Common variable immunodeficiency in two kindreds with heterogeneous phenotypes caused by novel heterozygous NFKB1 mutations

NFKB1 haploinsufficiengcy was first described in 2015 in three families with common variable immunodeficiency (CVID), presenting heterogeneously with symptoms of increased infectious susceptibility, skin lesions, malignant lymphoproliferation and autoimmunity. The described mutations all led to a rapid degradation of the mutant protein, resulting in a p50 haploinsufficient state. Since then, more than 50 other mutations have been reported, located throughout different domains of NFKB1 with the majority situated in the N-terminal Rel homology domain (RHD). The clinical spectrum has also expanded with possible disease manifestations in almost any organ system. In silico prediction tools are often used to estimate the pathogenicity of NFKB1 variants but to prove causality between disease and genetic findings, further downstream functional validation is required. In this report, we studied 2 families with CVID and two novel variants in NFKB1 (c.1638-2A>G and c.787G>C). Both mutations affected mRNA and/or protein expression of NFKB1 and resulted in excessive NLRP3 inflammasome activation in patient macrophages and upregulated interferon stimulated gene expression. Protein-protein interaction analysis demonstrated a loss of interaction with NFKB1 interaction partners for the p.V263L mutation. In conclusion, we proved pathogenicity of two novel variants in NFKB1 in two families with CVID characterized by variable and incomplete penetrance.Peer reviewe

Common variable immunodeficiency in two kindreds with heterogeneous phenotypes caused by novel heterozygous NFKB1 mutations

NFKB1 haploinsufficiengcy was first described in 2015 in three families with common variable immunodeficiency (CVID), presenting heterogeneously with symptoms of increased infectious susceptibility, skin lesions, malignant lymphoproliferation and autoimmunity. The described mutations all led to a rapid degradation of the mutant protein, resulting in a p50 haploinsufficient state. Since then, more than 50 other mutations have been reported, located throughout different domains of NFKB1 with the majority situated in the N-terminal Rel homology domain (RHD). The clinical spectrum has also expanded with possible disease manifestations in almost any organ system. In silico prediction tools are often used to estimate the pathogenicity of NFKB1 variants but to prove causality between disease and genetic findings, further downstream functional validation is required. In this report, we studied 2 families with CVID and two novel variants in NFKB1 (c.1638-2A>G and c.787G>C). Both mutations affected mRNA and/or protein expression of NFKB1 and resulted in excessive NLRP3 inflammasome activation in patient macrophages and upregulated interferon stimulated gene expression. Protein-protein interaction analysis demonstrated a loss of interaction with NFKB1 interaction partners for the p.V263L mutation. In conclusion, we proved pathogenicity of two novel variants in NFKB1 in two families with CVID characterized by variable and incomplete penetrance.Peer reviewe

Antigenic Peptide Prediction From E6 and E7 Oncoproteins of HPV Types 16 and 18 for Therapeutic Vaccine Design Using Immunoinformatics and MD Simulation Analysis

Human papillomavirus (HPV) induced cervical cancer is the second most common cause of death, after breast cancer, in females. Three prophylactic vaccines by Merck Sharp & Dohme (MSD) and GlaxoSmithKline (GSK) have been confirmed to prevent high-risk HPV strains but these vaccines have been shown to be effective only in girls who have not been exposed to HPV previously. The constitutively expressed HPV oncoproteins E6 and E7 are usually used as target antigens for HPV therapeutic vaccines. These early (E) proteins are involved, for example, in maintaining the malignant phenotype of the cells. In this study, we predicted antigenic peptides of HPV types 16 and 18, encoded by E6 and E7 genes, using an immunoinformatics approach. To further evaluate the immunogenic potential of the predicted peptides, we studied their ability to bind to class I major histocompatibility complex (MHC-I) molecules in a computational docking study that was supported by molecular dynamics (MD) simulations and estimation of the free energies of binding of the peptides at the MHC-I binding cleft. Some of the predicted peptides exhibited comparable binding free energies and/or pattern of binding to experimentally verified MHC-I-binding epitopes that we used as references in MD simulations. Such peptides with good predicted affinity may serve as candidate epitopes for the development of therapeutic HPV peptide vaccines

