bluuebunny/crossref_metadata_2025 huggingface dataset:
Local Backbone Structure Prediction of Proteins
Authors: de Brevern Alexandre G. , Benros Cristina , Gautier Romain , Valadié Héléne , Hazout Serge , Etchebest Catherine
Published: January 2025

A statistical analysis of the PDB structures has led us to define a new set of small 3D structural prototypes called Protein Blocks (PBs). This structural alphabet includes 16 PBs, each one is defined by the (Φ, Ψ) dihedral angles of 5 consecutive residues. The amino acid distributions observed in sequence windows encompassing these PBs are used to predict by a Bayesian approach the local 3D structure of proteins from the sole knowledge of their sequences. LocPred is a software which allows the users to submit a protein sequence and performs a prediction in terms of PBs. The prediction results are given both textually and graphically.
Annotating Significant Pairs of Transcription Factor Binding Sites in Regulatory DNA
Authors: Rateitschak Katja , Müller Tobias , Vingron Martin
Published: January 2025

In the presented work we search for transcription factor binding sites (BS) by including additional information about typical BS patterns. The new proposed score combines the ordinary profile score based on TRANSFAC-matrices together with a score based on pairs of BS. The latter score positively weights pairs of BS that tend to occur together in many regulatory DNA-sequences, in contrast to a random background model. The empirical BS pair frequencies result from our evaluation of a large dataset of orthologous genes.
Identification and Analysis of a New Family of Bacterial Serine Proteinases
Authors: Pandit Shashi B. , Srinivasan N.
Published: January 2025

A family of hypothetical proteins, identified predominantly from archaeal genomes, has been analyzed in order to understand its functional characteristics. Using extensive sequence similarity searches it is inferred that this family is remotely related (best sequence identity is 19%) to ClpP proteinases that belongs to serine proteinase class. This family of hypothetical proteins is referred to as SDH proteinase family based on conserved sequential order of Ser, Asp and His residues and predicted serine proteinase activity. Results of fold recognition of SDH family sequences confirmed the remote relationship between SDH proteinases and Clp proteinases and revealed similar tertiary location of putative catalytic triad residues critical for serine proteinase function. However, the best sequence alignment we could obtain suggests that while catalytic Ser is conserved across Clp and SDH proteinases the location of the other catalytic triad residues, namely, His and Asp are swapped in their amino acid alignment positions and hence in 3-D structure. The evidence of conserved catalytic triad suggests that SDH could be a new family of serine proteinases with the fold of Clp proteinase, however sharing the catalytic triad order of carboxypeptidase clan. Signal peptide sequence identified at the N-terminus of some of the homologues suggests that these might be secretory serine proteinases involved in cleavage of extracellular proteins while the remote homologues, ClpP proteinases, are known to work in intracellular environment.
In silico Reconstruction of Nutrient-Sensing Signal Transduction Pathways in Aspergillus nidulans
Authors: Muthuvijayan Vignesh , Marten Mark R.
Published: January 2025

We report here probable nutrient-sensing signal transduction pathways in Aspergillus nidulans, a model filamentous fungus, based on sequence homology studies with known Saccharomyces cerevisiae and Schizosaccharomyces pombe proteins. Specifically, we identified A. nidulans homologs for yeast proteins involved in (1) filamentation-invasion, (2) cAMP-PKA, (3) pheromone response, (4) cell integrity and (5) TOR signaling pathways. We have also studied autophagy, one of the most important cellular responses regulated by TOR signaling. The Basic Local Alignment Search Tool program "blastp" was used to assess the homology of proteins. We note that by using a highly conservative approach, 70% of the S. cerevisiae signal transduction proteins (107 proteins out of 153 proteins studied) have significant homologs in A. nidulans. Using a slightly less conservative approach, we are able to identify homologs for as high as 91% of the S. cerevisiae signal transduction proteins (139 proteins out of 153 proteins studied). The filamentation-invasion, cell integrity and TOR signaling pathways showed greatest similarity with S. cerevisiae, while the cAMP-PKA and pheromone response pathways showed greater similarity with S. pombe. Based on these results, probable pathways in A. nidulans were constructed using well-established S. cerevisiae and S. pombe models.
Collection of Soluble Variants of Membrane Proteins for	Transcriptomics and Proteomics
Authors: Möller Steffen , Mix Eilhard , Blüggel Martin , Serrano-Fernández Pablo , Koczan Dirk , Kotsikoris Vasilis , Kunz Manfred , Watson Michael , Pahnke Jens , Illges Harald , Kreutzer Michael , Mikkat Stefan , Thiesen Hans-Jürgen , Glocker Michael O. , Zettl Uwe K. , Ibrahim Saleh M.
Published: January 2025

The existence of a soluble splice variant for a gene encoding a transmembrane protein suggests that this gene plays a role in intercellular signalling, particularly in immunological processes. Also, the absence of a splice variant of a reported soluble variant suggests exclusive control of the solubilisation by proteolytic cleavage. Soluble splice variants of membrane proteins may also be interesting targets for crystallisation as their structure may be expected to preserve, at least partially, their function as integral membrane proteins, whose structures are most difficult to determine.

