The formulation of network models from global protein studies is essential to understand the functioning of organisms. Network models of the proteome enable the application of Complex Network Analysis, a quantitative framework to investigate large complex networks using techniques from graph theory, statistical physics, dynamical systems and other fields. This approach has provided many insights into the functional organization of the proteome so far and will likely continue to do so. Currently, several network concepts have emerged in the field of proteomics. It is important to highlight the differences between these concepts, since different representations allow different insights into functional organization. One such concept is the protein interaction network, which contains proteins as nodes and undirected edges representing the occurrence of binding in large-scale protein-protein interaction studies. A second concept is the protein-signaling network, in which the nodes correspond to levels of post-translationally modified forms of proteins and directed edges to causal effects through post-translational modification, such as phosphorylation. Several other network concepts were introduced for proteomics. Although all formulated as networks, the concepts represent widely different physical systems. Therefore caution should be taken when applying relevant topological analysis. We review recent literature formulating and analyzing such networks.
IntroductionGenetic predisposition to multiple sclerosis (MS) in Sardinia (Italy) has been associated with five DRB1*-DQB1* haplotypes of the human leukocyte antigen (HLA). Given the complexity of these associations, an in-depth re-analysis was performed with the specific aims of confirming the haplotype associations; establishing the independence of the associated haplotypes; and assessing patients' genotypic risk of developing MS.Methods and ResultsA transmission disequilibrium test (TDT) of the DRB1*-DQB1* haplotypes in 943 trio families, confirmed a higher than expected transmission rate (over-transmission) of the *13:03-*03:01 (OR = 2.9, P = 7.6×10−3), *04:05-*03:01 (OR = 2.4, P = 4.4×10−6) and *03:01-*02:01 (OR = 2.1, P = 1.0×10−15) haplotype. In contrast, the *16:01-*05:02 (OR = 0.5, P = 5.4×10−11) and the *15:02-*06:01 (OR = 0.3, P = 1.5×10−3) haplotypes exhibited a lower than expected transmission rate (under-transmission). The independence of the transmission of each positively and negatively associated haplotype was confirmed relative to all positively associated haplotypes, and to the negatively associated *16:01-*05:02 haplotype. In patients, carriage of two predisposing haplotypes, or of protective haplotypes, respectively increased or decreased the patient's risk of developing MS. The risk of MS followed a multiplicative model of genotypes, which was, in order of decreasing ORs: *04:05-*0301/*03:01-*02:01 (OR = 4.5); *03:01-*02:01/*03:01-*02:01 (OR = 4.1); and the *16:01-*05:02/*16:01-*0502 (OR = 0.2) genotypes. Analysis of DRB1 and DQB1 protein chain residues showed that the Val/Gly residue at position 86 of the DRB1 chain was the only difference between the protective *16:01- *15:02 alleles and the predisposing *15:01 one. Similarly, the Ala/Val residue at position 38 of the DQB1 chain differentiated the positively associated *06:02 allele and the negatively associated *05:02, *06:01 alleles.ConclusionsThese findings show that the association of specific, independent DRB1*-DQB1* haplotypes confers susceptibility or resistance to MS in the MS-prone Sardinian population. The data also supports a functional role for specific residues of the DRB1 and DQB1 proteins in predisposing patients to MS.
Sardinia is a major Island in the Mediterranean with a high incidence of multiple sclerosis, a chronic autoimmune inflammatory disease of the central nervous system. Disease susceptibility in Sardinian population has been associated with five alleles of major histocompatibility complex (MHC) class II DRB1 gene. We performed 120 ns of molecular dynamics simulation on one predisposing and one protective alleles, unbound and in complex with the two relevant peptides: Myelin Basic Protein and Epstein Barr Virus derived peptide. In particular we focused on the MHC peptide binding groove dynamics. The predisposing allele was found to form a stable complex with both the peptides, while the protective allele displayed stability only when bound with myelin peptide. The local flexibility of the MHC was probed dividing the binding groove into four compartments covering the well known peptide anchoring pockets. The predisposing allele in the first half cleft exhibits a narrower and more rigid groove conformation in the presence of myelin peptide. The protective allele shows a similar behavior, while in the second half cleft it displays a narrower and more flexible groove conformation in the presence of viral peptide. We further characterized these dynamical differences by evaluating H-bonds, hydrophobic and stacking interaction networks, finding striking similarities with super-type patterns emerging in other autoimmune diseases. The protective allele shows a defined preferential binding to myelin peptide, as confirmed by binding free energy calculations. All together, we believe the presented molecular analysis could help to design experimental assays, supports the molecular mimicry hypothesis and suggests that propensity to multiple sclerosis in Sardinia could be partly linked to distinct peptide-MHC interaction and binding characteristics of the antigen presentation mechanism.
Alzheimer’s disease (AD) is a neurodegenerative disorder representing the leading cause of dementia and is affecting nearly 44 million people worldwide. AD is characterized by a progressive decline in acetylcholine levels in the cholinergic systems, which results in severe memory loss and cognitive impairments. Expression levels and activity of butyrylcholinesterase (BChE) enzyme has been noted to increase significantly in the late stages of AD, thus making it a viable drug target. A series of hydroxylated 2-phenylbenzofurans compounds were designed, synthesized and their inhibitory activities toward acetylcholinesterase (AChE) and BChE enzymes were evaluated. Two compounds (15 and 17) displayed higher inhibitory activity towards BChE with IC50 values of 6.23 μM and 3.57 μM, and a good antioxidant activity with EC50 values 14.9 μM and 16.7 μM, respectively. The same compounds further exhibited selective inhibitory activity against BChE over AChE. Computational studies were used to compare protein-binding pockets and evaluate the interaction fingerprints of the compound. Molecular simulations showed a conserved protein residue interaction network between the compounds, resulting in similar interaction energy values. Thus, combination of biochemical and computational approaches could represent rational guidelines for further structural modification of these hydroxy-benzofuran derivatives as future drugs for treatment of AD.
Fibromyalgia Syndrome (FMS) is a chronic disease characterized by widespread pain, and difficult to diagnose and treat. We analyzed the plasma metabolic profile of patients with FMS by using a metabolomics approach combining Liquid Chromatography-Quadrupole-Time Of Flight/Mass Spectrometry (LC-Q-TOF/MS) with multivariate statistical analysis, aiming to discriminate patients and controls. LC-Q-TOF/MS analysis of plasma (FMS patients: n = 22 and controls: n = 21) identified many lipid compounds, mainly lysophosphocholines (lysoPCs), phosphocholines and ceramides. Multivariate statistical analysis was performed to identify the discriminating metabolites. A protein docking and molecular dynamic (MD) study was then performed, using the most discriminating lysoPCs, to validate the binding to Platelet Activating Factor (1-alkyl-2-acetyl-sn-glycero-3-phosphocholine, PAF) Receptor (PAFr). Discriminating metabolites between FMS patients and controls were identified as 1-tetradecanoyl-sn-glycero-3-phosphocholine [PC(14∶0/0∶0)] and 1-hexadecanoyl-sn-glycero-3-phosphocholine [PC(16∶0/0∶0)]. MD and docking indicate that the ligands investigated have similar potentialities to activate the PAFr receptor. The application of a metabolomic approach discriminated FMS patients from controls, with an over-representation of PC(14∶0/0∶0) and PC(16∶0/0∶0) compounds in the metabolic profiles. These results and the modeling of metabolite-PAFr interaction, allowed us to hypothesize that lipids oxidative fragmentation might generate lysoPCs in abundance, that in turn will act as PAF-like bioactivators. Overall results suggest disease biomarkers and potential therapeutical targets for FMS.
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