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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Multistep modeling of protein structure: application towards refinement of tyr-tRNA synthetase

The scope of multistep modeling (MSM) is expanding by adding a least-squares minimization step in the procedure to fit backbone reconstruction consistent with a set of C-alpha coordinates. The analytical solution of Phi and Psi angles, that fits a C-alpha x-ray coordinate is used for tyr-tRNA synthetase. Phi and Psi angles for the region where the above mentioned method fails, are obtained by minimizing the difference in C-alpha distances between the computed model and the crystal structure in a least-squares sense. We present a stepwise application of this part of MSM to the determination of the complete backbone geometry of the 321 N terminal residues of tyrosine tRNA synthetase to a root mean square deviation of 0.47 angstroms from the crystallographic C-alpha coordinates.

NASA Discipline Exobiology↗
DOE OSTI2018

Determination and Refinement of the Crystal Structure of Proteins Block Allocation Group at Brookhaven National Laboratory

Students and teachers from across Long Island (Eastport South Manor HS, Northport HS, Bayshore HS, Connetquot HS, Pendleton Hauppauge HS, William Floyd HS, Shelter Island HS) are collaborating on the crystallization, generation of putative ligands, and elucidation of protein structures at the NSLS II at BNL as part of the SPARK program.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Multi-scale structural analysis of proteins by deep semantic segmentation

Abstract Motivation Recent advances in computational methods have facilitated large-scale sampling of protein structures, leading to breakthroughs in protein structural prediction and enabling de novo protein design. Establishing methods to identify candidate structures that can lead to native folds or designable structures remains a challenge, since few existing metrics capture high-level structural features such as architectures, folds and conformity to conserved structural motifs. Convolutional Neural Networks (CNNs) have been successfully used in semantic segmentation—a subfield of image classification in which a class label is predicted for every pixel. Here, we apply semantic segmentation to protein structures as a novel strategy for fold identification and structure quality assessment. Results We train a CNN that assigns each residue in a multi-domain protein to one of 38 architecture classes designated by the CATH database. Our model achieves a high per-residue accuracy of 90.8% on the test set (95.0% average per-class accuracy; 87.8% average per-structure accuracy). We demonstrate that individual class probabilities can be used as a metric that indicates the degree to which a randomly generated structure assumes a specific fold, as well as a metric that highlights non-conformative regions of a protein belonging to a known class. These capabilities yield a powerful tool for guiding structural sampling for both structural prediction and design. Availability and implementation The trained classifier network, parser network, and entropy calculation scripts are available for download at https://git.io/fp6bd, with detailed usage instructions provided at the download page. A step-by-step tutorial for setup is provided at https://goo.gl/e8GB2S. All Rosetta commands, RosettaRemodel blueprints, and predictions for all datasets used in the study are available in the Supplementary Information. Supplementary information Supplementary data are available at Bioinformatics online.

Eguchi, Raphael R.↗
DOE OSTI2020

PersGNN: Applying Topological Data Analysis and Geometric Deep Learning to Structure-Based Protein Function Prediction

Understanding protein structure-function relationships is a key challenge in computational biology, with applications across the biotechnology and pharmaceutical industries. While it is known that protein structure directly impacts protein function, many functional prediction tasks use only protein sequence. In this work, we isolate protein structure to make functional annotations for proteins in the Protein Data Bank in order to study the expressiveness of different structure-based prediction schemes. We present PersGNN - an end-to-end trainable deep learning model that combines graph representation learning with topological data analysis to capture a complex set of both local and global structural features. While variations of these techniques have been successfully applied to proteins before, we demonstrate that our hybridized approach, PersGNN, outperforms either method on its own as well as a baseline neural network that learns from the same information. PersGNN achieves a 9.3% boost in area under the precision recall curve (AUPR) compared to the best individual model, as well as high F1 scores across different gene ontology categories, indicating the transferability of this approach.

Swenson, Nicolas↗
DOE OSTI2013

On the reproducibility of protein crystal structures: five atomic resolution structures of trypsin

