A fragment-based approach for the in silico prediction of blood-brain barrier permeation

Blood-brain barrier (BBB) permeation is an essential property for drugs that act in the central nervous system (CNS) for the treatment of human diseases, such as epilepsy, depression, Alzheimer's disease, Parkinson disease, schizophrenia, among others. In the present work, quantitative structure-property relationship (QSPR) studies were conducted for the development and validation of in silico models for the prediction of BBB permeation. The data set used has substantial chemical diversity and a relatively wide distribution of property values. The generated QSPR models showed good statistical parameters and were successfully employed for the prediction of a test set containing 48 compounds. The predictive models presented herein are useful in the identification, selection and design of new drug candidates having improved pharmacokinetic properties.

Expression analysis and in silico characterization of intronic long noncoding RNAs in renal cell carcinoma: emerging functional associations

Abstract Background Intronic and intergenic long noncoding RNAs (lncRNAs) are emerging gene expression regulators. The molecular pathogenesis of renal cell carcinoma (RCC) is still poorly understood, and in particular, limited studies are available for intronic lncRNAs expressed in RCC Methods Microarray experiments were performed with custom-designed arrays enriched with probes for lncRNAs mapping to intronic genomic regions. Samples from 18 primary RCC tumors and 11 nontumor adjacent matched tissues were analyzed. Meta-analyses were performed with microarray expression data from three additional human tissues (normal liver, prostate tumor and kidney nontumor samples), and with large-scale public data for epigenetic regulatory marks and for evolutionarily conserved sequences. Results A signature of 29 intronic lncRNAs differentially expressed between RCC and nontumor samples was obtained (false discovery rate (FDR) <5%). A signature of 26 intronic lncRNAs significantly correlated with the RCC five-year patient survival outcome was identified (FDR <5%, p-value ≤0.01). We identified 4303 intronic antisense lncRNAs expressed in RCC, of which 22% were significantly (p <0.05) cis correlated with the expression of the mRNA in the same locus across RCC and three other human tissues. Gene Ontology (GO) analysis of those loci pointed to 'regulation of biological processes’ as the main enriched category. A module map analysis of the protein-coding genes significantly (p <0.05) trans correlated with the 20% most abundant lncRNAs, identified 51 enriched GO terms (p <0.05). We determined that 60% of the expressed lncRNAs are evolutionarily conserved. At the genomic loci containing the intronic RCC-expressed lncRNAs, a strong association (p <0.001) was found between their transcription start sites and genomic marks such as CpG islands, RNA Pol II binding and histones methylation and acetylation. Conclusion Intronic antisense lncRNAs are widely expressed in RCC tumors. Some of them are significantly altered in RCC in comparison with nontumor samples. The majority of these lncRNAs is evolutionarily conserved and possibly modulated by epigenetic modifications. Our data suggest that these RCC lncRNAs may contribute to the complex network of regulatory RNAs playing a role in renal cell malignant transformation.

Pharmacokinetic properties and in silico ADME modeling in drug discovery

The discovery and development of a new drug are time-consuming, difficult and expensive. This complex process has evolved from classical methods into an integration of modern technologies and innovative strategies addressed to the design of new chemical entities to treat a variety of diseases. The development of new drug candidates is often limited by initial compounds lacking reasonable chemical and biological properties for further lead optimization. Huge libraries of compounds are frequently selected for biological screening using a variety of techniques and standard models to assess potency, affinity and selectivity. In this context, it is very important to study the pharmacokinetic profile of the compounds under investigation. Recent advances have been made in the collection of data and the development of models to assess and predict pharmacokinetic properties (ADME - absorption, distribution, metabolism and excretion) of bioactive compounds in the early stages of drug discovery projects. This paper provides a brief perspective on the evolution of in silico ADME tools, addressing challenges, limitations, and opportunities in medicinal chemistry.

