A Structural Proteomics Exploration of Synphilin-1 and Alpha-Synuclein Interaction in Pathogenesis of Parkinson's Disease.

Pathological significance of interaction of Synphilin-1 with mutated alpha-synuclein is well known to have serious consequences in causing the formation of inclusion bodies that are linked to Parkinson's disease (PD). Information extracted so far pointed out that specific mutations, A53T, A30P, and E46K, in alpha-synuclein promote such interactions. However, a detailed structural study of this interaction is pending due to the unavailability of the complete structures of the large protein Synphilin-1 of chain length 919 residues and the mutated alpha-synuclein having all the reported specific mutations so far.

IDPpred: a new sequence-based predictor for identification of intrinsically disordered protein with enhanced accuracy.

Discovery of intrinsically disordered proteins (IDPs) and protein hybrids that contain both intrinsically disordered protein regions (IDPRs) along with ordered regions has changed the sequence-structure-function paradigm of protein. These proteins with lack of persistently fixed structure are often found in all organisms and play vital roles in various biological processes. Some of them are considered as potential drug targets due to their overrepresentation in pathophysiological processes.

Application of sequence semantic and integrated cellular geography approach to study alternative biogenesis of exonic circular RNA.

Background: Concurrent existence of lncRNA and circular RNA at both nucleus and cytosol within a cell at different proportions is well reported. Previous studies showed that circular RNAs are synthesized in nucleus followed by transportation across the nuclear membrane and the export is primarily defined by their length. lncRNAs primarily originated through inefficient splicing and seem to use NXF1 for cytoplasm export.

TemPred: A Novel Protein Template Search Engine to Improve Protein Structure Prediction.

Among new protein structure predictors, the recently developed AlphaFold predictor relies on contact map in line with contact map potential based threading model that basically relies on fold recognition. In parallel, sequence similarity based homology model relies on homologue recognition. Both of these methods rely on sequence-structure or sequence-sequence similarity with protein with known structure in absence of which, as argued in the development of AlphaFold, the structure prediction becomes quite challenging.

ProtPCV: A Fixed Dimensional Numerical Representation of Protein Sequence to Significantly Reduce Sequence Search Time.

Protein sequence is a wealth of experimental information which is yet to be exploited to extract information on protein homologues. Consequently, it is observed from publications that dynamic programming, heuristics and HMM profile-based alignment techniques along with the alignment free techniques do not directly utilize ordered profile of physicochemical properties of a protein to identify its homologue. Also, it is found that these works lack crucial bench-marking or validation in absence of which their incorporation in search engines may appears to be questionable.

APT: An Automated Probe Tracker From Gene Expression Data.

Out of currently available semi-automatic tools for detecting diagnostic probes relevant to a pathophysiological condition, ArrayMining and GEO2R of NCBI are most popular. The shortcomings of ArrayMining and GEO2R are that both tools list the probes ordering them on the basis of their individual statistical level of significances with only difference of statistical methods used by them. While the latest tool GEO2R outputs either top 250 or all genes following its own ranking mechanism, ArrayMining requires number of probes to be inputted by the user.

An improved protein structure evaluation using a semi-empirically derived structure property.

Background: In the backdrop of challenge to obtain a protein structure under the known limitations of both experimental and theoretical techniques, the need of a fast as well as accurate protein structure evaluation method still exists to substantially reduce a huge gap between number of known sequences and structures. Among currently practiced theoretical techniques, homology modelling backed by molecular dynamics based optimization appears to be the most popular one. However it suffers from contradictory indications of different validation parameters generated from a set of protein models which are predicted against a particular target protein.

EcircPred: Sequence and secondary structural property based computational identification of exonic circular RNAs.

Circular RNAs are new class of stable non-coding RNAs, whose expressions are specific to tissues as well as developmental stages and reported to act as gene regulators. Conspicuous presences of some of them as biomarkers for cancers, aging etc. are well reported.

A new search subspace to compensate failure of cavity-based localization of ligand-binding sites.

The common exercise adopted in almost all the ligand-binding sites (LBS) predictive methods is to considerably reduce the search space up to a meager fraction of the whole protein. In this exercise it is assumed that the LBS are mostly localized within a search subspace, cavities, which topologically appear to be valleys within a protein surface. Therefore, extraction of cavities is considered as a most important preprocessing step for finally predicting LBS.