Details of five very high-resolution accurate structures of bovine trypsin are compared in the context of the reproducibility of models obtained from crystals grown under identical conditions. Structural studies of proteins usually rely on a model obtained from one crystal. By investigating the details of this model, crystallographers seek to obtain insight into the function of the macromolecule. It is therefore important to know which details of a protein structure are reproducible or to what extent they might differ. To address this question, the high-resolution structures of five crystals of bovine trypsin obtained under analogous conditions were compared. Global parameters and structural details were investigated. All of the models were of similar quality and the pairwise merged intensities had large correlation coefficients. The C{sup α} and backbone atoms of the structures superposed very well. The occupancy of ligands in regions of low thermal motion was reproducible, whereas solvent molecules containing heavier atoms (such as sulfur) or those located on the surface could differ significantly. The coordination lengths of the calcium ion were conserved. A large proportion of the multiple conformations refined to similar occupancies and the residues adopted similar orientations. More than three quarters of the water-molecule sites were conserved within 0.5 Å and more than one third were conserved within 0.1 Å. An investigation of the protonation states of histidine residues and carboxylate moieties was consistent for all of the models. Radiation-damage effects to disulfide bridges were observed for the same residues and to similar extents. Main-chain bond lengths and angles averaged to similar values and were in agreement with the Engh and Huber targets. Other features, such as peptide flips and the double conformation of the inhibitor molecule, were also reproducible in all of the trypsin structures. Therefore, many details are similar in models obtained from different crystals. However, several features of residues or ligands located in flexible parts of the macromolecule may vary significantly, such as side-chain orientations and the occupancies of certain fragments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Computational Prediction of Coiled–Coil Protein Gelation Dynamics and Structure

Protein hydrogels represent an important and growing biomaterial for a multitude of applications, including diagnostics and drug delivery. We have previously explored the ability to engineer the thermoresponsive supramolecular assembly of coiled–coil proteins into hydrogels with varying gelation properties, where we have defined important parameters in the coiled–coil hydrogel design. Using Rosetta energy scores and Poisson–Boltzmann electrostatic energies, we iterate a computational design strategy to predict the gelation of coiled–coil proteins while simultaneously exploring five new coiled–coil protein hydrogel sequences. Provided this library, we explore the impact of in silico energies on structure and gelation kinetics, where we also reveal a range of blue autofluorescence that enables hydrogel disassembly and recovery. As a result of this library, we identify the new coiled–coil hydrogel sequence, Q5, capable of gelation within 24 h at 4 °C, a more than 2-fold increase over that of our previous iteration Q2. The fast gelation time of Q5 enables the assessment of structural transition in real time using small-angle X-ray scattering (SAXS) that is correlated to coarse-grained and atomistic molecular dynamics simulations revealing the supramolecular assembling behavior of coiled–coils toward nanofiber assembly and gelation. This work represents the first system of hydrogels with predictable self-assembly, autofluorescent capability, and a molecular model of coiled–coil fiber formation.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Structure based alignment and clustering of proteins (STRALCP)

Disclosed are computational methods of clustering a set of protein structures based on local and pair-wise global similarity values. Pair-wise local and global similarity values are generated based on pair-wise structural alignments for each protein in the set of protein structures. Initially, the protein structures are clustered based on pair-wise local similarity values. The protein structures are then clustered based on pair-wise global similarity values. For each given cluster both a representative structure and spans of conserved residues are identified. The representative protein structure is used to assign newly-solved protein structures to a group. The spans are used to characterize conservation and assign a "structural footprint" to the cluster.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Structural and Biophysical Characterization of the Mycobacterium tuberculosis Protein Rv0577, a Protein Associated with Neutral Red Staining of Virulent Tuberculosis Strains and Homologue of the Streptomyces coelicolor Protein KbpA

The 261-residue Mycobacterium tuberculosis protein Rv0577 is a prominent antigen in tuberculosis patients, the responsible component for neutral red staining of virulent strains of M. tuberculosis, a putative component in a methylglyoxal detoxification pathway, and an agonist of toll-like receptor 2. It also has 36% sequence identity to AfsK-binding protein A (KbpA), a component in the complex secondary metabolite pathways in the Streptomycetes genus from which many commercial antibiotics are derived. To gain insight into the biological function of Rv0577 and the family of KpbA kinase regulators, the crystal structure for Rv0577 was determined to a resolution of 1.75 Å (3OXH), binding properties with neutral red and deoxyadenosine (Ado) surveyed, backbone dynamics measured, and thermal stability assayed by CD spectroscopy. The protein is composed of four approximate repeats with an topology arranged radially in consecutive pairs to form two continuous eight-strand -sheets capped on both ends with an -helix. The two -sheets intersect in the center at roughly a right angle and form an asymmetric deep “saddle” on both sides of the protein, saddle one (P11 to A129) and saddle two (L143 to A258), that may serve to bind ligands. NMR chemical shift perturbation experiments show that neutral red binds to Rv0577, further cementing the role of Rv0577 in the neutral red staining of virulent strains of M. tuberculosis. Similar experiments show that adenosine also bind to Rv0577, although less tightly, with estimated dissociation constants of 4.1 ± 0.3 mM for saddle one and > 1 M for saddle two. Heteronuclear steady-state {1H}-15N NOE, T1, and T2 values were generally uniform through-out the sequence with only a few modest pockets of differences suggestive of slightly different motion in loops between -strands in saddle 1. Circular dichroism spectroscopy characterization of the thermal stability of Rv0577 indicated irreversible unfolding upon heating with an estimated melting temperature of 56 °C. While it is not known if Rv0577 has a kinase regulatory role similar to its Streptomyces homolog KbpA, protein kinase and phosphatase signaling help M. tuberculosis adapt to the hostile host environment during infections. Consequently, new anti-tuberculosis drugs targeting Rv0577 may act by interfering with multiple mechanisms; a potential signaling machinery as well as toll-like receptor 2 activation and the methylglyoxal detoxification pathway.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Distance‐based reconstruction of protein quaternary structures from inter‐chain contacts

