Interfacial residues in protein-protein complexes are in the eyes of the beholder.

Interactions between proteins are vital in almost all biological processes. The characterization of protein-protein interactions helps us understand the mechanistic basis of biological processes, thereby enabling the manipulation of proteins for biotechnological and clinical purposes. The interface residues of a protein-protein complex are assumed to have the following two properties: (a) they always interact with a residue of a partner protein, which forms the basis for distance-based interface residue identification methods, and (b) they are solvent-exposed in the isolated form of the protein and become buried in the complex form, which forms the basis for Accessible Surface Area (ASA)-based methods. The study interrogates this popular assumption by recognizing interface residues in protein-protein complexes through these two methods. The results show that a few residues are identified uniquely by each method, and the extent of conservation, propensities, and their contribution to the stability of protein-protein interaction varies substantially between these residues. The case study analyses showed that interface residues, unique to distance, participate in crucial interactions that hold the proteins together, whereas the interface residues unique to the ASA method have a potential role in the recognition, dynamics, and specificity of the complex and can also be a hotspot. Overall, the study recommends applying both distance and ASA methods so that some interface residues missed by either method but crucial to the stability, recognition, dynamics, and function of protein-protein complexes are identified in a complementary manner.

The alteration of structural network upon transient association between proteins studied using graph theory.

Proteins such as enzymes perform their function by predominant non-covalent bond interactions between transiently interacting units. There is an impact on the overall structural topology of the protein, albeit transient nature of such interactions, that enable proteins to deactivate or activate. This aspect of the alteration of the structural topology is studied by employing protein structural networks, which are node-edge representative models of protein structure, reported as a robust tool for capturing interactions between residues. Several methods have been optimized to collect meaningful, functionally relevant information by studying alteration of structural networks. In this article, different methods of comparing protein structural networks are employed, along with spectral decomposition of graphs to study the subtle impact of protein-protein interactions. A detailed analysis of the structural network of interacting partners is performed across a dataset of around 900 pairs of bound complexes and corresponding unbound protein structures. The variation in network parameters at, around, and far away from the interface are analyzed. Finally, we present interesting case studies, where an allosteric mechanism of structural impact is understood from communication-path detection methods. The results of this analysis are beneficial in understanding protein stability, for future engineering, and docking studies.

Comparative analysis of permanent and transient domain-domain interactions in multi-domain proteins.

Protein domains are structural, functional, and evolutionary units. These domains bring out the diversity of functionality by means of interactions with other co-existing domains and provide stability. Hence, it is important to study intra-protein inter-domain interactions from the perspective of types of interactions. Domains within a chain could interact over short timeframes or permanently, rather like protein-protein interactions (PPIs). However, no systematic study has been carried out between two classes, namely permanent and transient domain-domain interactions. In this work, we studied 263 two-domain proteins, belonging to either of these classes and their interfaces on the basis of several factors, such as interface area and details of interactions (number, strength, and types of interactions). We also characterized them based on residue conservation at the interface, correlation of residue motions across domains, its involvement in repeat formation, and their involvement in particular molecular processes. Finally, we could analyze the interactions arising from domains in two-domain monomeric proteins, and we observed significant differences between these two classes of domain interactions and a few similarities. This study will help to obtain a better understanding of structure-function and folding principles of multi-domain proteins.

Transcriptome data analysis of primary cardiomyopathies reveals perturbations in arachidonic acid metabolism.

Introduction: Cardiomyopathies are complex heart diseases with significant prevalence around the world. Among these, primary forms are the major contributors to heart failure and sudden cardiac death. As a high-energy demanding engine, the heart utilizes fatty acids, glucose, amino acid, lactate and ketone bodies for energy to meet its requirement. However, continuous myocardial stress and cardiomyopathies drive towards metabolic impairment that advances heart failure (HF) pathogenesis. So far, metabolic profile correlation across different cardiomyopathies remains poorly understood. Methods: In this study, we systematically explore metabolic differences amongst primary cardiomyopathies. By assessing the metabolic gene expression of all primary cardiomyopathies, we highlight the significantly shared and distinct metabolic pathways that may represent specialized adaptations to unique cellular demands. We utilized publicly available RNA-seq datasets to profile global changes in the above diseases (|log2FC| ≥ 0.28 and BH adjusted p-val 0.1) and performed gene set analysis (GSA) using the PAGE statistics on KEGG pathways. Results: Our analysis demonstrates that genes in arachidonic acid metabolism (AA) are significantly perturbed across cardiomyopathies. In particular, the arachidonic acid metabolism gene PLA2G2A interacts with fibroblast marker genes and can potentially influence fibrosis during cardiomyopathy. Conclusion: The profound significance of AA metabolism within the cardiovascular system renders it a key player in modulating the phenotypes of cardiomyopathies.