Untersuchung der DNA-bindenden Eigenschaften neuer Nukleobasen-gekoppelter Pyrrolcarboxamide, Combilexine und Hetaren[a]carbazol-Derivate: Validierung und Etablierung von in-vitro- und in-silico-Methoden

Da maligne Neoplasien durch Mutationen in Proto-Onko- und/oder Tumorsuppressorgenen ausgelöst werden, stellt die DNA eines der wichtigsten Targets für die Entwicklung neuer Zytostatika dar. Auch bei den im Arbeitskreis Pindur designten und synthetisier-ten Verbindungen der Nukleobasen-gekoppelten Pyrrolcarboxamid-, der Hetaren[a]carbazol- und der Combilexin-Reihe handelt es sich um DNA-Liganden mit potentiell antitumoraktiven Eigenschaf-ten. Die einen dualen Bindemodus aufweisenden Combilexine bestehen aus einem Interkalator (u. a. Naphthalimid, Acridon), der über einen Linker variabler Kettenlänge mit einer rinnenbin-denden, von Netropsin abgeleiteten Bispyrrol-, oder einer bioisosteren Imidazol-, Thiazol- oder Thiophen-pyrrolcarboxamid-struktur verknüpft ist. Das N-terminale Ende der Combilexine wird von einer N,N-Dimethylaminopropyl- oder -ethyl-Seitenkette gebildet. Die DNA-Affinitäten der Liganden wurden mittels Tm-Wert-Messung-en bestimmt. Diese Denaturierungsexperimente wurden sowohl mit poly(dAdT)2- als auch mit Thymus-DNA (~42% GC-Anteil) durchge-führt, um Aussagen zur Stärke und zur Sequenzselektivität der DNA-Bindung machen zu können. Des Weiteren wurden die Bindekon-stanten einiger ausgewählter Vertreter mit Hilfe des Ethidium-bromid-Verdrängungsassays ermittelt; einige Testverbindungen wurden zudem auf potentiell vorhandene, TOPO I-inhibierende Eigenschaften untersucht. Diese biochemischen und biophysika-lischen Tests wurden durch Molecular Modelling-Studien ergänzt, die die Berechnung von molekularen Eigenschaften, die Durch-führung von Konformerenanalysen und die Simulation von DNA-Ligand-Komplexen (Docking) umfassten. Durch Korrelation der in vitro-Befunde mit den in silico-Daten gelang es, vor allem für die Substanzklasse der Combilexine einige richtungweisende Struktur-Wirkungsbeziehungen aufzustellen. So konnte gezeigt werden, dass die Einführung eines Imidazol-Rings in die rinnen-bindende Hetaren-pyrrolcarboxamid-Struktur der Combilexine aufgrund der H-Brücken-Akzeptor-Funktion des sp2-hybridisierten N-Atoms eine Verschiebung der Sequenzselektivität der DNA-Bindung von AT- zu GC-reichen Arealen der DNA bedingt. Zudem erwies sich ein C3-Linker für die Verknüpfung des Naphthalimids mit dem rinnenbindenden Strukturelement als am besten geeignet, während bei den Acridon-Derivaten die Verbindungen mit einem N-terminalen Buttersäure-Linker die höchste DNA-Affinität aufwiesen. Dies ist sehr wahrscheinlich auf die im Vergleich zum Naphthalimid-Molekül geringere y-Achsen-Ausdehnung (bzgl. eines x/y-Koordinatensystems) des Acridons zurückzuführen. Die ermittelten Struktur-Wirkungsbeziehungen können dazu herangezogen werden, das rationale Design neuer DNA-Liganden mit potentiell stärkerer DNA-Bindung zu optimieren.

Die Verbindung von Kleinwinkelstreuung und in silico-Methodik zur Aufklärung von Konformationswechseln großer Proteinkomplexe

