Integrating population and single-cell variations in vaccine responses identifies a naturally adjuvanted human immune setpoint.

Multimodal single-cell profiling methods can capture immune cell variations unfolding over time at the molecular, cellular, and population levels. Transforming these data into biological insights remains challenging. Here, we introduce a framework to integrate variations at the human population and single-cell levels in vaccination responses. Comparing responses following AS03-adjuvanted versus unadjuvanted influenza vaccines with CITE-seq revealed AS03-specific early (day 1) response phenotypes, including a B cell signature of elevated germinal center competition. A correlated network of cell-type-specific transcriptional states defined the baseline immune status associated with high antibody responders to the unadjuvanted vaccine. Certain innate subsets in the network appeared "naturally adjuvanted," with transcriptional states resembling those induced uniquely by AS03-adjuvanted vaccination. Consistently, CD14+ monocytes from high responders at baseline had elevated phospho-signaling responses to lipopolysaccharide stimulation. Our findings link baseline immune setpoints to early vaccine responses, with positive implications for adjuvant development and immune response engineering.

Multiscale integration of human and single-cell variations reveals unadjuvanted vaccine high responders are naturally adjuvanted.

Advances in multimodal single cell analysis can empower high-resolution dissection of human vaccination responses. The resulting data capture multiple layers of biological variations, including molecular and cellular states, vaccine formulations, inter- and intra-subject differences, and responses unfolding over time. Transforming such data into biological insight remains a major challenge. Here we present a systematic framework applied to multimodal single cell data obtained before and after influenza vaccination without adjuvants or pandemic H5N1 vaccination with the AS03 adjuvant. Our approach pinpoints responses shared across or unique to specific cell types and identifies adjuvant specific signatures, including pro-survival transcriptional states in B lymphocytes that emerged one day after vaccination. We also reveal that high antibody responders to the unadjuvanted vaccine have a distinct baseline involving a rewired network of cell type specific transcriptional states. Remarkably, the status of certain innate immune cells in this network in high responders of the unadjuvanted vaccine appear "naturally adjuvanted": they resemble phenotypes induced early in the same cells only by vaccination with AS03. Furthermore, these cell subsets have elevated frequency in the blood at baseline and increased cell-intrinsic phospho-signaling responses after LPS stimulation ex vivo in high compared to low responders. Our findings identify how variation in the status of multiple immune cell types at baseline may drive robust differences in innate and adaptive responses to vaccination and thus open new avenues for vaccine development and immune response engineering in humans.

Multiomics integration of 22 immune-mediated monogenic diseases reveals an emergent axis of human immune health.

Monogenic diseases are often studied in isolation due to their rarity. Here we utilize multiomics to assess 22 monogenic immune-mediated conditions with age- and sex-matched healthy controls. Despite clearly detectable disease-specific and "pan-disease" signatures, individuals possess stable personal immune states over time. Temporally stable differences among subjects tend to dominate over differences attributable to disease conditions or medication use. Unsupervised principal variation analysis of personal immune states and machine learning classification distinguishing between healthy controls and patients converge to a metric of immune health (IHM). The IHM discriminates healthy from multiple polygenic autoimmune and inflammatory disease states in independent cohorts, marks healthy aging, and is a pre-vaccination predictor of antibody responses to influenza vaccination in the elderly. We identified easy-to-measure circulating protein biomarker surrogates of the IHM that capture immune health variations beyond age. Our work provides a conceptual framework and biomarkers for defining and measuring human immune health.

Bioactivation of Isoxazole-Containing Bromodomain and Extra-Terminal Domain (BET) Inhibitors.