Influence of pH on indole-dependent heterodimeric interactions between Anopheles gambiae odorant-binding proteins OBP1 and OBP4.

Insect Odorant Binding Proteins (OBPs) constitute important components of their olfactory apparatus, as they are essential for odor recognition. OBPs undergo conformational changes upon pH change, altering their interactions with odorants. Moreover, they can form heterodimers with novel binding characteristics. Anopheles gambiae OBP1 and OBP4 were found capable of forming heterodimers possibly involved in the specific perception of the attractant indole. In order to understand how these OBPs interact in the presence of indole and to investigate the likelihood of a pH-dependent heterodimerization mechanism, the crystal structures of OBP4 at pH 4.6 and 8.5 were determined. Structural comparison to each other and with the OBP4-indole complex (3Q8I, pH 6.85) revealed a flexible N-terminus and conformational changes in the α4-loop-α5 region at acidic pH. Fluorescence competition assays showed a weak binding of indole to OBP4 that becomes further impaired at acidic pH. Additional Molecular Dynamic and Differential Scanning Calorimetry studies displayed that the influence of pH on OBP4 stability is significant compared to the modest effect of indole. Furthermore, OBP1-OBP4 heterodimeric models were generated at pH 4.5, 6.5, and 8.5, and compared concerning their interface energy and cross-correlated motions in the absence and presence of indole. The results indicate that the increase in pH may induce the stabilization of OBP4 by increasing its helicity, thereby enabling indole binding at neutral pH that further stabilizes the protein and possibly promotes the creation of a binding site for OBP1. A decrease in interface stability and loss of correlated motions upon transition to acidic pH may provoke the heterodimeric dissociation allowing indole release. Finally, we propose a potential OBP1-OBP4 heterodimer formation/disruption mechanism induced by pH change and indole binding.

A census of actin-associated proteins in humans.

Actin filaments help in maintaining the cell structure and coordinating cellular movements and cargo transport within the cell. Actin participates in the interaction with several proteins and also with itself to form the helical filamentous actin (F-actin). Actin-binding proteins (ABPs) and actin-associated proteins (AAPs) coordinate the actin filament assembly and processing, regulate the flux between globular G-actin and F-actin in the cell, and help maintain the cellular structure and integrity. We have used protein-protein interaction data available through multiple sources (STRING, BioGRID, mentha, and a few others), functional annotation, and classical actin-binding domains to identify actin-binding and actin-associated proteins in the human proteome. Here, we report 2482 AAPs and present an analysis of their structural and sequential domains, functions, evolutionary conservation, cellular localization, abundance, and tissue-specific expression patterns. This analysis provides a base for the characterization of proteins involved in actin dynamics and turnover in the cell.

Structural rationale to understand the effect of disease-associated mutations on Myotubularin.

Myotubularin or MTM1 is a lipid phosphatase that regulates vesicular trafficking in the cell. The MTM1 gene is mutated in a severe form of muscular disease, X-linked myotubular myopathy or XLMTM, affecting 1 in 50,000 newborn males worldwide. There have been several studies on the disease pathology of XLMTM, but the structural effects of missense mutations of MTM1 are underexplored due to the unavailability of a crystal structure. MTM1 consists of three domains-a lipid-binding N-terminal GRAM domain, the phosphatase domain and a coiled-coil domain which aids dimerisation of Myotubularin homologs. While most mutations reported to date map to the phosphatase domain of MTM1, the other two domains on the sequence are also frequently mutated in XLMTM. To understand the overall structural and functional effects of missense mutations on MTM1, we curated several missense mutations and performed in silico and in vitro studies. Apart from significantly impaired binding to substrate, abrogation of phosphatase activity was observed for a few mutants. Possible long-range effects of mutations from non-catalytic domains on phosphatase activity were observed as well. Coiled-coil domain mutants have been characterised here for the first time in XLMTM literature.

