EDPDB: a multifunctional tool for protein structure analysis

1995 ◽  
Vol 28 (5) ◽  
pp. 624-630 ◽  
Author(s):  
X.-J. Zhang ◽  
B. W. Matthews
Keyword(s):  
Protein Structure ◽  
Solvent Accessibility ◽  
Protein Structures ◽  
Relevant Information ◽  
Fortran Program ◽  
Large Set ◽  
Protein Structure Analysis ◽  
Van Der Waals Volume ◽  
Biologically Relevant

EDPDB is a Fortran program that simplifies the analysis of protein structure and makes it easy to extract various types of geometrical and biologically relevant information for the molecule both in isolation as well as in its crystallographic context. EDPDB offers a large set of functions by which the user can evaluate, select and manipulate the coordinates of protein structures. Types of calculation available include the determination of solvent accessibility, bond lengths and torsion angles, determination of the van der Waals volume of a group of atoms, determination of the best-fit plane through a set of points, evaluation of crystal contacts between a molecule in a crystal and all symmetry-related molecules, and the determination of `hinge-bending' motion between protein domains. It is also possible to compare different structures, to perform coordinate manipulations and to edit coordinate files. The program augments the graphic analysis of protein structure by allowing the user to construct a simple set of commands that will rapidly screen an entire structure. It may also make special purpose analyses feasible without complicated programming.

TOP: a new method for protein structure comparisons and similarity searches

2000 ◽  
Vol 33 (1) ◽  
pp. 176-183 ◽  
Author(s):  
Guoguang Lu
Keyword(s):  
User Interface ◽  
Protein Structure ◽  
Protein Structures ◽  
Three Dimensional ◽  
Data Bank ◽  
Structure Alignment ◽  
Dimensional Structure ◽  
Protein Structure Alignment ◽  
Protein Structure Analysis ◽  
Structure Comparison

In order to facilitate the three-dimensional structure comparison of proteins, software for making comparisons and searching for similarities to protein structures in databases has been developed. The program identifies the residues that share similar positions of both main-chain and side-chain atoms between two proteins. The unique functions of the software also include database processingviaInternet- and Web-based servers for different types of users. The developed method and its friendly user interface copes with many of the problems that frequently occur in protein structure comparisons, such as detecting structurally equivalent residues, misalignment caused by coincident match of Cαatoms, circular sequence permutations, tedious repetition of access, maintenance of the most recent database, and inconvenience of user interface. The program is also designed to cooperate with other tools in structural bioinformatics, such as the 3DB Browser software [Prilusky (1998).Protein Data Bank Q. Newslett.84, 3–4] and the SCOP database [Murzin, Brenner, Hubbard & Chothia (1995).J. Mol. Biol.247, 536–540], for convenient molecular modelling and protein structure analysis. A similarity ranking score of `structure diversity' is proposed in order to estimate the evolutionary distance between proteins based on the comparisons of their three-dimensional structures. The function of the program has been utilized as a part of an automated program for multiple protein structure alignment. In this paper, the algorithm of the program and results of systematic tests are presented and discussed.

scholarly journals Evaluation of variability in high resolution protein structures by global distance scoring

2017 ◽  
Author(s):  
Risa Anzai ◽  
Yoshiki Asami ◽  
Waka Inoue ◽  
Hina Ueno ◽  
Koya Yamada ◽  
...  
Keyword(s):  
High Resolution ◽  
Global Analysis ◽  
Protein Structures ◽  
Data Bank ◽  
Relevant Information ◽  
Systematic Analysis ◽  
Structure Variation ◽  
Model Calculations ◽  
Biologically Relevant ◽  
Global Comparison

AbstractSystematic analysis of statistical and dynamical properties of proteins is critical to understanding cellular events. Extraction of biologically relevant information from a set of high-resolution structures is important because it can provide mechanistic details behind the functional properties of protein families, enabling rational comparison between families. Most of the current structure comparisons are pairwise-based, which hampers the global analysis of increasing contents in the Protein Data Bank. Additionally, pairing of protein structures introduces uncertainty with respect to reproducibility because it frequently accompanies other settings for superimposition. This study introduces intramolecular distance scoring, for the analysis of human proteins, for each of which at least several high-resolution are available. We show that the results are comprehensively used to overview advances at the atomic level exploration of each protein and protein family. This method, and the interpretation based on model calculations, provide new criteria for understanding specific and non-specific structure variation in a protein, enabling global comparison of the dynamics among a vast variety of proteins from different species.

