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The number of protein structures is increasing due to the individual initiatives and rapid development of structure determination techniques. Structure-based sequence alignments of distantly related proteins enable the investigation of structural, evolutionary and functional relationships between proteins and their domains leading to their common evolutionary origin. Protein Alignments organized as Structural Superfamilies (PASS2) is a database that provides such alignments of members of protein domain superfamilies of known structure and with less than 40% sequence identity. PASS2 has been continuously updated in accordance to Structural Classification of Proteins (SCOP), and now Structural Classification of Proteins - extended (SCOPe). The current update directly corresponds to SCOPe 2.06, dealing with 2006 domain superfamilies of known structure and about 14 000 domains. Alignments have been augmented by features such as hidden Markov models, highly conserved residues, structural motifs and gene ontology terms, which are available for download. In this update, we introduce the concepts of 'extreme structural outliers' and 'split superfamilies' as well., (© The Author(s) 2019. Published by Oxford University Press.)

Accurate sequence alignments are crucial for modelling and to provide an evolutionary picture of related proteins. It is well-known that alignments are hard to obtain during distant relationships. Three thousand and fifty-two alignments of 218 pairs of protein domain structural entries, with <40% sequence identity, belonging to different structural classes, of diverse domain sizes and length-rigid/variable domains were performed using 12 programs. Structural parameters such as root mean square deviation, secondary-structural content and equivalences were considered for critical assessment. Methods that compare fragments and permit twists and translations align well during distant relationships and length variations.

Purpose: A number of proteome studies have been performed recently to identify pheromone-related protein expression and their molecular function using genetically modified rodents' urine. However, no such studies have used Indian commensal rodents; interestingly, in a previous investigation, we confirmed the presence of volatile molecules in commensal rodents urine and these molecules seem to be actively involved in pheromonal communication. Therefore, the present study aims to identify the major urinary protein [MUP] present in commensal rat urine, which will help us to understand the protein's expression pattern and intrinsic properties among the rodents globally., Experimental Design: Initially, the total urinary proteins were separated by 1-D and 2-D electrophoresis and then subsequently analyzed by Matrix Assisted Laser Desorption Ionization-Time of Flight and Mass Spectrometer (MALDI-TOF/MS). Furthermore, they were then fragmented with the aid of a Tandem Mass Spectrometer (TOF/TOF) and the identified sequences aligned and confirmed using similarity with the deduced primary structures of members of the lipocalin superfamily., Results: The SDS-PAGE protein profiles showed distinct proteins with molecular masses of 15, 22.4, 25, 28, 42, 50, 55, 68, and 91 kDa. Of these proteins, the 22.4 kDa protein was considered to be target candidate. When 2D elctrophoresis was carried out, about approximately 50 spots were detected with different masses and various pI ranges. The 22.4 kDa protein was found to have a pI of about 4.9.This 22.4 kDa protein spot was digested and subjected to mass spectrometry; it was identified as rat MUP. The fragmented peptides from the rat MUP at 935, 1026, 1192, and 1303 m/z were further fragmented with the aid of MS/MS and generated de novo sequence and this confirmed this protein to be the MUP present in the urine of commensal rats., Conclusion: The present investigation confirms the presence of MUP with a molecular mass of 22.4 kDa in the urine of commensal rats. This protein may be involved in the binding of volatile molecules and opens up a discussion about how volatile and non-volatile molecules in the commensal rats' urine may contribute chemo-communication.

