Global stability of protein folding from an empirical free energy function

Ruiz‐Blanco, Yasser B.; Marrero-Ponce, Yovani; Paz, Waldo; García, Y.; Salgado, Jesús

doi:10.1016/j.jtbi.2012.12.023

Cited by 15 publications

(10 citation statements)

References 41 publications

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“…Here, 29 indices were calculated, comprising: 1–8) Eight indices associated with the dihedral angles, phi and psi, of the protein’s backbone (wPsiH, wPsiS, wPsiI, wPhiH, wPhiS, wPhiI, Phi, Psi); 9–10) The accessible surface area (A) and the superficiality index (wSp); 11) The buried non-polar area (ΔAnp); 12) A measure of the folding degree (lnFD) introduced in our previous report [41]; 13) The squared radius of the protein (wR2); 14–20) Seven contact-based indices (wNc, wFLC, wNLC, wCO, wLCO, wRWCO, wCTP), each one weighted with seven of the above mentioned amino acid properties (HP, ECI, IP, Z1, Z2, Z3, ISA), in order to distinguish contacts involving different residues; 21–29) Nine thermodynamic indices (Gw(F), Gs(F), W(F), ΔGs, HBd, ΔGel, ΔGw, ΔGLJ, ΔGtor) associated with the number of hydrogen bonds in the backbone of the protein and several empirical approaches capturing folding free energy contributions [42, 43] referring to Lenard-Jones and electrostatic interactions, torsion potential, superficial free energy, hydrophobic effect, etc. A summary of all the structure-based indices is presented in the Additional file 2: Tables SI-3 and SI-4.…”

Section: Methodsmentioning

confidence: 99%

Exploring general-purpose protein features for distinguishing enzymes and non-enzymes within the twilight zone

et al. 2017

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BackgroundComputational prediction of protein function constitutes one of the more complex problems in Bioinformatics, because of the diversity of functions and mechanisms in that proteins exert in nature. This issue is reinforced especially for proteins that share very low primary or tertiary structure similarity to existing annotated proteomes. In this sense, new alignment-free (AF) tools are needed to overcome the inherent limitations of classic alignment-based approaches to this issue. We have recently introduced AF protein-numerical-encoding programs (TI2BioP and ProtDCal), whose sequence-based features have been successfully applied to detect remote protein homologs, post-translational modifications and antibacterial peptides. Here we aim to demonstrate the applicability of 4 AF protein descriptor families, implemented in our programs, for the identification enzyme-like proteins. At the same time, the use of our novel family of 3D–structure-based descriptors is introduced for the first time. The Dobson & Doig (D&D) benchmark dataset is used for the evaluation of our AF protein descriptors, because of its proven structural diversity that permits one to emulate an experiment within the twilight zone of alignment-based methods (pair-wise identity <30%). The performance of our sequence-based predictor was further assessed using a subset of formerly uncharacterized proteins which currently represent a benchmark annotation dataset.ResultsFour protein descriptor families (sequence-composition-based (0D), linear-topology-based (1D), pseudo-fold-topology-based (2D) and 3D–structure features (3D), were assessed using the D&D benchmark dataset. We show that only the families of ProtDCal’s descriptors (0D, 1D and 3D) encode significant information for enzymes and non-enzymes discrimination. The obtained 3D–structure-based classifier ranked first among several other SVM-based methods assessed in this dataset. Furthermore, the model leveraging 1D descriptors, showed a higher success rate than EzyPred on a benchmark annotation dataset from the Shewanella oneidensis proteome.ConclusionsThe applicability of ProtDCal as a general-purpose-AF protein modelling method is illustrated through the discrimination between two comprehensive protein functional classes. The observed performances using the highly diverse D&D dataset, and the set of formerly uncharacterized (hard-to-annotate) proteins of Shewanella oneidensis, places our methodology on the top range of methods to model and predict protein function using alignment-free approaches.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1758-x) contains supplementary material, which is available to authorized users.

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Section: Methodsmentioning

confidence: 99%

Exploring general-purpose protein features for distinguishing enzymes and non-enzymes within the twilight zone

et al. 2017

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“…i-1)Thermodynamics, which are novel physics-based indices designed to describe the main factors involved in protein folding stability [ 28 , 37 ]. These indices deal with residue-residue electronic interactions, Van der Waals interactions, dihedral torsion potential, backbone hydrogen bond formation, and hydrophobic effect.…”

Section: Methodsmentioning

confidence: 99%

“…In addition to computing a wide diversity of sequence- and structure-based descriptors, ProtDCal has an special menu called Thermo&Kinetics , which permits the application of empirical models designed by some of the authors to predict protein folding free energy [ 28 ] and its different contributions: the loss of configurational free energy, the hydrophobic effect free energy and the close-packing interaction free energy; as well as a model for predicting folding rate constant [ 50 ], and a scoring potential intended to discriminate among near-native and non-native structural decoys [ 29 ]. All of these models require PDB files as inputs.…”

Section: Methodsmentioning

confidence: 99%

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ProtDCal: A program to compute general-purpose-numerical descriptors for sequences and 3D-structures of proteins

et al. 2015

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BackgroundThe exponential growth of protein structural and sequence databases is enabling multifaceted approaches to understanding the long sought sequence-structure-function relationship. Advances in computation now make it possible to apply well-established data mining and pattern recognition techniques to these data to learn models that effectively relate structure and function. However, extracting meaningful numerical descriptors of protein sequence and structure is a key issue that requires an efficient and widely available solution.ResultsWe here introduce ProtDCal, a new computational software suite capable of generating tens of thousands of features considering both sequence-based and 3D-structural descriptors. We demonstrate, by means of principle component analysis and Shannon entropy tests, how ProtDCal’s sequence-based descriptors provide new and more relevant information not encoded by currently available servers for sequence-based protein feature generation. The wide diversity of the 3D-structure-based features generated by ProtDCal is shown to provide additional complementary information and effectively completes its general protein encoding capability. As demonstration of the utility of ProtDCal’s features, prediction models of N-linked glycosylation sites are trained and evaluated. Classification performance compares favourably with that of contemporary predictors of N-linked glycosylation sites, in spite of not using domain-specific features as input information.ConclusionsProtDCal provides a friendly and cross-platform graphical user interface, developed in the Java programming language and is freely available at: http://bioinf.sce.carleton.ca/ProtDCal/. ProtDCal introduces local and group-based encoding which enhances the diversity of the information captured by the computed features. Furthermore, we have shown that adding structure-based descriptors contributes non-redundant additional information to the features-based characterization of polypeptide systems. This software is intended to provide a useful tool for general-purpose encoding of protein sequences and structures for applications is protein classification, similarity analyses and function prediction.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-015-0586-0) contains supplementary material, which is available to authorized users.

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“…2). The method requires an understanding of protein catalytic mechanisms and structure‐function relationships as well as thermal stability mechanisms 34–36. However, the scope of rational design applications is still limited due to the weak understanding of the catalytic and thermal stability mechanisms of proteins.…”

Section: Rational Design To Improve Protein Thermal Stabilitymentioning

confidence: 99%

Preis für Eltern‐Kind‐Experimente

2016

Chemie in nserer Zeit

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Global stability of protein folding from an empirical free energy function

Cited by 15 publications

References 41 publications

Exploring general-purpose protein features for distinguishing enzymes and non-enzymes within the twilight zone

Exploring general-purpose protein features for distinguishing enzymes and non-enzymes within the twilight zone

ProtDCal: A program to compute general-purpose-numerical descriptors for sequences and 3D-structures of proteins

Preis für Eltern‐Kind‐Experimente

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