Bhageerath-H: A homology/ab initio hybrid server for predicting tertiary structures of monomeric soluble proteins

Abstract Background Accurate prediction of protein tertiary structures is highly desired as the knowledge of protein structures provides invaluable insights into protein functions. We have designed two approaches to protein structure prediction, including a template-based modeling approach (called ProALIGN) and an ab initio prediction approach (called ProFOLD). Briefly speaking, ProALIGN aligns a target protein with templates through exploiting the patterns of context-specific alignment motifs and then builds the final structure with reference to the homologous templates. In contrast, ProFOLD uses an end-to-end neural network to estimate inter-residue distances of target proteins and builds structures that satisfy these distance constraints. These two approaches emphasize different characteristics of target proteins: ProALIGN exploits structure information of homologous templates of target proteins while ProFOLD exploits the co-evolutionary information carried by homologous protein sequences. Recent progress has shown that the combination of template-based modeling and ab initio approaches is promising. Results In the study, we present FALCON2, a web server that integrates ProALIGN and ProFOLD to provide high-quality protein structure prediction service. For a target protein, FALCON2 executes ProALIGN and ProFOLD simultaneously to predict possible structures and selects the most likely one as the final prediction result. We evaluated FALCON2 on widely-used benchmarks, including 104 CASP13 (the 13th Critical Assessment of protein Structure Prediction) targets and 91 CASP14 targets. In-depth examination suggests that when high-quality templates are available, ProALIGN is superior to ProFOLD and in other cases, ProFOLD shows better performance. By integrating these two approaches with different emphasis, FALCON2 server outperforms the two individual approaches and also achieves state-of-the-art performance compared with existing approaches. Conclusions By integrating template-based modeling and ab initio approaches, FALCON2 provides an easy-to-use and high-quality protein structure prediction service for the community and we expect it to enable insights into a deep understanding of protein functions.

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Ab initio construction of protein tertiary structures using a hierarchical approach

Journal of Molecular Biology ◽

10.1006/jmbi.2000.3835 ◽

2000 ◽

Vol 300 (1) ◽

pp. 171-185 ◽

Cited By ~ 132

Author(s):

Yu Xia ◽

Enoch S. Huang ◽

Michael Levitt ◽

Ram Samudrala

Keyword(s):

Ab Initio ◽

Hierarchical Approach ◽

Tertiary Structures

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Ab initio method for predicting tertiary structures of globular proteins

Fluid Phase Equilibria ◽

10.1016/s0378-3812(97)00285-9 ◽

1998 ◽

Vol 144 (1-2) ◽

pp. 403-413 ◽

Cited By ~ 2

Author(s):

Yukio Kobayashi ◽

Hiroyuki Sasabe ◽

Nobuhiko Saitô

Keyword(s):

Ab Initio ◽

Globular Proteins ◽

Ab Initio Method ◽

Tertiary Structures

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Resdiue-residue contact driven protein structure prediction using optimization and machine learning

10.32469/10355/62281 ◽

2017 ◽

Author(s):

◽

Badri Adhikari

Keyword(s):

Machine Learning ◽

Protein Structure ◽

Ab Initio ◽

Protein Structure Prediction ◽

Structure Prediction ◽

Tertiary Structures ◽

Contact Prediction ◽

Residue Contacts ◽

Structure Reconstruction ◽

Ab Initio Structure

Significant improvements in the prediction of protein residue-residue contacts are observed in the recent years. These contacts, predicted using a variety of coevolution-based and machine learning methods, are the key contributors to the recent progress in ab initio protein structure prediction, as demonstrated in the recent CASP experiments. Continuing the development of new methods to reliably predict contact maps, tools to assess the utility of predicted contacts, and methods to construct protein tertiary structures from predicted contacts, are essential to further improve ab initio structure prediction. In this dissertation, three contributions are described -- (a) DNCON2, a two-level convolutional neural network-based method for protein contact prediction, (b) ConEVA, a toolkit for contact assessment and evaluation, and (c) CONFOLD, a method of building protein 3D structures from predicted contacts and secondary structures. Additional related contributions on protein contact prediction and structure reconstruction are also described. DNCON2 and CONFOLD demonstrate state-of-the-art performance on contact prediction and structure reconstruction from scratch. All three protein structure methods are available as software or web server which are freely available to the scientific community.

