Abstract
Drug-like compounds are most of the time denied approval and use owing to the unexpected clinical side effects and cross-reactivity observed during clinical trials. These unexpected outcomes ...resulting in significant increase in attrition rate centralizes on the selected drug targets. These targets may be disease candidate proteins or genes, biological pathways, disease-associated microRNAs, disease-related biomarkers, abnormal molecular phenotypes, crucial nodes of biological network or molecular functions. This is generally linked to several factors, including incomplete knowledge on the drug targets and unpredicted pharmacokinetic expressions upon target interaction or off-target effects. A method used to identify targets, especially for polygenic diseases, is essential and constitutes a major bottleneck in drug development with the fundamental stage being the identification and validation of drug targets of interest for further downstream processes. Thus, various computational methods have been developed to complement experimental approaches in drug discovery. Here, we present an overview of various computational methods and tools applied in predicting or validating drug targets and drug-like molecules. We provide an overview on their advantages and compare these methods to identify effective methods which likely lead to optimal results. We also explore major sources of drug failure considering the challenges and opportunities involved. This review might guide researchers on selecting the most efficient approach or technique during the computational drug discovery process.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The current increase in Gene Ontology (GO) annotations of proteins in the existing genome databases and their use in different analyses have fostered the improvement of several biomedical and ...biological applications. To integrate this functional data into different analyses, several protein functional similarity measures based on GO term information content (IC) have been proposed and evaluated, especially in the context of annotation-based measures. In the case of topology-based measures, each approach was set with a specific functional similarity measure depending on its conception and applications for which it was designed. However, it is not clear whether a specific functional similarity measure associated with a given approach is the most appropriate, given a biological data set or an application, i.e., achieving the best performance compared to other functional similarity measures for the biological application under consideration. We show that, in general, a specific functional similarity measure often used with a given term IC or term semantic similarity approach is not always the best for different biological data and applications. We have conducted a performance evaluation of a number of different functional similarity measures using different types of biological data in order to infer the best functional similarity measure for each different term IC and semantic similarity approach. The comparisons of different protein functional similarity measures should help researchers choose the most appropriate measure for the biological application under consideration.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
Gene Ontology (GO) semantic similarity tools enable retrieval of semantic similarity scores, which incorporate biological knowledge embedded in the GO structure for comparing or classifying ...different proteins or list of proteins based on their GO annotations. This facilitates a better understanding of biological phenomena underlying the corresponding experiment and enables the identification of processes pertinent to different biological conditions. Currently, about 14 tools are available, which may play an important role in improving protein analyses at the functional level using different GO semantic similarity measures. Here we survey these tools to provide a comprehensive view of the challenges and advances made in this area to avoid redundant effort in developing features that already exist, or implementing ideas already proven to be obsolete in the context of GO. This helps researchers, tool developers, as well as end users, understand the underlying semantic similarity measures implemented through knowledge of pertinent features of, and issues related to, a particular tool. This should empower users to make appropriate choices for their biological applications and ensure effective knowledge discovery based on GO annotations.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
High-throughput biology technologies have yielded complete genome sequences and functional genomics data for several organisms, including crucial microbial pathogens of humans, animals and plants. ...However, up to 50% of genes within a genome are often labeled "unknown", "uncharacterized" or "hypothetical", limiting our understanding of virulence and pathogenicity of these organisms. Even though biological functions of proteins encoded by these genes are not known, many of them have been predicted to be involved in key processes in these organisms. In particular, for Mycobacterium tuberculosis, some of these "hypothetical" proteins, for example those belonging to the Pro-Glu or Pro-Pro-Glu (PE/PPE) family, have been suspected to play a crucial role in the intracellular lifestyle of this pathogen, and may contribute to its survival in different environments. We have generated a functional interaction network for Mycobacterium tuberculosis proteins and used this to predict functions for many of its hypothetical proteins. Here we performed functional enrichment analysis of these proteins based on their predicted biological functions to identify annotations that are statistically relevant, and analysed and compared network properties of hypothetical proteins to the known proteins. From the statistically significant annotations and network information, we have tried to derive biologically meaningful annotations related to infection and disease. This quantitative analysis provides an overview of the functional contributions of Mycobacterium tuberculosis "hypothetical" proteins to many basic cellular functions, including its adaptability in the host system and its ability to evade the host immune response.