A multimethod approach in the development of a novel XNA ligase

This presentation depicted an initial approach on the development of ligases that join modified genetic information systems that are chemically developed and different from DNA and RNA (named ‘xeno nucleic acids’ or ‘XNA’). These enzymes are necessary to push the field of synthetic biology forward since gene sized XNAs cannot be obtained by chemical synthesis and available polymerases. Therefore, they are essential for the establishment of organisms with artificial information systems. During the past decade, ‘In vitro’ evolution methodologies have been used to modify or improve the activity of a wide variety of enzymes. Computational design shortens the path for obtaining an efficient XNA ligase. Via a multi-method approach we aim to induce a class switching activity of the Paramecium Bursaria Chlorella virus (PBCV-1) DNA ligase. HNA (1,5-anhydrohexitol nucleic acid) is chosen to be the alternative XNA substrate. HNA has an A-form like shape and has a wider diameter than DNA/RNA. PBCV-1 ligase was chosen as the wild-type enzyme (WT) in which specific amino acids will be mutate. The small and flexible nature of the enzyme and the proven initial activity against 2’OMe RNA make this a viable candidate for in vitro evolution experiments. To infer conservation, the Jensen Shannon Divergence algorithm (JSD) is used since it includes the features of several existing conservation determining methods. A suitable Multiple Sequence Alignment (MSA) was designed through a combination of NCBI/BLAST homology search, Clustal Omega alignment software, ElimDupes and Jalview. Next to its use in JSD, the MSA was used in MISTIC (Mutual Information Server to Infer Coevolution) to infer coevolution apart from the conservation analysis feature. After the conservation and the coevolution analysis, free energy calculations of the WT complex with DNA using the crystal structure, were implemented to analyze free energy changes upon mutagenesis. Together, these three approaches identified, crucial (regions of) amino acids to be randomized by mutagenesis. Building on these results, physics-based modelling methods will be performed to search for low free- energy states and to optimize the residues in the active site considering the presence of the HNA substrate. Since there is no crystal structure, the design of the PBCV-1 ligase in complex with a nicked HNA infers the docking of nicked HNA in the chlorella virus DNA ligase. HADDOCK was selected for this purpose since it has a good record in protein-DNA docking and allows introduction of HNA oligomers. A model complex was obtained by docking, which will be optimized by molecular dynamics simulations. Selected mutants will be characterized by different methods (e.g. NMR and kinetic experiments using a stopped flow instruments). Extensive molecular dynamics simulations along the reaction path of the strand joining step will be performed for best mutant ligases. Computed energy profiles will be compared to the experimental physicochemical data. In the experimental part, the lately developed technique of CST (Compartmentalized Self-Tagging) (Pinheiro V., et al., Curr Protoc Nucleic Acid Chem. 2014, 57) will be used to test the computational hypothesis.status: publishe

Rational Design of XNA Processing Enzymes

Xenobiotic Nucleic Acids (XNA) are synthetic analogues of natural nucleic acids (DNA and RNA). They are developed for applications such as therapeutics, diagnostics and alternative carriers of genetic information. The main goal of the PhD research is to develop a 'toolbox' with enzymes for XNA in molecular biology that is based on rational insights. In chapter 2, currently available computer-driven algorithms were explored for their potential use to alter the affinity of DNA-binding enzymes for DNA towards XNA polymers. The Chlorella virus (ChVLig) DNA ligase was used as a test model for this. Due to the low uniformity between the results, these were categorized and compared within each cluster of algorithms to make a rational initial selection of potential mutants. After determining the optimal conditions to express wild-type ligase and its variants, selected mutants were screened for their activity to join (ligate) broken XNA fragments with different hybrid setups. Although no activity was observed for XNA-modified fragments, the generated results emphasized the general importance of the structure of the enzyme rather than its amino acid sequence. Based on these results, it was concluded that not only the amino acid composition of the enzyme but also the general structure and dynamics of the enzyme-substrate complex are critical to be included in rational protein redesign experiments. To study this, a reliable model for the desired XNA complex is necessary. In chapter 3, a new computer-aided method was developed to generate reliable models for nucleic acids that are centrally bound in toroidal proteins. This approach was applied again to ChVLig, the test model also used in Chapter 2. The in silico results indicated that a stable enzyme complex with XNA could only be obtained if the central cavity in the torus was enlarged with an extra amino acid. The in vitro results confirmed that the 189insG mutant of ChVLig clearly shows the intended enzyme activity. This 189insG mutant from ChVLig is an important new tool for synthetic genetics that enables the synthesis of longer XNA gene fragments, complementing the 'toolbox' with existing XNA polymerases. In chapter 4, the method developed in chapter 3 was generalized into a publicly accessible software platform where a model can be generated for XNA-bound nucleic acid binding proteins starting from a PDB structure available in complex with DNA or RNA. In addition, the concept was further expanded to perform mutation analyzes in silico to optimize XNA binding and obtain the orthogonality required for use in xenobiology (PREDICT). Along with a new nucleic acid fragment screening test, the initial results obtained for ligases, endonuclease and polymerases provide a solid groundwork for the rational development of XNA-processing enzymes.status: publishe

In silico structural elucidation of RNA-dependent RNA polymerase towards the identification of potential Crimean-Congo Hemorrhagic Fever Virus inhibitors