This paper presents a dataset derived from the literature in an attempt to collect all reported soluble variants of membrane proteins, be they splice variants or shedded. A list of soluble variants is derived in silico from Ensembl. These are checked on their presence in multiple organisms and their number of membranespanning regions is inspected. The findings then are confirmed by a comparison with identified proteins of a recent global proteomics study of human blood plasma. Finally, a tool to support the identification of novel soluble variants by proteomics is provided.
Natural Antisense as Potential Regulator of Alternative	Initiation, Splicing and Termination
Authors: Enerly Espen , Sheng Zeng , Li Kuo-Bin
Published: January 2025

In humans an estimated 35–60% of genes are alternatively spliced. A large number of genes also show alternative initiation or termination. Regulation of these processes is still poorly understood. For alternative splicing it is believed that the relative concentration of certain proteins and the presence of certain regulatory elements are the key factors determining alterations in splicing pattern. However, there is evidence that antisense RNA might be part of the regulatory processes. Antisense RNA molecules could bind to the target pre-mRNA in a sequence-specific fashion, sterically blocking targeted splice sites and redirecting the spliceosome to available and unhindered splice sites. Here we describe an in silico investigation to identify human sense/antisense pairs with alternative initiation or termination in the sense gene and where only one of the isoforms overlaps the antisense transcript. Alternatively spliced genes with antisense transcripts covering the alternatively used splice site are also identified. Our analyses are based on the ASAP splicing annotation database from UCLA, the antisense transcripts data from Yelin et al., 2003, and the H-invitational full-length cDNA database from JBIRC, Japan. These data gives new insight into the complexity of genomic organization and provide candidate loci for experimentalists to study antisense mediated regulation of alternative initiation, splicing and termination. Our result contains 468 clusters with this characteristic genomic organization and can be found at http://aistar.bii.a-star.edu.sg/.
T Cell Receptor/Peptide/MHC Molecular Characterization and	Standardized pMHC Contact Sites in IMGT/3Dstructure-DB
Authors: Kaas Quentin , Lefranc Marie-Paule
Published: January 2025

One of the key elements in the adaptive immune response is the presentation of peptides by the major histocompatibility complex (MHC) to the T cell receptors (TR) at the surface of T cells. The characterization of the TR/peptide/MHC trimolecular complexes (TR/pMHC) is crucial to the fields of immunology, vaccination and immunotherapy. In order to facilitate data comparison and cross-referencing between experiments from different laboratories whatever the receptor, the chain type, the domain, or the species, IMGT, the international ImMunoGeneTics information system® (http://imgt.cines.fr), has developed IMGT-ONTOLOGY, the first ontology in immunogenetics and immunoinformatics. In IMGT/3Dstructure-DB, the IMGT three-dimensional structure database, TR/pMHC molecular characterization and pMHC contact analysis are made according to the IMGT Scientific chart rules, based on the IMGT-ONTOLOGY concepts. IMGT/3Dstructure-DB provides the standardized IMGT gene and allele names (CLASSIFICATION), the standardized IMGT labels (DESCRIPTION) and the IMGT unique numbering (NUMEROTATION). As the IMGT structural unit is the domain, amino acids at conserved positions always have the same number in the IMGT databases, tools and Web resources. For the TR alpha and beta chains, the amino acids in contact with the peptide/MHC (pMHC) are defined according to the IMGT unique numbering for V-DOMAIN. The MHC cleft that binds the peptide is formed by two groove domains (G-DOMAIN), each one comprising four antiparallel beta strands and one alpha helix. The IMGT unique numbering for G-DOMAIN applies both to the first two domains (G-ALPHA1 and G-ALPHA2) of the MHC class I alpha chain, and to the first domain (G-ALPHA and G-BETA) of the two MHC class II chains, alpha and beta. Based on the IMGT unique numbering, we defined eleven contact sites for the analysis of the pMHC contacts. The TR/pMHC contact description, based on the IMGT numbering, can be queried in the IMGT/StucturalQuery tool, at http://imgt.cines.fr. Availability: IMGT/3Dstructure-DB is freely available at http://imgt.cines.fr.
Identification and Characterization of Bombyx	mori eIF5A Gene through Bioinformatics Approaches
Authors: Hu ZhiGang , Chen KePing , Wang LinLing , Yao Qin
Published: January 2025

As the genome of B. mori is available in GenBank and the EST database of B. mori is expanding, identification of novel genes of B. mori was conceivable by data-mining techniques and bioinformatics tools. In this study, we used the in silico cloning method to identify eukaryotic initiation factor 5A (eIF5A) gene in B. mori. With the hypusine formation, eIF5A is involved in the regulation of cell proliferation and apoptosis. Using the computer program MEGA3, we conducted a search for homologs of eIF5A among many eukaryotic species and confirmed that the eIF5A was conserved in all organisms investigated. This gene has been registered in GenBank under the accession number DQ104412.
Identification of Candidate Genes at Quantitative Trait Loci on	Chicken Chromosome Z Using Orthologous Comparison of Chicken, Mouse, and Human	Genomes
Authors: Ankra-Badu Georgina A. , Aggrey Samuel E.
Published: January 2025

