb.imsc.res.in/vicekb.

bioinformatics↗

bioRxiv2023

Cheminformatics analysis of multi-target structure-activity landscape of environmental chemicals binding to human endocrine receptors

In human exposome, environmental chemicals can target, and disrupt different endocrine axes, ultimately leading to several endocrine disorders. Such chemicals, termed endocrine disrupting chemicals (EDCs), can promiscuously bind to different endocrine receptors and lead to varying biological endpoints. Thus, understanding the complexity in molecule-receptor binding of environmental chemicals can aid in the development of robust toxicity predictors. Towards this, the ToxCast project has generated the largest resource on the chemical-receptor activity data for environmental chemicals that were screened across various endocrine receptors. However, the heterogeneity in the multi-target structure-activity landscape of such chemicals is not yet explored. In this study, we systematically curated the chemicals targeting 8 human endocrine receptors, their activity values and biological endpoints from the ToxCast chemical library. We employed dual-activity difference and triple-activity difference maps to identify single-, dual-, and triple-target cliffs across different target combinations. We annotated the identified activity cliffs through matched molecular pair (MMP) based approach, and observed that a small fraction of activity cliffs form MMPs. Further, we structurally classified the activity cliffs and observed that R-group cliffs form the highest fraction among the cliffs identified in various target combinations. Finally, we leveraged the mechanism of action (MOA) annotations to analyze structure-mechanism relationships, identified strong MOA-cliffs and weak MOA-cliffs, for each of the 8 endocrine receptors. Overall, insights from this first study analyzing the structure-activity landscape of environmental chemicals targeting multiple human endocrine receptors, will likely contribute towards the development of better toxicity prediction models for characterizing the human chemical exposome.

pharmacology and toxicology↗

bioRxiv2023

Analysis of structure-activity and structure-mechanism relationships among thyroid stimulating hormone receptor binding chemicals by leveraging ToxCast library

Thyroid stimulating hormone receptor (TSHR) is an integral part of the hypothalamic-pituitary-thyroid axis. Notably, dysregulation in TSHR activation in humans can lead to adverse effects such as Graves disease, hypothyroidism and Hashimotos disease. Moreover, animal studies have shown that binding of endocrine disrupting chemicals (EDCs) with TSHR can lead to developmental toxicity. Several such chemicals have also been screened for their adverse physiological effects in human cell lines through various high-throughput assays under the ToxCast project. The vast resource of data generated through ToxCast has enabled the development of different toxicity predictors, but they can be limited in their predictive ability due to the heterogeneity in structure-activity relationships among chemicals. In an attempt to explore this heterogeneity, we systematically investigated structure-activity and structure-mechanism relationships among the TSHR binding chemicals from ToxCast. By employing structure-activity similarity (SAS) map, we identified 79 activity cliffs among 509 chemicals in the TSHR agonist dataset and 69 activity cliffs among 650 chemicals in the TSHR antagonist dataset. Further, by using the matched molecular pair (MMP) approach, we find that the resultant activity cliffs (MMP-cliffs) are a subset of activity cliffs identified via the SAS map approach. Moreover, by leveraging ToxCast mechanism of action (MOA) annotations for chemicals common to both TSHR agonist and antagonist datasets, we identified 3 chemical pairs as Strong MOA-cliffs and 19 chemical pairs as Weak MOA-cliffs. In conclusion, the insights from this systematic analysis of the structure-activity as well as the structure-mechanism relationships of TSHR binding chemicals are likely to inform ongoing efforts towards development of better predictive toxicity models for characterizing the chemical exposome.

pharmacology and toxicology↗

bioRxiv2023

T9GPred: A Comprehensive Computational Tool for the Prediction of Type 9 Secretion System, Gliding Motility and the Associated Secreted Proteins

