P3DOCK: a protein–RNA docking webserver based on template-based and template-free docking

2019 ◽  
Vol 36 (1) ◽  
pp. 96-103 ◽  
Author(s):  
Jinfang Zheng ◽  
Xu Hong ◽  
Juan Xie ◽  
Xiaoxue Tong ◽  
Shiyong Liu
Keyword(s):  
Success Rate ◽  
Clustering Algorithm ◽  
Hybrid Methods ◽  
3D Structure ◽  
Three Dimensional ◽  
Protein Docking ◽  
Ease Of Use ◽  
Supplementary Information ◽  
Main Function ◽  
Rna Interaction

AbstractMotivationThe main function of protein–RNA interaction is to regulate the expression of genes. Therefore, studying protein–RNA interactions is of great significance. The information of three-dimensional (3D) structures reveals that atomic interactions are particularly important. The calculation method for modeling a 3D structure of a complex mainly includes two strategies: free docking and template-based docking. These two methods are complementary in protein–protein docking. Therefore, integrating these two methods may improve the prediction accuracy.ResultsIn this article, we compare the difference between the free docking and the template-based algorithm. Then we show the complementarity of these two methods. Based on the analysis of the calculation results, the transition point is confirmed and used to integrate two docking algorithms to develop P3DOCK. P3DOCK holds the advantages of both algorithms. The results of the three docking benchmarks show that P3DOCK is better than those two non-hybrid docking algorithms. The success rate of P3DOCK is also higher (3–20%) than state-of-the-art hybrid and non-hybrid methods. Finally, the hierarchical clustering algorithm is utilized to cluster the P3DOCK’s decoys. The clustering algorithm improves the success rate of P3DOCK. For ease of use, we provide a P3DOCK webserver, which can be accessed at www.rnabinding.com/P3DOCK/P3DOCK.html. An integrated protein–RNA docking benchmark can be downloaded from http://rnabinding.com/P3DOCK/benchmark.html.Availability and implementationwww.rnabinding.com/P3DOCK/P3DOCK.html.Supplementary informationSupplementary data are available at Bioinformatics online.

scholarly journals Reconstruction of Three-Dimensional Object from Two-Dimensional Images by Utilizing Distance Regularized Level Algorithm and Mesh Object Generation

2020 ◽  
Vol 17 (3) ◽  
pp. 0899
Author(s):  
Samera Shams Hussei ◽  
Sukaina Sh Altyar ◽  
Lubab Ahmed Tawfeeq ◽  
Eman S. Harba
Keyword(s):  
Good Accuracy ◽  
Low Cost ◽  
3D Structure ◽  
Three Dimensional ◽  
High Accuracy ◽  
Ease Of Use ◽  
3D Scanner ◽  
Object A ◽  
Human Organs ◽  
Dimensional Object

Three-dimensional (3D) reconstruction from images is a most beneficial method of object regeneration by using a photo-realistic way that can be used in many fields. For industrial fields, it can be used to visualize the cracks within alloys or walls. In medical fields, it has been used as 3D scanner to reconstruct some human organs such as internal nose for plastic surgery or to reconstruct ear canal for fabricating a hearing aid device, and others. These applications need high accuracy details and measurement that represent the main issue which should be taken in consideration, also the other issues are cost, movability, and ease of use which should be taken into consideration. This work has presented an approach for design and constructed a low-cost three-dimensional object scanner. We have proposed a 3D canal reconstruction system (ear or nose) based on using 2D images for reconstruction 3D object. A low-cost EndoScope with a proposed program based upon utilized the segmentation algorithm type “Distance Regularized Level” to segment active edges from images then generate mesh object in order to generate 3D structure for small canals or cracks. The results show good accuracy of the reconstructed object in both details and their measurements which are related to the success in the reconstruction of algorithm that yields good three-dimensional meshes object.  

scholarly journals iScore: a novel graph kernel-based function for scoring protein–protein docking models