This study was undertaken to identify novel candidate genes at quantitative trait loci (QTL) on chicken chromosome Z (GGAZ) by comparing orthologous regions of chicken, human and mouse genomes. Primer sequences from marker flanking QTL positions (https://acedb.asg.wur.nl/) were obtained from www.iastate.edu/chickmap and blasted against the chicken genome (www.ensembl.org) using BLASTN. The best matches were those with the highest score, lowest E-values and highest percent identity. Orthologous regions in mice and humans, together with genes located on or around those loci were identified using the Ensembl website. Forty-six chicken genes, 91 mouse genes and 60 human genes associated with QTL on GGAZ were identified in the current study. Among the most promising candidate genes for egg production and egg shell quality are annexin A1 (ANXA1), osteoclast stimulating factor (OSF), thrombospondin-4 (THBS4), programmed cell death proteins (PDCD), follistatin (FST), growth hormone receptor (GHR), interferon (IFN) α and β. The chicken IFN α and β were located on GGAZ around position 13,000,000 bp on the draft chicken sequence map. The neuronal nicotinic acetylcholine receptor (nAChR) is located at a QTL region for abdominal fat (GGAZ 25483091 bp). Nicotine is an agonist at the nAChRs and has been shown to decrease lipolysis and triglyceride uptake, thereby reducing net storage in adipose tissue. Therefore, the nAchRs could be used as therapeutic targets for regulating feed intake and obesity. This study has identified 197 putative candidate genes in probable QTL regions of chicken chromosome Z.
Gauss-Function-Based Model of Hydrophobicity Density in	Proteins
Authors: Konieczny Leszek , Brylinski Michal , Roterman Irena
Published: January 2025

The model adopting the three-dimensional Gauss function to express the hydrophobicity distribution in proteins is presented in this paper. The tendency to create the hydrophobic center during protein folding is expressed in form of an external force field of the form of three-dimensional Gauss function which directs the folding polypeptide to locate the hydrophobic residues in a central part of the molecule and hydrophilic ones exposed toward the molecular surface. The decrease of the differences between hydrophobicity distribution as it appears at each step of the folding simulation and the expected hydrophobicity distribution (three-dimensional Gauss function) is the convergence criterion together with traditional non-bonding interaction optimization. The model was applied to fold the hypothetical membrane protein (target protein in CASP6) TA0354_69_121 from Thermoplasma acidophilum.
Analysis and Prediction of Helix Shift Errors in Homology	Modeling
Authors: Bock Christoph , Hesser Jürgen
Published: January 2025

High sequence identity between two proteins (e.g. > 60% is a strong evidence for high structural similarity. However, internal shifts in one of the two proteins can sometimes give rise to unexpectedly high structural differences. This, in turn, causes unreliable structure predictions when two such proteins are used in homology modeling. Here, we perform a computational analysis of helix shifts and we show that their occurrence can be predicted with statistical learning methods.

Our results indicate that helix shifts increase the RMS error by factor 2.6 compared to those protein pairs without a helix shift. Although helix shifts are rare (1.6% of helices and a commensurately higher number of proteins are affected), they therefore pose a significant problem for reliable structure prediction systems. In this paper, we prototype a new approach for model quality assessment and demonstrate that it can successfully warn against helix shifts. A support vector machine trained on a wide range of sequence and structure properties predicts the occurrence of helix shifts with a sensitivity of 74.2% and a specificity of 83.6%. On an equalized test dataset, this corresponds to an accuracy of 78.9%. Projected to the full dataset, it translates to an accuracy of 83.4%.

Our analysis shows that helix shift detection is a valuable building block for highly reliable structure prediction systems. Furthermore, the statistical learning based approach to helix shift detection that we employ here is orthogonal to well-established model quality assessment methods (which use geometric constraint checking or mean force potentials). Therefore, a further increase of prediction accuracy is expected from the combination of these methods.
Analysis of Tandem Repeats Found in 44 Prokaryotic Genomes
Authors: Mizuta Satoshi , Munakata Hikaru , Aimaiti Abulimiti , Oya Ichitaro , Oosawa Kenji , Shimizu Toshio
Published: January 2025

Genomes contain various types of repetitive sequences. They may be used as probes for seeking genome rearrangements because they are rather free from the natural selection if they are located in the intergenic regions. In this study, we searched for tandem repeats (TRs) in 44 prokaryotic genomes by the color-coding method and sought the signs of genome rearrangements by detailed analysis of the detected TRs. We found 13,542 tandem repeats from 44 prokaryotic genomes in total ranging from several tens to one thousand per genome. The results of statistical analysis show that TRs tend to exist on high base composition bias regions in some genomes. Moreover, we recognized the characteristic distribution patterns of equivalent TR-pairs in 12 genomes, which are expected to indicate the occurrence of whole-genome duplication (WGD) on the genomes. It is demonstrated that TRs could indeed be used for seeking genome rearrangements. Although it has not been made clear at this time whether or not WGD had occurred in prokaryotic genomes, the results of the analyses of equivalent TR-pairs in this study are thought to be evidences of WGD in these genomes.
In silico Analysis of Genes Nucleoprotein,	Neuraminidase and Hemagglutinin: A Comparative Study on Different Strains of	Influenza A (Bird Flu) Virus Sub-Type H5N1
Authors: Anwar Tamanna , Lal Sunil K. , Khan Asad U.
Published: January 2025

