Current Approaches in Supersecondary Structures Investigation.
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ABSTRACT:
SUBMITTER: Rudnev VR
PROVIDER: S-EPMC8584461 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:We will consider in this chapter supersecondary structures (SSS) as a set of secondary structure elements (SSEs) found in protein domains. Some SSS arrangements/topologies have been consistently observed within known tertiary structural domains. We use them in the context of repeating supersecondary structures that self-assemble in a symmetric arrangement to form a domain. We call them protodomains (or protofolds). Protodomains are some of the most interesting and insightful SSSs. Within a given 3D protein domain/fold, recognizing such sets may give insights into a possible evolutionary process of duplication, fusion, and coevolution of these protodomains, pointing to possible original protogenes. On protein folding itself, pseudosymmetric domains may point to a "directed" assembly of pseudosymmetric protodomains, directed by the only fact that they are tethered together in a protein chain. On function, tertiary functional sites often occur at protodomain interfaces, as they often occur at domain-domain interfaces in quaternary arrangements.First, we will briefly review some lessons learned from a previously published census of pseudosymmetry in protein domains (Myers-Turnbull, D. et al., J Mol Biol. 426:2255-2268, 2014) to introduce protodomains/protofolds. We will observe that the most abundant and diversified folds, or superfolds, in the currently known protein structure universe are indeed pseudosymmetric. Then, we will learn by example and select a few domain representatives of important pseudosymmetric folds and chief among them the immunoglobulin (Ig) fold and go over a pseudosymmetry supersecondary structure (protodomain) analysis in tertiary and quaternary structures. We will point to currently available software tools to help in identifying pseudosymmetry, delineating protodomains, and see how the study of pseudosymmetry and the underlying supersecondary structures can enrich a structural analysis. This should potentially help in protein engineering, especially in the development of biologics and immunoengineering.
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Project description:Recent advances in three-dimensional electron microscopy (3D EM) have enabled the quantitative visualization of the structural building blocks of proteins at improved resolutions. We provide algorithms to detect the secondary structures (α-helices and β-sheets) from proteins for which the volumetric maps are reconstructed at 6-10Å resolution. Additionally, we show that when the resolution is coarser than 10Å, some of the supersecondary structures can be detected from 3D EM maps. For both these algorithms, we employ tools from computational geometry and differential topology, specifically the computation of stable/unstable manifolds of certain critical points of the distance function induced by the molecular surface. Our results connect mathematically well-defined constructions with bio-chemically induced structures observed in proteins.
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Project description:We present a fragment-search based method for predicting loop conformations in protein models. A hierarchical and multidimensional database has been set up that currently classifies 105,950 loop fragments and loop flanking secondary structures. Besides the length of the loops and types of bracing secondary structures the database is organized along four internal coordinates, a distance and three types of angles characterizing the geometry of stem regions. Candidate fragments are selected from this library by matching the length, the types of bracing secondary structures of the query and satisfying the geometrical restraints of the stems and subsequently inserted in the query protein framework where their fit is assessed by the root mean square deviation (r.m.s.d.) of stem regions and by the number of rigid body clashes with the environment. In the final step remaining candidate loops are ranked by a Z-score that combines information on sequence similarity and fit of predicted and observed phi/psi main chain dihedral angle propensities. Confidence Z-score cut-offs were determined for each loop length that identify those predicted fragments that outperform a competitive ab initio method. A web server implements the method, regularly updates the fragment library and performs prediction. Predicted segments are returned, or optionally, these can be completed with side chain reconstruction and subsequently annealed in the environment of the query protein by conjugate gradient minimization. The prediction method was tested on artificially prepared search datasets where all trivial sequence similarities on the SCOP superfamily level were removed. Under these conditions it is possible to predict loops of length 4, 8 and 12 with coverage of 98, 78 and 28% with at least of 0.22, 1.38 and 2.47 A of r.m.s.d. accuracy, respectively. In a head-to-head comparison on loops extracted from freshly deposited new protein folds the current method outperformed in a approximately 5:1 ratio an earlier developed database search method.
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Project description:Knowledge of supersecondary structures can provide important information about its spatial structure of protein. Some approaches have been developed for the prediction of protein supersecondary structure. However, the feature used by these approaches is primarily based on amino acid sequences. In this study, a novel model is presented to predict protein supersecondary structure by use of chemical shifts (CSs) information derived from nuclear magnetic resonance (NMR) spectroscopy. Using these CSs as inputs of the method of quadratic discriminant analysis (QD), we achieve the overall prediction accuracy of 77.3%, which is competitive with the same method for predicting supersecondary structures from amino acid compositions in threefold cross-validation. Moreover, our finding suggests that the combined use of different chemical shifts will influence the accuracy of prediction.
