Assessment of Detection and Refinement Strategies for de novo Protein Structures Using Force Field and Statistical Potentials

2006 ◽  
Vol 3 (1) ◽  
pp. 312-324 ◽  
Author(s):  
Michael S. Lee ◽  
Mark A. Olson
Keyword(s):  
Force Field ◽  
De Novo ◽  
Protein Structures ◽  
Statistical Potentials

Statistical Force-Field for Structural Modeling Using Chemical Cross-Linking/mass Spectrometry Distance Constraints

2018 ◽  
Author(s):  
Allan J. R. Ferrari ◽  
Fabio C. Gozzo ◽  
Leandro Martinez
Keyword(s):  
Mass Spectrometry ◽  
Amino Acid ◽  
Force Field ◽  
Protein Structures ◽  
Protein Structure Determination ◽  
Structural Modeling ◽  
Cross Linking ◽  
Amino Acid Residues ◽  
Distance Constraints ◽  
Chemical Cross Linking

<div><p>Chemical cross-linking/Mass Spectrometry (XLMS) is an experimental method to obtain distance constraints between amino acid residues, which can be applied to structural modeling of tertiary and quaternary biomolecular structures. These constraints provide, in principle, only upper limits to the distance between amino acid residues along the surface of the biomolecule. In practice, attempts to use of XLMS constraints for tertiary protein structure determination have not been widely successful. This indicates the need of specifically designed strategies for the representation of these constraints within modeling algorithms. Here, a force-field designed to represent XLMS-derived constraints is proposed. The potential energy functions are obtained by computing, in the database of known protein structures, the probability of satisfaction of a topological cross-linking distance as a function of the Euclidean distance between amino acid residues. The force-field can be easily incorporated into current modeling methods and software. In this work, the force-field was implemented within the Rosetta ab initio relax protocol. We show a significant improvement in the quality of the models obtained relative to current strategies for constraint representation. This force-field contributes to the long-desired goal of obtaining the tertiary structures of proteins using XLMS data. Force-field parameters and usage instructions are freely available at http://m3g.iqm.unicamp.br/topolink/xlff <br></p></div><p></p><p></p>

scholarly journals De novo design of a reversible phosphorylation-dependent switch for membrane targeting

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Leon Harrington ◽  
Jordan M. Fletcher ◽  
Tamara Heermann ◽  
Derek N. Woolfson ◽  
Petra Schwille
Keyword(s):  
Protein Interactions ◽  
Lipid Membrane ◽  
De Novo ◽  
Protein Localization ◽  
Protein Structures ◽  
Spatiotemporal Pattern ◽  
Membrane Targeting ◽  
Protein Protein Interactions ◽  
Reversible Phosphorylation ◽  
Potential Applications

AbstractModules that switch protein-protein interactions on and off are essential to develop synthetic biology; for example, to construct orthogonal signaling pathways, to control artificial protein structures dynamically, and for protein localization in cells or protocells. In nature, the E. coli MinCDE system couples nucleotide-dependent switching of MinD dimerization to membrane targeting to trigger spatiotemporal pattern formation. Here we present a de novo peptide-based molecular switch that toggles reversibly between monomer and dimer in response to phosphorylation and dephosphorylation. In combination with other modules, we construct fusion proteins that couple switching to lipid-membrane targeting by: (i) tethering a ‘cargo’ molecule reversibly to a permanent membrane ‘anchor’; and (ii) creating a ‘membrane-avidity switch’ that mimics the MinD system but operates by reversible phosphorylation. These minimal, de novo molecular switches have potential applications for introducing dynamic processes into designed and engineered proteins to augment functions in living cells and add functionality to protocells.

scholarly journals Optimization in S-SAD phasing - difference between solved and unsolved structure

2014 ◽  
Vol 70 (a1) ◽  
pp. C613-C613
Author(s):  
Jan Stránský ◽  
Tomáš Kovaľ ◽  
Lars Østergaard ◽  
Jarmila Dušková ◽  
Tereza Skálová ◽  
...  
Keyword(s):  
Data Processing ◽  
De Novo ◽  
Protein Structures ◽  
X Ray Diffraction ◽  
X Ray ◽  
Structure Solution ◽  
Sad Phasing ◽  
Optimal Values ◽  
Grant Agency ◽  
Intensity Reading