Background: Distantly related proteins adopt and retain similar structural scaffolds despite length variations that could be as much as two-fold in some protein superfamilies. In this paper, we describe an analysis of indel regions that accommodate length variations amongst related proteins. We have developed an algorithm CUSP, to examine multi-membered PASS2 superfamily alignments to identify indel regions in an automated manner. Further, we have used the method to characterize the length, structural type and biochemical features of indels in related protein domains., Results: CUSP, examines protein domain structural alignments to distinguish regions of conserved structure common to related proteins from structurally unconserved regions that vary in length and type of structure. On a non-redundant dataset of 353 domain superfamily alignments from PASS2, we find that 'length- deviant' protein superfamilies show > 30% length variation from their average domain length. 60% of additional lengths that occur in indels are short-length structures (< 5 residues) while 6% of indels are > 15 residues in length. Structural types in indels also show class-specific trends., Conclusion: The extent of length variation varies across different superfamilies and indels show class-specific trends for preferred lengths and structural types. Such indels of different lengths even within a single protein domain superfamily could have structural and functional consequences that drive their selection, underlying their importance in similarity detection and computational modelling. The availability of systematic algorithms, like CUSP, should enable decision making in a domain superfamily-specific manner.

Background: Multiple sequence alignment algorithms are very important tools in molecular biology today. Accurate alignment of proteins is central to several areas such as homology modelling, docking studies, understanding evolutionary trends and study of structure-function relationships. In recent times, improvement of existing progressing programs and implementation of new iterative algorithms have made a significant change in this field., Results: We report an alignment algorithm that combines progressive dynamic algorithm, local substructure alignment and iterative refinement to achieve an improved, user-interactive tool. Large-scale benchmarking studies show that this FMALIGN server produces alignments that, aside from preservation of functional and structural conservation, have accuracy comparable to other popular multiple alignment programs., Conclusions: The FMALIGN server allows the user to fix conserved regions in equivalent position in the alignment thereby reducing the chance of global misalignment to a great extent. FMALIGN is available at http://caps.ncbs.res.in/FMALIGN/Home.html.

Background: The functional selection and three-dimensional structural constraints of proteins in nature often relates to the retention of significant sequence similarity between proteins of similar fold and function despite poor sequence identity. Organization of structure-based sequence alignments for distantly related proteins, provides a map of the conserved and critical regions of the protein universe that is useful for the analysis of folding principles, for the evolutionary unification of protein families and for maximizing the information return from experimental structure determination. The Protein Alignment organised as Structural Superfamily (PASS2) database represents continuously updated, structural alignments for evolutionary related, sequentially distant proteins., Description: An automated and updated version of PASS2 is, in direct correspondence with SCOP 1.63, consisting of sequences having identity below 40% among themselves. Protein domains have been grouped into 628 multi-member superfamilies and 566 single member superfamilies. Structure-based sequence alignments for the superfamilies have been obtained using COMPARER, while initial equivalencies have been derived from a preliminary superposition using LSQMAN or STAMP 4.0. The final sequence alignments have been annotated for structural features using JOY4.0. The database is supplemented with sequence relatives belonging to different genomes, conserved spatially interacting and structural motifs, probabilistic hidden markov models of superfamilies based on the alignments and useful links to other databases. Probabilistic models and sensitive position specific profiles obtained from reliable superfamily alignments aid annotation of remote homologues and are useful tools in structural and functional genomics. PASS2 presents the phylogeny of its members both based on sequence and structural dissimilarities. Clustering of members allows us to understand diversification of the family members. The search engine has been improved for simpler browsing of the database., Conclusions: The database resolves alignments among the structural domains consisting of evolutionarily diverged set of sequences. Availability of reliable sequence alignments of distantly related proteins despite poor sequence identity and single-member superfamilies permit better sampling of structures in libraries for fold recognition of new sequences and for the understanding of protein structure-function relationships of individual superfamilies. PASS2 is accessible at http://www.ncbs.res.in/~faculty/mini/campass/pass2.html

