Computational studies of the interaction between the HIV-1 integrase tetramer and the cofactor LEDGF/p75: Insights from molecular dynamics simulations and the informational spectrum method

A crystal structure of the integrase binding domain (IBD) of the lens epithelium-derived growth factor (LEDGF/p75) in complex with the dimer of the HIV-1 integrase (IN) catalytic core domain (CCD) provides useful information that might help in the understanding of essential protein-protein contacts in HIV-1. However, mutagenic studies indicated that interactions between the full-length proteins were more extensive than the contacts observed in the co-crystal structure of the isolated domains. On the other hand, the biochemical characterization of the interaction between full-length IN and LEDGF/p75 has recently proved that LEDGF/p75 promotes IN tetramerization with two LEDGF/p75 IBD molecules bound to the IN tetramer. This experimental evidence suggests that to obtain a complete structural description of the interactions between the two proteins, the full-length tetrameric structure of IN should be considered. Our aim was to obtain a detailed picture of HIV-1 IN interactions with cellular co-factors that was of general interest, particularly for the development of small molecule IN inhibitors, which mimic the IBD of LEDGF/p75. To this end, we performed bioinformatics analyses to identify protein sequence domains involved in long-range recognition. Subsequently, we applied molecular dynamics techniques to investigate the detailed interactions between the complete tetrameric form of IN and two molecules of the IBD of LEDGF/p75. Our dynamic picture is in agreement with experimental data and, thereby, provides new details of the IN-LEDGF/p75 interaction

Annotation Of The Functional Impact Of Coding Genetic Variants

Summary. Coding genetic variants can have profound effects on protein function. Computational tools for the prediction of these effects are used to complement and guide experimental biological studies. Phylogenetic analyses that determine the evolutionary relationship among related sequences are commonly used to distinguish between functionally significant and insignificant gene variations. Here, we have reviewed applications of the non-alignment sequence analyses method for phylogenetic analyses, ISTREE. Furthermore, we assessed how an unsupervised ISTREE-d3 method based on the universal d3 measure responds to this task compared to supervised and semi-supervised ISTREE methods that were previously used in two studies. The findings presented here suggest that ISTREE-d3 can efficiently substitute for the corresponding supervised models, given that it is more suitable for automatic applications. In conclusion, the ISTREE-d3 method has a broad biological relevance and represents a promising approach in functional assessment of coding gene variations

Natural autoantibodies in healthy neonatals recognizing a peptide derived from the second conserved region of HIV-1 gp120

Background/Aim. High sera reactivity with a peptide derived from human immunodeficiency virus HIV-I envelope protein gp120, NMI., correlate with non-progressive HIV-1 infection and also may have protective role in breast and prostate cancer. We also detected a low NTM1 reactive antibodies titer in healthy HIV negative sera and showed that antibody levels can be significantly increased with vigorous physical activity. However, the immune system seems to be unresponsive or tolerant to this peptide, implicating that the NTM1 sequence encompasses or overlaps a certain innate immune epitope. The aim of this study was to present evidences that NTM1 binding antibodies are components of innate immune humoral response, by confirming their presence in sera of newborn babies. For this purpose we collected a set of 225 innate antigen sequences reported in the literature and screened it for candidate antigens with the highest sequence and spectral similarity to NTM1 derived from HIV-1 gp120. Methods. Sera from 18 newborns were tested using ELISA, with peptide NTM1. Sequences from innate antigen database were aligned by an EMBOSS Water bioinformatics tool. Results. We identified NTM1 reactive antibodies in sera of HIV negative newborn babies. Further, in order to identify which of already known innate antigens are the most similar to NTM1 peptide we screened innate immune antigen sequence database collected from the literature. This screening revealed that the most similar sequence are ribonucleoproteins RO60, in addition to previously identified N-terminus of vasoactive intestinal peptide. Conclusion. The results of this study confirm the hypothesis that NTM1 recognizing antibodies are a part of humoral innate immune response. Further, computational similarity screening revealed a vasoactive intestinal peptide and RO60 as the most similar sequences and the strongest candidate antigens. In the light of the presented results, it is appealing that testing blood reactivity at birth, with specific innate antigens, particularly a vasoactive intestinal peptide, can reveal the potential to develop- or boost protective immune response in breast and prostate cancer and HIV infection later in life

