A rational free energy-based approach to understanding and targeting disease-causing missense mutations.

BACKGROUND AND SIGNIFICANCE: Intellectual disability is a condition characterized by significant limitations in cognitive abilities and social/behavioral adaptive skills and is an important reason for pediatric, neurologic, and genetic referrals. Approximately 10% of protein-encoding genes on the X chromosome are implicated in intellectual disability, and the corresponding intellectual disability is termed X-linked ID (XLID). Although few mutations and a small number of families have been identified and XLID is rare, collectively the impact of XLID is significant because patients usually are unable to fully participate in society. OBJECTIVE: To reveal the molecular mechanisms of various intellectual disabilities and to suggest small molecules which by binding to the malfunctioning protein can reduce unwanted effects. METHODS: Using various in silico methods we reveal the molecular mechanism of XLID in cases involving proteins with known 3D structure. The 3D structures were used to predict the effect of disease-causing missense mutations on the folding free energy, conformational dynamics, hydrogen bond network and, if appropriate, protein-protein binding free energy. RESULTS: It is shown that the vast majority of XLID mutation sites are outside the active pocket and are accessible from the water phase, thus providing the opportunity to alter their effect by binding appropriate small molecules in the vicinity of the mutation site. CONCLUSIONS: This observation is used to demonstrate, computationally and experimentally, that a particular condition, Snyder-Robinson syndrome caused by the G56S spermine synthase mutation, might be ameliorated by small molecule binding

The Energy Landscape Analysis of Cancer Mutations in Protein Kinases

The growing interest in quantifying the molecular basis of protein kinase activation and allosteric regulation by cancer mutations has fueled computational studies of allosteric signaling in protein kinases. In the present study, we combined computer simulations and the energy landscape analysis of protein kinases to characterize the interplay between oncogenic mutations and locally frustrated sites as important catalysts of allostetric kinase activation. While structurally rigid kinase core constitutes a minimally frustrated hub of the catalytic domain, locally frustrated residue clusters, whose interaction networks are not energetically optimized, are prone to dynamic modulation and could enable allosteric conformational transitions. The results of this study have shown that the energy landscape effect of oncogenic mutations may be allosteric eliciting global changes in the spatial distribution of highly frustrated residues. We have found that mutation-induced allosteric signaling may involve a dynamic coupling between structurally rigid (minimally frustrated) and plastic (locally frustrated) clusters of residues. The presented study has demonstrated that activation cancer mutations may affect the thermodynamic equilibrium between kinase states by allosterically altering the distribution of locally frustrated sites and increasing the local frustration in the inactive form, while eliminating locally frustrated sites and restoring structural rigidity of the active form. The energy landsape analysis of protein kinases and the proposed role of locally frustrated sites in activation mechanisms may have useful implications for bioinformatics-based screening and detection of functional sites critical for allosteric regulation in complex biomolecular systems

Sequence and Structure Signatures of Cancer Mutation Hotspots in Protein Kinases

Protein kinases are the most common protein domains implicated in cancer, where somatically acquired mutations are known to be functionally linked to a variety of cancers. Resequencing studies of protein kinase coding regions have emphasized the importance of sequence and structure determinants of cancer-causing kinase mutations in understanding of the mutation-dependent activation process. We have developed an integrated bioinformatics resource, which consolidated and mapped all currently available information on genetic modifications in protein kinase genes with sequence, structure and functional data. The integration of diverse data types provided a convenient framework for kinome-wide study of sequence-based and structure-based signatures of cancer mutations. The database-driven analysis has revealed a differential enrichment of SNPs categories in functional regions of the kinase domain, demonstrating that a significant number of cancer mutations could fall at structurally equivalent positions (mutational hotspots) within the catalytic core. We have also found that structurally conserved mutational hotspots can be shared by multiple kinase genes and are often enriched by cancer driver mutations with high oncogenic activity. Structural modeling and energetic analysis of the mutational hotspots have suggested a common molecular mechanism of kinase activation by cancer mutations, and have allowed to reconcile the experimental data. According to a proposed mechanism, structural effect of kinase mutations with a high oncogenic potential may manifest in a significant destabilization of the autoinhibited kinase form, which is likely to drive tumorigenesis at some level. Structure-based functional annotation and prediction of cancer mutation effects in protein kinases can facilitate an understanding of the mutation-dependent activation process and inform experimental studies exploring molecular pathology of tumorigenesis

Universal Quantitative Kinase Assay Based on Diagonal SCX Chromatography and Stable Isotope Dimethyl Labeling Provides High-definition Kinase Consensus Motifs for PKA and Human Mps1

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IN SILICO MODELING THE EFFECT OF SINGLE POINT MUTATIONS AND RESCUING THE EFFECT BY SMALL MOLECULES BINDING

Single-point mutation in genome, for example, single-nucleotide polymorphism (SNP) or rare genetic mutation, is the change of a single nucleotide for another in the genome sequence. Some of them will result in an amino acid substitution in the corresponding protein sequence (missense mutations); others will not. This investigation focuses on genetic mutations resulting in a change in the amino acid sequence of the corresponding protein. This choice is motivated by the fact that missense mutations are frequently found to affect the native function of proteins by altering their structure, interaction and other properties and cause diseases. A particular disease is the Snyder-Robinson syndrome (SRS), which is an X-linked mental retardation found to be caused by missense mutations in human spermine synthase (SMS). In this thesis, a rational approach to predict the effects of missense mutations on SMS wild-type characteristics was carried. Following this work, a structure-based virtual screening of small molecules was applied to rescue the disease-causing effect by searching the small molecules to stabilize the malfunctioning SMS mutant dimer