scholarly journals Redetermination of the first unknown protein MicroED structure by high resolution X-ray diffraction

2021 ◽  
Author(s):  
Hongyi Xu ◽  
Xiaodong Zou ◽  
Martin Högbom ◽  
Hugo Lebrette
Keyword(s):  
Protein Structures ◽  
Real Life ◽  
Relevant Information ◽  
Binding Pocket ◽  
X Ray Diffraction ◽  
X Ray ◽  
Biologically Relevant ◽  
Atomic Structures ◽  
Unknown Protein ◽  
Wide Range

Microcrystal electron diffraction (MicroED) has the potential to considerably impact the field of structural biology. Indeed, the method can solve atomic structures of a wide range of molecules, beyond the reach of single particle cryo-electron microscopy, exploiting crystals too small for X-ray diffraction (XRD) even using X-ray free-electron lasers. However, until the first unknown protein structure – a R2-like ligand binding oxidase from Sulfolobus acidocaldarius (SaR2lox) – was recently solved at 3.0 Å resolution, MicroED had only been used to study known protein structures previously obtained by XRD. Here, after adapting sample preparation protocols, the structure of the SaR2lox protein originally solved by MicroED was redetermined by XRD at 2.1 Å resolution. In light of the higher resolution XRD data and taking into account experimental differences of the methods, the quality of the MicroED structure is examined. The analysis demonstrates that MicroED provided an overall accurate model, revealing biologically relevant information specific to SaR2lox, such as the absence of an ether cross-link, but did not allow to detect the presence of a ligand visible by XRD in the protein binding pocket. Furthermore, strengths and weaknesses of MicroED compared to XRD are discussed in the perspective of this real-life protein example. The study provides fundaments to help MicroED become a method of choice for solving novel protein structures.

PSAP: protein structure analysis package

2007 ◽  
Vol 40 (4) ◽  
pp. 773-777 ◽  
Author(s):  
B. Balamurugan ◽  
M. N. A. Md. Roshan ◽  
B. Shaahul Hameed ◽  
K. Sumathi ◽  
R. Senthilkumar ◽  
...  
Keyword(s):  
Protein Structure ◽  
Structure Analysis ◽  
Protein Structures ◽  
Three Dimensional ◽  
Protein Structure Analysis ◽  
Molecular Graphics ◽  
Client Machine ◽  
Analysis Package ◽  
Functional Features ◽  
Atomic Coordinates

A computing engine, theProtein Structure Analysis Package(PSAP), has been developed to calculate and display various hidden structural and functional features of three-dimensional protein structures. The proposed computing engine has several utilities to enable structural biologists to analyze three-dimensional protein molecules and provides an easy-to-use Web interface to compute and visualize the necessary features dynamically on the client machine. Users need to provide the Protein Data Bank (PDB) identification code or upload three-dimensional atomic coordinates from the client machine. For visualization, the free molecular graphics programsRasMolandJmolare deployed in the computing engine. Furthermore, the computing engine is interfaced with an up-to-date local copy of the PDB. The atomic coordinates are updated every week and hence users can access all the structures available in the PDB. The computing engine is free and is accessible online at http://iris.physics.iisc.ernet.in/psap/.

scholarly journals Identifying and quantifying radiation damage at the atomic level

2015 ◽  
Vol 22 (2) ◽  
pp. 201-212 ◽  
Author(s):  
Markus Gerstel ◽  
Charlotte M. Deane ◽  
Elspeth F. Garman
Keyword(s):  
Radiation Damage ◽  
Disulfide Bonds ◽  
Solvent Accessibility ◽  
Global Radiation ◽  
Protein Structures ◽  
Large Set ◽  
Damage Site ◽  
Site Specific ◽  
Statistical Survey ◽  
And Function

