Sparsely-connected autoencoder (SCA) for single cell RNAseq data mining

Abstract Single-cell RNA sequencing (scRNAseq) is an essential tool to investigate cellular heterogeneity. Thus, it would be of great interest being able to disclose biological information belonging to cell subpopulations, which can be defined by clustering analysis of scRNAseq data. In this manuscript, we report a tool that we developed for the functional mining of single cell clusters based on Sparsely-Connected Autoencoder (SCA). This tool allows uncovering hidden features associated with scRNAseq data. We implemented two new metrics, QCC (Quality Control of Cluster) and QCM (Quality Control of Model), which allow quantifying the ability of SCA to reconstruct valuable cell clusters and to evaluate the quality of the neural network achievements, respectively. Our data indicate that SCA encoded space, derived by different experimentally validated data (TF targets, miRNA targets, Kinase targets, and cancer-related immune signatures), can be used to grasp single cell cluster-specific functional features. In our implementation, SCA efficacy comes from its ability to reconstruct only specific clusters, thus indicating only those clusters where the SCA encoding space is a key element for cells aggregation. SCA analysis is implemented as module in rCASC framework and it is supported by a GUI to simplify it usage for biologists and medical personnel

SOHSite: incorporating evolutionary information and physicochemical properties to identify protein S-sulfenylation sites

Distribution of KEGG pathway annotations for S-sulfenylated proteins. (DOCX 15 kb

Deconvoluting kinase inhibitor induced cardiotoxicity

Many drugs designed to inhibit kinases have their clinical utility limited by cardiotoxicity-related label warnings or prescribing restrictions. While this liability is widely recognized, designing safer kinase inhibitors (KI) requires knowledge of the causative kinase(s). Efforts to unravel the kinases have encountered pharmacology with nearly prohibitive complexity. At therapeutically relevant concentrations, KIs show promiscuity distributed across the kinome. Here, to overcome this complexity, 65 KIs with known kinome-scale polypharmacology profiles were assessed for effects on cardiomyocyte (CM) beating. Changes in human iPSC-CM beat rate and amplitude were measured using label-free cellular impedance. Correlations between beat effects and kinase inhibition profiles were mined by computation analysis (Matthews Correlation Coefficient) to identify associated kinases. Thirty kinases met criteria of having (1) pharmacological inhibition correlated with CM beat changes, (2) expression in both human-induced pluripotent stem cell-derived cardiomyocytes and adult heart tissue, and (3) effects on CM beating following single gene knockdown. A subset of these 30 kinases were selected for mechanistic follow up. Examples of kinases regulating processes spanning the excitation–contraction cascade were identified, including calcium flux (RPS6KA3, IKBKE) and action potential duration (MAP4K2). Finally, a simple model was created to predict functional cardiotoxicity whereby inactivity at three sentinel kinases (RPS6KB1, FAK, STK35) showed exceptional accuracy in vitro and translated to clinical KI safety data. For drug discovery, identifying causative kinases and introducing a predictive model should transform the ability to design safer KI medicines. For cardiovascular biology, discovering kinases previously unrecognized as influencing cardiovascular biology should stimulate investigation of underappreciated signaling pathways

New Perspectives, Opportunities, and Challenges in Exploring the Human Protein Kinome.

The human protein kinome comprises 535 proteins that, with the exception of approximately 50 pseudokinases, control intracellular signaling networks by catalyzing the phosphorylation of multiple protein substrates. While a major research focus of the last 30 years has been cancer-associated Tyr and Ser/Thr kinases, over 85% of the kinome has been identified to be dysregulated in at least one disease or developmental disorder. Despite this remarkable statistic, for the majority of protein kinases and pseudokinases, there are currently no inhibitors progressing toward the clinic, and in most cases, details of their physiologic and pathologic mechanisms remain at least partially obscure. By curating and annotating data from the literature and major public databases of phosphorylation sites, kinases, and disease associations, we generate an unbiased resource that highlights areas of unmet need within the kinome. We discuss strategies and challenges associated with characterizing catalytic and noncatalytic outputs in cells, and describe successes and new frontiers that will support more comprehensive cancer-targeting and therapeutic evaluation in the future. Cancer Res; 78(1); 15-29. ©2017 AACR

Thirty years of molecular dynamics simulations on posttranslational modifications of proteins

Posttranslational modifications (PTMs) are an integral component to how cells respond to perturbation. While experimental advances have enabled improved PTM identification capabilities, the same throughput for characterizing how structural changes caused by PTMs equate to altered physiological function has not been maintained. In this Perspective, we cover the history of computational modeling and molecular dynamics simulations which have characterized the structural implications of PTMs. We distinguish results from different molecular dynamics studies based upon the timescales simulated and analysis approaches used for PTM characterization. Lastly, we offer insights into how opportunities for modern research efforts on in silico PTM characterization may proceed given current state-of-the-art computing capabilities and methodological advancements.Comment: 64 pages, 11 figure

3D struktury fosforylace

Fosforylace je běžná post-translační modifikace proteinů využívaná téměř ve všech buněčných procesech. Přidání fosfátové skupiny na vedlejší řetězec aminokyseliny může z důvodu velikosti fosfátové skupiny a jejího negativního náboje způsobit strukturní změny proteinu a ovlivnit proteinové interakce. Fosforylace také může vést ke změně proteinové funkce, aktivity, a dokonce umístění proteinu v rámci buňky. Experimentální studium fosforylačních míst je velmi časově a finančně náročné i dnes v době hmotnostní spektrometrie. Z tohoto důvodu je předmětem výzkumu mnoha bioinformatických vědeckých skupin predikce fosforylačních míst. Současné analýzy fosforylačních míst studovaly především nefosforylovaná fosforylační místa a rozdělení a zastoupení aminokyselin v jejich sekvenčním okolí. Protože ke specificitě proteinových kináz ale mohou přispívat i aminokyseliny sekvenčně sice vzdálené, ale strukturně blízké, byly v této práci studovány 3D strukturní vlastnosti fosforylačních míst. Zároveň byla poprvé rozsáhle zkoumána fosforylační místa ve fosforylovaném stavu a výsledky byly srovnány s fosforylačními místy v nefosforylovaném stavu. Fosforylační místa byla nalezena především ve smyčkách a na povrchu proteinů. Aminokyseliny v jejich okolí byly častěji hydrofilní, pozitivně nabité a méně blízko sebe než...Protein phosphorylation is a common post-translational protein modification used in almost all cellular processes. When a phosphate group is added to an amino acid side chain, it may alter the protein conformation and protein-protein interactions due to its size and its negative charge. It may also change the protein function, activity and even localization within the cell. Experimental detection of phosphorylation is still extremely labor demanding and very expensive, even when deploying protein mass spectrometry. For this very reason many bioinformatics scientific groups focus on the prediction of protein phosphorylation sites. Recent analyses of phosphorylation sites studied mainly non-phosphorylated phosphorylation sites and the distribution and representation of amino acids sequentially neighboring them. Since sequentially more distant, but structurally close amino acids can contribute to the recognition of protein substrate by protein kinase, structural environment of phosphorylation sites was studied in this thesis. Furthermore, 3D structures of phosphorylation sites were comprehensively studied for the first time in a phosphorylated state and the results were compared with the results obtained from the analysis of non- phosphorylated sites. Phosphorylation sites were found mostly within...Katedra filosofie a dějin přírodních vědDepartment of Philosophy and History of ScienceFaculty of SciencePřírodovědecká fakult