Protein Structure Evaluation using an All-Atom Energy Based Empirical Scoring Function

Narang, Pooja; Bhushan, Kumkum; Bose, Surojit; Jayaram, B.

doi:10.1080/07391102.2006.10531234

Cited by 35 publications

(22 citation statements)

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“…To verify this, we calculated van der Waals energies of 20 homotrimers in each of the 19683 conformations. As described in our earlier work, 83,84 we have adopted AMBER parameters (AMBERff99SB) and a 12−6 Figure 10. The data corresponding to zero population of tripeptides are excluded.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

From Ramachandran Maps to Tertiary Structures of Proteins

2015

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Sequence to structure of proteins is an unsolved problem. A possible coarse grained resolution to this entails specification of all the torsional (Φ, Ψ) angles along the backbone of the polypeptide chain. The Ramachandran map quite elegantly depicts the allowed conformational (Φ, Ψ) space of proteins which is still very large for the purposes of accurate structure generation. We have divided the allowed (Φ, Ψ) space in Ramachandran maps into 27 distinct conformations sufficient to regenerate a structure to within 5 Å from the native, at least for small proteins, thus reducing the structure prediction problem to a specification of an alphanumeric string, i.e., the amino acid sequence together with one of the 27 conformations preferred by each amino acid residue. This still theoretically results in 27(n) conformations for a protein comprising "n" amino acids. We then investigated the spatial correlations at the two-residue (dipeptide) and three-residue (tripeptide) levels in what may be described as higher order Ramachandran maps, with the premise that the allowed conformational space starts to shrink as we introduce neighborhood effects. We found, for instance, for a tripeptide which potentially can exist in any of the 27(3) "allowed" conformations, three-fourths of these conformations are redundant to the 95% confidence level, suggesting sequence context dependent preferred conformations. We then created a look-up table of preferred conformations at the tripeptide level and correlated them with energetically favorable conformations. We found in particular that Boltzmann probabilities calculated from van der Waals energies for each conformation of tripeptides correlate well with the observed populations in the structural database (the average correlation coefficient is ∼0.8). An alpha-numeric string and hence the tertiary structure can be generated for any sequence from the look-up table within minutes on a single processor and to a higher level of accuracy if secondary structure can be specified. We tested the methodology on 100 small proteins, and in 90% of the cases, a structure within 5 Å is recovered. We thus believe that the method presented here provides the missing link between Ramachandran maps and tertiary structures of proteins. A Web server to convert a tertiary structure to an alphanumeric string and to predict the tertiary structure from the sequence of a protein using the above methodology is created and made freely accessible at http://www.scfbio-iitd.res.in/software/proteomics/rm2ts.jsp.

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Section: ■ Results and Discussionmentioning

confidence: 99%

From Ramachandran Maps to Tertiary Structures of Proteins

2015

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“…jsp) for narrowing down the search space of tertiary structures of small globular proteins (Narang et al 2005(Narang et al , 2006. It combines physics based potentials with biophysical fi lters to arrive at 100 plausible candidate structures starting from sequence and secondary structure information.…”

Section: Discussionmentioning

confidence: 99%

ProRegIn: A regularity index for the selection of native-like tertiary structures of proteins

et al. 2007

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Automated protein tertiary structure prediction from sequence information alone remains an elusive goal to computational prescriptions. Dividing the problem into three stages viz. secondary structure prediction, generation of plausible main chain loop dihedrals and side chain dihedral optimization, considerable progress has been achieved in our laboratory (http://www.scfbio-iitd.res.in/bhageerath/index.jsp) and elsewhere for proteins with less than 100 amino acids. As a part of our on-going efforts in this direction and to facilitate tertiary structure selection/rejection in containing the combinatorial explosion of trial structures for a specified amino acid sequence, we describe here a web-enabled tool ProRegIn (Protein Regularity Index) developed based on the regularity in the Phi, Psi dihedral angles of the amino acids that constitute loop regions. We have analysed the dihedrals in loop regions in a non-redundant dataset of 7351 proteins drawn from the Protein Data Bank and categorized them as helix-like or sheet-like (regular) or irregular. We noticed that the regularity thus defined exceeds 86% for Phi barring glycine and 70% for Psi for all the amino acid side chains including glycine, compelling us to reexamine the conventional view that loops are irregular regions structurally. The regularity index is presented here as a simple tool that finds its application in protein structure analysis as a discriminatory scoring function for rapid screening before the more compute intensive atomic level energy calculations could be undertaken. The tool is made freely accessible over the internet at www.scfbio-iitd.res.in/software/proregin.jsp.

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“…There is lot of work gone into proteins to understand the ultimate truth of real hideous information [1][2][3]. In these line and to understand the buried information in proteins this work has been taken up.…”

Section: Introductionmentioning

confidence: 99%

The Nature of Proteins

Ekambaram

Vinobha²,

Vijayasarathy

et al. 2009

2009 International Association of Computer Science and Information Technology - Spring Conference

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There is lot of work gone into proteins to understand the nature of proteins. Hydrophobic interaction is the dominant force that drives the proteins to carry out the biochemical reactions in all living being. Carbon is the only element that contributes towards this hydrophobic interaction. In this study the carbon distribution along the protein sequence has been computed by representing the protein sequence as a series of atoms instead of amino acids. Given any length, there is a maximum frequency occurs at 31.44% of carbon. That is any globular proteins prefer to have 31.44% of carbon. This is not only in global but also in local. This newly identified carbon distribution profile is hoped to help in identification and development of active sites, study of protein stability, evolutionary understating of proteins, gene identification and to solve the long-standing problem of protein-protein and protein-DNA specific and non-specific interactions. This can also distinguish poisonous, viral and diseased proteins from the normal one.

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Protein Structure Evaluation using an All-Atom Energy Based Empirical Scoring Function

Cited by 35 publications

References 100 publications

From Ramachandran Maps to Tertiary Structures of Proteins

From Ramachandran Maps to Tertiary Structures of Proteins

ProRegIn: A regularity index for the selection of native-like tertiary structures of proteins

The Nature of Proteins

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