The avian influenza (bird flu) is an infectious disease of birds, ranging from a mild to a severe form of illness. Influenza viruses pose significant challenges to both human and animal health. The proteins, nucleoprotein (NP), neuraminidase (NA) and hemagglutinin (HA) of influenza A virus (Bird flu virus) sub-type A/Hatay/2004/(H5N1) from chicken were selected for this study. Our in silico analysis predicted that HA of influenza A virus is highly sensitive to mutations and hence it is significant for its pathogenic nature. None of the mutations was detected as an important change except in NA where K332R was at a PKC phosphorylation site. Analysis of the sequence comparison showed that the maximum number of mutations were observed in HA. These mutations are significant as they are involved in change in polarity or hydrophobicity as well as in propensity of each amino acid residue to stabilize the secondary structure. The program MAPMUTATION can be used to monitor the mutations, and predict the trend of mutations.
Metal Transportome of Neurospora crassa
Authors: Kiranmayi Patnala , Mohan Pamarthi Maruthi
Published: January 2025

Neurospora crassa has been the model filamentous fungus for the study of many fundamental cellular mechanisms of transport and metabolism. The recently completed genome sequence of N. crassa has over 10,000 genes without significant matches for a large number of genes (41%) in the sequence databases, indeed presents many challenges for new discoveries. Using transporter database and BLAST searches a total of 65 open reading frames for putative cation transporter genes have been identified in N. crassa. These were further confirmed by characteristic features of the family like transmembrane domains (TOPPRED 2), conserved motifs (Clustal W) and phylogenetic analysis (TREETOP). In Neurospora cation transporter genes constitute nearly 18.3% of the total membrane transport systems, which is higher than E. coli (8.8%), S. cerevisiae (13.7%), S. pombe (17.2%), A. fumigatus (10.1%), A. thaliana (16.8%) and H. sapiens (15.6%). We refer to the complete complement of metal ion transporter genes as "Metal Transportome". There are a total of 33 putative transporters for alkali and alkaline earth metals constituting 18 for calcium (P-ATPase, VIC, CaCA, Mid1), 7 for sodium (P-ATPase, CPA1, CPA2), 4 for potassium (Trk, VIC, KUP), and 4 for magnesium (MIT). Transition metal ion transporters account for 32 transporters including 7 for zinc (ZIP), 6 for copper (Ctr2, Ctr1), 2 each for manganese (Nramp), iron (OFeT), arsenite (ArsAB, ACR3) and other metal ions (ABC and P-ATPase) and 1 each for nickel (NiCoT) and chromate (CHR). N. crassa has 7 linkage groups of which LGI harbors 21 of metal ion transporters and in contrast LGVII has only 2. Studies on metal transportomes of different organisms will help to unravel the role of metal ion transporters in homeostasis.
Molecular Evolution of Serine/Arginine Splicing Factors Family	(SR) by Positive Selection
Authors: Escobar Andrés J. Gutiérrez , Arenas Aylan Farid , Gómez-Marin Jorge Enrique
Published: January 2025

The serine-rich (SR) protein family is involved in the pre-mRNA splicing process and the DNA sequences of the corresponding genes are highly conserved in the metazoan organisms. The mammalian SR proteins consist of one or two characteristic RNA binding domains (RBD), containing the signature sequences RDAEDA and SWQDLKD and a RS (arginine/serine-rich) domain. We used the amino acid and nucleotide sequences deposited in GenBank and Swiss-Prot databases to perform a phylogenetic analysis using bioinformatics tools. The results of the phylogenetic trees suggest that this family has evolved by several gene duplication events as a result of a positive selection mechanism.
ISHAN: Sequence Homology Analysis Package
Authors: Shil Pratip , Dudani Niraj , Vidyasagar Pandit B.
Published: January 2025

Sequence based homology studies play an important role in evolutionary tracing and classification of proteins. Various methods are available to analyze biological sequence information. However, with the advent of proteomics era, there is a growing demand for analysis of huge amount of biological sequence information, and it has become necessary to have programs that would provide speedy analysis. ISHAN has been developed as a homology analysis package, built on various sequence analysis tools viz FASTA, ALIGN, CLUSTALW, PHYLIP and CODONW (for DNA sequences). This JAVA application offers the user choice of analysis tools. For testing, ISHAN was applied to perform phylogenetic analysis for sets of Caspase 3 DNA sequences and NF- κB p105 amino acid sequences. By integrating several tools it has made analysis much faster and reduced manual intervention.
IMGT Standardization for Statistical Analyses of T Cell Receptor	Junctions: The TRAV-TRAJ Example
Authors: Bleakley Kevin , Giudicelli Véronique , Wu Yan , Lefranc Marie-Paule , Biau Gérard
Published: January 2025