The 3,5-dimethylisoxazole motif has become a useful and popular acetyl-lysine mimic employed in isoxazole-containing bromodomain and extra-terminal (BET) inhibitors but may introduce the potential for bioactivations into toxic reactive metabolites. As a test, we coupled deep neural models for quinone formation, metabolite structures, and biomolecule reactivity to predict bioactivation pathways for 32 BET inhibitors and validate the bioactivation of select inhibitors experimentally. Based on model predictions, inhibitors were more likely to undergo bioactivation than reported non-bioactivated molecules containing isoxazoles. The model outputs varied with substituents indicating the ability to scale their impact on bioactivation. We selected OXFBD02, OXFBD04, and I-BET151 for more in-depth analysis. OXFBD's bioactivations were evenly split between traditional quinones and novel extended quinone-methides involving the isoxazole yet strongly favored the latter quinones. Subsequent experimental studies confirmed the formation of both types of quinones for OXFBD molecules, yet traditional quinones were the dominant reactive metabolites. Modeled I-BET151 bioactivations led to extended quinone-methides, which were not verified experimentally. The differences in observed and predicted bioactivations reflected the need to improve overall bioactivation scaling. Nevertheless, our coupled modeling approach predicted BET inhibitor bioactivations including novel extended quinone methides, and we experimentally verified those pathways highlighting potential concerns for toxicity in the development of these new drug leads.

Structure, function and dynamics in acyl carrier proteins.

Carrier proteins are four-helix bundles that covalently hold metabolites and secondary metabolites, such as fatty acids, polyketides and non-ribosomal peptides. These proteins mediate the production of many pharmaceutically important compounds including antibiotics and anticancer agents. Acyl carrier proteins (ACPs) can be found as part of a multi-domain polypeptide (Type I ACPs), or as part of a multiprotein complex (Type II). Here, the main focus is on ACP2 and ACP3, domains from the type I trans-AT polyketide synthase MmpA, which is a core component of the biosynthetic pathway of the antibiotic mupirocin. During molecular dynamics simulations of their apo, holo and acyl forms ACP2 and ACP3 both form a substrate-binding surface-groove. The substrates bound to this surface-groove have polar groups on their acyl chain exposed and forming hydrogen bonds with the solvent. Bulky hydrophobic residues in the GXDS motif common to all ACPs, and similar residues on helix III, appear to prohibit the formation of a deep tunnel in type I ACPs and type II ACPs from polyketide synthases. In contrast, the equivalent positions in ACPs from type II fatty acid synthases, which do form a deep solvent-excluded substrate-binding tunnel, have the small residue alanine. During simulation, ACP3 with mutations I61A L36A W44L forms a deep tunnel that can fully bury a saturated substrate in the core of the ACP, in contrast to the surface groove of the wild type ACP3. Similarly, in the ACP from E. coli fatty acid synthase, a type II ACP, mutations can change ligand binding from being inside a deep tunnel to being in a surface groove, thus demonstrating how changing a few residues can modify the possibilities for ligand binding.

Structural modelling and molecular dynamics of a multi-stress responsive WRKY TF-DNA complex towards elucidating its role in stress signalling mechanisms in chickpea.

Chickpea is a premier food legume crop with high nutritional quality and attains prime importance in the current era of 795 million people being undernourished worldwide. Chickpea production encounters setbacks due to various stresses and understanding the role of key transcription factors (TFs) involved in multiple stresses becomes inevitable. We have recently identified a multi-stress responsive WRKY TF in chickpea. The present study was conducted to predict the structure of WRKY TF to identify the DNA-interacting residues and decipher DNA-protein interactions. Comparative modelling approach produced 3D model of the WRKY TF with good stereochemistry, local/global quality and further revealed W19, R20, K21, and Y22 motifs within a vicinity of 5 Å to the DNA amongst R18, G23, Q24, K25, Y36, Y37, R38 and K47 and these positions were equivalent to the 2LEX WRKY domain of Arabidopsis. Molecular simulations analysis of reference protein -PDB ID 2LEX, along with Car-WRKY TF modelled structure with the DNA coordinates derived from PDB ID 2LEX and docked using HADDOCK were executed. Root Mean Square (RMS) Deviation and RMS Fluctuation values yielded consistently stable trajectories over 50 ns simulation. Strengthening the obtained results, neither radius of gyration, distance and total energy showed any signs of DNA-WRKY complex falling apart nor any significant dissociation event over 50 ns run. Therefore, the study provides first insights into the structural properties of multi-stress responsive WRKY TF-DNA complex in chickpea, enabling genome wide identification of TF binding sites and thereby deciphers their gene regulatory networks.

In Silico Structural, Virtual Screening and Docking Studies of Human Cytochrome P450 2A7 Protein.