Sequence alignments are models that capture the structural, functional and evolutionary relationships between proteins. Structure-guided sequence alignments are helpful in the case of distantly related proteins with poor sequence identity, thus rendering routine sequence alignment methods ineffective. Protein Alignment organized as Structural Superfamilies or PASS2 database provides such sequence alignments of protein domains within a superfamily as per the Structural Classification of Proteins extended (SCOPe) database. The current update of PASS2 (i.e. PASS2.7) is following the latest release of SCOPe (2.07) and we provide data for 14 323 protein domains that are <40% identical and are organized into 2024 superfamilies. Several useful features derived from the alignments, such as conserved secondary structural motifs, HMMs and residues conserved across the superfamily, are also reported. Protein domains that are deviant from the rest of the members of a superfamily may compromise the quality of the alignment, and we found this to be the case in ∼7% of the total superfamilies we considered. To improve the alignment by objectively identifying such 'outliers', in this update, we have used a k -means-based unsupervised machine learning method for clustering superfamily members, where features provided were length of domains aligned, Cα-RMSD derived from the rigid-body superposition of all members and gaps contributed to the alignment by each domain. In a few cases, we have split the superfamily as per the clusters predicted and provided complete data for each cluster. A new feature included in this update is absolutely conserved interactions (ACIs) between residue backbones and side chains, which are obtained by aligning protein structure networks using structure-guided sequence alignments of superfamilies. ACIs provide valuable information about functionally important residues and the structure–function relationships of proteins. The ACIs and the corresponding conserved networks for backbone and sidechain have been marked on the superimposed structure separately. Database URL The updated version of the PASS2 database is available at http://caps.ncbs.res.in/pass2/. [ABSTRACT FROM AUTHOR]

Abstract: Protein functional annotation relies on the identification of accurate relationships, sequence divergence being a key factor. This is especially evident when distant protein relationships are demonstrated only with three-dimensional structures. To address this challenge, we describe a computational approach to purposefully bridge gaps between related protein families through directed design of protein-like “linker” sequences. For this, we represented SCOP domain families, integrated with sequence homologues, as multiple profiles and performed HMM-HMM alignments between related domain families. Where convincing alignments were achieved, we applied a roulette wheel-based method to design 3,611,010 protein-like sequences corresponding to 374 SCOP folds. To analyze their ability to link proteins in homology searches, we used 3024 queries to search two databases, one containing only natural sequences and another one additionally containing designed sequences. Our results showed that augmented database searches showed up to 30% improvement in fold coverage for over 74% of the folds, with 52 folds achieving all theoretically possible connections. Although sequences could not be designed between some families, the availability of designed sequences between other families within the fold established the sequence continuum to demonstrate 373 difficult relationships. Ultimately, as a practical and realistic extension, we demonstrate that such protein-like sequences can be “plugged-into” routine and generic sequence database searches to empower not only remote homology detection but also fold recognition. Our richly statistically supported findings show that complementary searches in both databases will increase the effectiveness of sequence-based searches in recognizing all homologues sharing a common fold. [Copyright &y& Elsevier]

Background: Related protein domains of a superfamily can be specified by proteins of diverse lengths. The structural and functional implications of indels in a domain scaffold have been examined. Methodology: In this study, domain superfamilies with large length variations (more than 30% difference from average domain size, referred as 'length-deviant' superfamilies and 'length-rigid' domain superfamilies (<10% length difference from average domain size) were analyzed for the functional impact of such structural differences. Our delineated dataset, derived from an objective algorithm, enables us to address indel roles in the presence of peculiar structural repeats, functional variation, protein-protein interactions and to examine 'domain contexts' of proteins tolerant to large length variations. Amongst the top-10 length-deviant superfamilies analyzed, we found that 80% of length-deviant superfamilies possess distant internal structural repeats and nearly half of them acquired diverse biological functions. In general, lengthdeviant superfamilies have higher chance, than length-rigid superfamilies, to be engaged in internal structural repeats. We also found that ~40% of length-deviant domains exist as multi-domain proteins involving interactions with domains from the same or other superfamilies. Indels, in diverse domain superfamilies, were found to participate in the accretion of structural and functional features amongst related domains. With specific examples, we discuss how indels are involved directly or indirectly in the generation of oligomerization interfaces, introduction of substrate specificity, regulation of protein function and stability. Conclusions: Our data suggests a multitude of roles for indels that are specialized for domain members of different domain superfamilies. These specialist roles that we observe and trends in the extent of length variation could influence decision making in modeling of new superfamily members. Likewise, the observed limits of length variation, specific for each domain superfamily would be particularly relevant in the choice of alignment length search filters commonly applied in protein sequence analysis. [ABSTRACT FROM AUTHOR]