Type 9 secretion system (T9SS) is one of the least characterized secretion systems exclusively found in the Bacteroidetes phylum which comprise various environmental and economically relevant bacteria. While T9SS plays a central role in bacterial movement termed gliding motility, survival and pathogenicity, there is an unmet need for a comprehensive tool that predicts T9SS, gliding motility and proteins secreted via T9SS. In this study, we develop such a computational tool, Type 9 secretion system and Gliding motility Prediction (T9GPred). To build this tool, we manually curated published experimental evidence and identified mandatory components for T9SS and gliding motility prediction. We also compiled experimentally characterized proteins secreted via T9SS and determined the presence of three unique types of C-terminal domain signals, and these insights were leveraged to predict proteins secreted via T9SS. Notably, using recently published experimental evidence, we show that T9GPred has high predictive power. Thus, we used T9GPred to predict the presence of T9SS, gliding motility and associated secreted proteins across 693 completely sequenced Bacteroidetes strains. T9GPred predicted 402 strains to have T9SS, of which 327 strains are also predicted to exhibit gliding motility. Further, T9GPred also predicted putative secreted proteins for the 402 strains. In a nutshell, T9GPred is a novel computational tool for systems-level prediction of T9SS and streamlining future experimentation. The source code of the computational tool is available in our GitHub repository: https://github.com/asamallab/T9GPred. The tool and its predicted results are compiled in a web server available at: https://cb.imsc.res.in/t9gpred/.

bioinformatics↗

bioRxiv2022

EPEK: creation and analysis of an Ectopic Pregnancy Expression Knowledgebase

Ectopic pregnancy (EP) is one of the leading causes of maternal mortality, where the fertilized embryo grows outside of the uterus. Recent experiments on mice have uncovered the importance of genetic factors in the transport of embryos inside the uterus. In the past, efforts have been made to identify possible gene or protein markers in EP in humans through multiple expression studies. Although there exist comprehensive gene resources for other maternal health disorders, there is no specific resource that compiles the genes associated with EP from such expression studies. Here, we address that knowledge gap by creating a computational resource, Ectopic Pregnancy Expression Knowledgebase (EPEK), that involves manual compilation and curation of expression profiles of EP in humans from published articles. In EPEK, we compiled information on 314 differentially expressed genes, 17 metabolites, and 3 SNPs associated with EP. Computational analyses on the gene set from EPEK showed the implication of cellular signaling processes in EP. We also identified possible exosome markers that could be clinically relevant in the diagnosis of EP. In a nutshell, EPEK is the first and only dedicated resource on the expression profile of EP in humans. EPEK is accessible at https://cb.imsc.res.in/epek.

bioinformatics↗

bioRxiv2022

Identification of activity cliffs in structure-activity landscape of androgen receptor binding chemicals

Androgen mimicking environmental chemicals can bind to Androgen receptor (AR) and can cause severe effects on the reproductive health of males. Predicting such endocrine disrupting chemicals (EDCs) in the human exposome is vital for improving current chemical regulations. To this end, QSAR models have been developed to predict androgen binders. However, a continuous structure-activity relationship (SAR) wherein chemicals with similar structure have similar activity does not always hold. Activity landscape analysis can help map the structure-activity landscape and identify unique features such as activity cliffs. Here we performed a systematic investigation of the chemical diversity along with the global and local structure-activity landscape of a curated list of 144 AR binding chemicals. Specifically, we clustered the AR binding chemicals and visualized the associated chemical space. Thereafter, consensus diversity plot was used to assess the global diversity of the chemical space. Subsequently, the structure-activity landscape was investigated using SAS maps which capture the activity difference and structural similarity among the AR binders. This analysis led to a subset of 41 AR binding chemicals forming 86 activity cliffs, of which 14 are activity cliff generators. Additionally, SALI scores were computed for all pairs of AR binding chemicals and the SALI heatmap was also used to evaluate the activity cliffs identified using SAS map. Finally, we provide a classification of the 86 activity cliffs into six categories using structural information of chemicals at different levels. Overall, this investigation reveals the heterogeneous nature of the structure-activity landscape of AR binding chemicals and provides insights which will be crucial in preventing false prediction of chemicals as androgen binders and developing predictive computational toxicity models in the future.

