39 research outputs found
A prospective compound screening contest identified broader inhibitors for Sirtuin 1
Potential inhibitors of a target biomolecule, NAD-dependent deacetylase Sirtuin 1, were identified by a contest-based approach, in which participants were asked to propose a prioritized list of 400 compounds from a designated compound library containing 2.5 million compounds using in silico methods and scoring. Our aim was to identify target enzyme inhibitors and to benchmark computer-aided drug discovery methods under the same experimental conditions. Collecting compound lists derived from various methods is advantageous for aggregating compounds with structurally diversified properties compared with the use of a single method. The inhibitory action on Sirtuin 1 of approximately half of the proposed compounds was experimentally accessed. Ultimately, seven structurally diverse compounds were identified
From Hydra to Humans: Insights into molecular mechanisms of aging and longevity
Human aging is characterized by progressive functional decline that coincides with both increased morbidity and mortality. Aging affects every human being and only few individuals achieve longevity, a very special phenotype marked by extraordinary healthy aging. This thesis consists of three chapters; each one is devoted to a separate project that contributes to the growing body of knowledge about aging and longevity. The work required the compilation, management and analysis of diverse big data sets and the application of cutting-edge statistical and computational methods.
Chapter 1 - A functional genomics study was conducted in the potentially immortal freshwater polyp Hydra using body part-specific microarray and RNA sequencing data. The results revealed gene expression patterns that allow boundary maintenance during Hydra’s continuous cell proliferation and tissue self-renewal. Furthermore, this study provided evidence for de-acetylation as a key mechanism underlying compartmentalization. Surprisingly, FoxO, which is known to substantially drive developmental processes and stem cell renewal in Hydra, did not seem to be affected by the acetylation status.
Chapter 2 - Long-lived individuals (LLI, >95 years of age) epitomize the healthy aging phenotype and are thought to carry beneficial genetic variants that predispose to human longevity. Despite extensive research efforts, only few of these genetic factors in LLI have been identified so far. In contrast to previous investigations which mainly focused on intronic variants, a genome-wide exome-based case-control study was performed. DNA samples of more than 1,200 German LLI, including 599 centenarians (≥100 years), and about 6,900 younger controls were used for single-variant and gene-based association analyses that yielded two new candidate longevity genes, fructosamine 3 kinase related protein (FN3KRP) and phosphoglycolate phosphatase (PGP). FN3KRP functions in the deglycation of proteins to restore their function, while PGP via controlling glycerol-3-phosphate levels affects both glucose and fat metabolism. Given the biological functions of the genes, their longevity-associations appear very plausible.
Chapter 3 - In recent years, the intestinal microbiome (GM) has increasingly gained attention in aging and longevity research. A 16S rRNA microbiome study was conducted using 1301 stool samples of healthy individuals (age range: 19 - 104 years) that were drawn from three cohorts. The aim was to investigate potential associations among GM composition, host genetics and environmental factors during aging. The GM composition changed with age, showing an increase of opportunistic pathogens that may generate an inflammatory environment in the gut. Age explained only ~1% of the inter-individual variation, whereas anthropometric measures, genetic background and dietary patterns together explained 20%. Strikingly, clear GM population stratification in terms of four enterotype-like clusters was observed, which were predominantly associated with dietary patterns. The correction for these clusters was shown to increase the comparability of findings from the different cohorts. In addition, the LLI showed a specific gut microbial pattern, which is in line with previously published reports.