In dieser Dissertation wurden die Methoden Homologiemodellierung und Molekulardynamik genutzt, um die Struktur und das Verhalten von Proteinen in Lösung zu beschreiben. Mit Hilfe der Röntgenkleinwinkelstreuung wurden die mit den Computermethoden erzeugten Vorhersagen verifiziert. Für das alpha-Hämolysin, ein Toxin von Staphylococcus aureus, das eine heptamere Pore formen kann, wurde erstmalig die monomere Struktur des Protein in Lösung beschrieben. Homologiemodellierung auf Basis verwandter Proteine, deren monomere Struktur bekannt war, wurde verwendet, um die monomere Struktur des Toxins vorherzusagen. Flexibilität von Strukturelementen in einer Molekulardynamiksimulation konnte mit der Funktionalität des Proteines korreliert werden: Intrinsische Flexibilität versetzt das Protein in die Lage den Konformationswechsel zur Pore nach Assemblierung zu vollziehen. Röntgenkleinwinkelstreuung bewies die Unterschiede der monomeren Struktur zu den Strukturen der verwandten Proteine und belegt den eigenen Vorschlag zur Struktur. Überdies konnten Arbeiten an einer Mutante, die in einer sogenannten Präporenkonformation arretiert und nicht in der Lage ist eine Pore zu formen, zeigen, dass dieser Übergangszustand mit der Rotationsachse senkrecht zur Membran gelagert ist. Eine geometrische Analyse beweist, dass es sterisch möglich ist ausgehend von dieser Konformation die Konformation der Pore zu erreichen. Eine energetische und kinetische Analyse dieses Konformationswechsels steht noch aus. Ein weiterer Teil der Arbeit befasst sich mit den Konformationswechseln von Hämocyaninen. Diese wurden experimentell mittels Röntgenkleinwinkelstreuung verfolgt. Konformationswechsel im Zusammenhang mit der Oxygenierung konnten für die 24meren Hämocyanine von Eurypelma californicum und Pandinus imperator beschrieben werden. Für eine Reihe von Hämocyaninen ist nachgewiesen, dass sie unter Einfluss des Agenz SDS Tyrosinaseaktivität entfalten können. Der Konformationswechsel der Hämocyanine von E. californicum und P. imperator bei der Aktivierung zur Tyrosinase mittels SDS wurde experimentell bestätigt und die Stellung der Dodekamere der Hämocyanine als wesentlich bei der Aktivierung festgestellt. Im Zusammenhang mit anderen Arbeiten gilt damit die Relaxierung der Struktur unter SDS-Einfluss und der sterische Einfluss auf die verbindenden Untereinheiten b & c als wahrscheinliche Ursache für die Aktivierung zur Tyrosinase. Eigene Software zum sogenannten rigid body-Modellierung auf der Basis von Röntgenkleinwinkelstreudaten wurde erstellt, um die Streudaten des hexameren Hämocyanins von Palinurus elephas und Palinurus argus unter Einfluss der Effektoren Urat und Koffein strukturell zu interpretieren. Die Software ist die erste Implementierung eines Monte Carlo-Algorithmus zum rigid body-Modelling. Sie beherrscht zwei Varianten des Algorithmus: In Verbindung mit simulated annealing können wahrscheinliche Konformationen ausgefiltert werden und in einer anschließenden systematischen Analyse kann eine Konformation geometrisch beschrieben werden. Andererseits ist ein weiterer, reiner Monte Carlo-Algorithmus in der Lage die Konformation als Dichteverteilung zu beschreiben.

Cross-reactions vs co-sensitization evaluated by in silico motifs and in vitro IgE microarray testing

Using an in silico allergen clustering method, we have recently shown that allergen extracts are highly cross-reactive. Here we used serological data from a multi-array IgE test based on recombinant or highly purified natural allergens to evaluate whether co-reactions are true cross-reactions or co-sensitizations by allergens with the same motifs.

Besnoitia besnoiti protein disulfide isomerase (BbPDI): molecular characterization, expression and in silico modelling

