Motif mining: an assessment and perspective for amyloid fibril prediction tool

Amyloid fibril forming regions in protein sequences are associated with a number of diseases. Experimental evidences compel in favor of the hypothesis that short motif regions are responsible for its amyloidogenic behavior. Thus, identifying these short peptides is critical in understanding the cause of diseases associated with aggregation of proteins and developing sequencetargeted anti-aggregation drugs. Owing to the constraints of wet lab molecular techniques for the identification of amyloid fibril forming targets, computational methods are implemented to offer better and affordable in silico predictions. The present study takes into consideration an assessment and perspective of the recent tools available for predicting a peptide status: amyloidogenic or non-amyloidogenic. To the best of our knowledge, the existing review articles on amyloidogenic prediction tools have not touched upon their effectiveness in terms of true positive rates or false positive rates. In this work, we compare few tools such as Aggrescan, Amylpred and FoldAmyloid to evaluate the performance of their predictability based on the experimentally proved data in terms of specificity, sensitivity, Matthews Correlation Coefficient and Balanced accuracy. As evident from the results, a significant reduction of sensitivity associated with a gain in specificity is noted in all the tools considered under the present study.     

Machine learning study of classifiers trained with biophysiochemical properties of amino acids to predict fibril forming Peptide motifs

It is important to understand the cause of amyloid illnesses by predicting the short protein fragments capable of forming amyloid-like fibril motifs aiding in the discovery of sequence-targeted anti-aggregation drugs. It is extremely desirable to design computational tools to provide affordable in silico predictions owing to the limitations of molecular techniques for their identification. In this research article, we tried to study, from a machine learning perspective, the performance of several machine learning classifiers that use heterogenous features based on biochemical and biophysical properties of amino acids to discriminate between amyloidogenic and non-amyloidogenic regions in peptides. Four conventional machine learning classifiers namely Support Vector Machine, Neural network, Decision tree and Random forest were trained and tested to find the best classifier that fits the problem domain well. Prior to classification, novel implementations of two biologically-inspired feature optimization techniques based on evolutionary algorithms and methodologies that mimic social life and a multivariate method based on projection are utilized in order to remove the unimportant and uninformative features. Among the dimenionality reduction algorithms considered under the study, prediction results show that algorithms based on evolutionary computation is the most effective. SVM best suits the problem domain in its fitment among the classifiers considered. The best classifier is also compared with an online predictor to evidence the equilibrium maintained between true positive rates and false positive rates in the proposed classifier. This exploratory study suggests that these methods are promising in providing amyloidogenity prediction and may be further extended for large-scale proteomic studies.     

Cation-mediated interplay of loops in chaperonin-10

The ubiquitously occurring chaperonins consist of a large tetradecameric Chaperonin-60, forming a cylindrical assembly, and a smaller heptameric Chaperonin-10. For a functional protein folding cycle, Chaperonin-10 caps the cylindrical Chaperonin-60 from one end forming an asymmetric complex. The oligomeric assembly of Chaperonin-10 is known to be highly plastic in nature. In Mycobacterium tuberculosis, the plasticity has been shown to be modulated by reversible binding of divalent cations. Binding of cations confers rigidity to the metal binding loop, and also promotes stability of the oligomeric structure. We have probed the conformational effects of cation binding on the Chaperonin-10 structure through fluorescence studies and molecular dynamics simulations. Fluorescence studies show that cation binding induces reduced exposure and flexibility of the dome loop. The simulations corroborate these results and further indicate a complex landscape of correlated motions between different parts of the molecule. They also show a fascinating interplay between two distantly spaced loops, the metal binding "dome loop" and the GroEL-binding "mobile loop", suggesting an important cation-mediated role in the recognition of Chaperonin-60. In the presence of cations the mobile loop appears poised to dock onto the Chaperonin-60 structure. The divalent metal ions may thus act as key elements in the protein folding cycle, and trigger a conformational switch for molecular recognition.     

Crystal structure of trehalose-6-phosphate phosphatase-related protein: biochemical and biological implications

We report here the crystal structure of a trehalose-6-phosphate phosphatase-related protein (T6PP) from Thermoplasma acidophilum, TA1209, determined by the dual-wavelength anomalous diffraction (DAD) method. T6PP is a member of the haloacid dehalogenase (HAD) superfamily with significant sequence homology with trehalose-6-phosphate phosphatase, phosphoserine phosphatase, P-type ATPases and other members of the family. T6PP possesses a core domain of known alpha/beta-hydrolase fold, characteristic of the HAD family, and a cap domain, with a tertiary fold consisting of a four-stranded beta-sheet with two alpha-helices on one side of the sheet. An active-site magnesium ion and a glycerol molecule bound at the interface between the two domains provide insight into the mode of substrate binding by T6PP. A trehalose-6-phosphate molecule modeled into a cage formed by the two domains makes favorable interactions with the protein molecule. We have confirmed that T6PP is a trehalose phosphatase from amino acid sequence, three-dimensional structure, and biochemical assays.     