Radiation damage impedes macromolecular diffraction experiments. Alongside the well known effects of global radiation damage, site-specific radiation damage affects data quality and the veracity of biological conclusions on protein mechanism and function. Site-specific radiation damage follows a relatively predetermined pattern, in that different structural motifs are affected at different dose regimes: in metal-free proteins, disulfide bonds tend to break first followed by the decarboxylation of aspartic and glutamic acids. Even within these damage motifs the decay does not progress uniformly at equal rates. Within the same protein, radiation-induced electron density decay of a particular chemical group is faster than for the same group elsewhere in the protein: an effect known as preferential specific damage. Here,BDamage, a new atomic metric, is defined and validated to recognize protein regions susceptible to specific damage and to quantify the damage at these sites. By applyingBDamageto a large set of known protein structures in a statistical survey, correlations between the rates of damage and various physicochemical parameters were identified. Results indicate that specific radiation damage is independent of secondary protein structure. Different disulfide bond groups (spiral, hook, and staple) show dissimilar radiation damage susceptibility. There is a consistent positive correlation between specific damage and solvent accessibility.

scholarly journals MISCAST: MIssense variant to protein StruCture Analysis web SuiTe

2020 ◽  
Vol 48 (W1) ◽  
pp. W132-W139
Author(s):  
Sumaiya Iqbal ◽  
David Hoksza ◽  
Eduardo Pérez-Palma ◽  
Patrick May ◽  
Jakob B Jespersen ◽  
...  
Keyword(s):  
Protein Structure ◽  
Amino Acid ◽  
Structure Analysis ◽  
Protein Structures ◽  
Missense Variant ◽  
Protein Structure Analysis ◽  
Missense Variants ◽  
Functional Features ◽  
And Function ◽  
A Site

Abstract Human genome sequencing efforts have greatly expanded, and a plethora of missense variants identified both in patients and in the general population is now publicly accessible. Interpretation of the molecular-level effect of missense variants, however, remains challenging and requires a particular investigation of amino acid substitutions in the context of protein structure and function. Answers to questions like ‘Is a variant perturbing a site involved in key macromolecular interactions and/or cellular signaling?’, or ‘Is a variant changing an amino acid located at the protein core or part of a cluster of known pathogenic mutations in 3D?’ are crucial. Motivated by these needs, we developed MISCAST (missense variant to protein structure analysis web suite; http://miscast.broadinstitute.org/). MISCAST is an interactive and user-friendly web server to visualize and analyze missense variants in protein sequence and structure space. Additionally, a comprehensive set of protein structural and functional features have been aggregated in MISCAST from multiple databases, and displayed on structures alongside the variants to provide users with the biological context of the variant location in an integrated platform. We further made the annotated data and protein structures readily downloadable from MISCAST to foster advanced offline analysis of missense variants by a wide biological community.

High-Resolution Hydroxyl Radical Protein Footprinting: Biophysics Tool for Drug Discovery

2018 ◽  
Vol 47 (1) ◽  
pp. 315-333 ◽  
Author(s):  
Janna Kiselar ◽  
Mark R. Chance
Keyword(s):  
Protein Structure ◽  
High Resolution ◽  
Hydroxyl Radical ◽  
Solvent Accessibility ◽  
Side Chains ◽  
Protein Footprinting ◽  
Hydroxyl Radical Protein Footprinting ◽  
Wide Range ◽  
Hydroxyl Radical Footprinting

Hydroxyl radical footprinting (HRF) of proteins with mass spectrometry (MS) is a widespread approach for assessing protein structure. Hydroxyl radicals react with a wide variety of protein side chains, and the ease with which radicals can be generated (by radiolysis or photolysis) has made the approach popular with many laboratories. As some side chains are less reactive and thus cannot be probed, additional specific and nonspecific labeling reagents have been introduced to extend the approach. At the same time, advances in liquid chromatography and MS approaches permit an examination of the labeling of individual residues, transforming the approach to high resolution. Lastly, advances in understanding of the chemistry of the approach have led to the determination of absolute protein topologies from HRF data. Overall, the technology can provide precise and accurate measures of side-chain solvent accessibility in a wide range of interesting and useful contexts for the study of protein structure and dynamics in both academia and industry.

scholarly journals Iditis: Protein Structure Database

1998 ◽  
Vol 54 (6) ◽  
pp. 1071-1077 ◽  
Author(s):  
Stephen Gardner ◽  
Janet Thornton
Keyword(s):  
User Interface ◽  
Protein Structure ◽  
Experimental Design ◽  
Graphical User Interface ◽  
Molecular Interactions ◽  
Protein Structures ◽  
Structure Database ◽  
Wide Range ◽  
Database Engine