Integrated relational database of human protein-protein interactions

Protein-protein interactions’ data are stored in various publicly available databases of different types and formats. In this work, a new database for protein-protein interactions is created by integrating data from multiple existing databases. This task is not trivial since different databases use distinct gene or protein identifiers for protein annotation. Additionally, they use different methods to determine interaction scores, and the interactions are obtained through diverse experimental or predictive methods. As a result, two databases may store different data about the same interaction. To integrate data from various databases, namely BioGRID, STRING, HIPPIE, IntAct, and Reactome, into a single PPI database, the following process is undertaken. Initially, data is downloaded from these databases in the MITAB format, encompassing all pertinent interaction information such as protein identifiers, publication sources and other. In order to obtain unique protein identifiers in all PPIs in the database, the UniProt ID mapping tool was used to determine UniProt IDs. Next, since scoring systems differ among databases, for every interaction a new score is calculated using MISCORE tool as an additional metrics unique for all the PPIs in the database. The resulting database contains tens of millions of human PPIs from five different sources.Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 202

New age for alignment-free methods for sequence analyses

Progress in a wide range of fields ranging from population genetics to precision medicine may be attributed to availability of big biological data. Alignment-free sequence comparison is the methodology of choice in data-intensive applications given that it is significantly faster and requires less resources compared to traditional sequence comparison based on pairwise or multiple sequence alignment. The symbiosis of alignment-free methods with machine learning is a paradigm of new age in bioinformatics, as it ensures the much needed boost to quicken the complex predictions on large datasets, particularly of molecules with low sequence identity. In this talk, I will present two stories in which I will describe approaches to predict functional consequences of gene variants and imperfect tandem repeats in protein sequences.Special Edition of Book of Abstract

Combined in silico and experimental approach to identify the peptide mimetic of the nanobody that stabilize functional conformational state of the beta2 adrenergic receptor (β2AR)

Stabilization of specific G-protein coupled receptor (GPCR) conformation is achieved by ligand binding to orthosteric or allosteric sites on a GPCRs. A crucial unresolved issue in GPCRs activation/signaling is the role of receptor structural conformations in G protein/effector protein selection. One of the possible approaches to get comprehensive depiction of GPCRs activation dynamics are molecular simulations and recently described nanobody-derived intrabodies. Monomeric single-domain antibody (nanobody) from the Camelid family was found to allosterically bind to and stabilizes distinct conformational states of the β2AR. By applying informational spectrum method (ISM), a virtual spectroscopy method for investigation of the protein-protein interactions, we have designed peptide mimetic of the nanobody related to the β2AR (nanobody derived peptide, NDP). Further, interaction between NDP and the ligand-bound β2AR active conformation have been studied by protein-peptide docking, molecular dynamics simulations and metadynamics calculations of free energy binding. Finally, the affinity of selected NDPs towards agonist-activated β2AR was also studied by microscale thermophoresis (MST) and by bioluminescence resonance energy transfer (BRET) based β-arrestin 2 recruitment assay. MST data predicted micromolar range interaction of selected NDPs with the β2AR, while the preliminary β-arrestin 2 recruitment results suggest prospective further modification and optimization of NDPs toward effective modulators of the β2AR.Special Edition of Book of Abstract

Identification of hemagglutinin structural domain and polymorphisms which may modulate swine H1N1 interactions with human receptor

