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Motivation Alternative splicing, as an essential regulatory mechanism in normal mammalian cells, is frequently disturbed in cancer and other diseases. Switches in the expression of most dominant alternative isoforms can alter protein interaction networks of associated genes giving rise to disease and disease progression. Here, we present CanIsoNet, a database to view, browse and search isoform switching events in diseases. CanIsoNet is the first webserver that incorporates isoform expression data with STRING interaction networks and ClinVar annotations to predict the pathogenic impact of isoform switching events in various diseases. Results Data in CanIsoNet can be browsed by disease or searched by genes or isoforms in annotation-rich data tables. Various annotations for 11 811 isoforms and 14 357 unique isoform switching events across 31 different disease types are available. The network density score for each disease-specific isoform, PFAM domain IDs of disrupted interactions, domain structure visualization of transcripts and expression data of switched isoforms for each sample is given. Additionally, the genes annotated in ClinVar are highlighted in interactive interaction networks. Availability and implementation CanIsoNet is freely available at https://www.caniso.net. The source codes can be found under a Creative Common License at https://github.com/kahramanlab/CanIsoNet_Web. Supplementary information Supplementary data are available at Bioinformatics Advances online.

MotivationAlternative splicing, as an essential regulatory mechanism in normal mammalian cells, is frequently disturbed in cancer and other diseases. Switches in the expression of most dominant alternative isoforms can alter protein interaction networks of associated genes giving rise to a disease or disease progression. Here, we present CanIsoNet (disease-specific isoform interaction network), a database to view, browse and search these isoform switching events. CanIsoNet is the first webserver that incorporates isoform expression data with STRING interaction networks and ClinVar annotations to predict the pathogenic impact of isoform switching events in various diseases.ResultsData in CanIsoNet can be browsed by disease or searched by genes or isoforms in annotation-rich data tables. Various annotations for 11,072 isoforms and 13,531 unique isoform switching events across 28 different tissue types are provided. The network density score for each disease-specific isoform, PFAM domain IDs of disrupted interactions, domain structure visualization of transcripts and expression data of switched isoforms for each sample are given. Additionally, the genes annotated in ClinVar are highlighted in the interactive interaction network.AvailabilityCanIsoNet is freely available at https://caniso.net. The source codes can be found under a Creative Common License at https://github.com/kahramanlab/CanIsoNet_Web.Supplementary InformationSupplementary data are available at Bioinformatics online.

Rapid progress has recently been made in the elucidation of the genetic basis of childhood-onset inherited generalized dystonia (IGD) due to the implementation of genomic sequencing methodologies. We identified four patients with childhood-onset IGD harboring novel disease-causing mutations in lysine-specific histone methyltransferase 2B gene (KMT2B) by whole-exome sequencing. The main focus of this paper is to gain novel pathophysiological insights through understanding the molecular consequences of these mutations.The disease course is mostly progressive, evolving from lower limbs into generalized dystonia, which could be associated with dysarthria, dysphonia, intellectual disability, orofacial dyskinesia, and sometimes distinct dysmorphic facial features. In two patients, motor performances improved after bilateral implantation of deep brain stimulation in the globus pallidus internus (GPi-DBS). Pharmacotherapy with trihexyphenidyl reduced dystonia in two patients.We discovered three novel KMT2B mutations. Our analyses revealed that the mutation in patient 1 (c.7463 A > G, p.Y2488C) is localized in the highly conserved FYRC domain of KMT2B. This mutation holds the potential to alter the inter-domain FYR interactions, which could lead to KMT2B instability. The mutations in patients 2 and 3 (c.3602dupC, p.M1202Dfs*22; c.4229delA, p.Q1410Rfs*12) lead to predicted unstable transcripts, likely to be subject to degradation by non-sense mediated decay.Childhood-onset progressive dystonia with orofacial involvement is one of the main clinical manifestations of KMT2B mutations. In all, 26% (18/69) of the reported cases have T2 signal alterations of the globus pallidus internus, mostly at a younger age. Anticholinergic medication and GPi-DBS are promising treatment options and shall be considered early.An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Rapid progress has recently been made in the elucidation of the genetic basis of childhood-onset inherited generalized dystonia (IGD) due to the implementation of genomic sequencing methodologies. We identified four patients with childhood-onset IGD harboring novel disease-causing mutations in lysine-specific histone methyltransferase 2B gene (KMT2B) by whole-exome sequencing. The main focus of this paper is to gain novel pathophysiological insights through understanding the molecular consequences of these mutations. The disease course is mostly progressive, evolving from lower limbs into generalized dystonia, which could be associated with dysarthria, dysphonia, intellectual disability, orofacial dyskinesia, and sometimes distinct dysmorphic facial features. In two patients, motor performances improved after bilateral implantation of deep brain stimulation in the globus pallidus internus (GPi-DBS). Pharmacotherapy with trihexyphenidyl reduced dystonia in two patients. We discovered three novel KMT2B mutations. Our analyses revealed that the mutation in patient 1 (c.7463A > G, p.Y2488C) is localized in the highly conserved FYRC domain of KMT2B. This mutation holds the potential to alter the inter-domain FYR interactions, which could lead to KMT2B instability. The mutations in patients 2 and 3 (c.3596_3697insC, p.M1202Dfs*22; c.4229delA, p.Q1410Rfs*12) lead to predicted unstable transcripts, likely to be subject to degradation by non-sense-mediated decay. Childhood-onset progressive dystonia with orofacial involvement is one of the main clinical manifestations of KMT2B mutations. In all, 26% (18/69) of the reported cases have T2 signal alterations of the globus pallidus internus, mostly at a younger age. Anticholinergic medication and GPi-DBS are promising treatment options and shall be considered early.