Abstract Predicting the quaternary structure of protein complex is an important problem. Inter‐chain residue‐residue contact prediction can provide useful information to guide the ab initio reconstruction of quaternary structures. However, few methods have been developed to build quaternary structures from predicted inter‐chain contacts. Here, we develop the first method based on gradient descent optimization (GD) to build quaternary structures of protein dimers utilizing inter‐chain contacts as distance restraints. We evaluate GD on several datasets of homodimers and heterodimers using true/predicted contacts and monomer structures as input. GD consistently performs better than both simulated annealing and Markov Chain Monte Carlo simulation. Starting from an arbitrarily quaternary structure randomly initialized from the tertiary structures of protein chains and using true inter‐chain contacts as input, GD can reconstruct high‐quality structural models for homodimers and heterodimers with average TM‐score ranging from 0.92 to 0.99 and average interface root mean square distance from 0.72 Å to 1.64 Å. On a dataset of 115 homodimers, using predicted inter‐chain contacts as restraints, the average TM‐score of the structural models built by GD is 0.76. For 46% of the homodimers, high‐quality structural models with TM‐score ≥ 0.9 are reconstructed from predicted contacts. There is a strong correlation between the quality of the reconstructed models and the precision and recall of predicted contacts. Only a moderate precision or recall of inter‐chain contact prediction is needed to build good structural models for most homodimers. Moreover, GD improves the quality of quaternary structures predicted by AlphaFold2 on a Critical Assessment of Techniques for Protein Structure Prediction–Critical Assessments of Predictions of Interactions dataset.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Protein crystal structure from non-oriented, single-axis sparse X-ray data

X-ray free-electron lasers (XFELs) have inspired the development of serial femtosecond crystallography (SFX) as a method to solve the structure of proteins. SFX datasets are collected from a sequence of protein microcrystals injected across ultrashort X-ray pulses. The idea behind SFX is that diffraction from the intense, ultrashort X-ray pulses leaves the crystal before the crystal is obliterated by the effects of the X-ray pulse. The success of SFX at XFELs has catalyzed interest in analogous experiments at synchrotron-radiation (SR) sources, where data are collected from many small crystals and the ultrashort pulses are replaced by exposure times that are kept short enough to avoid significant crystal damage. The diffraction signal from each short exposure is so `sparse' in recorded photons that the process of recording the crystal intensity is itself a reconstruction problem. Using the EMC algorithm, a successful reconstruction is demonstrated here in a sparsity regime where there are no Bragg peaks that conventionally would serve to determine the orientation of the crystal in each exposure. In this proof-of-principle experiment, a hen egg-white lysozyme (HEWL) crystal rotating about a single axis was illuminated by an X-ray beam from an X-ray generator to simulate the diffraction patterns of microcrystals from synchrotron radiation. Millions of these sparse frames, typically containing only ~200 photons per frame, were recorded using a fast-framing detector. It is shown that reconstruction of three-dimensional diffraction intensity is possible using the EMC algorithm, even with these extremely sparse frames and without knowledge of the rotation angle. Further, the reconstructed intensity can be phased and refined to solve the protein structure using traditional crystallographic software. In conclusion, this suggests that synchrotron-based serial crystallography of micrometre-sized crystals can be practical with the aid of the EMC algorithm even in cases where the data are sparse.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Nanoscale probing of electron-regulated structural transitions in silk proteins by near-field IR imaging and nano-spectroscopy

Silk protein fibres produced by silkworms and spiders are renowned for their unparalleled mechanical strength and extensibility arising from their high-β-sheet crystal contents as natural materials. Investigation of β-sheet-oriented conformational transitions in silk proteins at the nanoscale remains a challenge using conventional imaging techniques given their limitations in chemical sensitivity or limited spatial resolution. Here, we report on electron-regulated nanoscale polymorphic transitions in silk proteins revealed by near-field infrared imaging and nano-spectroscopy at resolutions approaching the molecular level. The ability to locally probe nanoscale protein structural transitions combined with nanometre-precision electron-beam lithography offers us the capability to finely control the structure of silk proteins in two and three dimensions. Our work paves the way for unlocking essential nanoscopic protein structures and critical conditions for electron-induced conformational transitions, offering new rules to design protein-based nanoarchitectures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