Chemical shift optimization in multidimensional NMR spectra by AUREMOL-SHIFTOPT

A problem often encountered in multidimensional NMR-spectroscopy is that an existing chemical shift list of a protein has to be used to assign an experimental spectrum but does not fit sufficiently well for a safe assignment. A similar problem occurs when temperature or pressure series of n-dimensional spectra are to be evaluated automatically. We have developed two different algorithms, AUREMOL-SHIFTOPT1 and AUREMOL-SHIFTOPT2 that fulfill this task. In the present contribution their performance is analyzed employing a set of simulated and experimental two-dimensional and three-dimensional spectra obtained from three different proteins. A new z-score based on atom and amino acid specific chemical shift distributions is introduced to weight the chemical shift contributions in different dimensions properly.     

Isolation and identification of an anticancer drug,taxol from <Emphasis Type="Italic">Phyllosticta tabernaemontanae</Emphasis>, a leaf spot fungus of an angiosperm, <Emphasis Type="Italic">Wrightia tinctoria</Emphasis>

Phyllosticta tabernaemontanae, a leaf spot fungus isolated from the diseased leaves of Wrightia tinctoria, showed the production of taxol, an anticancer drug, on modified liquid medium (MID) and potato dextrose broth (PDB) medium in culture for the first time. The presence of taxol was confirmed by spectroscopic and chromatographic methods of analysis. The amount of taxol produced by this fungus was quantified using high performance liquid chromatography (HPLC). The maximum amount of taxol production was recorded in the fungus grown on MID medium (461 μg/L) followed by PDB medium (150 μg/L). The production rate was increased to 9.2 × 10³ fold than that found in the culture broth of earlier reported fungus, Taxomyces andreanae. The results designate that P. tabernaemontanae is an excellent candidate for taxol production. The fungal taxol extracted also showed a strong cytotoxic activity in the in vitro culture of tested human cancer cells by apoptotic assay.     

Protein localization by recognition of membrane curvature

Bacteria often sort proteins to specific subcellular locations, but many of the chemical beacons that specify those sites and subsequently recruit proteins have not been identified. Recent reports suggest that some bacterial proteins localize to specific subcellular sites by recognizing either convex or concave membrane curvature. Thus, degrees of membrane curvature, dictated by the shape of the cell, can define a geometric cue for the recruitment of curvature-sensing proteins.     

Human recombinant resistin protein displays a tendency to aggregate by forming intermolecular disulfide linkages

Resistin, a small cysteine rich protein secreted by adipocytes, has been proposed to be a link between obesity and type II diabetes by modulating the insulin signaling pathway and thus inducing insulin resistance. Resistin protein, with 11 cysteine residues, was not significantly homologous at the amino acid level to any other known cysteine rich proteins. Resistin cDNA derived from human subcutaneous adipose tissue was expressed in Escherichia coli as an N-terminal six-His-tag fusion protein. The overexpressed recombinant resistin was purified to homogeneity from inclusion bodies, after solubilization in 8 M urea, using a metal affinity column. While MALDI-TOF mass spectrometric analysis of the purified protein generated a single peak corresponding to the estimated size of 11.3 kDa, the protein exhibited a concentration-dependent oligomerization which is evident from size exclusion chromatography. The oligomeric structure was SDS-insensitive but beta-mercaptoethanol-sensitive, pointing to the importance of disulfide linkages in resistin oligomerization. Estimation of free cysteine residues using the NBD-Cl assay revealed a concentration- and time-dependent increase in the extent of formation of disulfide linkages. The presence of intermolecular disulfide bond(s), crucial in maintaining the global conformation of resistin, was further evident from fluorescence emission spectra. Circular dichroism spectra revealed that recombinant resistin has a tendency to reversibly convert from alpha-helical to beta-sheet structure as a direct function of protein concentration. Our novel observations on the biophysical and biochemical features of human resistin, particularly those shared with prion proteins, may have a bearing on its likely physiological function.     

YABBY polarity genes mediate the repression of KNOX homeobox genes in Arabidopsis

The YABBY (YAB) genes specify abaxial cell fate in lateral organs in Arabidopsis. Loss-of-function mutants in two early-expressing YAB genes, FILAMENTOUS FLOWER (FIL) and YAB3, do not exhibit vegetative phenotypes as a result of redundancy. Mutations in these genes result in the derepression of the KNOX homeobox genes SHOOTMERISTEMLESS (STM), BREVIPEDICELLUS, and KNAT2 in the leaves and in the partial rescue of stm mutants. Here, we show that fil yab3 double mutants exhibit ectopic meristem formation on the adaxial surfaces of cotyledons and leaf blades. We propose that in addition to abaxial specification, lateral organ development requires YAB function to downregulate KNOTTED homeobox genes so that meristem initiation and growth are restricted to the apex.