Due to its clinical relevance, modulation of functionally relevant amino acids in protein-protein complexes has attracted a great deal of attention. To this end, many approaches have been proposed to predict partner-selecting, i.e., specificity-determining positions in evolutionarily close complexes. These approaches can be grouped into sequence-based machine learning and structure-based energy-driven methods. In this work, we assessed these methods’ ability to map the specificity-determining positions of Axl, a receptor tyrosine kinase involved in cancer progression and immune-related diseases. For this, we used three sequence-based predictors – SDPred, Multi-RELIEF, and Sequence Harmony – and a structure-based approach by utilizing HADDOCK and extensive molecular dynamics simulations. As a result, we show that (i) sequence-based methods overpredict the number of specificity-determining positions for Axl complexes and that (ii) combining sequence-based approaches with HADDOCK provides the most coherent set of predictions. Our work lays out a critical study on the comparative performance specificity-determining position predictors. It also presents a combined sequence-structure-based approach, which can guide the development of therapeutic molecules capable of combatting Axl misregulation in different types of diseases.

In all living organisms, protein kinases regulate various cell signaling events through phosphorylation. The phosphorylation occurs upon transferring an ATP's terminal phosphate to a target residue. Because of the central role of protein kinases in several proliferative pathways, point mutations occurring within the kinase's ATP-binding site can lead to a constitutively active enzyme, and ultimately, to cancer. A select set of these point mutations can also make the enzyme drug resistant toward the available kinase inhibitors. Because of technical and economical limitations, rapid experimental exploration of the impact of these mutations remains to be a challenge. This underscores the importance of kinase-ligand binding affinity prediction tools that are poised to measure the efficacy of inhibitors in the presence of kinase mutations. To this end, here, we compare the performances of six web-based scoring tools (DSX-ONLINE, KDEEP, HADDOCK2.2, PDBePISA, Pose&Rank, and PRODIGY-LIG) in assessing the impact of kinase mutations on their interactions with their inhibitors. This assessment is carried out on a new structure-based BINDKIN benchmark we compiled. BINDKIN contains wild-type and mutant structure pairs of kinase-inhibitor complexes, together with their corresponding experimental binding affinities (in the form of IC50, K-d, and K-i). The performance of various web servers over BINDKIN shows that they cannot predict the binding affinities (Delta Gs) of wild-type and mutant cases directly. Still, they could catch whether a mutation improves or worsens the ligand binding (Delta Delta Gs) where the highest Pearson's R correlation coefficient is reached by DSX-ONLINE over the K-i dataset. When homology models are used instead of K-i-associated crystal structures, DSX-ONLINE loses its predictive capacity. These results highlight that there is room to improve the available scoring functions to estimate the impact of protein kinase point mutations on inhibitor binding. The BINDKIN benchmark with all related results is freely accessible online (https://github.com/CSB-KaracaLab/BINDKIN).