pharmacology and toxicology↗

bioRxiv2022

Effects of Neurofeedback training on performance in laboratory tasks: A systematic review

Neurofeedback procedures are attracting increasing attention in the neuroscience community. Based on the principle that participants, through suitable feedback, may learn to affect specific aspects of their brain activity, neurofeedback has been applied to basic research, translational, and clinical science alike. A large segment of the extant empirical research as well as review articles have focused on the extent to which neurofeedback interventions affect mental health outcomes, cognitive capacity, aging, and other complex behaviors. Another segment has aimed to characterize the extent to which neurofeedback affects the targeted neural processes. At this time, there is no current systematic review of the effects of neurofeedback on healthy participants performance in experimental tasks. Such a review is relevant in this rapidly evolving field because changes in experimental task performance are traditionally considered a hallmark of changing neurocognitive processes, often established in neurotypical individuals. This systematic review addresses this gap in the literature using the PRISMA method, building on earlier reviews on the same topic. Empirical studies using EEG or fMRI to alter brain processes linked to established, well-defined cognitive and affective laboratory tasks were reviewed. Substantial variability was found regarding the nature of the control for placebo effects, the implementation of the feedback, and the neural targets of feedback. Importantly, only a minority of the studies reported statistically meaningful effects of neurofeedback on performance in cognitive and affective tasks. Examining effect sizes and p-values in a subset of studies found no evidence for reporting bias, while also not finding systematic relations between study characteristics such as sample size or experimental control on the one hand and efficacy on the other. Implications for future work are discussed.

neuroscience↗

bioRxiv2022

Scaffold and structural diversity of the secondary metabolite space of medicinal fungi

Medicinal fungi including mushrooms have well documented therapeutic uses. The MeFSAT database provides a curated library of more than 1800 secondary metabolites produced by medicinal fungi for potential use in high throughput screening (HTS) studies. In this study, we perform a cheminformatics based investigation of the scaffold and structural diversity of the secondary metabolite space of medicinal fungi, and moreover, perform a detailed comparison with approved drugs, other natural product libraries and semi-synthetic libraries. We find that the secondary metabolite space of MeFSAT has similar or higher scaffold diversity in comparison to other natural product libraries analysed here. Notably, 94% of the scaffolds in the secondary metabolite space of MeFSAT are not present in the approved drugs. Further, we find that the secondary metabolites of medicinal fungi, on the one hand are structurally far from the approved drugs, while on the other hand are close in terms of molecular properties to approved drugs. Lastly, chemical space visualization using dimensionality reduction methods showed that the secondary metabolite space has minimal overlap with the approved drug space. In a nutshell, our results underscore that the secondary metabolite space of medicinal fungi is a valuable resource for identifying potential lead molecules for natural product based drug discovery.

pharmacology and toxicology↗

bioRxiv2022

IMPPAT 2.0: an enhanced and expanded phytochemical atlas of Indian medicinal plants

Compilation, curation, digitization and exploration of the phytochemical space of Indian medicinal plants can expedite ongoing efforts toward natural product and traditional knowledge based drug discovery. To this end, we present IMPPAT 2.0, an enhanced and expanded database, compiling manually curated information on 4010 Indian medicinal plants, 17967 phytochemicals, 1095 therapeutic uses and 1133 traditional Indian medicinal formulations. Notably, IMPPAT 2.0 compiles associations at the level of plant parts, and provides a FAIR compliant non-redundant in silico stereo-aware library of 17967 phytochemicals from Indian medicinal plants. The phytochemical library has been annotated with several useful properties to enable easier exploration of the chemical space. We also filtered a subset of 1335 drug-like phytochemicals of which majority have no similarity to existing approved drugs. Using cheminformatics, we have characterized the molecular complexity and molecular scaffold based structural diversity of the phytochemical space of Indian medicinal plants, and performed a comparative analysis with other chemical libraries. Altogether, IMPPAT is the largest phytochemical atlas of Indian medicinal plants which is accessible at: https://cb.imsc.res.in/imppat/.