Among CYPs, CYP2A sub-family is well known for its function to metabolise xenobiotics. CYP2A includes three members: CYP2A6, CYP2A7 and CYP2A13. Of these three proteins, structure and function of CYP2A6 and CYP2A13 are widely studied, whereas very little study has been carried out on CYP2A7. In the initial in vitro studies on CYP2A7, full protein in its active form could not be expressed. The exact structure and function of CYP2A7 is still not revealed. However, up-regulation of CYP2A7 has been reported in malignant oesophageal cells and colon cancer cells. In the present study, we generated the structure of CYP2A7 protein. The modelled proteins were validated and subjected to molecular docking analyses. The energy and RMSD calculations demonstrated that the protein is highly conserved in nature, i.e., the protein is not much flexible. Here the ligand molecules of NCI Diversity Set II from the ZINC database against the active site of the CYP2A7 protein were screened. Five compounds that possess good inhibitory activity against CYP2A7 active site were identified. The top ranking molecule (ZINC01572309) has a minimum energy score of -12.0 kcal/Mol. This compound is thus a good starting point for further development of strong inhibitors. Our in silico approach could help in better structural and functional analysis of CYP2A7. Apart from structural description of CYP2A7, elaboration of binding sites for inhibitors provides us with an opportunity to utilise binding pockets in targeted inactivation of this protein for further research.

Highlights of the 1st Student Symposium of the ISCB RSG UK.

This short report summarises the scientific content and activities of a student-led event, the 1st student symposium by the UK Regional Student Group of the International Society for Computational Biology. The event took place on the 8th of October 2014.

In-silico structural, virtual screening and docking studies of Human Cytochrome P450 2A7 protein.

Among CYPs, CYP2A sub-family is well known for its function to metabolize xenobiotics. CYP2A includes three members: CYP2A6, CYP2A7 and CYP2A13. Of these three proteins, structure and function of CYP2A6 and CYP2A13 are widely studied whereas very little study has been carried out on CYP2A7. In the initial in vitro studies on CYP2A7, full protein in its active form could not be expressed. The exact structure and function of CYP2A7 is still not revealed. However, up-regulation of CYP2A7 has been reported in malignant oesophageal cells and colon cancer cells. In the present study, we generated the structure of CYP2A7 protein. The modelled proteins were validated and subjected to molecular docking analyses. The energy and RMSD calculations demonstrated that the protein is highly conserved in nature i.e. the protein is not much flexible. Here the ligand molecules of NCI Diversity Set II from the ZINC database against the active site of the CYP2A7 protein were screened. Five compounds that possess good inhibitory activity against CYP2A7 active site were identified. The top ranking molecule (ZINC01572309) has a minimum energy score of -12.0 Kcal/Mol. This compound is thus a good starting point for further development of strong inhibitors. Our in silico approach could help in better structural and functional analysis of CYP2A7. Apart from structural description of CYP2A7, elaboration of binding sites for inhibitors provides us with an opportunity to utilize binding pockets in targeted inactivation of this protein for further research.

3D structure generation, virtual screening and docking of human Ras-associated binding (Rab3A) protein involved in tumourigenesis.

Rab3A is expressed predominantly in brain and synaptic vesicles. Rab3A is involved specifically in tethering and docking of synaptic vesicles prior to fusion which is a critical step in regulated release of neurotransmitters. The precise function of Rab3A is still not known. However, up-regulation of Rab3A has been reported in malignant neuroendocrine and breast cancer cells. In the present study, the structure of Rab3A protein was generated using MODELLER 9v8 software. The modeled protein structure was validated and subjected to molecular docking analyses. Docking with GTP was carried out on the binding site of Rab3A using GOLD software. The Rab3A-GTP complex has best GOLD fitness value of 77.73. Ligplot shows hydrogen bondings (S16, S17, V18, G19, K20, T21, S22, S31, T33, A35, S38, T39 and G65) and hydrophobic interacting residues (F25, F32, P34, F36, V37, D62 and A64) with the GTP ligands in the binding site of Rab3A protein. Here, the ligand molecules of NCI diversity set II from the ZINC database against the active site of the Rab3A protein were screened. For this purpose, the incremental construction algorithm of GLIDE and the genetic algorithm of GOLD were used. Docking results were analyzed for top ranking compounds using a consensus scoring function of X-Score to calculate the binding affinity and Ligplot was used to measure protein-ligand interactions. Five compounds which possess good inhibitory activity and may act as potential high affinity inhibitors against Rab3A active site were identified. The top ranking molecule (ZINC13152284) has a Glide score of -6.65 kcal/mol, X-Score of -3.02 kcal/mol and GOLD score of 64.54 with 03 hydrogen bonds and 09 hydrophobic contacts. This compound is thus a good starting point for further development of strong inhibitors.