Under normal conditions, cells of almost all tissue types express the same predominant canonical transcript isoform at each gene locus. In cancer, however, splicing regulation is often disturbed, leading to cancer-specific switches in the most dominant transcripts (MDT). To address the pathogenic impact of these switches, we have analyzed isoform-specific protein–protein interaction disruptions in 1,209 cancer samples covering 27 different cancer types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) project of the International Cancer Genomics Consortium (ICGC). Our study revealed large variations in the number of cancer-specific MDT (cMDT) with the highest frequency in cancers of female reproductive organs. Interestingly, in contrast to the mutational load, cancers arising from the same primary tissue had a similar number of cMDT. Some cMDT were found in 100% of all samples in a cancer type, making them candidates for diagnostic biomarkers. cMDT tend to be located at densely populated network regions where they disrupted protein interactions in the proximity of pathogenic cancer genes. A gene ontology enrichment analysis showed that these disruptions occurred mostly in protein translation and RNA splicing pathways. Interestingly, samples with mutations in the spliceosomal complex tend to have higher number of cMDT, while other transcript expressions correlated with mutations in non-coding splice-site and promoter regions of their genes. This work demonstrates for the first time the large extent of cancer-specific alterations in alternative splicing for 27 different cancer types. It highlights distinct and common patterns of cMDT and suggests novel pathogenic transcripts and markers that induce large network disruptions in cancers.

Protein kinases regulate various cell signaling events in a diverse range of species through phosphorylation. The phosphorylation occurs upon transferring the terminal phosphate of an ATP molecule to a designated target residue. Due to the central role of protein kinases in proliferative pathways, point mutations occurring within or in the vicinity of ATP binding pocket can render the enzyme overactive, leading to cancer. Combatting such mutation-induced effects with the available drugs has been a challenge, since these mutations usually happen to be drug resistant. Therefore, the functional study of naturally and/or artificially occurring kinase mutations have been at the center of attention in diverse biology-related disciplines. Unfortunately, rapid experimental exploration of the impact of such mutations remains to be a challenge due to technical and economical limitations. Therefore, the availability of kinase-ligand binding affinity prediction tools is of great importance. Within this context, we have tested six state-of-the-art web-based affinity predictors (DSX-ONLINE, KDEEP, HADDOCK2.2, PDBePISA, Pose&Rank, and PRODIGY-LIG) in assessing the impact of kinase mutations with their ligand interactions. This assessment is performed on our structure-based protein kinase mutation benchmark, BINDKIN. BINDKIN contains 23 wild type-mutant pairs of kinase-small molecule complexes, together with their corresponding binding affinity data (in the form of IC50, Kd, and Ki). The web-server performances over BINDKIN show that the raw server predictions fail to produce good correlations with the experimental data. However, when we start looking in to the direction of change (whether a mutation improves/worsens the binding), we observe that over Ki data, DSX-ONLINE achieves a Pearson’s R correlation coefficient of 0.97. When we used homology models instead of crystal structures, this correlation drops to 0.45. These results highlight that there is still room to improve the available web-based predictors to estimate the impact of protein kinase point mutations. We present our BINDKIN benchmark and all the related results online for the sake of aiding such improvement efforts. Our files can be reached at https://github.com/CSB-KaracaLab/BINDKIN

Regional Student Groups (RSGs) of the International Society for Computational Biology Student Council (ISCB-SC) have been instrumental to connect computational biologists globally and to create more awareness about bioinformatics education. This article highlights the initiatives carried out by the RSGs both nationally and internationally to strengthen the present and future of the bioinformatics community. Moreover, we discuss the future directions the organization will take and the challenges to advance further in the ISCB-SC main mission: "Nurture the new generation of computational biologists". ispartof: F1000Res vol:8 pages:ISCB Comm J-1574- ispartof: location:England status: Published online