Besnoitia besnoiti is an apicomplexan parasite responsible for bovine besnoitiosis, a disease with a high prevalence in tropical and subtropical regions and re-emerging in Europe. Despite the great economical losses associated with besnoitiosis, this disease has been underestimated and poorly studied, and neither an effective therapy nor an efficacious vaccine is available. Protein disulfide isomerase (PDI) is an essential enzyme for the acquisition of the correct three-dimensional structure of proteins. Current evidence suggests that in Neosporacaninum and Toxoplasmagondii, which are closely related to B. besnoiti, PDI play an important role in host cell invasion, is a relevant target for the host immune response, and represents a promising drug target and/or vaccine candidate. In this work, we present the nucleotide sequence of the B. besnoiti PDI gene. BbPDI belongs to the thioredoxin-like superfamily (cluster 00388) and is included in the PDI_a family (cluster defined cd02961) and the PDI_a_PDI_a'_c subfamily (cd02995). A 3D theoretical model was built by comparative homology using Swiss-Model server, using as a template the crystallographic deduced model of Tapasin-ERp57 (PDB code 3F8U chain C). Analysis of the phylogenetic tree for PDI within the phylum apicomplexa reinforces the close relationship among B. besnoiti, N. caninum and T. gondii. When subjected to a PDI-assay based on the polymerisation of reduced insulin, recombinant BbPDI expressed in E. coli exhibited enzymatic activity, which was inhibited by bacitracin. Antiserum directed against recombinant BbPDI reacted with PDI in Western blots and by immunofluorescence with B. besnoiti tachyzoites and bradyzoites.

Engineering Tocopherol Selectivity in alpha-TTP: A Combined In Vitro/In Silico Study

"We present a combined in vitro/in silico study to determine the molecular origin of the selectivity of a-tocopherol transfer" "protein (a-TTP) towards a-tocopherol. Molecular dynamics simulations combined to free energy perturbation calculations predict a binding free energy for a-tocopherol to a-TTP 8.26+2.13 kcal mol{1 lower than that of c-tocopherol. Our calculations show that c-tocopherol binds to a-TTP in a significantly distorted geometry as compared to that of the natural ligand. Variations in the hydration of the binding pocket and in the protein structure are found as well. We propose a mutation, A156L, which significantly modifies the selectivity properties of a-TTP towards the two tocopherols. In particular, our simulations predict that A156L binds preferentially to c-tocopherol, with striking structural similarities to the wild-type- a-tocopherol complex. The affinity properties are confirmed by differential scanning fluorimetry as well as in vitro competitive binding assays. Our data indicate that residue A156 is at a critical position for determination of the selectivity of a-TTP. The engineering of TTP mutants with modulating binding properties can have potential impact at industrial level for easier purification of single tocopherols from vitamin E mixtures coming from natural oils or synthetic processes. Moreover," "the identification of a c-tocopherol selective TTP offers the possibility to challenge the hypotheses for the evolutionary development of a mechanism for a-tocopherol selection in omnivorous animals."

Identification and in silico analyses of novel TGFBR1 and TGFBR2 mutations in Marfan syndrome-related disorders

Very recently, heterozygous mutations in the genes encoding transforming growth factor beta receptors I (TGFBR1) and II (TGFBR2) have been reported in Loeys-Dietz aortic aneurysm syndrome (LDS). In addition, dominant TGFBR2 mutations have been identified in Marfan syndrome type 2 (MFS2) and familial thoracic aortic aneurysms and dissections (TAAD). In the past, mutations of these genes were associated with atherosclerosis and several human cancers. Here, we report a total of nine novel and one known heterozygous sequence variants in the TGFBR1 and TGFBR2 genes in nine of 70 unrelated individuals with MFS-like phenotypes who previously tested negative for mutations in the gene encoding the extracellular matrix protein fibrillin-1 (FBN1). To assess the pathogenic impact of these sequence variants, in silico analyses were performed by the PolyPhen, SIFT, and Fold-X algorithms and by means of a 3D homology model of the TGFBR2 kinase domain. Our results showed that in all but one of the patients the pathogenic effect of at least one sequence variant is highly probable (c.722C > T, c.799A > C, and c.1460G > A in TGFBR1 and c.773T > G, c.1106G > T, c.1159G > A, c.1181G > A, and c.1561T > C in TGFBR2). These deleterious alleles occurred de novo or segregated with the disease in the families, indicating a causative association between the sequence variants and clinical phenotypes. Since TGFBR2 mutations found in patients with MFS-related disorders cannot be distinguished from heterozygous TGFBR2 mutations reported in tumor samples, we emphasize the importance of segregation analysis in affected families. In order to be able to find the mutation that is indeed responsible for a MFS-related phenotype, we also propose that genetic testing for sequence alterations in TGFBR1 and TGFBR2 should be complemented by mutation screening of the FBN1 gene.

