How Accurately Can We Model Protein Structures with Dihedral Angles?

Author(s):  
Xuefeng Cui ◽  
Shuai Cheng Li ◽  
Dongbo Bu ◽  
Babak Alipanahi Ramandi ◽  
Ming Li
2013 ◽  
Vol 8 (1) ◽  
pp. 5 ◽  
Author(s):  
Xuefeng Cui ◽  
Shuai Cheng Li ◽  
Dongbo Bu ◽  
Babak Alipanahi ◽  
Ming Li

Biomolecules ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 193 ◽  
Author(s):  
William R. Taylor

The model of protein folding proposed by Ptitsyn and colleagues involves the accretion of secondary structures around a nucleus. As developed by Efimov, this model also provides a useful way to view the relationships among structures. Although somewhat eclipsed by later databases based on the pairwise comparison of structures, Efimov’s approach provides a guide for the more automatic comparison of proteins based on an encoding of their topology as a string. Being restricted to layers of secondary structures based on beta sheets, this too has limitations which are partly overcome by moving to a more generalised secondary structure lattice that can encompass both open and closed (barrel) sheets as well as helical packing of the type encoded by Murzin and Finkelstein on small polyhedra. Regular (crystalline) lattices, such as close-packed hexagonals, were found to be too limited so pseudo-latticses were investigated including those found in quasicrystals and the Bernal tetrahedron-based lattice that he used to represent liquid water. The Bernal lattice was considered best and used to generate model protein structures. These were much more numerous than those seen in Nature, posing the open question of why this might be.


Author(s):  
Hannes Braberg ◽  
Ignacia Echeverria ◽  
Robyn M. Kaake ◽  
Andrej Sali ◽  
Nevan J. Krogan

2016 ◽  
Author(s):  
Nicole Balasco ◽  
Luciana Esposito ◽  
Luigi Vitagliano

The definition of the structural basis of the conformational preferences of the genetically encoded aminoacid residues is crucial to decipher the physical code of protein folding and would have a huge impact on our understanding of protein structure and function. Indeed, although a large number of computational and experimental investigations have highlighted that the different protein residues show distinct conformational propensities, none of the current hypotheses is able to satisfactorily explain these preferences. In the last decades, we and others have clearly demonstrated that several geometrical parameters of protein backbone (bond angles, peptide bond distortions from planarity, and pyramidalization of the carbonyl carbon atom) are heavily dependent on the local conformation (φ/ψ dihedral angles) [1-8]. Moreover, a correlation between bond distances such as CO and CN has been detected in ultrahigh resolution protein structures [9]. Concerning bond angles, most of these investigations have been focused on the NCαC (τ) angle, shown to be significantly affected by both φ/ψ dihedral angles. In this framework, we here evaluated the impact of the local geometry on the residues conformational preferences by performing statistical analyses on a dataset of non-redundant protein chains selected from the Protein data Bank (PDB). Our data highlight a clear link between residue conformational preferences and local geometry. References 1. Karplus PA. Protein Sci. 1996; 5:1406-20. 2. Berkholz DS, Shapovalov MV, Dunbrack RL Jr, Karplus PA. Structure, 2009;17:1316-25. 3. Esposito L, Balasco N, De Simone A, Berisio R, Vitagliano L. Biomed Res Int, 2013;2013:326914. 4. Improta, R., L. Vitagliano, and L. Esposito, Proteins, 2015; 83:1973-86. 5. Improta, R., L. Vitagliano, and L. Esposito, Acta crystallographica D, 2015; 71:1272-83. 6. Esposito L, De Simone A, Zagari A, Vitagliano L. J Mol Biol, 2005; 347:483-7. 7. Berkholz DS, Driggers CM, Shapovalov MV, Dunbrack RL Jr, Karplus PA. Proc Natl Acad Sci, 2012;109:449-53. 8. Esposito L, Vitagliano L, Zagari A, Mazzarella L. Protein Sci, 2000; 9:2038-42. 9. Esposito L, Vitagliano L, Zagari A, Mazzarella L. Protein Eng, 2000; 13:825-8


2005 ◽  
Vol 347 (3) ◽  
pp. 483-487 ◽  
Author(s):  
Luciana Esposito ◽  
Alfonso De Simone ◽  
Adriana Zagari ◽  
Luigi Vitagliano

2003 ◽  
Vol 36 (1) ◽  
pp. 34-42 ◽  
Author(s):  
John P. Priestle

Because of the relatively low-resolution diffraction of typical protein crystals, structure refinement is usually carried out employing stereochemical restraints to increase the effective number of observations. Well defined values for bond lengths and angles are available from small-molecule crystal structures. Such values do not exist for dihedral angles because of the concern that the strong crystal contacts in small-molecule crystal structures could distort the dihedral angles. This paper examines the dihedral-angle distributions in ultra-high-resolution protein structures (1.2 Å or better) as a means of analysing the population frequencies of dihedral angles in proteins and compares these with the stereochemical restraints currently used in one of the more widely used molecular-dynamics refinement packages,X-PLOR, and its successor,CNS. Discrepancies between the restraints used in these programs and what is actually seen in high-resolution protein structures are examined and an improved set of dihedral-angle restraint parameters are derived from these inspections.


2019 ◽  
Vol 17 (02) ◽  
pp. 1950006 ◽  
Author(s):  
Ashish Runthala ◽  
Shibasish Chowdhury

In contrast to ab-initio protein modeling methodologies, comparative modeling is considered as the most popular and reliable algorithm to model protein structure. However, the selection of the best set of templates is still a major challenge. An effective template-ranking algorithm is developed to efficiently select only the reliable hits for predicting the protein structures. The algorithm employs the pairwise as well as multiple sequence alignments of template hits to rank and select the best possible set of templates. It captures several key sequences and structural information of template hits and converts into scores to effectively rank them. This selected set of templates is used to model a target. Modeling accuracy of the algorithm is tested and evaluated on TBM-HA domain containing CASP8, CASP9 and CASP10 targets. On an average, this template ranking and selection algorithm improves GDT-TS, GDT-HA and TM_Score by 3.531, 4.814 and 0.022, respectively. Further, it has been shown that the inclusion of structurally similar templates with ample conformational diversity is crucial for the modeling algorithm to maximally as well as reliably span the target sequence and construct its near-native model. The optimal model sampling also holds the key to predict the best possible target structure.


2018 ◽  
Author(s):  
Alberto Perez ◽  
Kari Gaalswyk ◽  
Christopher P. Jaroniec ◽  
Justin L. MacCallum

AbstractThere is a pressing need for new computational tools to integrate data from diverse experimental approaches in structural biology. We present a strategy that combines sparse paramagnetic solid-state NMR restraints with physics-based atomistic simulations. Our approach explicitly accounts for uncertainty in the interpretation of experimental data through the use of a semi-quantitative mapping between the data and the restraint energy that is calibrated by extensive simulations. We apply our approach to solid-state NMR data for the model protein GB1 labeled with Cu2+-EDTA at six different sites. We are able to determine the structure to ca. 1 Å accuracy within a single day of computation on a modest GPU cluster. We further show that in 4 of 6 cases, the data from only a single paramagnetic tag are sufficient to fold the protein to high accuracy.


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