Molecular dynamic simulation and inhibitor prediction of cysteine synthase structured model as a potential drug target for trichomoniasis.

In our presented research, we made an attempt to predict the 3D model for cysteine synthase (A2GMG5_TRIVA) using homology-modeling approaches. To investigate deeper into the predicted structure, we further performed a molecular dynamics simulation for 10 ns and calculated several supporting analysis for structural properties such as RMSF, radius of gyration, and the total energy calculation to support the predicted structured model of cysteine synthase. The present findings led us to conclude that the proposed model is stereochemically stable. The overall PROCHECK G factor for the homology-modeled structure was -0.04. On the basis of the virtual screening for cysteine synthase against the NCI subset II molecule, we present the molecule 1-N, 4-N-bis [3-(1H-benzimidazol-2-yl) phenyl] benzene-1,4-dicarboxamide (ZINC01690699) having the minimum energy score (-13.0 Kcal/Mol) and a log P value of 6 as a potential inhibitory molecule used to inhibit the growth of T. vaginalis infection.

A conserved motif flags acyl carrier proteins for ß-branching in polyketide synthesis.

Type I polyketide synthases often use programmed ß-branching, via enzymes of a 'hydroxymethylglutaryl-CoA synthase (HCS) cassette', to incorporate various side chains at the second carbon from the terminal carboxylic acid of growing polyketide backbones. We identified a strong sequence motif in acyl carrier proteins (ACPs) where ß-branching is known to occur. Substituting ACPs confirmed a correlation of ACP type with ß-branching specificity. Although these ACPs often occur in tandem, NMR analysis of tandem ß-branching ACPs indicated no ACP-ACP synergistic effects and revealed that the conserved sequence motif forms an internal core rather than an exposed patch. Modeling and mutagenesis identified ACP helix III as a probable anchor point of the ACP-HCS complex whose position is determined by the core. Mutating the core affects ACP functionality, whereas ACP-HCS interface substitutions modulate system specificity. Our method for predicting ß-carbon branching expands the potential for engineering new polyketides and lays a basis for determining specificity rules.

In silico prediction of 3D structure of Mn superoxide dismutase of Scylla serrata and its binding properties with inhibitors.

In the present study, we used computational methods to model crab and rat MnSOD using the crystal structure of MnSOD from Homo sapiens (PDB code: 1MSD) as template by comparative modeling approach. We performed molecular dynamics simulations to study dynamic behavior of the crab MnSOD. The modeled proteins were validated and subjected to molecular docking analyses. Molecular docking tool was used to elucidate a comparative binding mode of the crab and rat SOD with potent inhibitors of SOD such as hydrogen peroxide (H2O2), potassium cyanide (KCN) and sodium dodecyl sulphate (SDS). The predicted valid structure of crab MnSOD did not show any interaction with KCN but close interaction with H2O2 and SDS. A possible inhibitory mechanism of SDS and H2O2 due to their interaction with the amino acids present in the active site of the MnSOD of the above two animals are elucidated. This allowed us to predict the binding modes of the proteins to elucidate probable mode of action and sites of interference.

Structural and functional conservation profiles of novel cathepsin L-like proteins identified in the Drosophila melanogaster genome.

