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Protein–Nanoparticle Interactions
Published in Lajos P. Balogh, Nano-Enabled Medical Applications, 2020
Iseult Lynch, Kenneth A. Dawson
We have reported recently that a range of different nanoparticles, including polymer particles, cerium oxide, carbon nanotubes, and poly(ethylene glycol) (PEG)-coated QDs, enhance the rate of fibrillation of the amyloidogenic protein β-2-microglobulin under conditions where the protein is in a slightly molten, globular state at pH 2.5 [39]. As the fibrils imaged by transmission electron microscopy (TEM) do not appear to grow out of the nanoparticles (Fig. 8.4), we have suggested a mechanism based on the locally increased concentration of the protein in the vicinity of the nanoparticle surface. This, we believe, increases the probability of the formation of a critical oligomer that, once formed, returns to the solution phase. Multiple layers of protein bound to the particles and interaction with the particles does not appear to have much effect on the protein conformation as determined by fluorescence of the tryptophan residues, with slight effects observed for the innermost protein layer, and no observed effects for subsequent layers [39].
Relationships between Inflammation and Immunopathology of Malaria
Published in Mary M. Stevenson, Malaria: Host Responses to Infection, 2017
The term interleukin-1 was adopted in 1979 to rationalize the nomenclature of a monokine known even then to have various distinct functions.91 It is now appreciated that at least two distinct polypeptide cytokines, termed IL-1α and IL-1β, produced by a diverse variety of cell types, have these properties and that, as reviewed recently,38,92 the array of functions these cytokines possess is extraordinarily wide. These reviews also summarize the great functional overlap between IL-1 and TNF; both, for example, are endogenous pyrogens, and as such are equal candidates for generating the fever of malaria. These shared functions were initially puzzling, since comparisons of either form of IL-1 to TNF revealed no obvious homology in amino acid sequence. When secondary protein conformation was compared, however, close structural homology between these three molecules became apparent,93 rationalizing their shared functions and suggesting their evolution from a common ancestral cytokine. Once this family tree is appreciated it is not so surprising that TNF induces release of IL-1 from endothelial cells94 and monocytes,95 and that the reverse induction evidently may occur.96 Moreover, it is now (late 1987) beginning to emerge that TNF and IL-1 synergize powerfully.97 When considered with their concommitant production under so many circumstances, this synergy implies that the experimental use of either one of these monokines alone, while instructive, gives only part of the true in vivo picture.
Caenorhabditis elegans Aging is Associated with a Decline in Proteostasis
Published in Shamim I. Ahmad, Aging: Exploring a Complex Phenomenon, 2017
Human aging is often marked by the late onset of neurodegenerative diseases. Most have misfolding at their core and are thereby referred to as diseases of protein conformation [7]. Such diseases include Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), prion disease, Alzheimer's disease (AD) and polyglutamine-expansion diseases including Huntington's disease (HD), Kennedy's disease, and spinocerebellar ataxias (SCAs). All of the above are invariably characterized by the deposition of misfolded protein in the form of aggregates, inclusions bodies, or plaques. Such protein misfolding is toxic, leading to “toxic gain-of-function” phenotypes [8,9]. Furthermore, each of these diseases is progressive, age-dependent, and usually fatal.
Advancing cancer diagnostics with artificial intelligence and spectroscopy: identifying chemical changes associated with breast cancer
Published in Expert Review of Molecular Diagnostics, 2019
Abdullah C.S. Talari, Shazza Rehman, Ihtesham U Rehman
PCA loading plot analysis of amide I region has described biochemical differences among four subtypes. Firstly, PC-1 loading plot (blue) has sensitive in protein conformation of different subtypes. Every PC of this region is sensitive to protein conformation. Collagen at 1667 cm−1 (either unordered or β sheets) is positively separated triple negative and majority of HER2 subtypes. PC-3 loading plot (red) has pretty much sensitive in 1654 cm−1 (α-helical confirmation of collagen), 1614 cm−1 (tyrosine), 1604 cm−1 (phenylalanine and tyrosine), and 1576 cm−1 (guanine) and 1634 cm−1 (amide I). PC-4 loading plot (green) has shown that majority of triple negative, luminal A, and HER2 subtypes are positively separated at 1671 (β sheet structures of protein conformation) and 1575 (ring breathing mode of DNA bases), and some of the luminal Band HER2 and luminal A are negatively separated at 1601 (phenylalanine) and 1547 (proline) [36]. Collagen was important for separating luminal A and luminal B from rest of the subtypes but nucleic acids and amino acids were more important in separating triple negatives from rest of the subtypes. In a nut shell, PCA of amide I region is sensitive to protein conformation of different subtypes.