2019 ◽  
Vol 36 (1) ◽  
pp. 112-121 ◽  
Author(s):  
Cunliang Geng ◽  
Yong Jung ◽  
Nicolas Renaud ◽  
Vasant Honavar ◽  
Alexandre M J J Bonvin ◽  
...  
Keyword(s):  
Protein Complexes ◽  
Three Dimensional ◽  
Protein Docking ◽  
Graph Representation ◽  
Supplementary Information ◽  
Scoring Functions ◽  
Computational Docking ◽  
3D Structures ◽  
Novel Approach ◽  
Protein Interfaces

Abstract Motivation Protein complexes play critical roles in many aspects of biological functions. Three-dimensional (3D) structures of protein complexes are critical for gaining insights into structural bases of interactions and their roles in the biomolecular pathways that orchestrate key cellular processes. Because of the expense and effort associated with experimental determinations of 3D protein complex structures, computational docking has evolved as a valuable tool to predict 3D structures of biomolecular complexes. Despite recent progress, reliably distinguishing near-native docking conformations from a large number of candidate conformations, the so-called scoring problem, remains a major challenge. Results Here we present iScore, a novel approach to scoring docked conformations that combines HADDOCK energy terms with a score obtained using a graph representation of the protein–protein interfaces and a measure of evolutionary conservation. It achieves a scoring performance competitive with, or superior to, that of state-of-the-art scoring functions on two independent datasets: (i) Docking software-specific models and (ii) the CAPRI score set generated by a wide variety of docking approaches (i.e. docking software-non-specific). iScore ranks among the top scoring approaches on the CAPRI score set (13 targets) when compared with the 37 scoring groups in CAPRI. The results demonstrate the utility of combining evolutionary, topological and energetic information for scoring docked conformations. This work represents the first successful demonstration of graph kernels to protein interfaces for effective discrimination of near-native and non-native conformations of protein complexes. Availability and implementation The iScore code is freely available from Github: https://github.com/DeepRank/iScore (DOI: 10.5281/zenodo.2630567). And the docking models used are available from SBGrid: https://data.sbgrid.org/dataset/684). Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Atomic-level evolutionary information improves protein-protein interface scoring

2021 ◽  
Author(s):  
Chloé Quignot ◽  
Pierre Granger ◽  
Pablo Chacón ◽  
Raphael Guerois ◽  
Jessica Andreani
Keyword(s):  
Success Rate ◽  
Protein Interactions ◽  
Protein Docking ◽  
Atomic Level ◽  
Supplementary Information ◽  
Evolutionary Information ◽  
General Strategy ◽  
Scoring Functions ◽  
Success Rates ◽  
Novel Strategy

Abstract Motivation The crucial role of protein interactions and the difficulty in characterising them experimentally strongly motivates the development of computational approaches for structural prediction. Even when protein-protein docking samples correct models, current scoring functions struggle to discriminate them from incorrect decoys. The previous incorporation of conservation and coevolution information has shown promise for improving protein-protein scoring. Here, we present a novel strategy to integrate atomic-level evolutionary information into different types of scoring functions to improve their docking discrimination. Results : We applied this general strategy to our residue-level statistical potential from InterEvScore and to two atomic-level scores, SOAP-PP and Rosetta interface score (ISC). Including evolutionary information from as few as ten homologous sequences improves the top 10 success rates of individual atomic-level scores SOAP-PP and Rosetta ISC by respectively 6 and 13.5 percentage points, on a large benchmark of 752 docking cases. The best individual homology-enriched score reaches a top 10 success rate of 34.4%. A consensus approach based on the complementarity between different homology-enriched scores further increases the top 10 success rate to 40%. Availability All data used for benchmarking and scoring results, as well as a Singularity container of the pipeline, are available at http://biodev.cea.fr/interevol/interevdata/ Supplementary information Supplementary data are available at Bioinformatics online.