The diversity of immunoglobulin (IG) and T cell receptor (TR) chains depends on several mechanisms: combinatorial diversity, which is a consequence of the number of V, D and J genes and the N-REGION diversity, which creates an extensive and clonal somatic diversity at the V-J and V-D-J junctions. For the IG, the diversity is further increased by somatic hypermutations. The number of different junctions per chain and per individual is estimated to be 10 $^{12}$ . We have chosen the human TRAV-TRAJ junctions as an example in order to characterize the required criteria for a standardized analysis of the IG and TR V-J and V-D-J junctions, based on the IMGT-ONTOLOGY concepts, and to serve as a first IMGT junction reference set (IMGT®, http://imgt.cines.fr). We performed a thorough statistical analysis of 212 human rearranged TRAV-TRAJ sequences, which were aligned and analysed by the integrated IMGT/V-QUEST software, which includes IMGT/JunctionAnalysis, then manually expert-verified. Furthermore, we compared these 212 sequences with 37 other human TRAV-TRAJ junction sequences for which some particularities (potential sequence polymorphisms, sequencing errors, etc.) did not allow IMGT/JunctionAnalysis to provide the correct biological results, according to expert verification. Using statistical learning, we constructed an automatic warning system to predict if new, automatically analysed TRAV-TRAJ sequences should be manually re-checked. We estimated the robustness of this automatic warning system.
Improved Prediction of Allergenicity by Combination of Multiple	Sequence Motifs
Authors: Kong Waiming , Tan Tsu Soo , Tham Lawrence , Choo Keng Wah
Published: January 2025

The identification and validation of protein allergens have become more important nowadays as more and more transgenic proteins are introduced into our food chains. Current allergen prediction algorithms focus on the identification of single motif or single allergen peptide for allergen detection. However, an analysis of the 575 allergen dataset shows that most allergens contain multiple motifs. Here, we present a novel algorithm that detects allergen by making use of combinations of motifs. Sensitivity of 0.772 and specificity of 0.904 were achieved by the proposed algorithm to predict allergen. The specificity of the proposed approach is found to be significantly higher than traditional single motif approaches. The high specificity of the proposed algorithm is useful in filtering out false positives, especially when laboratory resources are limited.
Elementary Mode Analysis to Study the Preculturing Effect on the	Metabolic State of Lactobacillus rhamnosus During Growth on	Mixed Substrates
Authors: Gayen Kalyan , Gupta Manish , Venkatesh Kareenhalli V.
Published: January 2025

Quantification of metabolism through elementary modes offers insights into the working of a metabolic network. We have determined the fluxes of elementary modes through linear optimization using the stoichiometry of the elementary modes as a constraint. We apply this methodology to obtain insights into the effect of preculturing on growth of Lactobacillus rhamnosus on medium containing mixed substrates. L. rhamnosus, a microaerophilic organism, produces flavor compounds such as diacetyl and acetoin during growth on glucose and citrate. The uptake of citrate has been shown to be sensitive to preculturing states of the cells. Elementary modes demonstrated that citrate was utilized by the organism as a sole carbon source. Further, both glucose and citrate was catabolized by this organism through aerobic and anaerobic routes. The flux analysis indicated that only 21 elementary modes were operational during growth of L. rhamnosus on glucose and citrate. Glucose specifically accounted for 6 elementary modes, while the remaining 15 involved citrate as substrate. The modes associated with glucose were mainly operational when cells were precultured on glucose. It was observed that all the 21 modes contributed to the fluxes when the cells were precultured on citrate. The NADH recycling through lactate formation and oxygen uptake were dependent on the preculturing state. The analysis also demonstrated that preculturing on citrate yielded better productivity of diacetyl and acetoin.
BioCompass: A Novel Functional Inference Tool that Utilizes MeSH	Hierarchy to Analyze Groups of Genes
Authors: Nakazato Takeru , Takinaka Toru , Mizuguchi Hironori , Matsuda Hideo , Bono Hidemasa , Asogawa Minoru
Published: January 2025

Microarray technology has become employed widely for biological researchers to identify genes associated with conditions such as diseases and drugs. To date, many methods have been developed to analyze data covering a large number of genes, but they focus only on statistical significance and cannot decipher the data with biological concepts. Gene Ontology (GO) is utilized to understand the data with biological interpretation; however, it is restricted to specific ontology such as biological process, molecular function, and cellular component. Here, we attempted to apply MeSH (Medical Subject Headings) to interpret groups of genes from biological viewpoint. To assign MeSH terms to genes, in this study, contexts associated with genes are retrieved from full set of MEDLINE data using machine learning, and then extracted MeSH terms from retrieved articles. Utilizing the developed method, we implemented a software called BioCompass. It generates high-scoring lists and hierarchical lists for diseases MeSH terms associated with groups of genes to utilize MeSH and GO tree, and illustrated a wiring diagram by linking genes with extracted association from articles. Researchers can easily retrieve genes and keywords of interest, such as diseases and drugs, associated with groups of genes. Using retrieved MeSH terms and OMIM in conjunction with, we could obtain more disease information associated with target gene. BioCompass helps researchers to interpret groups of genes such as microarray data from a biological viewpoint.
A Machine Learning Based Method for the Prediction of Secretory	Proteins Using Amino Acid Composition, Their Order and Similarity-Search
Authors: Garg Aarti , Raghava Gajendra P.S.
Published: January 2025