pharmacology and toxicology↗

bioRxiv2020

MeFSAT: A curated natural product database specific to secondary metabolites of medicinal fungi

Fungi are a rich source of secondary metabolites which constitutes a valuable and diverse chemical space of natural products. Medicinal fungi have been used in traditional medicine to treat human ailments for centuries. To date, there is no devoted resource on secondary metabolites and therapeutic uses of medicinal fungi. Such a dedicated resource compiling dispersed information on medicinal fungi across published literature will facilitate ongoing efforts towards natural product based drug discovery. Here, we present the first comprehensive manually curated database on Medicinal Fungi Secondary metabolites And Therapeutics (MeFSAT) that compiles information on 184 medicinal fungi, 1830 secondary metabolites and 149 therapeutics uses. Importantly, MeFSAT contains a non-redundant in silico natural product library of 1830 secondary metabolites along with information on their chemical structures, computed physicochemical properties, drug-likeness properties, predicted ADMET properties, molecular descriptors and predicted human target proteins. By comparing the physicochemical properties of secondary metabolites in MeFSAT with other small molecules collections, we find that fungal secondary metabolites have high stereochemical complexity and shape complexity similar to other natural product libraries. Based on multiple scoring schemes, we have filtered a subset of 228 drug-like secondary metabolites in MeFSAT database. By constructing and analyzing chemical similarity networks, we show that the chemical space of secondary metabolites in MeFSAT is highly diverse. The compiled information in MeFSAT database is openly accessible at: https://cb.imsc.res.in/mefsat/.

bioinformatics↗

bioRxiv2020

Concerted interactions between multiple gp41 trimers and the target cell lipidome may be required for HIV-1 entry

The HIV-1 envelope glycoprotein gp41 mediates the fusion between viral and host cell membranes leading to virus entry and target cell infection. Despite years of research, important aspects of this process such as the number of gp41 trimers involved and how they orchestrate the rearrangement of the lipids in the apposed membranes along the fusion pathway remain obscure. To elucidate these molecular underpinnings, we performed coarse-grained molecular dynamics simulations of HIV-1 virions pinned to the CD4 T cell membrane by different numbers of gp41 trimers. We built realistic cell and viral membranes by mimicking their respective lipid compositions. We found that a single gp41 was inadequate for mediating fusion. Lipid mixing between membranes, indicating the onset of fusion, was efficient when 3 or more gp41 trimers pinned the membranes. The gp41 trimers interacted strongly with many different lipids in the host cell membrane, triggering lipid configurational rearrangements, exchange, and mixing. Simpler membranes, comprising fewer lipid types, displayed strong resistance to fusion, revealing the crucial role of the lipidomes in HIV-1 entry. Performing simulations at different temperatures, we estimated the free energy barrier to lipid mixing, and hence membrane stalk formation, with 4 tethering gp41 trimers to be ~6.2 kcal/mol, a >4-fold reduction over estimates without gp41. Together, these findings present molecular-level, quantitative insights into the early stages of gp41-mediated HIV-1 entry. Preventing the requisite gp41 molecules from tethering the membranes or altering membrane lipid compositions may be potential intervention strategies. SIGNIFICANCEInteractions between viral envelope proteins and host cell surface receptors leading to HIV-1 entry are well studied, however the role of membrane lipids remains obscure, although entry hinges on lipid mixing and the fusion of viral and cell membranes. We performed detailed simulations of HIV-1 and target cell membranes tethered by viral gp41 trimeric proteins to elucidate the proteo-lipidic contributions to viral entry. We found that the cooperative effects of multiple gp41 trimers and natural lipidomes of the membranes facilitate membrane fusion. The functional domains of gp41 altered local lipid concentrations, reduced membrane repulsions, and facilitated inter-membrane lipid mixing. These molecular-level insights offer a glimpse of the cryptic mechanisms underlying HIV-1 entry and suggest new interventions to combat HIV-1 infection.

biophysics↗