Ancestral sequence reconstruction: accounting for structural information by averaging over replacement matrices

2018 ◽  
Vol 35 (15) ◽  
pp. 2562-2568
Author(s):  
Asher Moshe ◽  
Tal Pupko
Keyword(s):  
Structural Information ◽  
Solvent Accessibility ◽  
3D Structure ◽  
Three Dimensional ◽  
Ancestral Sequence ◽  
Supplementary Information ◽  
Ancestral Sequence Reconstruction ◽  
Ancestral Sequences ◽  
Sequence Reconstruction ◽  
And Function

Abstract Motivation Ancestral sequence reconstruction (ASR) is widely used to understand protein evolution, structure and function. Current ASR methodologies do not fully consider differences in evolutionary constraints among positions imposed by the three-dimensional (3D) structure of the protein. Here, we developed an ASR algorithm that allows different protein sites to evolve according to different mixtures of replacement matrices. We show that assigning replacement matrices to protein positions based on their solvent accessibility leads to ASR with higher log-likelihoods compared to naïve models that assume a single replacement matrix for all sites. Improved ASR log-likelihoods are also demonstrated when solvent accessibility is predicted from protein sequences rather than inferred from a known 3D structure. Finally, we show that using such structure-aware mixture models results in substantial differences in the inferred ancestral sequences. Availability and implementation http://fastml.tau.ac.il. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals EROS-DOCK: protein–protein docking using exhaustive branch-and-bound rotational search

2019 ◽  
Vol 35 (23) ◽  
pp. 5003-5010 ◽  
Author(s):  
Maria Elisa Ruiz Echartea ◽  
Isaure Chauvot de Beauchêne ◽  
David W Ritchie
Keyword(s):  
Force Field ◽  
Branch And Bound ◽  
3D Structure ◽  
Quality Criteria ◽  
Search Space ◽  
Protein Docking ◽  
Coarse Grained ◽  
Supplementary Information ◽  
Binary Complex ◽  
The Individual

Abstract Motivation Protein–protein docking algorithms aim to predict the 3D structure of a binary complex using the structures of the individual proteins. This typically involves searching and scoring in a 6D space. Many docking algorithms use FFT techniques to exhaustively cover the search space and to accelerate the scoring calculation. However, FFT docking results often depend on the initial protein orientations with respect to the Fourier sampling grid. Furthermore, Fourier-transforming a physics-base force field can involve a serious loss of precision. Results Here, we present EROS-DOCK, an algorithm to rigidly dock two proteins using a series of exhaustive 3D rotational searches in which non-clashing orientations are scored using the ATTRACT coarse-grained force field model. The rotational space is represented as a quaternion ‘π-ball’, which is systematically sub-divided in a ‘branch-and-bound’ manner, allowing efficient pruning of rotations that will give steric clashes. The algorithm was tested on 173 Docking Benchmark complexes, and results were compared with those of ATTRACT and ZDOCK. According to the CAPRI quality criteria, EROS-DOCK typically gives more acceptable or medium quality solutions than ATTRACT and ZDOCK. Availability and implementation The EROS-DOCK program is available for download at http://erosdock.loria.fr. Supplementary information Supplementary data are available at Bioinformatics online.

Methods for three-dimensional reconstruction of cellular components within a thick section

1986 ◽  
Vol 44 ◽  
pp. 18-21
Author(s):  
J. Frank ◽  
B. F. McEwen ◽  
M. Radermacher ◽  
C. L. Rieder
Keyword(s):  
Tilt Angle ◽  
Tomographic Reconstruction ◽  
3D Structure ◽  
Three Dimensional ◽  
Thick Section ◽  
Three Dimensional Reconstruction ◽  
Axis Ratio ◽  
Dimensional Reconstruction ◽  
Cellular Components

The tomographic reconstruction from multiple projections of cellular components, within a thick section, offers a way of visualizing and quantifying their three-dimensional (3D) structure. However, asymmetric objects require as many views from the widest tilt range as possible; otherwise the reconstruction may be uninterpretable. Even if not for geometric obstructions, the increasing pathway of electrons, as the tilt angle is increased, poses the ultimate upper limitation to the projection range. With the maximum tilt angle being fixed, the only way to improve the faithfulness of the reconstruction is by changing the mode of the tilting from single-axis to conical; a point within the object projected with a tilt angle of 60° and a full 360° azimuthal range is then reconstructed as a slightly elliptic (axis ratio 1.2 : 1) sphere.