Background: The novel A/H1N1 influenza virus, which recently emerged in North America is most closely related to North American H1N1/N2 swine viruses. Until the beginning of 2009, North American swine H1N1/N2 viruses have only sporadically infected humans as dead-end hosts. In 2009 the A/H1N1 virus acquired the capacity to spread efficiently by human to human transmission. The novel A/H1N1 influenza virus has struck thousands of people in more than 70 countries and killed more than 140, representing a public health emergency of international concern. Here we have studied properties of hemagglutinin of A/H1N1 which may modulate virus/receptor interaction. Results: Analyses by ISM bioinformatics platform of the HA1 protein of North American swine H1N1/N2 viruses and the new A/H1N1 showed that both groups of viruses differed in conserved characteristics that reflect a distinct propensity of these viruses to undergo a specific interaction with swine or human host proteins or receptors. Swine H1N1/N2 viruses that sporadically infected humans featured both the swine and the human interaction pattern. Substitutions F71S, T128S, E302K, M314L in HA1 of swine H1N1 viruses from North America are identified as critical for the human interaction pattern of A/H1N1 and residues D94, D196 and D274 are predicted to be hotspots for polymorphisms which could increase infectivity of A/H1N1 virus. At least one of these residues has already emerged in the A/H1N1 isolates from Spain, Italy and USA. The domain 286-326 was identified to be involved in virus/receptor interaction. Conclusion: Our results (i) contribute to better understanding of the origin of the novel A/H1N1 influenza virus, (ii) provide a tool for monitoring its molecular evolution (iii) predicts hotspots associated with enhanced infectivity in humans and (iv) identify therapeutic and diagnostic targets for prevention and treatment of A/H1N1 infection

Evolution of 2014/15 H3N2 Influenza Viruses Circulating in US: Consequences for Vaccine Effectiveness and Possible New Pandemic

A key factor in the effectiveness of the seasonal influenza vaccine is its immunological compatibility with the circulating viruses during the season. Here we propose a new bioinformatics approach for analysis of influenza viruses which could be used as an efficient tool for selection of vaccine viruses, assessment of the effectiveness of seasonal influenza vaccines, and prediction of the epidemic/pandemic potential of novel influenza viruses

Computational design and characterization of nanobody-derived peptides that stabilize the active conformation of the β2-adrenergic receptor (β2-AR)

This study aimed to design and functionally characterize peptide mimetics of the nanobody (Nb) related to the β2-adrenergic receptor (β2-AR) (nanobody-derived peptide, NDP). We postulated that the computationally derived and optimized complementarity-determining region 3 (CDR3) of Nb is sufficient for its interaction with receptor. Sequence-related Nb-families preferring the agonist-bound active conformation of β2-AR were analysed using the informational spectrum method (ISM) and β2-AR:NDP complexes studied using protein-peptide docking and molecular dynamics (MD) simulations in conjunction with metadynamics calculations of free energy binding. The selected NDP of Nb71, designated P3, was 17 amino acids long and included CDR3. Metadynamics calculations yielded a binding free energy for the β2-AR:P3 complex of ΔG = (−7.23 ± 0.04) kcal/mol, or a Kd of (7.9 ± 0.5) μM, for T = 310 K. In vitro circular dichroism (CD) spectropolarimetry and microscale thermophoresis (MST) data provided additional evidence for P3 interaction with agonist-activated β2-AR, which displayed ~10-fold higher affinity for P3 than the unstimulated receptor (MST-derived EC50 of 3.57 µM vs. 58.22 µM), while its ability to inhibit the agonist-induced interaction of β2-AR with β-arrestin 2 was less evident. In summary, theoretical and experimental evidence indicated that P3 preferentially binds agonist-activated β2-AR. © 2019, The Author(s)

Feature-Based Classification of Amino Acid Substitutions outside Conserved Functional Protein Domains

There are more than 500 amino acid substitutions in each human genome, and bioinformatics tools irreplaceably contribute to determination of their functional effects. We have developed feature-based algorithm for the detection of mutations outside conserved functional domains (CFDs) and compared its classification efficacy with the most commonly used phylogeny-based tools, PolyPhen-2 and SIFT. The new algorithm is based on the informational spectrum method (ISM), a feature-based technique, and statistical analysis. Our dataset contained neutral polymorphisms and mutations associated with myeloid malignancies from epigenetic regulators ASXL1, DNMT3A, EZH2, and TET2. PolyPhen-2 and SIFT had significantly lower accuracies in predicting the effects of amino acid substitutions outside CFDs than expected, with especially low sensitivity. On the other hand, only ISM algorithm showed statistically significant classification of these sequences. It outperformed PolyPhen-2 and SIFT by 15% and 13%, respectively. These results suggest that feature-based methods, like ISM, are more suitable for the classification of amino acid substitutions outside CFDs than phylogeny-based tools