The present work shows that a thorough bioinformatics expertise helps to address the complexity of the two phenotypes aging and longevity. One highlight of the thesis is the discovery of two new candidate longevity loci that, in view of the limited output of previous study approaches, enlarge the existing database
Leishmaniasis
Leishmaniasis is a major global health challenge, affecting approximately 12 million of the poorest people in 100 countries. It is a deforming and fatal disease in the visceral form. Therapies for leishmaniasis are numerically restricted, basically consisting of the administration of miltefosine, pentavalent antimonials, amphotericin B, or pentamidine. This is an important vulnerability against therapy efficiency that must be overcome by the scientific community. This book discusses important aspects of the disease, such as treatment, epidemiology, and molecular and cell biology. The information contained herein is important for young researchers as they seek to develop safe and effective treatments for this neglected tropical disease
FUNCTION-DRIVEN APPROACHES TO THE DESIGN OF OPTOGENETIC TOOLS
Proteins play a wide variety of roles in biology despite being produced from a small set of common subunits; this commonality can be exploited to understand the dynamics by which proteins fold into structures and perform their manifold functions and, subsequently, design new proteins for use both in research and as nanoscale machines in industry. While this design process has classically involved residue-level redesign of existing protein backbones and, more recently, the de novo design of backbones according to geometrical parameters, the increasing complexity of optogenetic photosystems, biosensors, and other mechanisms for making use of proteins with specific functions has established a need for a design protocol that can reconcile their various structural exigencies with the function-specific elements of as wide an array of proteins as possible in order to make best use of them. Requirement-driven design eschews specific structural templates in favor of general requirements dependent on the intended function of the design, and so can exploit the vastness of protein structural space in finding solutions to increasingly complex design problems. Here, we present three new advances in the requirement-driven design of proteins as diagnostic tools, including a more general photosystem for the direct optogenetic control of protein-protein interactions, a series of algorithmic improvements to the leading implementation of requirement-driven design in the Rosetta macromolecular design software suite, and a new version of that algorithm capable of performing requirement-driven backbone design and residue-level backbone optimization simultaneously. These technologies collectively represent a significant improvement in our ability to control the activity of proteins with a wide variety of control schemes and produce functional proteins for arbitrary requirement sets more generally.Doctor of Philosoph
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TOWARDS UNDERSTANDING MODE-OF-ACTION OF TRADITIONAL MEDICINES BY USING IN SILICO TARGET PREDICTION
Traditional medicines (TM) have been used for centuries to treat illnesses, but in many cases
their modes-of-action (MOAs) remain unclear. Given the increasing data of chemical
ingredients of traditional medicines and the availability of large-scale bioactivity data linking
chemical structures to activities against protein targets, we are now in a position to propose
computational hypotheses for the MOAs using in silico target prediction. The MOAs were
established from supporting literature. The in silico target prediction, which is based on the
“Molecular Similarity Principle”, was modelled via two models: a Naïve Bayes Classifier and
a Random Forest Classifier. Chapter 2 discovered the relationship of 46 traditional Chinese
medicine (TCM) therapeutic action subclasses by mapping them into a dendrogram using the
predicted targets. Overall, the most frequent top three enriched targets/pathways were
immune-related targets such as tyrosine-protein phosphatase non-receptor type 2 (PTPN2)
and digestive system such as mineral absorption. Two major protein families, G-protein
coupled receptor (GPCR), and protein kinase family contributed to the diversity of the
bioactivity space, while digestive system was consistently annotated pathway motif. Chapter 3
compared the chemical and bioactivity space of 97 anti-cancer plants’ compounds of TCM,
Ayurveda and Malay traditional medicine. The comparison of the chemical space revealed
that benzene, anthraquinone, flavone, sterol, pentacyclic triterpene and cyclohexene were the
most frequent scaffolds in those TM. The annotation of the bioactivity space with target
classes showed that kinase class was the most significant target class for all groups. From a
phylogenetic tree of the anti-cancer plants, only eight pairs of plants were phylogenetically
related at either genus, family or order level. Chapter 4 evaluated synergy score of pairwise
compound combination of Shexiang Baoxin Pill (SBP), a TCM formulation for myocardial
infarction. The score was measured from the topological properties, pathway dissimilarity and
mean distance of all the predicted targets of a combination on a representative network of the
disease. The method found four synergistic combinations, ginsenoside Rb3 and cholic acid,
ginsenoside Rb2 and ginsenoside Rb3, ginsenoside Rb3 and 11-hydroxyprogesterone and
ginsenoside Rb2 and ginsenoside Rd agreed with the experimental results. The modulation of
androgen receptor, epidermal growth factor and caspases were proposed for the synergistic
actions. Altogether, in silico target prediction was able to discover the bioactivity space of
different TMs and elucidate the MOA of multiple formulations and two major health
concerns: cancer and myocardial infarction. Hence, understanding the MOA of the traditional
medicine could be beneficial in providing testable hypotheses to guide towards finding new
molecular entities
Ca2+-sensitive Mef2c protein interactions and chromatin function in microglia-like cells
Alzheimer’s disease (AD) is a progressive neurodegenerative disorder for which there are no disease-modifying therapies. Genetic studies have identified over 50 susceptibility loci
for sporadic AD including the locus encoding the transcription factor MEF2C. Most of the genes implicated in AD-risk are exclusively or preferentially expressed in microglia. Furthermore, AD-risk variants are enriched in microglial open chromatin regions that contain DNA binding motifs for MEF2C. Therefore, genetic variants that disrupt MEF2C binding to DNA in microglia may alter cis-gene expression, contributing to AD-risk. Understanding how MEF2C functions in microglia may provide valuable insights into the genetic basis of AD-risk.