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Project description:We present a generic solvated coarse-grained protein model that can be used to characterize the driving forces behind protein folding. Each amino acid is coarse-grained with two beads, a backbone, and a side chain. Although the backbone beads are modeled as polar entities, side chains are hydrophobic, polar, or charged, thus allowing the exploration of how sequence patterning determines a protein fold. The change in orientation of the atoms of the coarse-grained unit is captured by the addition of two oppositely charged dummy particles inside the backbone coarse-grained bead. These two dummy charges represent a dipole that can fluctuate, thus introducing structural polarization into the coarse-grained model. Realistic ?/? content is achieved de novo without any biases in the force field toward a particular secondary structure. The dipoles created by the dummy particles interact with each other and drive the protein models to fold into unique structures depending on the amino acid patterning and presence of capping residues. We have also characterized the role of dipole-dipole and dipole-charge interactions in shaping the secondary and supersecondary structure of proteins. Formation of helix bundles and ?-strands are also discussed.
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Project description:The remarkable predominance of right-handedness in beta-alpha-beta helical crossovers has been previously explained in terms of thermodynamic stability and kinetic accessibility, but a different kinetic trapping mechanism may also play a role. If the beta-sheet contacts are made before the crossover helix is fully formed, and if the backbone angles of the folding helix follows the energetic pathway of least resistance, then the helix would impart a torque on the ends of the two strands. Such a torque would tear apart a left-handed conformation but hold together a right-handed one. Right-handed helical crossovers predominate even in all-alpha proteins, where previous explanations based on the preferred twist of the beta sheet do not apply. Using simple molecular simulations, we can reproduce the right-handed preference in beta-alpha-beta units, without imposing specific beta-strand geometry. The new kinetic trapping mechanism is dubbed the "phone cord effect" because it is reminiscent of the way a helical phone cord forms superhelices to relieve torsional stress. Kinetic trapping explains the presence of a right-handed superhelical preference in alpha helical crossovers and provides a possible folding mechanism for knotted proteins.
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Project description:This work evaluates the hypothesis that proteins with an identical supersecondary structure (SSS) share a unique set of residues--SSS-determining residues--even though they may belong to different protein families and have very low sequence similarities. This hypothesis was tested on two groups of sandwich-like proteins (SPs). Proteins in each group have an identical SSS, but their sequence similarity is below the "twilight zone." To find the SSS-determining residues specific to each group, a unique structure-based algorithm of multiple sequences alignment was developed. The units of alignment are individual strands and loops rather than whole sequences. The algorithm is based on the alignment of residues that form hydrogen bonds between corresponding strands. Structure-based alignment revealed that 30-35% of the positions in the sequences in each group of proteins are "conserved positions" occupied either by hydrophobic-only or hydrophilic-only residues. Moreover, each group of SPs is characterized by a unique set of SSS-determining residues found at the conserved positions. The set of SSS-determining residues has very high sensitivity and specificity for identifying proteins with a corresponding SSS: It is an "amino acid tag" that brands a sequence as having a particular SSS. Thus, the sets of SSS-determining residues can be used to classify proteins and to predict the SSS of a query amino acid sequence.
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Project description:Glioblastoma is the most common malignant central nervous system (CNS) tumor (48.3%), with a median survival of only about 14.6 months. Although the CNS is an immune-privileged site, activated T cells can cross the blood-brain barrier. The recent successes of several immunotherapies for various cancers have drawn interest in immunotherapy for treatment of malignant glioma. There have been extensive attempts to evaluate the efficiency of immunotherapy against malignant glioma. Passive immunotherapy for malignant glioma includes monoclonal antibody-mediated immunotherapy, cytokine-mediated therapy, and adoptive cell transfer, also known as chimeric antigen receptor T cell treatment. On the other hand, active immunotherapy, which stimulates the patient's adaptive immune system against specific tumor-associated antigens, includes cancer vaccines that are divided into peptide vaccines and cell-based vaccines. In addition, there is immune checkpoint blockade therapy, which increases the efficiency of immunotherapy by reducing the resistance of malignant glioma to immunotherapy. Despite centuries of efforts, immunotherapeutic successes for malignant glioma remain limited. However, many clinical trials of adoptive cell transfer immunotherapy on malignant glioma are ongoing, and the outcomes are eagerly awaited. In addition, although there are still several obstacles, current clinical trials using personalized neoantigen-based dendritic cell vaccines offer new hope to glioblastoma patients. Furthermore, immune checkpoint targeted therapy is expected to decipher the mechanism of immunotherapy resistance in malignant glioma in the near future. More studies are needed to increase the efficacy of immunotherapy in malignant glioma. We hope that immunotherapy will become a new treatment of malignant glioma.
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