Can correct protein models be identified?

By Björn Wallner, Arne Elofsson. 2003

755 citations recorded by the source corpus.

Subfields: Materials Chemistry, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Materials Chemistry

In Molecular Biology

Citations in the corpus

Toward the estimation of the absolute quality of individual protein structure models (2010, background): “…alternative models of the same protein sequence (Benkert et al., 2008; Eramian et al., 2008; Marti-Renom et al., 2000; McGuffin, 2008; Melo and Feytmans, 1998; Pettitt et al., 2005; Randall and Baldi, 2008; Samudrala and Moult, 1998; Tosatto, 2005; Wallner and Elofsson, 2003; Zhou and Zhou, 2002).”
Outcome of a Workshop on Applications of Protein Models in Biomedical Research (2009, background): “2006; Sippl, 1993; Wallner and Elofsson, 2003).”
ProQ3D: improved model quality assessments using deep learning (2016, methodology): “In the benchmark we used the updated ProQ version (ProQres) that is able to predict the local model quality (Wallner and Elofsson, 2006).”
The HDOCK server for integrated protein–protein docking (2020, methodology): “Speci ﬁ cally, for user-input structures, if the input is a protein, the ProQ program is used to evaluate the quality 81,82 , where the LGscore and MaxSub are measured as the quality parameters.”
Estimation of model accuracy in CASP13 (2019, methodology): “The finally used network has been trained on (3) and contains 3 hidden layers of width 20.”
Methods for estimation of model accuracy in CASP12 (2017, background): “77 From original ProQ publication.(6) From ProQ2 publication.”
SELECTpro: effective protein model selection using a structure-based energy function resistant to BLUNDERs (2008, methodology): “For example, the metaserver method Pmodeller [22] combines consensus (Pcons [23]) and structure-based methods (ProQ [24]) to predict protein structures more accurately than either method in isolation.”
Improved model quality assessment using ProQ2 (2012, methodology): “Residues were grouped in six different groups: (1) Arg, Lys; (2) Asp, Glu; (3) His, Phe, Trp, Tyr; (4) Asn, Gln, Ser, Thr; (5) Ala, Ile, Leu, Met, Val, Cys; (6) Gly, Pro [15,33].”
The ModFOLD server for the quality assessment of protein structural models (2008, methodology): “Several MQAP servers exist for carrying out predictions on single models, for example ProQ (Wallner and Elofsson, 2003) and ProSA-web (Wiederstein and Sippl, 2007).”
QMEAN server for protein model quality estimation (2009, methodology): “…quality assessment servers operating on single models in its constituting terms: e.g. in comparison to the ModFOLD server (20) and the ProQ method (21), QMEAN additionally includes a more detailed distance-dependent all-atom interaction potential as well as a torsion angle potential over three…”
Improving sequence-based fold recognition by using 3D model quality assessment (2005, methodology): “The greatest number of improved results are seen here when the GDT_TS score is used as the similiary measure, though there is little in it, and the outcome shows that the use of MODCHECK, ProQ-LG and FRST show improvements when applied to FFAS, FFAS03, Orfeus and Pcons—four generated models.”
Identification of correct regions in protein models using structural, alignment, and consensus information (2006, methodology): “To reduce the number of parameters, the 167 atom types were grouped into thirteen different groups as described in Wallner and Elofsson (2003) .”
Pcons5: combining consensus, structural evaluation and fold recognition scores (2005, methodology): “This is the case for 20% of the Pmodeller5 models, but in none of these cases is the model significantly improved by the homology modeling procedure, thus the main reason for the increase in performance is the re-ranking of the models using ProQ [28].”
QMEAN: A comprehensive scoring function for model quality assessment (2008, background): “…for various purposes among which are fold recognition,33–37 identification of the native structure among decoys,38,39 model quality assessment25,40,41 or prediction of thermo stability.42 –45 Combining several statistical potential terms covering different aspects of protein structures or models…”