Computational approaches to high-throughput data are gaining importance because of explosion of sequences in the post-genomic era. This explosion of sequence data creates a huge gap among the domains of sequence structure and function, since the experimental techniques to determine the structure and function are very expensive, time taking, and laborious in nature. Therefore, there is an urgent need to emphasize on the development of computational approaches in the field of biological systems. Engagement of proteins in quaternary arrangements, such as domain swapping, might be relevant for higher compatibility of such genes at stress conditions. In this study, the capacity to engage in domain swapping was predicted from mere sequence information in the whole genome of holy Basil (Ocimum tenuiflorum), which is well known to be an anti-stress agent. Approximately, one-fourth of the proteins of O tenuiflorum are predicted to undergo three-dimensional (3D)-domain swapping. Furthermore, function annotation was carried out on all the predicted domain-swap sequences from the O tenuiflorum and Arabidopsis thaliana for their distribution in different Pfam protein families and gene ontology (GO) terms. These domain-swapped protein sequences are associated with many Pfam protein families with a wide range of GO annotation terms. A comparative analysis of domain-swap-predicted sequences in O tenuiflorum with gene products in A thaliana reveals that around 26% (2522 sequences) are close homologues across the 2 genomes. Functional annotation of predicted domain-swapped sequences infers that predicted domain-swap sequences are involved in diverse molecular functions, such as in gene regulation of abiotic stress conditions and adaptation to different environmental niches. Finally, the positively predicted sequences of A thaliana and O tenuiflorum were also examined for their presence in stress regulome, as recorded in our STIFDB database, to check the involvement of these proteins in different abiotic stresses. [ABSTRACT FROM AUTHOR]

Since proteins evolve by divergent evolution, proteins with distant homology to each other may or may not bear similar functions. Improved computational approaches are required to recognize distant homologues that are functionally similar. One of the methods of assigning function to sequences is to use profiles derived from sequences of known structure. We describe an update of the Genomic Distribution of protein structural domain Superfamilies (GenDiS) database, namely GenDiS+, which provides a projection of SCOP superfamily members on the sequence space (NR database, NCBI). The sequences are validated using structure-based sequence alignment profiles and domain and full-length sequence alignments. GenDiS+ is a 'tour de force' for detecting homologues within around 160 000 taxonomic identifiers, starting from nearly 11 000 domains of known structure. Features, like full-sequence alignment and phylogeny, domain sequence alignment and phylogeny, list of associated structural and sequence domains with strength of interactions, links to databases like Pfam, UniProt and ModBase and list of sequences with a PDB structure, are provided. [ABSTRACT FROM AUTHOR]

The number of protein structures is increasing due to the individual initiatives and rapid development of structure determination techniques. Structure-based sequence alignments of distantly related proteins enable the investigation of structural, evolutionary and functional relationships between proteins and their domains leading to their common evolutionary origin. Protein Alignments organized as Structural Superfamilies (PASS2) is a database that provides such alignments of members of protein domain superfamilies of known structure and with less than 40% sequence identity. PASS2 has been continuously updated in accordance to Structural Classification of Proteins (SCOP), and now Structural Classification of Proteins - extended (SCOPe). The current update directly corresponds to SCOPe 2.06, dealing with 2006 domain superfamilies of known structure and about 14 000 domains. Alignments have been augmented by features such as hidden Markov models, highly conserved residues, structural motifs and gene ontology terms, which are available for download. In this update, we introduce the concepts of 'extreme structural outliers' and 'split superfamilies' as well. [ABSTRACT FROM AUTHOR]