Most of the prediction methods for secretory proteins require the presence of a correct N-terminal end of the pre-protein for correct classification. As large scale genome sequencing projects sometimes assign the 5'-end of genes incorrectly, many proteins are encoded without the correct N-terminus leading to incorrect prediction. In this study, a systematic attempt has been made to predict secretory proteins irrespective of presence or absence of N-terminal signal peptides (also known as classical and non-classical secreted proteins respectively), using machine-learning techniques; artificial neural network (ANN) and support vector machine (SVM). We trained and tested our methods on a dataset of 3321 secretory and 3654 non-secretory mammalian proteins using five-fold cross-validation technique. First, ANN-based modules have been developed for predicting secretory proteins using 33 physico-chemical properties, amino acid composition and dipeptide composition and achieved accuracies of 73.1%, 76.1% and 77.1%, respectively. Similarly, SVM-based modules using 33 physico-chemical properties, amino acid, and dipeptide composition have been able to achieve accuracies of 77.4%, 79.4% and 79.9%, respectively. In addition, BLAST and PSI-BLAST modules designed for predicting secretory proteins based on similarity search achieved 23.4% and 26.9% accuracy, respectively. Finally, we developed a hybrid-approach by integrating amino acid and dipeptide composition based SVM modules and PSI-BLAST module that increased the accuracy to 83.2%, which is significantly better than individual modules. We also achieved high sensitivity of 60.4% with low value of 5% false positive predictions using hybrid module. A web server SRTpred has been developed based on above study for predicting classical and non-classical secreted proteins from whole sequence of mammalian proteins, which is available from http://www.imtech.res.in/raghava/srtpred/.
GASCO: Genetic Algorithm Simulation for Codon Optimization
Authors: Sandhu Kuljeet Singh , Pandey Sunil , Maiti Souvik , Pillai Beena
Published: January 2025

Codon optimization is a generic technique to achieve optimum expression of a foreign gene in the host's cell system. Selection of optimum codons depends on codon usage of the host genome and the presence of several desirable and undesirable sequence motifs. Searching these motifs in all possible combinations of the codons increases the search space exponentially with respect to sequence length. GASCO is an algorithm developed for the optimum codon selection using genetic algorithms. The algorithm reduces the search space and provides an approximate solution to the problem. The algorithm has applications in DNA vaccine design for successfully eliciting potent immune responses and synthetic gene design for metabolic pathway engineering. The software for the proposed algorithm is available on http://miracle.igib.res.in/gasco/.
A Data Integration Approach to Predict Host-Pathogen	Protein-Protein Interactions: Application to Recognize Protein Interactions	between Human and a Malarial Parasite
Authors: Krishnadev Oruganty , Srinivasan Narayanaswamy
Published: January 2025

Lack of large-scale efforts aimed at recognizing interactions between host and pathogens limits our understanding of many diseases. We present a simple and generally applicable bioinformatics approach for the analysis of possible interactions between the proteins of a parasite, Plasmodium falciparum, and human host. In the first step, the physically compatible interactions between the parasite and human proteins are recognized using homology detection. This dataset of putative in vitro interactions is combined with large-scale datasets of expression and sub-cellular localization. This integrated approach reduces drastically the number of false positives and hence can be used for generating testable hypotheses. We could recognize known interactions previously suggested in the literature. We also propose new predictions which involve interactions of some of the parasite proteins of yet unknown function. The method described is generally applicable to any host-pathogen pair and can thus be of general value to studies of host-pathogen protein-protein interactions.
Docking-MM-GB/SA and ADME Screening of HIV-1 NNRTI Inhibitor:	Nevirapine and its Analogues
Authors: Sengupta Dipankar , Verma Deeptak , Naik Pradeep Kumar
Published: January 2025

Nevirapine and its synthetic analogues, a class of non-nucleoside inhibitors (NNRTIs) of HIV-1 reverse transcriptase (RT), have been the objective of numerous studies focused to prepare better and safer anti-HIV drugs. We developed a library of nevirapine analogues (47) using combinatorial design and with structural modification at X, Y and R substituents in the parent structure of nevirapine. Their molecular interactions and binding affinities with reverse transcriptase (3HVT and 1VRT) have been studied using the docking-molecular mechanics based generalized Born/surface area (MM-GB/SA) solvation model. Final screening of these analogues is based on absorption, distribution, metabolism and excretion (ADME) properties. The proposed NNRTI analogues dock in a similar position and orientation in the active site of RT as co-crystallized nevirapine. In addition a linear correlation was observed between the calculated free energy of binding (FEB) and pIC $_{50}$ for the inhibitors with correlation coefficient R $^{2}$ of 0.9948, suggesting that the docked structure orientation and the interaction energies are reasonable. The electrostatic energy terms estimated by GB/SA showed important role on prediction of binding affinity (R $^{2}$ = 17.2%. Since we used two different HIV-1 RT crystal structures (3HVT and 1VRT), which are at different resolution (2.9 and 2.2 Å, we propose that structures with resolutions better than 3 Å can be used to produce reasonable docking results. Few analogues showed high binding affinity and activity with RT in compare to co-crystallized nevirapine. These analogues also well qualify ADME properties and showed good druggable characters. The work addressed to modify the X, Y and R substituents in the nevirapine scaffold to prepare synthetic analogues for second generation drug development against RT.
In silico Identification of Putative Drug	Targets from Different Metabolic Pathways of Aeromonas	hydrophila
Authors: Sharma Vibhuti , Gupta Preeti , Dixit Aparna
Published: January 2025

