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Deleterious single amino acid variation (SAV) is one of the leading causes of human diseases. Evaluating the functional impact of SAVs is crucial for diagnosis of genetic disorders. We previously developed a deep convolutional neural network predictor, DeepSAV, to evaluate the deleterious effects of SAVs on protein function based on various sequence, structural, and functional properties. DeepSAV scores of rare SAVs observed in the human population are aggregated into a gene-level score called GTS (Gene Tolerance of rare SAVs) that reflects a gene's tolerance to deleterious missense mutations and serves as a useful tool to study gene-disease associations. In this study, we aim to enhance the performance of DeepSAV by using expanded datasets of pathogenic and benign variants, more features, and neural network optimization. We found that multiple sequence alignments built from vertebrate-level orthologs yield better prediction results compared to those built from mammalian-level orthologs. For multiple sequence alignments built from BLAST searches, optimal performance was achieved with a sequence identify cutoff of 50% to remove distant homologs. this website The new version of DeepSAV exhibits the best performance among standalone predictors of deleterious effects of SAVs. We developed the DBSAV database (http//prodata.swmed.edu/DBSAV) that reports GTS scores of human genes and DeepSAV scores of SAVs in the human proteome, including pathogenic and benign SAVs, population-level SAVs, and all possible SAVs by single nucleotide variations. This database serves as a useful resource for research of human SAVs and their relationships with protein functions and human diseases.Non-coding RNA (ncRNA) genes assume increasing biological importance, with growing associations with diseases. Many ncRNA sources are transcript-centric, but for non-coding variant analysis and disease decipherment it is essential to transform this information into a comprehensive set of genome-mapped ncRNA genes. We present GeneCaRNA, a new all-inclusive gene-centric ncRNA database within the GeneCards Suite. GeneCaRNA information is integrated from four community-backed data structures the major transcript database RNAcentral with its 20 encompassed databases, and the ncRNA entries of three major gene resources HGNC, Ensembl and NCBI Gene. GeneCaRNA presents 219,587 ncRNA gene pages, a 7-fold increase from those available in our three gene mining sources. Each ncRNA gene has wide-ranging annotation, mined from >100 worldwide sources, providing a powerful GeneCards-leveraged search. The latter empowers VarElect, our disease-gene interpretation tool, allowing one to systematically decipher ncRNA variants. The combined power of GeneCaRNA with GeneHancer, our regulatory elements database, facilitates wide-ranging scrutiny of the non-coding terra incognita of gene networks and whole genome analyses.The Smc5/6 complex facilitates chromosome replication and DNA break repair. Within this complex, a subcomplex composed of Nse1, Nse3 and Nse4 is thought to play multiple roles through DNA binding and regulating ATP-dependent activities of the complex. However, how the Nse1-Nse3-Nse4 subcomplex carries out these multiple functions remain unclear. To address this question, we determine the crystal structure of the Xenopus laevis Nse1-Nse3-Nse4 subcomplex at 1.7 Å resolution and examine how it interacts with DNA. Our structural analyses show that the Nse1-Nse3 dimer adopts a closed conformation and forms three interfaces with a segment of Nse4, forcing it into a Z-shaped conformation. The Nse1-Nse3-Nse4 structure provides an explanation for how the lung disease immunodeficiency and chromosome breakage syndrome-causing mutations could dislodge Nse4 from Nse1-Nse3. Our DNA binding and mutational analyses reveal that the N-terminal and the middle region of Nse4 contribute to DNA interaction and cell viability. Integrating our data with previous crosslink mass spectrometry data, we propose potential roles of the Nse1-Nse3-Nse4 complex in binding DNA within the Smc5/6 complex.Fluoroquinolones (FQ) are antibiotics widely used in clinical practise, but the development of bacterial resistance to these drugs is currently a critical public health problem. In this context, ternary copper complexes of FQ (CuFQPhen) have been studied as a potential alternative. In this study, we compared the passive diffusion across the lipid bilayer of one of the most used FQ, ciprofloxacin (Cpx), and its ternary copper complex, CuCpxPhen, that has shown previous promising results regarding antibacterial activity and membrane partition. A combination of spectroscopic studies and molecular dynamics simulations were used and two different model membranes tested one composed of anionic phospholipids, and the other composed of zwitterionic phospholipids. The obtained results showed a significantly higher membrane permeabilization activity, larger partition, and a more favourable free energy landscape for the permeation of CuCpxPhen across the membrane, when compared to Cpx. Furthermore, the computational results indicated a more favourable translocation of CuCpxPhen across the anionic membrane, when compared to the zwitterionic one, suggesting a higher specificity towards the former. These findings are important to decipher the influx mechanism of CuFQPhen in bacterial cells, which is crucial for the ultimate use of CuFQPhen complexes as an alternative to FQ to tackle multidrug-resistant bacteria.Transient receptor potential (TRP) ion channels are a super-family of ion channels that mediate transmembrane cation flux with polymodal activation, ranging from chemical to physical stimuli. Furthermore, due to their ubiquitous expression and role in human diseases, they serve as potential pharmacological targets. Advances in cryo-EM TRP channel structural biology has revealed general, as well as diverse, architectural elements and regulatory sites among TRP channel subfamilies. Here, we review the endogenous and pharmacological ligand-binding sites of TRP channels and their regulatory mechanisms.The highly conserved C-terminal domain (CTD) of the largest subunit of RNA polymerase II comprises a consensus heptad (Y1S2P3T4S5P6S7) repeated multiple times. Despite the simplicity of its sequence, the essential CTD domain orchestrates eukaryotic transcription and co-transcriptional processes, including transcription initiation, elongation, and termination, and mRNA processing. These distinct facets of the transcription cycle rely on specific post-translational modifications (PTM) of the CTD, in which five out of the seven residues in the heptad repeat are subject to phosphorylation. A hypothesis termed the "CTD code" has been proposed in which these PTMs and their combinations generate a sophisticated landscape for spatiotemporal recruitment of transcription regulators to Pol II. In this review, we summarize the recent experimental evidence understanding the biological role of the CTD, implicating a context-dependent theme that significantly enhances the ability of accurate transcription by RNA polymerase II.