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Understanding the Roles of Secondary Shell Hotspots in Protein–Protein Complexes
No full textHotspots are interfacial residues in protein–protein complexes that contribute significantly to complex stability. Methods for identifying interfacial residues in protein–protein complexes are based on two approaches, namely, (a) distance-based methods, which identify residues that form direct interactions with the partner protein and (b) Accessibility Surface Area (ASA)-based methods, which identify those residues that are solvent-exposed in the isolated form of the protein and become buried upon complex formation. In this study, we introduce the concept of secondary shell hotspots, which are hotspots uniquely identified by the distance-based approach, staying buried in both the bound and isolated forms of the protein and yet forming direct interactions with the partner protein. From the analysis of the dataset curated from Docking Benchmark 5.5, comprising 94 protein–protein complexes, we find that secondary shell hotspots are more evolutionarily conserved and have distinct Chou-Fasman propensities and interaction patterns compared to other hotspots. Finally, we present detailed case studies to show that the interaction network formed by the secondary shell hotspots is crucial for complex stability and activity. Further, they act as potentially allosteric propagators and bridge interfacial and non-interfacial sites in the protein. Their in silico mutations to any other amino acid types cause significant destabilization. Overall, this study sheds light on the uniqueness and importance of secondary shell hotspots in protein–protein complexes
Phylograd: fast column-specific calculation of substitution model gradients
No full textBackground:Most popular tools for reconstructing phylogenetic trees from multiple sequence alignments use a model of molecular evolution in which a single substitution matrix or a small set of fixed matrices are shared between all columns. Models with column-specific rate matrices can in principle be fit by automatic differentiation methods, but in practice the heavy computational burden associated with computing the gradients of the many matrix exponentials has hindered exploration of such models.Implementation:Here, we present a highly efficient approach for reverse-mode differentiation of the log likelihood computed with Felsenstein’s algorithm under any time-reversible substitution model. PhyloGrad is implemented in Rust and has Python bindings to easily combine it with automatic differentiation tools.Results:Depending on the tree size, PhyloGrad is 30-100 times faster than automatic differentiation in Pytorch and uses 10-100 times less memory. Even in the task of fitting one global model it is still at least 10 times faster than IQ-TREE3. PhyloGrad accelerates current model optimizations and enables the field to easily explore and implement novel site-specific models
Connecting JWST discovered N/O-enhanced galaxies to globular clusters: evidence from chemical imprints
No full textRecent James Webb Space Telescope (JWST) observations have revealed a growing population of galaxies at z > 4 with elevated nitrogen-to-oxygen ratios. These 'N/O-enhanced' galaxies (NOEGs) exhibit near to supersolar N/O at sub-solar O/H, clearly deviating from the well-established scaling relation between N/O and O/H observed in local galaxies. The origin of this abundance anomaly is unclear. Interestingly, local globular clusters also exhibit anomalous light-element abundances, whose origin remains debated. In this work, we compare the chemical abundance patterns of 22 known NOEGs at 0 less than or similar to z less than or similar to 12-primarily discovered with JWST-to those observed in local globular clusters. We find similarities in the abundances of C, N, O, Fe, and He between the two populations. The similar abundance patterns support the scenario in which globular cluster stars formed within proto-cluster environments-similar to those traced by NOEGs-that were self-enriched. Indeed, the enhancement in N/O in early galaxies appears to be only found in dense stellar environments with Sigma(*) >= 10(2.5 )M (R) pc(-2), as expected for the progenitors of globular clusters in the Milky Way, and similar to those of star clusters identified in strongly lensed high-redshift galaxies. Furthermore, we find a tentative positive correlation between N/O ratios and stellar mass among NOEGs. The apparent high occurrence rate of NOEGs at high redshift is consistent with the picture of cluster-dominated star formation during the early stages of galaxy evolution. Measuring chemical abundances across diverse stellar environments in high-redshift galaxies will be crucial for elucidating the connection between NOEGs and globular clusters
Heteroaryl iminothioindoxyl (HA-ITI) photoswitches via regioselective aza-Wittig synthesis: unifying red-shifted absorption, largeE/Z band separation, and tunable thermal recovery
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Ubiquitination and autophagy in host-pathogen interactions: from immune surveillance to therapeutic targeting
No full textUbiquitination, the covalent attachment of ubiquitin to proteins and other cellular substrates, is a dynamic post-translational modification that enables cells to rapidly respond to internal and external threats. Beyond its canonical role in targeting proteins for proteasomal degradation, ubiquitination orchestrates the assembly of signalling complexes that regulate innate and adaptive immune responses, modulates inflammatory pathways and directs selective autophagy to eliminate intracellular pathogens through lysosomal degradation. To persist and replicate within the host, viruses, bacteria and parasites have evolved diverse mechanisms to evade, manipulate or exploit the host's ubiquitin and autophagy machinery. Some pathogens subvert these systems to dampen immune surveillance, whereas others co-opt them to facilitate replication or dissemination. In this Review, we examine how ubiquitin and autophagy shape host-pathogen interactions, uncover common and pathogen-specific strategies of immune evasion, and discuss emerging therapeutic approaches that aim to leverage these interconnected pathways to enhance antimicrobial immunity
Learnable Koopman-enhanced transformer-based time series forecasting with spectral control: simulation results
No full textSimuilation results regarding the article entitled Learnable Koopman-Enhanced Transformer-Based Time Series Forecasting with Spectral Contr
A synthetic biology roadmap for sustainable production of the plant-originated anti-cancer drug paclitaxel
No full textDataset for the DeepKoopFormer, Learnable DeepKoopFormer, DeepNeuralODEFormer, DeepLiquidFormer
No full textThese dataset consist of climate, energy, and cryptocurrency used in the forecasting task in different article