Pseudodominant Inheritance of Goitrous Congenital Hypothyroidism Caused by TPO Mutations: Molecular and in Silico Studies

Context and Objective: Most cases of goitrous congenital hypothyroidism (CH) from thyroid dyshormonogenesis 1) follow a recessive mode of inheritance and 2) are due to mutations in the thyroid peroxidase gene (TPO). We report the genetic mechanism underlying the apparently dominant inheritance of goitrous CH in a nonconsanguineous family of French Canadian origin. Design, Setting, and Participants: Two brothers identified by newborn TSH screening had severe hypothyroidism and a goiter with increased (99m)Tc uptake. The mother was euthyroid, but the father and two paternal uncles had also been diagnosed with goitrous CH. After having excluded PAX8 gene mutations, we hypothesized that the underlying defect could be TPO mutations. Results: Both compound heterozygous siblings had inherited a mutant TPO allele carried by their mother (c.1496delC; p.Pro499Argfs2X), and from their father, one brother had inherited a missense mutation (c.1978C-->G; p.Gln660Glu) and the other an insertion (c.1955insT; p.Phe653Valfs15X). The thyroid gland of one uncle who is a compound heterozygote for TPO mutations (p.Phe653Valfs15X/p.Gln660Glu) was removed because of concurrent multiple endocrine neoplasia type 2A. Immunohistochemistry revealed normal TPO staining, implying that Gln660Glu TPO is expressed properly. Modeling of this mutant in silico suggests that its three-dimensional structure is conserved, whereas the electrostatic binding energy between the Gln660Glu TPO and its heme group becomes repulsive. Conclusion: We report a pedigree presenting with pseudodominant goitrous CH due to segregation of three different TPO mutations. Although goitrous CH generally follows a recessive mode of inheritance, the high frequency of TPO mutations carriers may lead to pseudodominant inheritance.

Proteins in silico-modeling and sampling

Proteins are linear chain molecules made out of amino acids. Only when they fold to their native states, they become functional. This dissertation aims to model the solvent (environment) effect and to develop & implement enhanced sampling methods that enable a reliable study of the protein folding problem in silico. We have developed an enhanced solvation model based on the solution to the Poisson-Boltzmann equation in order to describe the solvent effect. Following the quantum mechanical Polarizable Continuum Model (PCM), we decomposed net solvation free energy into three physical terms– Polarization, Dispersion and Cavitation. All the terms were implemented, analyzed and parametrized individually to obtain a high level of accuracy. In order to describe the thermodynamics of proteins, their conformational space needs to be sampled thoroughly. Simulations of proteins are hampered by slow relaxation due to their rugged free-energy landscape, with the barriers between minima being higher than the thermal energy at physiological temperatures. In order to overcome this problem a number of approaches have been proposed of which replica exchange method (REM) is the most popular. In this dissertation we describe a new variant of canonical replica exchange method in the context of molecular dynamic simulation. The advantage of this new method is the easily tunable high acceptance rate for the replica exchange. We call our method Microcanonical Replica Exchange Molecular Dynamic (MREMD). We have described the theoretical frame work, comment on its actual implementation, and its application to Trp-cage mini-protein in implicit solvent. We have been able to correctly predict the folding thermodynamics of this protein using our approach.

