Fuzzy-oil-drop hydrophobic force field--a model to represent late-stage folding (in silico) of lysozyme

A model of hydrophobic collapse (in silico), which is generally considered to be the driving force for protein folding, is presented in this work. The model introduces the external field in the form of a fuzzy-oil-drop assumed to represent the environment. The drop is expressed in the form of a three-dimensional Gauss function. The usual probability value is assumed to represent the hydrophobicity distribution in the three-dimensional space of the virtual environment. The differences between this idealized hydrophobicity distribution and the one represented by the folded polypeptide chain is the parameter to be minimized in the structure optimization procedure. The size of fuzzy-oil-drop is critical for the folding process. A strong correlation between protein length and the dimension of the native and early-stage molecular form was found on the basis of single-domain proteins analysis. A previously presented early-stage folding (in silico) model was used to create the starting structure for the procedure of late-stage folding of lysozyme. The results of simulation were found to be promising, although additional improvements for the formation of beta-structure and disulfide bonds as well as the participation of natural ligand in folding process seem to be necessary.     

The utility of geometrical and chemical restraint information extracted from predicted ligand-binding sites in protein structure refinement

Exhaustive exploration of molecular interactions at the level of complete proteomes requires efficient and reliable computational approaches to protein function inference. Ligand docking and ranking techniques show considerable promise in their ability to quantify the interactions between proteins and small molecules. Despite the advances in the development of docking approaches and scoring functions, the genome-wide application of many ligand docking/screening algorithms is limited by the quality of the binding sites in theoretical receptor models constructed by protein structure prediction. In this study, we describe a new template-based method for the local refinement of ligand-binding regions in protein models using remotely related templates identified by threading. We designed a Support Vector Regression (SVR) model that selects correct binding site geometries in a large ensemble of multiple receptor conformations. The SVR model employs several scoring functions that impose geometrical restraints on the Cα positions, account for the specific chemical environment within a binding site and optimize the interactions with putative ligands. The SVR score is well correlated with the RMSD from the native structure; in 47% (70%) of the cases, the Pearson’s correlation coefficient is >0.5 (>0.3). When applied to weakly homologous models, the average heavy atom, local RMSD from the native structure of the top-ranked (best of top five) binding site geometries is 3.1 Å (2.9 Å) for roughly half of the targets; this represents a 0.1 (0.3) Å average improvement over the original predicted structure. Focusing on the subset of strongly conserved residues, the average heavy atom RMSD is 2.6 Å (2.3 Å). Furthermore, we estimate the upper bound of template-based binding site refinement using only weakly related proteins to be ～2.6 Å RMSD. This value also corresponds to the plasticity of the ligand-binding regions in distant homologues. The Binding Site Refinement (BSR) approach is available to the scientific community as a web server that can be accessed at http://cssb.biology.gatech.edu/bsr/.     

Ligation site in proteins recognized in silico

Recognition of a ligation site in a protein molecule is important for identifying its biological activity. The model for in silico recognition of ligation sites in proteins is presented. The idealized hydrophobic core stabilizing protein structure is represented by a three-dimensional Gaussian function. The experimentally observed distribution of hydrophobicity compared with the theoretical distribution reveals differences. The area of high differences indicates the ligation site. AVAILABILITY: http://bioinformatics.cm-uj.krakow.pl/activesite.     

Sequence-structure-function relation characterized in silico

Methods for biological function recognition in silico appeared to be useful also for identifying characteristics of structure-to-function relations. The introduction of a three-dimensional Gauss function was assumed to represent the hydrophobic core in a protein molecule. The discrepancy between idealized "fuzzy oil-drop" and the observed one in real proteins appeared to be localized in the ligation site or in the area of biological function related part of protein molecule. The examples of proteins presented in this paper reveal that the structure-function relation can be evaluated and characterized also using the profile of the difference in value between idealized and real hydrophobicity distribution along the polypeptide chain. The specificity of particular polypeptide chain fragments in respect to their biological function and their specific participation in active site creation is discussed in this paper. The scale allowing comparison of different proteins in respect to their ligand-binding sites characteristics is introduced.     

eMatchSite: Sequence Order-Independent Structure Alignments of Ligand Binding Pockets in Protein Models