An Improved Protein Surface Extraction Method Using Rotating Cylinder Probe.

For extraction of information on binding sites of a protein, the commonly known geometry-based methods utilize the corresponding PDB file to extract its surface as a first step. Finally, the surface is used to find the binding site atoms. As shown in this paper work, since none of the mostly used surface extraction methods can retrieve a sizeable percentage of the binding site atoms, the scope of development of a better method remains.

PCV: An Alignment Free Method for Finding Homologous Nucleotide Sequences and its Application in Phylogenetic Study.

Online retrieval of the homologous nucleotide sequences through existing alignment techniques is a common practice against the given database of sequences. The salient point of these techniques is their dependence on local alignment techniques and scoring matrices the reliability of which is limited by computational complexity and accuracy. Toward this direction, this work offers a novel way for numerical representation of genes which can further help in dividing the data space into smaller partitions helping formation of a search tree.

Protein structure validation using a semi-empirical method.

Current practice of validating predicted protein structural model is knowledge-based where scoring parameters are derived from already known structures to obtain decision on validation out of this structure information. For example, the scoring parameter, Ramachandran Score gives percentage conformity with steric-property higher value of which implies higher acceptability. On the other hand, Force-Field Energy Score gives conformity with energy-wise stability higher value of which implies lower acceptability.

Exploring geometric properties of gold nanoparticles using TEM images to explain their chaperone like activity for citrate synthase.

Study on geometric properties of nanoparticles and their relation with biomolecular activities, especially protein is quite a new field to explore. This work was carried out towards this direction where images of gold nanoparticles obtained from transmission electron microscopy were processed to extract their size and area profile at different experimental conditions including and excluding a protein, citrate synthase. Since the images were ill-posed, texture of a context-window for each pixel was used as input to a back-propagation network architecture to obtain decision on its membership as nanoparticle.

An ANN-GA model based promoter prediction in Arabidopsis thaliana using tilling microarray data.

Identification of promoter region is an important part of gene annotation. Identification of promoters in eukaryotes is important as promoters modulate various metabolic functions and cellular stress responses. In this work, a novel approach utilizing intensity values of tilling microarray data for a model eukaryotic plant Arabidopsis thaliana, was used to specify promoter region from non-promoter region.

Neurocognitive derivation of protein surface property from protein aggregate parameters.

Current work targeted to predicate parametric relationship between aggregate and individual property of a protein. In this approach, we considered individual property of a protein as its Surface Roughness Index (SRI) which was shown to have potential to classify SCOP protein families. The bulk property was however considered as Intensity Level based Multi-fractal Dimension (ILMFD) of ordinary microscopic images of heat denatured protein aggregates which was known to have potential to serve as protein marker.

A comparative study on the molecular descriptors for predicting drug-likeness of small molecules.

Screening of " drug-like" molecule from the molecular database produced through high throughput techniques and their large repositories requires robust classification. In our work, a set of heuristically chosen nine molecular descriptors including four from Lipinski's rule, were used as classification parameter for screening "drug-like" molecules. The robustness of classification was compared with four fundamental descriptors of Lipinski.

Functional group based Ligand binding affinity scoring function at atomic environmental level.

Use of knowledge based scoring function (KBSF) for virtual screening and molecular docking has become an established method for drug discovery. Lack of a precise and reliable free energy function that describes several interactions including water-mediated atomic interaction between amino-acid residues and ligand makes distance based statistical measure as the only alternative. Till now all the distance based scoring functions in KBSF arena use atom singularity concept, which neglects the environmental effect of the atom under consideration.

Surface characterization of proteins using multi-fractal property of heat-denatured aggregates.

Multi-fractal property of heat-denatured protein aggregates (HDPA) is characteristic of its individual form. The visual similarity between digitally generated microscopic images of HDPA with that of surface-image of its individual X-ray structures in protein databank (PDB) displayed using Visual Molecular Dynamics (VMD) viewer is the basis of the study. We deigned experiments to view the fractal nature of proteins at different aggregate scales.

FGO: a novel ontology for identification of ligand functional group.

Small molecules play crucial role in the modulation of biological functions by interacting with specific macromolecules. Hence small molecule interactions are captured by a variety of experimental methods to estimate and propose correlations between molecular structures to their biological activities. The tremendous expanse in publicly available small molecules is also driving new efforts to better understand interactions involving small molecules particularly in area of drug docking and pharmacogenomics.