Cathepsin L is a cysteine protease which degrades connective tissue proteins including collagen, elastin, and fibronectin. In this study, five well-characterized cathepsin L proteins from different arthropods were used as query sequences for the Drosophila genome database. The search yielded 10 cathepsin L-like sequences, of which eight putatively represent novel cathepsin L-like proteins. To understand the phylogenetic relationship among these cathepsin L-like proteins, a phylogenetic tree was constructed based on their sequences. In addition, models of the tertiary structures of cathepsin L were constructed using homology modeling methods and subjected to molecular dynamics simulations to obtain reasonable structure to understand its dynamical behavior. Our findings demonstrate that all of the potential Drosophila cathepsin L-like proteins contain at least one cathepsin propeptide inhibitor domain. Multiple sequence alignment and homology models clearly highlight the conservation of active site residues, disulfide bonds, and amino acid residues critical for inhibitor binding. Furthermore, comparative modeling indicates that the sequence/structure/function profiles and active site architectures are conserved.

Metabolic pathway analysis and molecular docking analysis for identification of putative drug targets in Toxoplasma gondii: novel approach.

Toxoplasma gondii is an obligate intracellular apicomplexan parasite that can infect a wide range of warm-blooded animals including humans. In humans and other intermediate hosts, toxoplasma develops into chronic infection that cannot be eliminated by host's immune response or by currently used drugs. In most cases, chronic infections are largely asymptomatic unless the host becomes immune compromised. Thus, toxoplasma is a global health problem and the situation has become more precarious due to the advent of HIV infections and poor toleration of drugs used to treat toxoplasma infection, having severe side effects and also resistance have been developed to the current generation of drugs. The emergence of these drug resistant varieties of T. gondii has led to a search for novel drug targets. We have performed a comparative analysis of metabolic pathways of the host Homo sapiens and the pathogen T. gondii. The enzymes in the unique pathways of T. gondii, which do not show similarity to any protein from the host, represent attractive potential drug targets. We have listed out 11 such potential drug targets which are playing some important work in more than one pathway. Out of these, one important target is Glutamate dehydrogenase enzyme; it plays crucial part in oxidation reduction, metabolic process and amino acid metabolic process. As this is also present in the targets of tropical diseases of TDR (Tropical disease related Drug) target database and no PDB and MODBASE 3D structural model is available, homology models for Glutamate dehydrogenase enzyme were generated using MODELLER9v6. The model was further explored for the molecular dynamics simulation study with GROMACS, virtual screening and docking studies with suitable inhibitors against the NCI diversity subset molecules from ZINC database, by using AutoDock-Vina. The best ten docking solutions were selected (ZINC01690699, ZINC17465979, ZINC17465983, ZINC18141294_03, ZINC05462670, ZINC01572309, ZINC18055497_01, ZINC18141294, ZINC05462674 and ZINC13152284_01). Further the Complexes were analyzed through LIGPLOT. On the basis of Complex scoring and binding ability it is deciphered that these NCI diversity set II compounds, specifically ZINC01690699 (as it has minimum energy score and one of the highest number of interactions with the active site residue), could be promising inhibitors for T. gondii using Glutamate dehydrogenase as Drug target.

Binding efficiencies of carbohydrate ligands with different genotypes of cholera toxin B: molecular modeling, dynamics and docking simulation studies.

Vibrio cholerae produces cholera toxin (CT) that consists of two subunits, A and B, and is encoded by a filamentous phage CTXΦ. The A subunit carries enzymatic activity that ribosylates ADP, whereas the B subunit binds to monosialoganglioside (GM1) receptor in epithelial cells. Molecular analysis of toxigenic V. cholerae strains indicated the presence of multiple ctxB genotypes. In this study, we employed a comparative modeling approach to define the structural features of all known variants of ctxB found in O139 serogroup V. cholerae. Modeling, molecular dynamics and docking simulations studies suggested subtle variations in the binding ability of ctxB variants to carbohydrate ligands of GM1 (galactose, sialic acid and N-acetyl galactosamine). These findings throw light on the molecular efficiencies of pathogenic isolates of V. cholerae harboring natural variants of ctxB in causing the disease, thus suggesting the need to consider ctxB variations when designing vaccines against cholera.

In silico prediction and characterization of 3D structure and binding properties of catalase from the commercially important crab, Scylla serrata.