Cryomicroscopy of crotoxin complex crystals at 400 KV

1989 ◽  
Vol 47 ◽  
pp. 826-827
Author(s):  
Jaap Brink ◽  
Wah Chiu
Keyword(s):  
Signal To Noise Ratio ◽  
3D Structure ◽  
Three Dimensional ◽  
Carbon Films ◽  
Depth Of Field ◽  
Basic Subunit ◽  
Ewald Sphere ◽  
Diffraction Patterns ◽  
Complex Crystals ◽  
Acidic Subunit

The crotoxin complex is a potent neurotoxin composed of a basic subunit (Mr = 12,000) and an acidic subunit (M = 10,000). The basic subunit possesses phospholipase activity whereas the acidic subunit shows no enzymatic activity at all. The complex's toxocity is expressed both pre- and post-synaptically. The crotoxin complex forms thin crystals suitable for electron crystallography. The crystals diffract up to 0.16 nm in the microscope, whereas images show reflections out to 0.39 nm2. Ultimate goal in this study is to obtain a three-dimensional (3D-) structure map of the protein around 0.3 nm resolution. Use of 100 keV electrons in this is limited; the unit cell's height c of 25.6 nm causes problems associated with multiple scattering, radiation damage, limited depth of field and a more pronounced Ewald sphere curvature. In general, they lead to projections of the unit cell, which at the desired resolution, cannot be interpreted following the weak-phase approximation. Circumventing this problem is possible through the use of 400 keV electrons. Although the overall contrast is lowered due to a smaller scattering cross-section, the signal-to-noise ratio of especially higher order reflections will improve due to a smaller contribution of inelastic scattering. We report here our preliminary results demonstrating the feasability of the data collection procedure at 400 kV.Crystals of crotoxin complex were prepared on carbon-covered holey-carbon films, quench frozen in liquid ethane, inserted into a Gatan 626 holder, transferred into a JEOL 4000EX electron microscope equipped with a pair of anticontaminators operating at −184°C and examined under low-dose conditions. Selected area electron diffraction patterns (EDP's) and images of the crystals were recorded at 400 kV and −167°C with dose levels of 5 and 9.5 electrons/Å, respectively.

Detection, Averaging, and 3D Reconstruction of Biological Specimens on Hypercubes (Transputer-based) Computers

1990 ◽  
Vol 48 (1) ◽  
pp. 454-455
Author(s):  
Jose-Maria Carazo ◽  
I. Benavides ◽  
S. Marco ◽  
J.L. Carrascosa ◽  
E.L. Zapata
Keyword(s):  
3D Reconstruction ◽  
3D Structure ◽  
Three Dimensional ◽  
Software Tools ◽  
Mapping Method ◽  
Computer Architectures ◽  
Parallel Computer ◽  
Reconstruction Process ◽  
Computing Power ◽  
Order Of Magnitude

Obtaining the three-dimensional (3D) structure of negatively stained biological specimens at a resolution of, typically, 2 - 4 nm is becoming a relatively common practice in an increasing number of laboratories. A combination of new conceptual approaches, new software tools, and faster computers have made this situation possible. However, all these 3D reconstruction processes are quite computer intensive, and the middle term future is full of suggestions entailing an even greater need of computing power. Up to now all published 3D reconstructions in this field have been performed on conventional (sequential) computers, but it is a fact that new parallel computer architectures represent the potential of order-of-magnitude increases in computing power and should, therefore, be considered for their possible application in the most computing intensive tasks.We have studied both shared-memory-based computer architectures, like the BBN Butterfly, and local-memory-based architectures, mainly hypercubes implemented on transputers, where we have used the algorithmic mapping method proposed by Zapata el at. In this work we have developed the basic software tools needed to obtain a 3D reconstruction from non-crystalline specimens (“single particles”) using the so-called Random Conical Tilt Series Method. We start from a pair of images presenting the same field, first tilted (by ≃55°) and then untilted. It is then assumed that we can supply the system with the image of the particle we are looking for (ideally, a 2D average from a previous study) and with a matrix describing the geometrical relationships between the tilted and untilted fields (this step is now accomplished by interactively marking a few pairs of corresponding features in the two fields). From here on the 3D reconstruction process may be run automatically.