Bioinformatics Analysis of Mutations Sheds Light on the Evolution of Dengue NS1 Protein With Implications in the Identification of Potential Functional and Druggable Sites.

Non-structural protein (NS1) is a 350 amino acid long conserved protein in the dengue virus. Conservation of NS1 is expected due to its importance in dengue pathogenesis. The protein is known to exist in dimeric and hexameric states. The dimeric state is involved in its interaction with host proteins and viral replication, and the hexameric state is involved in viral invasion. In this work, we performed extensive structure and sequence analysis of NS1 protein, and uncovered the role of NS1 quaternary states in its evolution. A three-dimensional modeling of unresolved loop regions in NS1 structure is performed. "Conserved" and "Variable" regions within NS1 protein were identified from sequences obtained from patient samples and the role of compensatory mutations in selecting destabilizing mutations were identified. Molecular dynamics (MD) simulations were performed to extensively study the effect of a few mutations on NS1 structure stability and compensatory mutations. Virtual saturation mutagenesis, predicting the effect of every individual amino acid substitution on NS1 stability sequentially, revealed virtual-conserved and variable sites. The increase in number of observed and virtual-conserved regions across NS1 quaternary states suggest the role of higher order structure formation in its evolutionary conservation. Our sequence and structure analysis could enable in identifying possible protein-protein interfaces and druggable sites. Virtual screening of nearly 10,000 small molecules, including FDA-approved drugs, permitted us to recognize six drug-like molecules targeting the dimeric sites. These molecules could be promising due to their stable interactions with NS1 throughout the simulation.

Transcriptome profiling of two Moringa species and insights into their antihyperglycemic activity.

BACKGROUND: Moringa concanensis Nimmo (MC), a plant that resembles Moringa oleifera Lam. (MO), has less scientific information but has traditionally been used as a medicinal plant. Moringa species have long been known for their medicinal qualities, which include antioxidant, anti-inflammatory, anticancer, and antihyperglycemic effects. We investigated the antidiabetic potential of MC and MO species in this study by using transcriptome profiling, metabolite analysis, and in vitro assay studies. RESULTS: Our transcriptome analysis revealed the expression of enzymes involved in the biosynthesis of quercetin, chlorogenic acid, and benzylamine, all of which have previously been shown to have antidiabetic activity. We compared the expression patterns of five different tissues from MC and MO and it was found that the key enzymes involved in the biosynthesis of these compounds were highly expressed in leaf tissue. The expression estimated by MC transcriptome data in different tissues was verified using RT-qPCR analysis. The amount of these compounds was further quantified in the crude leaf extract of both species and found that MC had a higher abundance of quercetin and chlorogenic acid than MO. The crude leaf extract from both MC and MO were further tested in vitro, and the results demonstrated strong inhibitory activity for α-glucosidase and DPP-IV enzymes. Our findings suggest that compounds in leaf tissue, such as quercetin, benzylamine, and chlorogenic acid, could play a significant role in this antidiabetic activity. In addition, when comparing MO plants, we found that MC had a slightly higher effect in expression, abundance, and inhibitory activity. CONCLUSIONS: This study presents the first report of MC transcriptome data, as well as a comparison of its anti-diabetic activity to MO. Our analysis discussed the significance of leaf tissue in antidiabetic activity compared to other tissues of both species. Overall, this study not only provides transcriptome resources for Moringa species, but also sheds light on antidiabetic potential of both species.

Integrative network analysis interweaves the missing links in cardiomyopathy diseasome.