Development of X-ray diffraction technologies have made de novo phasing of protein structures by single-wavelength anomalous dispersion by sulphur (S-SAD) more common. As anomalous differences in the sulphur atomic factors are in the order of errors of measurement, careful intensity reading and data processing are crucial. S-SAD was used for de novo phasing of a small 12 kDa protein with 4 sulphur atoms per molecule at 2.3 Å, where the data did not enable a straightforward structure solution. Data processing was performed using XDS [1] and scaling using XSCALE. The sulphur substructure was determined by SHELXD [2] and phases were obtained from SHELXE [2]. Both algorithms strongly depend on input parameters and default values did not lead to the correct phases. Therefore a systematic search of optimal values of several parameters was used to find a solution. This method helped to confirm sulphur substructure and to differentiate the handedness of the solutions. Moreover, a script for comfortable conversion of SHELX outputs to MTZ format was developed, using programmes included in the CCP4 package [3]. The previously unsolvable protein structure was successfully resolved with the described procedure. This work was supported by the Grant Agency of the Czech Technical University in Prague, (SGS13/219/OHK4/3T/14), the Czech Science Foundation (P302/11/0855), project BIOCEV CZ.1.05/1.1.00/02.0109 from the ERDF.

scholarly journals Get Phases from Arsenic Anomalous Scattering: de novo SAD Phasing of Two Protein Structures Crystallized in Cacodylate Buffer

PLoS ONE ◽  
2011 ◽  
Vol 6 (9) ◽  
pp. e24227 ◽  
Author(s):  
Xiang Liu ◽  
Heng Zhang ◽  
Xiao-Jun Wang ◽  
Lan-Fen Li ◽  
Xiao-Dong Su
Keyword(s):  
De Novo ◽  
Protein Structures ◽  
Anomalous Scattering ◽  
Cacodylate Buffer ◽  
Sad Phasing

scholarly journals De Novo Protein Design of Photochemical Reaction Centers

2021 ◽  
Author(s):  
Nathan Ennist ◽  
Zhenyu Zhao ◽  
Steven Stayrook ◽  
Bohdana Discher ◽  
P Leslie 'Les' Dutton ◽  
...  
Keyword(s):  
Reaction Center ◽  
Charge Separation ◽  
Rational Design ◽  
De Novo ◽  
Metal Cluster ◽  
Protein Structures ◽  
Essential Elements ◽  
Reaction Centers ◽  
Transient Absorption Spectroscopy

Abstract Natural photosynthetic protein complexes capture sunlight to power the energetic catalysis that supports life on Earth. Yet these natural protein structures carry an evolutionary legacy of complexity and fragility that encumbers protein reengineering efforts and obfuscates the underlying design rules for light-driven charge separation. De novo development of a simplified photosynthetic reaction center protein can clarify practical engineering principles needed to build new enzymes for efficient solar-to-fuel energy conversion. Here we report the rational design, X-ray crystal structure, and electron transfer activity of a multi-cofactor protein that incorporates essential elements of photosynthetic reaction centers. This highly stable, modular artificial protein framework can be reconstituted in vitro with interchangeable redox centers for nanometer-scale photochemical charge separation. Transient absorption spectroscopy demonstrates Photosystem II-like tyrosine and metal cluster oxidation, and we measure charge separation lifetimes exceeding 100 ms, ideal for light-activated catalysis. This de novo-designed reaction center builds upon engineering guidelines established for charge separation in earlier synthetic photochemical triads and modified natural proteins, and it shows how synthetic biology may lead to a new generation of genetically encoded, light-powered catalysts for solar fuel production.

scholarly journals A Generic Force Field for Simulating Native Protein Structures Using Dissipative Particle Dynamics

Soft Matter ◽  
2021 ◽  
Author(s):  
Rakesh K Vaiwala ◽  
Ganapathy Ayappa
Keyword(s):  
Molecular Dynamics ◽  
Force Field ◽  
Molecular Dynamics Simulations ◽  
Dissipative Particle Dynamics ◽  
Protein Structures ◽  
Particle Dynamics ◽  
Coarse Grained ◽  
Native Protein ◽  
Dynamics Simulations

A coarse-grained force field for molecular dynamics simulations of native structures of proteins in a dissipative particle dynamics (DPD) framework is developed. The parameters for bonded interactions are derived by...

scholarly journals Improved chemistry restraints for crystallographic refinement by integrating the Amber force field into Phenix

2020 ◽  
Vol 76 (1) ◽  
pp. 51-62 ◽  
Author(s):  
Nigel W. Moriarty ◽  
Pawel A. Janowski ◽  
Jason M. Swails ◽  
Hai Nguyen ◽  
Jane S. Richardson ◽  
...  
Keyword(s):  
Force Field ◽  
Active Sites ◽  
Protein Structures ◽  
Target Function ◽  
Real Space ◽  
Model Quality ◽  
Nonbonded Interactions ◽  
Amber Force Field ◽  
Quantum Mechanical Representation ◽  
Improved Model