To investigate the role of Mef2c in AD, mass spectrometry was used to identify proteins that co-purify with the endogenous protein in BV2 microglia-like cells. Two major Mef2c isoforms exist in BV2 cells that associate with 110 putative interactors including the transcriptional repressors, Hdac4, Hdac5, and Cabin1. Ionomycin treatment, that raises intracellular [Ca2+], caused the partial dissociation of these repressors from Mef2c and resulted in recruitment of the microglial amyloid-β response proteins, Yes1 and Smpdl3b to the Mef2c complex. However, no Mef2c-activating proteins were identified in the remodelled complex. Having demonstrated that ionomycin treatment remodels the Mef2c interactome, the effect of this treatment on chromatin accessibility in BV2 cells was investigated using ATAC-seq. This revealed that while the motifs for three transcription factors, Atf4, NFATC3 and p53, were enriched at Ca2+ -dependent differentially accessible
sites, Mef2c sites were not similarly enriched. However, Mef2c motif-containing differentially accessible regions were associated with genes that control the microglial
inflammatory response. This thesis investigated two mechanisms by which [Ca2+] levels potentially influence gene regulation; altered protein interactions and chromatin
accessibility and further contributes to our understanding of the transcription factor Mef2c, Ca2+ signalling, and chromatin function in BV2 cells. In conclusion, Ca2+ dysregulation in AD may result in remodelling of the Mef2c interactome leading to abnormal Mef2c-mediated inflammatory responses in microglia
INTEGRATED MOLECULAR PROFILING FOR ANALYZING AND PREDICTING THERAPEUTIC MECHANISM, RESPONSE, BIOMARKER AND TARGET
Ph.DDOCTOR OF PHILOSOPH
Comparative Modeling and Benchmarking Data Sets for Human Histone Deacetylases and Sirtuin Families
Histone
deacetylases (HDACs) are an important class of drug targets
for the treatment of cancers, neurodegenerative diseases, and other
types of diseases. Virtual screening (VS) has become fairly effective
approaches for drug discovery of novel and highly selective histone
deacetylase inhibitors (HDACIs). To facilitate the process, we constructed
maximal unbiased benchmarking data sets for HDACs (MUBD-HDACs) using
our recently published methods that were originally developed for
building unbiased benchmarking sets for ligand-based virtual screening
(LBVS). The MUBD-HDACs cover all four classes including Class III
(Sirtuins family) and 14 HDAC isoforms, composed of 631 inhibitors
and 24 609 unbiased decoys. Its ligand sets have been validated
extensively as chemically diverse, while the decoy sets were shown
to be property-matching with ligands and maximal unbiased in terms
of “artificial enrichment” and “analogue bias”.
We also conducted comparative studies with DUD-E and DEKOIS 2.0 sets
against HDAC2 and HDAC8 targets and demonstrate that our MUBD-HDACs
are unique in that they can be applied unbiasedly to both LBVS and
SBVS approaches. In addition, we defined a novel metric, i.e. NLBScore,
to detect the “2D bias” and “LBVS favorable”
effect within the benchmarking sets. In summary, MUBD-HDACs are the
only comprehensive and maximal-unbiased benchmark data sets for HDACs
(including Sirtuins) that are available so far. MUBD-HDACs are freely
available at http://www.xswlab.org/