In silico target fishing for rationalized ligand discovery exemplified on constituents of Ruta graveolens

The identification of targets whose interaction is likely to result in the successful treatment of a disease is of growing interest for natural product scientists. In the current study we performed an exemplary application of a virtual parallel screening approach to identify potential targets for 16 secondary metabolites isolated and identified from the aerial parts of the medicinal plant RUTA GRAVEOLENS L. Low energy conformers of the isolated constituents were simultaneously screened against a set of 2208 pharmacophore models generated in-house for the IN SILICO prediction of putative biological targets, i. e., target fishing. Based on the predicted ligand-target interactions, we focused on three biological targets, namely acetylcholinesterase (AChE), the human rhinovirus (HRV) coat protein and the cannabinoid receptor type-2 (CB (2)). For a critical evaluation of the applied parallel screening approach, virtual hits and non-hits were assayed on the respective targets. For AChE the highest scoring virtual hit, arborinine, showed the best inhibitory IN VITRO activity on AChE (IC (50) 34.7 muM). Determination of the anti-HRV-2 effect revealed 6,7,8-trimethoxycoumarin and arborinine to be the most active antiviral constituents with IC (50) values of 11.98 muM and 3.19 muM, respectively. Of these, arborinine was predicted virtually. Of all the molecules subjected to parallel screening, one virtual CB (2) ligand was obtained, i. e., rutamarin. Interestingly, in experimental studies only this compound showed a selective activity to the CB (2) receptor ( Ki of 7.4 muM) by using a radioligand displacement assay. The applied parallel screening paradigm with constituents of R. GRAVEOLENS on three different proteins has shown promise as an IN SILICO tool for rational target fishing and pharmacological profiling of extracts and single chemical entities in natural product research.

Modeling of human P450 oxidoreductase structure by in silico mutagenesis and MD simulation

P450 oxidoreductase (POR) is the obligate electron donor for microsomal cytochrome P450s and mutations in POR cause several metabolic disorders. We have modeled the structure of human P450 oxidoreductase by in silico amino acid replacements in the rat POR crystal structure. The rat POR has 94% homology with human POR and 38 amino acids were replaced to make its sequence identical to human POR. Several rounds of molecular dynamic simulations refined the model and removed structural clashes from side chain alterations of replaced amino acids. This approach has the advantage of keeping the cofactor contacts and structural features of the core enzyme intact which could not be achieved by homology based approaches. The final model from our approach was of high quality and compared well with experimentally determined structures of other PORs. This model will be used for analyzing the structural implications of mutations and polymorphisms in human POR.

Predictive oncology: a review of multidisciplinary, multiscale in silico modeling linking phenotype, morphology and growth.

Empirical evidence and theoretical studies suggest that the phenotype, i.e., cellular- and molecular-scale dynamics, including proliferation rate and adhesiveness due to microenvironmental factors and gene expression that govern tumor growth and invasiveness, also determine gross tumor-scale morphology. It has been difficult to quantify the relative effect of these links on disease progression and prognosis using conventional clinical and experimental methods and observables. As a result, successful individualized treatment of highly malignant and invasive cancers, such as glioblastoma, via surgical resection and chemotherapy cannot be offered and outcomes are generally poor. What is needed is a deterministic, quantifiable method to enable understanding of the connections between phenotype and tumor morphology. Here, we critically assess advantages and disadvantages of recent computational modeling efforts (e.g., continuum, discrete, and cellular automata models) that have pursued this understanding. Based on this assessment, we review a multiscale, i.e., from the molecular to the gross tumor scale, mathematical and computational "first-principle" approach based on mass conservation and other physical laws, such as employed in reaction-diffusion systems. Model variables describe known characteristics of tumor behavior, and parameters and functional relationships across scales are informed from in vitro, in vivo and ex vivo biology. We review the feasibility of this methodology that, once coupled to tumor imaging and tumor biopsy or cell culture data, should enable prediction of tumor growth and therapy outcome through quantification of the relation between the underlying dynamics and morphological characteristics. In particular, morphologic stability analysis of this mathematical model reveals that tumor cell patterning at the tumor-host interface is regulated by cell proliferation, adhesion and other phenotypic characteristics: histopathology information of tumor boundary can be inputted to the mathematical model and used as a phenotype-diagnostic tool to predict collective and individual tumor cell invasion of surrounding tissue. This approach further provides a means to deterministically test effects of novel and hypothetical therapy strategies on tumor behavior.

Properties of plant food allergens: In silico studies

International Comparative Medicine Symposium. Allergology. Revisión de métodos computacionales para determinar propiedades de alergenos alimentarios de plantas