Cardiomyopathies are progressive disease conditions that give rise to an abnormal heart phenotype and are a leading cause of heart failures in the general population. These are complex diseases that show co-morbidity with other diseases. The molecular interaction network in the localised disease neighbourhood is an important step toward deciphering molecular mechanisms underlying these complex conditions. In this pursuit, we employed network medicine techniques to systematically investigate cardiomyopathy's genetic interplay with other diseases and uncover the molecular players underlying these associations. We predicted a set of candidate genes in cardiomyopathy by exploring the DIAMOnD algorithm on the human interactome. We next revealed how these candidate genes form association across different diseases and highlighted the predominant association with brain, cancer and metabolic diseases. Through integrative systems analysis of molecular pathways, heart-specific mouse knockout data and disease tissue-specific transcriptomic data, we screened and ascertained prominent candidates that show abnormal heart phenotype, including NOS3, MMP2 and SIRT1. Our computational analysis broadens the understanding of the genetic associations of cardiomyopathies with other diseases and holds great potential in cardiomyopathy research.

Effects of a plant cyclotide on conformational dynamics and destabilization of ß-amyloid fibrils through molecular dynamics simulations.

Aggregation of ß-amyloid (Aß) peptide is one of the hallmarks of Alzheimer's disease (AD) which results in chronic and progressive neurodegeneration of the brain. A recent study by our group have shown the ability of cyclic disulfide-rich peptides ("cyclotides") isolated from a medicinal plant, Clitoria ternatea, to inhibit the aggregation of Aß peptides and reduce oxidative stress caused by reactive oxygen species using in vivo models of transgenic Caenorhabditis elegans. In the present study, through extensive computational docking and multi-ns molecular dynamics (MD) simulation, we evaluated if cyclotides can stably bind to Aß molecules and/or destabilize the Aß fibril by preventing conformational changes from α-helical to ß-sheet rich structures. We demonstrate that cyclotides bind effectively and stably to different forms of Aß structures via hydrogen bonding and hydrophobic interactions. One of the conserved hydrophobic interface residues, Tyr10 was mutated to Ala and the impact of this virtual mutation was estimated by additional MD simulations for the wild-type (WT) and mutant protein-peptide complexes. A detailed MD simulation analyses revealed that cyclotides form hydrogen bonds with the toxic amyloid assemblies thereby weakening the inter-strand hydrogen bonds between the Aß peptide. The φ-ѱ distribution map of residues in the cyclotide binding pocket that ideally adopt ß-sheet conformation show deviation towards right-handed ɑ-helical (ɑR) conformation. This effect was similar to that observed for the Tyr10Ala mutant and doubly so, for the cyclotide bound form. It is therefore possible to hypothesise that the opening up of amyloid ß-sheet is due to an unfolding process occurring in the Aß caused by cyclotide binding and inhibition. Our current findings provide novel structural insights on the mode of interaction between cyclotides and Aß fibrils and describe their anti-amyloid aggregation potential. This sheds light on the future of cyclotide-based drug design against protein aggregation, a hallmark event in many neurodegenerative diseases.

Computational tools to study RNA-protein complexes.

RNA is the key player in many cellular processes such as signal transduction, replication, transport, cell division, transcription, and translation. These diverse functions are accomplished through interactions of RNA with proteins. However, protein-RNA interactions are still poorly derstood in contrast to protein-protein and protein-DNA interactions. This knowledge gap can be attributed to the limited availability of protein-RNA structures along with the experimental difficulties in studying these complexes. Recent progress in computational resources has expanded the number of tools available for studying protein-RNA interactions at various molecular levels. These include tools for predicting interacting residues from primary sequences, modelling of protein-RNA complexes, predicting hotspots in these complexes and insights into derstanding in the dynamics of their interactions. Each of these tools has its strengths and limitations, which makes it significant to select an optimal approach for the question of interest. Here we present a mini review of computational tools to study different aspects of protein-RNA interactions, with focus on overall application, development of the field and the future perspectives.

A genome-wide search of Toll/Interleukin-1 receptor (TIR) domain-containing adapter molecule (TICAM) and their evolutionary divergence from other TIR domain containing proteins.