Aeromonas hydrophila is a major pathogen both of aquatic and terrestrial organisms, including humans. Infection with A. hydrophila results in severe economic losses to the aquaculture industry. In humans, Aeromonas hydrophila infections are known to cause gastroenteritis and wound infections. Investigations for developing a potential vaccine for its control are underway. The availability of the complete sequence information of A. hydrophila strain ATCC 7966 $^{T}$ genome has made it possible to carry out the in silico analysis of its genome for various aspects of its biology. Keeping in view the possible risks that A. hydrophila poses to humans, in silico analysis of the A. hydrophila genome was carried out for the identification of potential vaccine and drug targets. Our study revealed 2097 genes which are non-homologous to human genome. Screening these genes using the Database of Essential Genes (DEG) resulted in the identification of 379 genes as essential genes of the bacteria. Further analysis of the identified essential genes, using the Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathways database, revealed 87 enzymes of A. hydrophila that may be used as drug targets, as they are not present in humans. Of these, 15 enzymes belong to pathways present only in the bacteria, whereas 72 enzymes are from the pathways that are common to both human and the bacteria. These can be used as a platform for further investigation to develop effective drugs against A. hydrophila.
Association of antigenic properties to structure of the hepatitis C virus NS3 protein
Authors: Lara James , Khudyakov Yury
Published: January 2025

Sequence heterogeneity substantially affects antigenic properties of the major epitope in the hepatitis C virus (HCV) NS3 protein. To facilitate protein engineering of NS3 antigens immunologically reactive with antibody against the broad diversity of HCV variants we constructed a set of Bayesian Networks (BN) for predicting antigenicity based on structural parameters. Using homology modeling, tertiary (3D) structures of NS3 variants with known antigenic properties were predicted. Energy force field estimated using the 3D-models was found to be most strongly associated with the antigenic properties. The best BN-models showed 100% accuracy of prediction of immunological reactivity with tested serum specimens in 10-fold cross validation. Bootstrap analyses of BN’s constructed using selected features showed that secondary structure and electrostatic potential assessed from 3D-models are the most robust attributes associated with immunological reactivity of NS3 antigens. The data suggest that the BN models may guide the development of NS3 antigens with improved diagnostically relevant properties.
Evaluation of Codon Bias Perspectives in Phage Therapy of	Mycobacterium tuberculosis by Multivariate Analysis
Authors: Ranjan Ashutosh , Vidyarthi Ambrish Sharan , Poddar Raju
Published: January 2025

To reveal the relative synonymous codon usage and base composition variation in bacteriophages, six mycobacteriophages were used as a model system here and both parameters in these phages and their host bacteria, Mycobacterium tuberculosis, have been determined and compared. As expected for GC-rich genomes, there are predominantly G and C ending codons in all 6 phages. Both N $_{c}$ plot and correspondence analysis on relative synonymous codon usage indicate that mutation bias and translation selection influences codon usage variation in the 6 phages. Further analysis indicates that among 6 Mycobacterium phages Che9c, Bxz1 and TM4 may be extremely virulent in nature as most of their genes have high translation efficiency. Based on our data we suggest that the genes of above three phages are expressed rapidly by host's translation machinery. The information might be used to select the extremely virulent Mycobacterium tuberculosis phages suitable for phage therapy.
BETTY: Prediction of beta;-Strand Type from Sequence
Authors: Zimmermann Olav , Wang Longhui , Hansmann Ulrich H.E.
Published: January 2025

Most secondary structure prediction programs do not distinguish between parallel and antiparallel β-sheets. However, such knowledge would constrain the available topologies of a protein significantly, and therefore aid existing fold recognition algorithms. For this reason, we propose a technique which, in combination with existing secondary structure programs such as PSIPRED, allows one to distinguish between parallel and antiparallel β-sheets. We propose the use of a support vector machine (SVM) procedure, BETTY, to predict parallel and antiparallel sheets from sequence. We found that there is a strong signal difference in the sequence profiles which SVMs can efficiently extract. With strand type assignment accuracies of 90.7% and 83.3% for antiparallel and parallel strands, respectively, our method adds considerably to existing information on current 3-class secondary structure predictions.