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An Alternative Approach to Protein Folding

BioMed Research International ◽

10.1155/2013/583045 ◽

2013 ◽

Vol 2013 ◽

pp. 1-10

Author(s):

Yeona Kang ◽

Charles M. Fortmann

Keyword(s):

Protein Folding ◽

Ab Initio ◽

Diffusion Model ◽

Diffusion Theory ◽

Secondary Structures ◽

Drift Diffusion Model ◽

Drift Diffusion ◽

Desktop Computer ◽

Tertiary Structures ◽

Protein Secondary Structures

A diffusion theory-based, all-physicalab initioprotein folding simulation is described and applied. The model is based upon the drift and diffusion of protein substructures relative to one another in the multiple energy fields present. Without templates or statistical inputs, the simulations were run at physiologic and ambient temperatures (including pH). Around 100 protein secondary structures were surveyed, and twenty tertiary structures were determined. Greater than 70% of the secondary core structures with over 80% alpha helices were correctly identified on protein ranging from 30 to 200 amino-acid sequence. The drift-diffusion model predicted tertiary structures with RMSD values in the 3–5 Angstroms range for proteins ranging 30 to 150 amino acids. These predictions are among the best for an allab initioprotein simulation. Simulations could be run entirely on a desktop computer in minutes; however, more accurate tertiary structures were obtained using molecular dynamic energy relaxation. The drift-diffusion model generated realistic energy versus time traces. Rapid secondary structures followed by a slow compacting towards lower energy tertiary structures occurred after an initial incubation period in agreement with observations.

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A COMBINED APPROACH FOR AB INITIO CONSTRUCTION OF LOW RESOLUTION PROTEIN TERTIARY STRUCTURES FROM SEQUENCE

Biocomputing '99 ◽

10.1142/9789814447300_0050 ◽

1998 ◽

Cited By ~ 2

Author(s):

RAM SAMUDRALA ◽

YU XIA ◽

MICHAEL LEVITT ◽

ENOCH S HUANG

Keyword(s):

Ab Initio ◽

Combined Approach ◽

Low Resolution ◽

Tertiary Structures

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Ab initio band theory approach to electron energy loss near edge structures

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100104595 ◽

1988 ◽

Vol 46 ◽

pp. 506-507

Author(s):

Xudong Weng ◽

O.F. Sankey ◽

Peter Rez

Keyword(s):

Ab Initio ◽

Local Density ◽

Interpolation Method ◽

Atomic Orbital ◽

Plane Waves ◽

Large Set ◽

Theory Approach ◽

Band Theory ◽

Atomic Orbitals ◽

Pseudopotential Calculations

Single electron band structure techniques have been applied successfully to the interpretation of the near edge structures of metals and other materials. Among various band theories, the linear combination of atomic orbital (LCAO) method is especially simple and interpretable. The commonly used empirical LCAO method is mainly an interpolation method, where the energies and wave functions of atomic orbitals are adjusted in order to fit experimental or more accurately determined electron states. To achieve better accuracy, the size of calculation has to be expanded, for example, to include excited states and more-distant-neighboring atoms. This tends to sacrifice the simplicity and interpretability of the method.In this paper. we adopt an ab initio scheme which incorporates the conceptual advantage of the LCAO method with the accuracy of ab initio pseudopotential calculations. The so called pscudo-atomic-orbitals (PAO's), computed from a free atom within the local-density approximation and the pseudopotential approximation, are used as the basis of expansion, replacing the usually very large set of plane waves in the conventional pseudopotential method. These PAO's however, do not consist of a rigorously complete set of orthonormal states.

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Torus Circumference and Thickness Parameters From a Linear DNA Size Series Suggest How Toruses Self-Assemble

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100119430 ◽

1985 ◽

Vol 43 ◽

pp. 522-523

Author(s):

George C. Ruben ◽

Kenneth A. Marx

Keyword(s):

Tertiary Structure ◽

Dna Complexes ◽

Tertiary Structures ◽

Self Assembling ◽

Double Stranded Dna ◽

Calf Thymus ◽

Dna Organization ◽

Condensed Dna ◽

Dna Size

Certain double stranded DNA bacteriophage and viruses are thought to have their DNA organized into large torus shaped structures. Morphologically, these poorly understood biological DNA tertiary structures resemble spermidine-condensed DNA complexes formed in vitro in the total absence of other macromolecules normally synthesized by the pathogens for the purpose of their own DNA packaging. Therefore, we have studied the tertiary structure of these self-assembling torus shaped spermidine- DNA complexes in a series of reports. Using freeze-etch, low Pt-C metal (10-15Å) replicas, we have visualized the microscopic DNA organization of both calf Thymus( CT) and linear 0X-174 RFII DNA toruses. In these structures DNA is circumferentially wound, continuously, around the torus into a semi-crystalline, hexagonal packed array of parallel DNA helix sections.

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