Novel mutations in a Chinese family with two patients with succinic semialdehyde dehydrogenase deficiency
Published in Gynecological Endocrinology, 2020
Xiao-dan Chen, Yun-ting Lin, Min-yan Jiang, Xiu-zhen Li, Duan Li, Hao Hu, Li Liu
The monomeric SSADH protein is composed of the following three domains: an N-terminal NAD-binding domain (residues 48–173, 196–307, and 509–524), a catalytic domain (residues 308–508), and an oligomerization domain (residues174–195 and 525–535) [14].The missense variant was found to be located in the catalytic domain, while the deletion variant was in the N-terminal NAD binding domain. A glycine residue was substituted by an arginine residue (G441R) in the missense variant. This glycine residue is conserved across a vast majority of the species, from the zebrafish Danio rerio to rodents and humans (Figure 1(B)). The substitution of this glycine residue with an arginine residue may be essential because glycine is rather different from arginine. Glycine is nonpolar and hydrophobic, whereas arginine residue is basic. From the current structural modeling (Figure 1(F,G)), for the wild type, G441 only forms H-bonds with an amino acid (443 L) within 3 Å (Figure 1(G)). Nevertheless, six additional H-bonds with the rest of the four amino acids, including 388A, 389V, 390E, and 391K, were formed by G441R. Therefore, the missense mutation caused changes in H-bond formation. H-bonds are one of the most important interactions that form the secondary and tertiary protein structures [15]. Altered H-bond formation may result in structural imbalances and transformed conformational dynamics [16]. Hence, the formation of H-bonds between amino acid residues is important for maintaining protein conformation. On the basis of 3D modeling (Figure 1(F,G)), the deletion mutation was found to truncate the α-helix. This loss of α-helix transformed into a random coil, which may influence the combination of succinic semialdehyde and NAD.
Prioritization and characterization of validated biofilm blockers targeting glucosyltransferase C of Streptococcus mutans
Published in Artificial Cells, Nanomedicine, and Biotechnology, 2021
Hazza A. Alhobeira, Mohammed Al Mogbel, Saif Khan, Mahvish Khan, Shafiul Haque, Pallavi Somvanshi, Mohd Wahid, Raju K. Mandal
An exhaustive flexible docking protocol was implemented (Supplementary Information: Figure SI 1) on BIOVIA Discovery Studio platform. Briefly, this protocol permits for receptor flexibility during the docking of flexible ligands up to some extent [33]. The side-chains of specified amino acids (in this case Glu515, Asp477, Asp588, and Asn481) were allowed to move during the docking process. This movement allows the receptor to adapt to different ligands in an induced-fit model (Supplementary Information: Figure SI 2). The protocol employs a combination of components from other protocols to perform the docking, and is based on methods within CHARMm [34] to sample side-chain and ligand conformations. The detailed input parameters are given in Supplementary Information (SI) file. Flexible docking protocol performs the following steps: (i) Calculation of receptor side-chain conformations: Initially, the protocol creates protein side-chain conformations using the ChiFlex algorithm [35], (ii) Create ligand conformations: Low energy ligand conformations are created for the docking process using Generate Conformations protocol of BIOVIA Discovery Studio platform, (iii) Perform initial placement of the ligand conformations: The ligand conformations are docked into the active site of each receptor side-chain conformation using LibDock [36], (iv) Clustering to remove similar ligand poses: Poses are clustered irrespective of the protein conformation as the protein conformations are rebuilt during the next step, (v) Refine side-chains: In the presence of the ligand, the specified receptor side-chain residues are refined using the ChiRotor algorithm [35], and (vi) Refine docking: A final simulated annealing and energy minimization of each ligand pose was done by using CDOCKER [37]