BETTY has been implemented as an online service which academic researchers can access from our website http://www.fz-juelich.de/nic/cbb/service/service.php.
Analysis of Codon Usage Patterns and Predicted Highly Expressed	Genes for Six Phytopathogenic Xanthomonas Genomes Shows a	High Degree of Conservation
Authors: Sen Gargi , Sur Saubashya , Bose Debadin , Mondal Uttam , Furnholm Teal , Bothra Asim , Tisa Louis , Sen Arnab
Published: January 2025

Members of the genus Xanthomonas are significant phytopathogens, which cause diseases in several economically important crops including rice, canola, tomato, citrus, etc. We have analyzed the genomes of six recently sequenced Xanthomonas strains for their synonymous codon usage patterns for all of protein coding genes and specific genes associated with pathogenesis, and determined the predicted highly expressed (PHX) genes by the use of the codon adaptation index (CAI). Our results show considerable heterogeneity among the genes of these moderately G+C rich genomes. Most of the genes were moderate to highly biased in their codon usage. However, unlike ribosomal protein genes, which were governed by translational selection, those genes associated with pathogenesis (GAP) were affected by mutational pressure and were predicted to have moderate to low expression levels. Only two out of 339 GAP genes were in the PHX category. PHX genes present in clusters of orthologous groups of proteins (COGs) were identified. Genes in the plasmids present in two strains showed moderate to low expression level and only a couple of genes featured in the PHX list. Common genes present in the top-20 PHX gene-list were identified and their possible functions are discussed. Correspondence analysis showed that genes are highly confined to a core in the plot.
Prediction of Ubiquitin Proteins using Artificial Neural Networks,	Hidden Markov Model and Support Vector Machines
Authors: Jaiswal Kunal
Published: January 2025

Ubiquitin functions to regulate protein turnover in a cell by closely regulating the degradation of specific proteins. Such a regulatory role is very important, and thus I have analyzed the proteins that are ubiquitin-like, using an artificial neural network, support vector machines and a hidden Markov model (HMM). The methods were trained and tested on a set of 373 ubiquitin proteins and 373 non-ubiquitin proteins, obtained from Entrez protein database. The artificial neural network and support vector machine are trained and tested using both the physicochemical properties and PSSM matrices generated from PSI-BLAST, while in the HMM based method direct sequences are used for training-testing procedures. Further, the performance measures of the methods are calculated for test sequences, i.e. accuracy, specificity, sensitivity and Matthew's correlation coefficients of the methods are calculated. The highest accuracy of 90.2%, specificity of 87.04% and sensitivity of 94.08% was achieved using the support vector machine model with PSSM matrices. While accuracies of 86.82%, 83.37%, 80.18% and 72.11% were obtained for the support vector machine with physicochemical properties, neural network with PSSM matrices, neural networks with physicochemical properties, and hidden Markov model, respectively. As the accuracy for SVM model is better both using physicochemical properties and the PSSM matrices, it is concluded that kernel methods such as SVM outperforms neural networks and hidden Markov models.
HBAT: A Complete Package for Analysing Strong	and Weak Hydrogen Bonds in Macromolecular Crystal Structures
Authors: Tiwari Abhishek , Panigrahi Sunil K.
Published: January 2025

The program HBAT is a tool to automate the analysis of potential hydrogen bonds and similar type of weak interactions like halogen bonds and non-canonical interactions in macromolecular structures, available in Brookhaven Protein Database (PDB) file format. HBAT is written using PERL and TK languages. The program generates an MSOFFICE Excel compatible output file for statistical analysis. HBAT identify potential interactions based on geometrical criteria. A series of analysis reports like frequency tables, geometry distribution tables, furcations list are generated. A user friendly GUI offers freedom to select several parameters and options. Graphviz based visualization of hydrogen bond networks in 2D helps to study the cooperativity and anticooperativity geometry in hydrogen bond. HBAT supports post docking interaction analysis between PDB files for any target/receptor (in PDB files) and docked ligands/poses (in SDF). This tool can be implemented in active site interaction analysis, structure based drug design and molecular dynamics simulations.
Financial Devolution and Local Government: Citizen's Perception in Azad Jammu and Kashmir
Authors: Khan Zopash
Published: January 2025

This study aims to analyse the perception of citizens regarding accountability, competency, effectiveness, and challenges related to local government system. Respondent’s income, gender, age, familiarity with roles and responsibilities of local government members, and engagement in political discussions are important factors affecting their perception. Data has been collected through stratified random sampling. Citizens revealed that accountability and effectiveness of government will improve after financial devolution. Moreover, voters mostly preferred to cast their votes on the basis of personal affiliation. Education remains top expectation of citizens from the Local Government (LG). This study also provides policy tools for the local government policy makers.
Pakistan’s Strategy during COVID-19 Pandemic
Authors: Faisal Muhammad , Latif Ijaz
Published: January 2025

The COVID-19 pandemic emerged in December 2019. The virus affected every domain of human life across the world. In particular, economy is considered to be the most affected by COVID-19 pandemic. Most of the nation-states are still experiencing socio-economic consequences. Pakistan is also not an exceptional case in this context since the COVID-19 pandemic affected its economy as well. The country is still experiencing economic depression. Therefore, the current study examined the strategy employed by Pakistani government during COVID-19 pandemic. Moreover, the study also analyzed how government used its resources to feed the population. This research concluded that the government needs a vigilant long term policy framework to stabilize the worsening economic conditions of Pakistan.