KinMutBase, a database of human disease-causing protein kinase mutations

KinMutBase (http://www.uta.fi/imt/bioinfo/KinMutBase/ ) is a registry of mutations in human protein kinases related to disorders. Kinases are essential cellular signaling molecules, in which mutations can lead to diseases, including immunodeficiencies, cancers and endocrine disorders. The first release of KinMutBase contained information for protein tyrosine kinases. The current release includes also serine/threonine protein kinases, as well as an update of the tyrosine kinases. There are 251 entries altogether, representing 337 families and 621 patients. Mutations appear both in conserved hallmark residues of the kinases as well as in non-homologous sites. The KinMutBase WWW pages provide plenty of information, namely mutation statistics and display, clickable sequences with mutations and changes to restriction enzyme patterns

Strukturbiologische und zelluläre Charakterisierung Isoform-selektiver kovalent-allosterischer Akt-Inhibitoren

Die Proteinkinase Akt, die aus drei Isoformen (Akt1/Akt2/Akt3) besteht, ist ein zentraler Knotenpunkt innerhalb des PI3K/Akt/mTOR-Signalwegs. Genomische Veränderungen wie aktivierende Mutationen in PI3K und Amplifikationen von AKT-Genen können eine Überaktivierung der Akt-Isoformen und damit einhergehend verschiedene Krankheiten auslösen. Trotz intensiver Forschung in den letzten Jahrzehnten sind mehrere klinische Studien mit potenziellen Arzneimittelkandidaten gescheitert. Verantwortlich dafür sind u. a. der Mangel an Informationen über Isoform-spezifische Funktionen im Zusammenhang mit menschlichen Krankheiten sowie die nicht selektive Adressierung der Isoformen und die damit verbundenen Nebenwirkungen. In dieser Arbeit war das Hauptziel, strukturbiologische und zelluläre Systeme zu etablieren, die die Grundlage für ein strukturbasiertes Wirkstoffdesign von Isoform-selektiven kovalent-allosterischen Akt-Inhibitoren (CAAIs) bilden. Zu diesem Zweck wurde zunächst ein detaillierter Sequenz- und Strukturvergleich der Akt-Isoformen durchgeführt. Die Strukturanalyse und ein fundiertes Konstruktdesign ermöglichten die Entwicklung effizienter Expressions- und Reinigungsstrategien. Weiterhin konnte im Rahmen von Kristallisationsstudien ein einzigartiger Einblick in die Akt2-Bindungstasche gewonnen werden, indem diese in Akt1 nachgebildet wurde. Dieser Einblick, kombiniert mit biochemischen und massenspektrometrischen Daten, ermöglichte eine Evaluierung einer fokussierten Substanzbibliothek und eine Verifizierung des von einem Homologiemodell abgeleiteten CAAI-Designansatzes. Um weiterführende zelluläre Studien zu ermöglichen, wurde ein Ba/F3-Akt-Isoform-abhängiges Modellsystem etabliert. Mit Hilfe dieses Modellsystems konnten biochemische Selektivitätsprofile der fokussierten Substanzbibliothek erstmalig in den zellulären Kontext übertragen werden und dienten als Grundlage für weitere Studien an der menschlichen Krebszelllinie PANC1. Darueber hinaus zeigten zellulären Studien an Akt-knock-out-Modellen die Vorteile der Isoform-selektiven CAAIs gegenüber invasiven genetischen knock-outs für die Entschlüsselung der Isoform-spezifischen Funktionen von Akt.The protein kinase Akt, comprising three isoforms (Akt1/Akt2/Akt3), is a central signaling node within the PI3K/Akt/mTOR pathway. Genomic alterations such as activating mutations in PI3K and amplifications of AKT genes can trigger overactivation of Akt isoforms and concomitant various diseases. Despite intensive research in the last decades, several clinical trials with potential drug candidates have failed. Responsible for this are, among others, the lack of information on isoform-specific functions in the context of human disease and the non-selective targeting of the isoforms and associated side effects. In this work, the main objective was to establish structural biology and cellular systems that form the basis for structure-based drug design of isoform-selective covalent-allosteric Akt inhibitors (CAAIs). For this purpose, a detailed sequence and structural comparison of Akt isoforms was performed. Structural analysis and a founded construct design enabled the development of efficient expression and purification strategies. Furthermore, crystallization studies provided unique insight into the Akt2 binding pocket by mimicking it in Akt1. This insight, combined with biochemical and mass spectrometry data, allowed evaluation of a focused compound library and verification of the homology model-derived CAAI design approach. To enable further cellular studies, a Ba/F3-Akt isoform-dependent model system was established. Using this model system, biochemical selectivity profiles of the focused compound library could be transferred to the cellular context for the first time and served as a basis for further studies in the human cancer cell line PANC1. Furthermore, cellular studies on Akt knock-out models demonstrated the advantages of isoform-selective CAAIs over invasive genetic knock-outs for deciphering the isoform-specific functions of Akt