The enzyme catalase breaks down H(2)O(2), a potentially harmful oxidant, to H(2)O and O(2). Besides oxidase activity, the enzyme also exhibits peroxidase activity. Therefore, it plays an important role in maintaining health and regulating pathophysiology of the organisms. However, 3D structure of this important enzyme in invertebrates particularly in crabs is not yet available. Therefore, an attempt has been made to predict the structure of the crab catalase and to envisage its catalytic interaction with H(2)O(2). A three dimensional model of crab catalase was constructed using the NADPH binding site on Beef Liver catalase from Bos taurus (PDBID: 7CAT) as template by comparative modeling approach. Backbone conformation of the modeled structure by PROCHECK revealed that more than 98% of the residues fell in the allowed regions, ERRAT results confirmed good quality of modeled structure and VERIFY3D profile was satisfying. Molecular docking has been used to know the binding modes of hydrogen peroxide with the crab catalase protein. The receptor structures used for docking were derived from molecular dynamics (MD) simulations of homology modeled structure. The docking results showed that the three important determinant residues Arg68, Val70 and Arg108 in catalase were binding with H(2)O(2) as they had strong hydrogen bonding contacts with the substrate. Our analysis provides insight into the structural properties of crab catalase and defines its active sites for binding with substrate. These data are important for further studies of catalase of invertebrates in general and that of crabs in particular.

Prediction and analysis of paralogous proteins in Trichomonas vaginalis genome.

Trichomonas vaginalis causes trichomoniasis, second most sexually transmitted disease. The genome sequence draft of T. vaginalis was published by The Institute of Genomic Research reveals an abnormally large genome size of 160 Mb. It was speculated that a significant portion of the proteome contains paralogous proteins. The present study was aimed at identification and analysis of the paralogous proteins. The all against all search approach is used to identify the paralogous proteins. The dataset of proteins was retrieved from TIGR and TrichDB FTP server. The BLAST-P program performed all against all database searches against the protein database of Trichomonas vaginalis available at NCBI genome database. In the present study about 50,000 proteins were searched where 2,700 proteins were found to be paralogous under the rigid selection criteria. The Pfam database search has identified significant number of paralogous proteins which were further categorized among different 1496 paralogous protein in pfam families, 1027 paralogous protein contains domain, 60 proteins were having different repeats and 1092 paralogous protein sequences of clans. Such identification and functional annotation of paralogous proteins will also help in removing paralogous proteins from possible drug targets in future. Presence of huge number of paralogous proteins across wide range of gene families and domains may be one of the possible mechanisms involved in the T. vaginalis genome expansion and evolution.

Virtual screening of AmpC/ß-lactamase as target for antimicrobial resistance in Pseudomonas aeruginosa.

AmpC is a group I, class C -lactamase present in most Enterobacteriaceae and in Pseudomonas aeruginosa and other nonfermenting gram-negative bacilli. The ß-lactam class of antibiotics is one of the most important structural classes of antibacterial compounds and act by inhibiting the bacterial D ,D - transpeptidases that are responsible for the final step of peptidoglycan cross-linking. Our main aim in the study is to screen possible inhibitors against AmpC / ß - lactamase (an enzyme responsible for antimicrobial activity in Pseudomonas aeruginosa), through virtual screening of 1364 NCI (National Cancer Institute) diversity set II compounds. Homology Model of AmpC / ß - lactamase was constructed using MODELLER and the Model was validated using PROCHECK and Verify 3D programs to obtain a stable structure, which was further used for virtual screening of NCI (National Cancer Institute) diversity set II compounds through molecular Docking studies using Autodock. The amino acid sequence of the ß - lactamase was also subjected to ScanProsite web server to find any pattern present in the sequence. After the prediction of 3-dimensional model of AmpC/ ß-lactamase, the possible Active sites ofß - lactamase were determined using LIGSITE(csc) and CastP web servers simultaneously. The Docked complexes were validated and Enumerated based on the Autodock Scoring function to pick out the best inhibitor based on Autodock energy score. Thus from the entire 1364 NCI diversity set II compounds which were Docked, the best four docking solutions were selected (ZINC12670903, ZINC17465965, ZINC11681166 and ZINC13099024). Further the Complexes were analyzed through LIGPLOT for their interaction for the 4 best docked NCI diversity set II compounds. Thus from the Complex scoring and binding ability it is deciphered that these NCI diversity set II compounds could be promising inhibitors for Pseudomonas aeruginosa using AmpC /ß - lactamase as Drug target yet pharmacological studies have to confirm it.