Proteomic Analysis of Medicinal Plant Calotropis Gigantea by insilico Peptide Mass Fingerprinting

2020 ◽  
Vol 16 ◽  
Author(s):  
Saad Ur Rehman ◽  
Muhammad Rizwan ◽  
Sajid Khan ◽  
Azhar Mehmood ◽  
Anum Munir
Keyword(s):  
Medicinal Plant ◽  
Structure Prediction ◽  
3D Structure ◽  
Peptide Mass Fingerprinting ◽  
Protein Docking ◽  
Receptor Protein ◽  
Human Leukemia ◽  
Protein Database ◽  
Calotropis Gigantea ◽  
Peptide Mass

: Medicinal plants are the basic source of medicinal compounds traditionally used for the treatment of human diseases. Calotropis gigantea a medicinal plant belonging to the family of Apocynaceae in the plant kingdom and subfamily Asclepiadaceae usually bearing multiple medicinal properties to cure a variety of diseases. Background: The Peptide Mass Fingerprinting (PMF) identifies the proteins from a reference protein database by comparing the amino acid sequence that is previously stored in a database and identified. Method: The calculation of insilico peptide masses is done through the ExPASy PeptideMass and these masses are used to identify the peptides from MASCOT online server. Anticancer probability is calculated from the iACP server, docking of active peptides is done by CABS-dock the server. Objective: The purpose of the study is to identify the peptides having anti-cancerous properties by in-silico peptide mass fingerprinting. Results : The anti-cancerous peptides are identified with the MASCOT peptide mass fingerprinting server, the identified peptides are screened and only the anti-cancer are selected. De novo peptide structure prediction is used for 3D structure prediction by PEP-FOLD 3 server. The docking results confirm strong bonding with the interacting amino acids of the receptor protein of breast cancer BRCA1 which shows the best peptide binding to the Active chain, the human leukemia protein docking with peptides shows the accurate binding. Conclusion : These peptides are stable and functional and are the best way for the treatment of cancer and many other deadly diseases.

scholarly journals A Novel Pseudomonas geniculata AGE Family Epimerase/Isomerase and Its Application in d-Mannose Synthesis

Foods ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 1809
Author(s):  
Zhanzhi Liu ◽  
Ying Li ◽  
Jing Wu ◽  
Sheng Chen
Keyword(s):  
3D Structure ◽  
Three Dimensional ◽  
Optimal Temperature ◽  
Reaction Conditions ◽  
Enzymatic Production ◽  
Physiological Properties ◽  
Potential Applications ◽  
Kinetics Of ◽  
Optimal Reaction ◽  
Gene Age

d-mannose has exhibited excellent physiological properties in the food, pharmaceutical, and feed industries. Therefore, emerging attention has been applied to enzymatic production of d-mannose due to its advantage over chemical synthesis. The gene age of N-acetyl-d-glucosamine 2-epimerase family epimerase/isomerase (AGEase) derived from Pseudomonas geniculata was amplified, and the recombinant P. geniculata AGEase was characterized. The optimal temperature and pH of P. geniculata AGEase were 60 °C and 7.5, respectively. The Km, kcat, and kcat/Km of P. geniculata AGEase for d-mannose were 49.2 ± 8.5 mM, 476.3 ± 4.0 s−1, and 9.7 ± 0.5 s−1·mM−1, respectively. The recombinant P. geniculata AGEase was classified into the YihS enzyme subfamily in the AGE enzyme family by analyzing its substrate specificity and active center of the three-dimensional (3D) structure. Further studies on the kinetics of different substrates showed that the P. geniculata AGEase belongs to the d-mannose isomerase of the YihS enzyme. The P. geniculata AGEase catalyzed the synthesis of d-mannose with d-fructose as a substrate, and the conversion rate was as high as 39.3% with the d-mannose yield of 78.6 g·L−1 under optimal reaction conditions of 200 g·L−1d-fructose and 2.5 U·mL−1P. geniculata AGEase. This novel P. geniculata AGEase has potential applications in the industrial production of d-mannose.

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