Toll/Interleukin-1 receptor (TIR) domains are cytoplasmic domain that mediates receptor signalling. These domains are present in proteins like Toll-like receptors (TLR), its signaling adaptors and Interleukins, that form a major part of the immune system. These TIR domain containing signaling adaptors binds to the TLRs and interacts with their TIR domains for downstream signaling. We have examined the evolutionary divergence across the tree of life of two of these TIR domain containing adaptor molecules (TICAM) i.e., TIR domain-containing adapter-inducing interferon-ß (TRIF/TICAM1) and TIR domain containing adaptor molecule2 (TRAM/TICAM2), by using computational approaches. We studied their orthologs, domain architecture, conserved motifs, and amino acid variations. Our study also adds a timeframe to infer the duplication of TICAM protein from Leptocardii and later divergence into TICAM1/TRIF and TICAM2/TRAM. More evidence of TRIF proteins was seen, but the absence of conserved co-existing domains such as TRIF-NTD, TIR, and RHIM domains in distant relatives hints on diversification and adaptation to different biological functions. TRAM was lost in Actinopteri and has conserved domain architecture of TIR across species except in Aves. An additional isoform of TRAM, TAG (TRAM adaptor with the GOLD domain), could be identified in species in the Mesozoic era. Finally, the Hypothesis based Likelihood ratio test was applied to look for selection pressure amongst orthologues of TRIF and TRAM to search for positively selected sites. These residues were mostly seen in the non-structural region of the proteins. Overall, this study unravels evolutionary information on the adaptors TRAM and TRIF and how well they had duplicated to perform diverse functions by changes in their domain architecture across lineages.

Structures of distantly related interacting protein homologs are less divergent than non-interacting homologs.

Homologous proteins can display high structural variation due to evolutionary divergence at low sequence identity. This classical inverse relationship between sequence identity and structural similarity, established many years ago, has remained true between homologous proteins of known structure over time. However, a large number of heteromeric proteins also exist in the structural data bank, where the interacting subunits belong to the same fold and maintain low sequence identity between themselves. It is not clear if there is any selection pressure to deviate from the inverse sequence-structure relationship for such interacting distant homologs, in comparison to pairs of homologs which are not known to interact. We examined 12,824 fold pairs of interacting homologs of known structure, which includes both heteromers and multi-domain proteins. These were compared with monomeric proteins, resulting in 26,082 fold pairs as a dataset of non-interacting homologous systems. Interacting homologs were found to retain higher structural similarity than non-interacting homologs at diminishing sequence identity in a statistically significant manner. Interacting homologs are more similar in their 3D structures than non-interacting homologs and have a preference towards symmetric association. There appears to be a structural constraint between remote homologs due to this commitment.

Exploring the medicinally important secondary metabolites landscape through the lens of transcriptome data in fenugreek (Trigonella foenum graecum L.).

Fenugreek (Trigonella foenum-graecum L.) is a self-pollinated leguminous crop belonging to the Fabaceae family. It is a multipurpose crop used as herb, spice, vegetable and forage. It is a traditional medicinal plant in India attributed with several nutritional and medicinal properties including antidiabetic and anticancer. We have performed a combined transcriptome assembly from RNA sequencing data derived from leaf, stem and root tissues. Around 209,831 transcripts were deciphered from the assembly of 92% completeness and an N50 of 1382 bases. Whilst secondary metabolites of medicinal value, such as trigonelline, diosgenin, 4-hydroxyisoleucine and quercetin, are distributed in several tissues, we report transcripts that bear sequence signatures of enzymes involved in the biosynthesis of such metabolites and are highly expressed in leaves, stem and roots. One of the antidiabetic alkaloid, trigonelline and its biosynthesising enzyme, is highly abundant in leaves. These findings are of value to nutritional and the pharmaceutical industry.

Insights from the analysis of draft genome sequence of Crocus sativus L.

Saffron (Crocus sativus L.) is the low yielding plant of medicinal and economic importance. Therefore, it is of interest to report the draft genome sequence of C. sativus. The draft genome of C. sativus has been assembled using Illumina sequencing and is 3.01 Gb long covering 84.24% of genome. C. sativus genome annotation identified 53,546 functional genes (including 5726 transcription factors), 862,275 repeats and 964,231 SSR markers. The genes involved in the apocarotenoids biosynthesis pathway (crocin, crocetin, picrocrocin, and safranal) were found in the draft genome analysis.