The refinement of biomolecular crystallographic models relies on geometric restraints to help to address the paucity of experimental data typical in these experiments. Limitations in these restraints can degrade the quality of the resulting atomic models. Here, an integration of the full all-atom Amber molecular-dynamics force field into Phenix crystallographic refinement is presented, which enables more complete modeling of biomolecular chemistry. The advantages of the force field include a carefully derived set of torsion-angle potentials, an extensive and flexible set of atom types, Lennard–Jones treatment of nonbonded interactions and a full treatment of crystalline electrostatics. The new combined method was tested against conventional geometry restraints for over 22 000 protein structures. Structures refined with the new method show substantially improved model quality. On average, Ramachandran and rotamer scores are somewhat better, clashscores and MolProbity scores are significantly improved, and the modeling of electrostatics leads to structures that exhibit more, and more correct, hydrogen bonds than those refined using traditional geometry restraints. In general it is found that model improvements are greatest at lower resolutions, prompting plans to add the Amber target function to real-space refinement for use in electron cryo-microscopy. This work opens the door to the future development of more advanced applications such as Amber-based ensemble refinement, quantum-mechanical representation of active sites and improved geometric restraints for simulated annealing.

scholarly journals Protein structure refinement using a quantum mechanics-based chemical shielding predictor

2016 ◽  
Author(s):  
Lars A. Bratholm ◽  
Jan H. Jensen
Keyword(s):  
Quantum Mechanics ◽  
Simulated Annealing ◽  
Chemical Shift ◽  
Force Field ◽  
Chemical Shifts ◽  
Protein Structures ◽  
Empirical Methods ◽  
Structural Refinement ◽  
Chemical Shielding ◽  
Chemical Shift Prediction

The accurate prediction of protein chemical shifts using quantum mechanics (QM)-based method has been the subject of intense research for more than 20 years but so far empirical methods for chemical shift prediction have proven more accurate. In this paper we show that a QM-based predictor of protein backbone and CB chemical shifts (ProCS15, PeerJ 2016, 3:e1344) is of comparable accuracy to empirical chemical shift predictors after chemical shift-based structural refinement that removes small structural errors. We present a method by which quantum chemistry based predictions of isotropic chemical shielding values (ProCS15) can be used to refine protein structures using Markov Chain Monte Carlo (MCMC) simulations, relating the chemical shielding values to the experimental chemical shifts probabilistically. Two kinds of MCMC structural refinement simulations were performed using force field geometry optimized X-ray structures as starting points: Simulated annealing of the starting structure and constant temperature MCMC simulation followed by simulated annealing of a representative ensemble structure. Annealing of the CHARMM structure changes the CA-RMSD by an average of 0.4 Å but lowers the chemical shift RMSD by 1.0 and 0.7 ppm for CA and N. Conformational averaging has a relatively small effect (0.1 - 0.2 ppm) on the overall agreement with carbon chemical shifts but lowers the error for nitrogen chemical shifts by 0.4 ppm. If a residue-specific offset is included the ProCS15 predicted chemical shifts have RMSD values relative to experiment that are comparable to popular empirical chemical shift predictors. The annealed representative ensemble structures differs in CA-RMSD relative to the initial structures by an average of 2.0 Å, with >2.0 Å difference for six proteins. In four of the cases, the largest structural differences arise in structurally flexible regions of the protein as determined by NMR, and in the remaining two cases, the large structural change may be due to force field deficiencies. The overall accuracy of the empirical methods are slightly improved by annealing the CHARMM structure with ProCS15, which may suggest that the minor structural changes introduced by ProCS15-based annealing improves the accuracy of the protein structures. Having established that QM-based chemical shift prediction can deliver the same accuracy as empirical shift predictors we hope this can help increase the accuracy of related approaches such as QM/MM or linear scaling approaches or interpreting protein structural dynamics from QM-derived chemical shift.

scholarly journals Protein designer David Baker: I like doing things that seem like magic

2020 ◽  
Vol 7 (8) ◽  
pp. 1410-1412
Author(s):  
Weijie Zhao ◽  
Chu Wang
Keyword(s):  
Protein Design ◽  
De Novo ◽  
Protein Structures ◽  
Computational Prediction ◽  
Biological Functions ◽  
Personal Experiences ◽  
De Novo Protein Design ◽  
And Function ◽  
The University ◽  
Opening Up

Abstract Search ‘de novo protein design’ on Google and you will find the name David Baker in all results of the first page. Professor David Baker at the University of Washington and other scientists are opening up a new world of fantastic proteins. Protein is the direct executor of most biological functions and its structure and function are fully determined by its primary sequence. Baker's group developed the Rosetta software suite that enabled the computational prediction and design of protein structures. Being able to design proteins from scratch means being able to design executors for diverse purposes and benefit society in multiple ways. Recently, NSR interviewed Prof. Baker on this fast-developing field and his personal experiences.

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