The Crimean-Congo Hemorrhagic Fever virus (CCHFV) is a segmented negative single-stranded RNA virus (-ssRNA) which causes severe hemorrhagic fever in humans with a mortality rate of ~50%. To date, no vaccine has been approved. Treatment is limited to supportive care with few investigational drugs in practice. Previous studies have identified viral RNA dependent RNA Polymerase (RdRp) as a potential drug target due to its significant role in viral replication and transcription. Since no crystal structure is available yet, we report the structural elucidation of CCHFV-RdRp by in-depth homology modeling. Even with low sequence identity, the generated model suggests a similar overall structure as previously reported RdRps. More specifically, the model suggests the presence of structural/functional conserved RdRp motifs for polymerase function, the configuration of uniform spatial arrangement of core RdRp sub-domains, and predicted positively charged entry/exit tunnels, as seen in sNSV polymerases. Extensive pharmacophore modeling based on per-residue energy contribution with investigational drugs allowed the concise mapping of pharmacophoric features and identified potential hits. The combination of pharmacophoric features with interaction energy analysis revealed functionally important residues in the conserved motifs together with in silico predicted common inhibitory binding modes with highly potent reference compounds.status: publishe

Perspectives towards antiviral drug discovery against Ebola virus

Ebola virus disease (EVD), caused by Ebola viruses, resulted in more than 11 500 deaths according to a recent 2018 WHO report. With mortality rates up to 90%, it is nowadays one of the most deadly infectious diseases. However, no Food and Drug Administration-approved Ebola drugs or vaccines are available yet with the mainstay of therapy being supportive care. The high fatality rate and absence of effective treatment or vaccination make Ebola virus a category-A biothreat pathogen. Fortunately, a series of investigational countermeasures have been developed to control and prevent this global threat. This review summarizes the recent therapeutic advances and ongoing research progress from research and development to clinical trials in the development of small-molecule antiviral drugs, small-interference RNA molecules, phosphorodiamidate morpholino oligomers, full-length monoclonal antibodies, and vaccines. Moreover, difficulties are highlighted in the search for effective countermeasures against EVD with additional focus on the interplay between available in silico prediction methods and their evidenced potential in antiviral drug discovery.status: publishe

In silico Structure-based Identification of Novel Acetylcholinesterase Inhibitors Against Alzheimer's Disease

OBJECTIVE AND BACKGROUND: Inhibition of acetylcholinesterase (AChE) has gained much importance since the discovery of the involvement of peripheral anionic site as an allosteric regulator of AChE. Characterized by the formation of β-amyloid plaques, Alzheimer's disease (AD) is currently one of the leading causes of death across the world. Progression in this neurodegenerative disorder causes deficit in the cholinergic activity that leads towards cognitive decline. Therapeutic interventions in AD are largely focused upon AChE inhibitors designed essentially to prevent the loss of cholinergic function. The multifactorial AD pathology calls for Multitarget-directed ligands (MTDLs) to follow up on various components of the disease. Considering this approach, other related AD targets were also selected. Structure-based virtual screening was relied upon for the identification of lead compounds with anti-AD effect. METHOD: Several chemoinformatics approaches were used in this study, reporting four multi-target inhibitors: MCULE-7149246649-0-1, MCULE-6730554226-0-4, MCULE-1176268617-0-6 and MCULE-8592892575-0-1 with high binding energies that indicate better AChE inhibitory activity. Additional in-silico analysis hypothesized the abundant presence of aromatic interactions to be pivotal for interaction of selected compounds to the acetyl-cholinesterase. Additionally, we presented an alternative approach to determine protein-ligand stability by calculating the Gibbs-free energy change over time. Furthermore, this allows to rank potential hits for further in-vitro testing. RESULTS AND CONCLUSION: With no predicted indication of adverse effects on humans, this study unravels four active multi-target inhibitors against AChE with promising affinities and good ADMET profile for the potential use in AD treatment.status: publishe

In silico Structure-based Identification of Novel Acetylcholinesterase Inhibitors Against Alzheimer's Disease

OBJECTIVE AND BACKGROUND: Inhibition of acetylcholinesterase (AChE) has gained much importance since the discovery of the involvement of peripheral anionic site as an allosteric regulator of AChE. Characterized by the formation of β-amyloid plaques, Alzheimer's disease (AD) is currently one of the leading causes of death across the world. Progression in this neurodegenerative disorder causes deficit in the cholinergic activity that leads towards cognitive decline. Therapeutic interventions in AD are largely focused upon AChE inhibitors designed essentially to prevent the loss of cholinergic function. The multifactorial AD pathology calls for Multitarget-directed ligands (MTDLs) to follow up on various components of the disease. Considering this approach, other related AD targets were also selected. Structure-based virtual screening was relied upon for the identification of lead compounds with anti-AD effect. METHOD: Several chemoinformatics approaches were used in this study, reporting four multi-target inhibitors: MCULE-7149246649-0-1, MCULE-6730554226-0-4, MCULE-1176268617-0-6 and MCULE-8592892575-0-1 with high binding energies that indicate better AChE inhibitory activity. Additional in-silico analysis hypothesized the abundant presence of aromatic interactions to be pivotal for interaction of selected compounds to the acetyl-cholinesterase. Additionally, we presented an alternative approach to determine protein-ligand stability by calculating the Gibbs-free energy change over time. Furthermore, this allows to rank potential hits for further in-vitro testing. RESULTS AND CONCLUSION: With no predicted indication of adverse effects on humans, this study unravels four active multi-target inhibitors against AChE with promising affinities and good ADMET profile for the potential use in AD treatment.status: publishe