Detecting similarities between ligand binding sites in the absence of global homology between target proteins has been recognized as one of the critical components of modern drug discovery. Local binding site alignments can be constructed using sequence order-independent techniques, however, to achieve a high accuracy, many current algorithms for binding site comparison require high-quality experimental protein structures, preferably in the bound conformational state. This, in turn, complicates proteome scale applications, where only various quality structure models are available for the majority of gene products. To improve the state-of-the-art, we developed eMatchSite, a new method for constructing sequence order-independent alignments of ligand binding sites in protein models. Large-scale benchmarking calculations using adenine-binding pockets in crystal structures demonstrate that eMatchSite generates accurate alignments for almost three times more protein pairs than SOIPPA. More importantly, eMatchSite offers a high tolerance to structural distortions in ligand binding regions in protein models. For example, the percentage of correctly aligned pairs of adenine-binding sites in weakly homologous protein models is only 4–9% lower than those aligned using crystal structures. This represents a significant improvement over other algorithms, e.g. the performance of eMatchSite in recognizing similar binding sites is 6% and 13% higher than that of SiteEngine using high- and moderate-quality protein models, respectively. Constructing biologically correct alignments using predicted ligand binding sites in protein models opens up the possibility to investigate drug-protein interaction networks for complete proteomes with prospective systems-level applications in polypharmacology and rational drug repositioning. eMatchSite is freely available to the academic community as a web-server and a stand-alone software distribution at http://www.brylinski.org/ematchsite.

This is a PLOS Computational Biology Software Article

     

Fuzzy-Oil-Drop Hydrophobic Force Field—A Model to Represent Late-stage Folding (In Silico) of Lysozyme

Abstract

A model of hydrophobic collapse (in silico), which is generally considered to be the driving force for protein folding, is presented in this work. The model introduces the external field in the form of a fuzzy-oil-drop assumed to represent the environment. The drop is expressed in the form of a three-dimensional Gauss function. The usual probability value is assumed to represent the hydrophobicity distribution in the three-dimensional space of the virtual environment. The differences between this idealized hydrophobicity distribution and the one represented by the folded polypeptide chain is the parameter to be minimized in the structure optimization procedure. The size of fuzzy-oil-drop is critical for the folding process. A strong correlation between protein length and the dimension of the native and early-stage molecular form was found on the basis of single-domain proteins analysis. A previously presented early-stage folding (in silico) model was used to create the starting structure for the procedure of late-stage folding of lysozyme. The results of simulation were found to be promising, although additional improvements for the formation of β-structure and disulfide bonds as well as the participation of natural ligand in folding process seem to be necessary.     

eRepo-ORP: Exploring the Opportunity Space to Combat Orphan Diseases with Existing Drugs

About 7000 rare, or orphan, diseases affect more than 350 million people worldwide. Although these conditions collectively pose significant health care problems, drug companies seldom develop drugs for orphan diseases due to extremely limited individual markets. Consequently, developing new treatments for often life-threatening orphan diseases is primarily contingent on financial incentives from governments, special research grants, and private philanthropy. Computer-aided drug repositioning is a cheaper and faster alternative to traditional drug discovery offering a promising venue for orphan drug research. Here, we present eRepo-ORP, a comprehensive resource constructed by a large-scale repositioning of existing drugs to orphan diseases with a collection of structural bioinformatics tools, including eThread, eFindSite, and eMatchSite. Specifically, a systematic exploration of 320,856 possible links between known drugs in DrugBank and orphan proteins obtained from Orphanet reveals as many as 18,145 candidates for repurposing. In order to illustrate how potential therapeutics for rare diseases can be identified with eRepo-ORP, we discuss the repositioning of a kinase inhibitor for Ras-associated autoimmune leukoproliferative disease. The eRepo-ORP data set is available through the Open Science Framework at https://osf.io/qdjup/.     

SPI--structure predictability index for protein sequences

Estimation of structure predictability for a particular protein is difficult. Many methods estimate it in an a posteriori system evaluating the final, native protein structure. The SPI scale is intended to estimate the structure predictability of a particular amino acid sequence in an a priori system. A sequence-to-structure library was created based on the complete Protein Data Bank. The tetrapeptide was selected as a unit representing a well-defined structural motif. The early-stage folding structure (a model of which was presented elsewhere) was taken as the object for protein structure classification. Seven structural forms were distinguished for structure classification. The degree of determinability was estimated for the sequence-to-structure and structure-to-sequence relations particularly interesting for threading methods. A comparative analysis of the SPI and Q7 scales with the commonly used SOV and Q3 scales is presented. The complete contingency table, supplementary materials and all the programs used are available on request.     

Discontinuite hydrobiologique dans le detroit du Pas-de-Calais

Hydrobiological studies in the Straits of Dover show a differencebetween the characteristics of the French coastal water andthe open sea water. A cruise between Boulogne-sur-mer and Dover(October 15, 1985) confirms the existence of a frontal area(4 miles off the French coast). This area is characterized byan increase of the salinity (1%) and decrease of the suspendedmatter content (from 27 to 20 mg l^–1), of primary production(from 15 to 3 mg C m^–3h^–1) and of chlorophyll aconcentration (from 4.5 to 1.5 mg m^–3). The presence ofdifferent zooplanktonic species in the two water masses alsocharacterizes this discontinuity. Oncaea sp., Corycaeus anglicus,Centropages typicus and Calanus helgolandicus are indicatorspecies of open sea water, while Cyciopina littoralis and ‘Saphirella’are only present in coastal water.