Computational analysis of potential candidate genes involved in the cold stress response of ten Rosaceae members.

BACKGROUND: Plant species from Rosaceae family are economically important. One of the major environmental factors impacting those species is cold stress. Although several Rosaceae plant genomes have recently been sequenced, there have been very few research conducted on cold upregulated genes and their promoter binding sites. In this study, we used computational approaches to identify and analyse potential cold stress response genes across ten Rosaceae family members. RESULTS: Cold stress upregulated gene data from apple and strawberry were used to identify syntelogs in other Rosaceae species. Gene duplication analysis was carried out to better understand the distribution of these syntelog genes in different Rosaceae members. A total of 11,145 popular abiotic stress transcription factor-binding sites were identified in the upstream region of these potential cold-responsive genes, which were subsequently categorised into distinct transcription factor (TF) classes. MYB classes of transcription factor binding site (TFBS) were abundant, followed by bHLH, WRKY, and AP2/ERF. TFBS patterns in the promoter regions were compared among these species and gene families, found to be quite different even amongst functionally related syntelogs. A case study on important cold stress responsive transcription factor family, AP2/ERF showed less conservation in TFBS patterns in the promoter regions. This indicates that syntelogs from the same group may be comparable at the gene level but not at the level of cis-regulatory elements. Therefore, for such genes from the same family, different repertoire of TFs could be recruited for regulation and expression. Duplication events must have played a significant role in the similarity of TFBS patterns amongst few syntelogs of closely related species. CONCLUSIONS: Our study overall suggests that, despite being from the same gene family, different combinations of TFs may play a role in their regulation and expression. The findings of this study will provide information about potential genes involved in the cold stress response, which will aid future functional research of these gene families involved in many important biological processes.

DDX24 is required for muscle fiber organization and the suppression of wound-induced Wnt activity necessary for pole re-establishment during planarian regeneration.

Planarians have a remarkable ability to undergo whole-body regeneration. Successful regeneration outcome is determined by processes like polarity establishment at the wound site, which is followed by pole (organizer) specification. Interestingly, these determinants are almost exclusively expressed by muscles in these animals. However, the molecular toolkit that enables the functional versatility of planarian muscles remains poorly understood. Here we report that SMED_DDX24, a D-E-A-D Box RNA helicase, is necessary for planarian survival and regeneration. We found that DDX24 is enriched in muscles and its knockdown disrupts muscle fiber organization. This leads to defective pole specification, which in turn results in misregulation of many positional control genes specifically during regeneration. ddx24 RNAi also upregulates wound-induced Wnt signalling. Suppressing this ectopic Wnt activity rescues the knockdown phenotype by enabling better anterior pole regeneration. To summarize, our work highlights the role of an RNA helicase in muscle fiber organization, and modulating amputation-induced wnt levels, both of which seem critical for pole re-organization, thereby regulating whole-body regeneration.

Development of candidate gene-based markers and map-based cloning of a dominant rust resistance gene in cultivated groundnut (Arachis hypogaea L.).

A dominant rust resistance gene, VG 9514-Rgene was isolated through map-based cloning. Sequence analysis revealed non-synonymous mutations in the TIR, NBS and LRR region of the R-protein. Candidate gene-based markers from these SNPs revealed complete co-segregation of the isolated VG 9514-Rgene with rust resistance in a RIL population and confirmed their map position in between FRS 72 and SSR_GO340445 markers in arahy03 chromosome. Blastp search of VG 9514-Rprotein detected Arahy.T6DCA5 with >80.0% identity that localized at 142,544,745.0.142,549,184 in arahy03 chromosome. Ka/Ks calculation revealed that VG 9514-Rgene had undergone positive selection compared to four homologous genes in the groundnut genome. Homology based structure modelling of this R-protein revealed a typical consensus three-dimensional folding of TIR-NBS-LRR protein. Non-synonymous mutations in susceptible version of R-protein were mapped and found E268Q mutation in hhGRExE motif, Y309F in RNBS-A motif and I579T in MHD motif of NB-ARC domain are probable candidates for loss of function.

PASS2.7: a database containing structure-based sequence alignments and associated features of protein domain superfamilies from SCOPe.

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/.