The validation, enrichment and organization of the data stored in PDB files is essential for those data to be used accurately and efficiently for modelling, experimental design and the determination of molecular interactions. TheIditisprotein structure database has been designed to allow the widest possible range of queries to be performed across all available protein structures. TheIditisdatabase is the most comprehensive protein structure resource currently available, and contains over 500 fields of information describing all publicly deposited protein structures. A custom-written database engine and graphical user interface provide a natural and simple environment for the construction of searches for complex sequence- and structure-based motifs. Extensions and specialized interfaces allow the data generated by the database to used in conjunction with a wide range of applications.

scholarly journals Characterization of Non-Trivial Neighborhood Fold Constraints from Protein Sequences using Generalized Topohydrophobicity.

2008 ◽  
Vol 2 ◽  
pp. BBI.S426 ◽  
Author(s):  
Guillaume Fourty ◽  
Isabelle Callebaut ◽  
Jean-Paul Mornon
Keyword(s):  
Secondary Structure ◽  
Solvent Accessibility ◽  
Protein Structures ◽  
Comparative Modeling ◽  
Local Geometry ◽  
Large Set ◽  
Structural Constraints ◽  
Sequence Alignments ◽  
Multiple Sequence ◽  
Multiple Sequence Alignments

Prediction of key features of protein structures, such as secondary structure, solvent accessibility and number of contacts between residues, provides useful structural constraints for comparative modeling, fold recognition, ab-initio fold prediction and detection of remote relationships. In this study, we aim at characterizing the number of non-trivial close neighbors, or long-range contacts of a residue, as a function of its “topohydrophobic” index deduced from multiple sequence alignments and of the secondary structure in which it is embedded. The “topohydrophobic” index is calculated using a two-class distribution of amino acids, based on their mean atom depths. From a large set of structural alignments processed from the FSSP database, we selected 1485 structural sub-families including at least 8 members, with accurate alignments and limited redundancy. We show that residues within helices, even when deeply buried, have few non-trivial neighbors (0–2), whereas β-strand residues clearly exhibit a multimodal behavior, dominated by the local geometry of the tetrahedron (3 non-trivial close neighbors associated with one tetrahedron; 6 with two tetrahedra). This observed behavior allows the distinction, from sequence profiles, between edge and central β-strands within β-sheets. Useful topological constraints on the immediate neighborhood of an amino acid, but also on its correlated solvent accessibility, can thus be derived using this approach, from the simple knowledge of multiple sequence alignments.

scholarly journals Training data composition affects performance of protein structure analysis algorithms

2021 ◽  
Author(s):  
Alexander Derry ◽  
Kristy A. Carpenter ◽  
Russ B. Altman
Keyword(s):  
Protein Structure ◽  
Molecular Mechanisms ◽  
Protein Structures ◽  
Machine Learning Algorithms ◽  
Training Data ◽  
Training Set ◽  
Protein Structure Analysis ◽  
X Ray ◽  
X Ray Crystallography ◽  
Test Sets

The three-dimensional structures of proteins are crucial for understanding their molecular mechanisms and interactions. Machine learning algorithms that are able to learn accurate representations of protein structures are therefore poised to play a key role in protein engineering and drug development. The accuracy of such models in deployment is directly influenced by training data quality. The use of different experimental methods for protein structure determination may introduce bias into the training data. In this work, we evaluate the magnitude of this effect across three distinct tasks: estimation of model accuracy, protein sequence design, and catalytic residue prediction. Most protein structures are derived from X-ray crystallography, nuclear magnetic resonance (NMR), or cryo-electron microscopy (cryo-EM); we trained each model on datasets consisting of either all three structure types or of only X-ray data. We find that across these tasks, models consistently perform worse on test sets derived from NMR and cryo-EM than they do on test sets of structures derived from X-ray crystallography, but that the difference can be mitigated when NMR and cryo-EM structures are included in the training set. Importantly, we show that including all three types of structures in the training set does not degrade test performance on X-ray structures, and in some cases even increases it. Finally, we examine the relationship between model performance and the biophysical properties of each method, and recommend that the biochemistry of the task of interest should be considered when composing training sets.

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