Abstract
Over the past decade, studies of admixed populations have increasingly gained interest in both medical and population genetics. These studies have so far shed light on the patterns of ...genetic variation throughout modern human evolution and have improved our understanding of the demographics and adaptive processes of human populations. To date, there exist about 20 methods or tools to deconvolve local ancestry. These methods have merits and drawbacks in estimating local ancestry in multiway admixed populations. In this article, we survey existing ancestry deconvolution methods, with special emphasis on multiway admixture, and compare these methods based on simulation results reported by different studies, computational approaches used, including mathematical and statistical models, and biological challenges related to each method. This should orient users on the choice of an appropriate method or tool for given population admixture characteristics and update researchers on current advances, challenges and opportunities behind existing ancestry deconvolution methods.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The outcome of infection by Mycobacterium tuberculosis (Mtb) depends greatly on how the host responds to the bacteria and how the bacteria manipulates the host, which is facilitated by ...protein-protein interactions. Thus, to understand this process, there is a need for elucidating protein interactions between human and Mtb, which may enable us to characterize specific molecular mechanisms allowing the bacteria to persist and survive under different environmental conditions. In this work, we used the interologs method based on experimentally verified intra-species and inter-species interactions to predict human-Mtb functional interactions. These interactions were further filtered using known human-Mtb interactions and genes that are differentially expressed during infection, producing 190 interactions. Further analysis of the subcellular location of proteins involved in these human-Mtb interactions confirms feasibility of these interactions. We also conducted functional analysis of human and Mtb proteins involved in these interactions, checking whether these proteins play a role in infection and/or disease, and enriching Mtb proteins in a previously predicted list of drug targets. We found that the biological processes of the human interacting proteins suggested their involvement in apoptosis and production of nitric oxide, whereas those of the Mtb interacting proteins were relevant to the intracellular environment of Mtb in the host. Mapping these proteins onto KEGG pathways highlighted proteins belonging to the tuberculosis pathway and also suggested that Mtb proteins might use the host to acquire nutrients, which is in agreement with the intracellular lifestyle of Mtb. This indicates that these interactions can shed light on the interplay between Mtb and its human host and thus, contribute to the process of designing novel drugs with new biological mechanisms of action.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The emergence and spread of malaria drug resistance have resulted in the need to understand disease mechanisms and importantly identify essential targets and potential drug candidates. Malaria ...infection involves the complex interaction between the host and pathogen, thus, functional interactions between human and Plasmodium falciparum is essential to obtain a holistic view of the genetic architecture of malaria. Several functional interaction studies have extended the understanding of malaria disease and integrating such datasets would provide further insights towards understanding drug resistance and/or genetic resistance/susceptibility, disease pathogenesis, and drug discovery.
This study curated and analysed data including pathogen and host selective genes, host and pathogen protein sequence data, protein-protein interaction datasets, and drug data from literature and databases to perform human-host and P. falciparum network-based analysis. An integrative computational framework is presented that was developed and found to be reasonably accurate based on various evaluations, applications, and experimental evidence of outputs produced, from data-driven analysis.
This approach revealed 8 hub protein targets essential for parasite and human host-directed malaria drug therapy. In a semantic similarity approach, 26 potential repurposable drugs involved in regulating host immune response to inflammatory-driven disorders and/or inhibiting residual malaria infection that can be appropriated for malaria treatment. Further analysis of host-pathogen network shortest paths enabled the prediction of immune-related biological processes and pathways subverted by P. falciparum to increase its within-host survival.
Host-pathogen network analysis reveals potential drug targets and biological processes and pathways subverted by P. falciparum to enhance its within malaria host survival. The results presented have implications for drug discovery and will inform experimental studies.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The Sickle Cell Disease (SCD) Ontology (SCDO, https://scdontology.h3abionet.org/) provides a comprehensive knowledge base of SCD management, systems and standardized human and machine-readable ...resources that unambiguously describe terminology and concepts about SCD for researchers, patients and clinicians. The SCDO was launched in 2016 and is continuously updated in quantity, as well as in quality, to effectively support the curation of SCD research, patient databasing and clinical informatics applications. SCD knowledge from the scientific literature is used to update existing SCDO terms and create new terms where necessary. Here, we report major updates to the SCDO, from December 2019 until April 2021, for promoting interoperability and facilitating SCD data harmonization, sharing and integration across different studies and for retrospective multi-site research collaborations. SCDO developers continue to collaborate with the SCD community, clinicians and researchers to improve specific ontology areas and expand standardized descriptions to conditions influencing SCD phenotypic expressions and clinical manifestations of the sickling process, e.g. thalassemias. Database URL: https://scdontology.h3abionet.org/.
Genomic medicine is set to drastically improve clinical care globally due to high throughput technologies which enable speedy
detection and analysis of clinically relevant mutations. However, the ...variability in the
prediction methods and categorization of functionally relevant genetic variants can pose specific challenges in some populations.
mutation prediction tools could lead to high rates of false positive/negative results, particularly in African genomes that harbor the highest genetic diversity and that are disproportionately underrepresented in public databases and reference panels. These issues are particularly relevant with the recent increase in initiatives, such as the Human Heredity and Health (H3Africa), that are generating huge amounts of genomic sequence data in the absence of policies to guide genomic researchers to return results of variants in so-called actionable genes to research participants. This report (i) provides an inventory of publicly available Whole Exome/Genome data from Africa which could help improve reference panels and explore the frequency of pathogenic variants in actionable genes and related challenges, (ii) reviews available
prediction mutation tools and the criteria for categorization of pathogenicity of novel variants, and (iii) proposes recommendations for analyzing pathogenic variants in African genomes for their use in research and clinical practice. In conclusion, this work proposes criteria to define mutation pathogenicity and actionability in human genetic research and clinical practice in Africa and recommends setting up an African expert panel to oversee the proposed criteria.
•A deterministic model to study the dynamics of human immune response to Mycobacterium tuberculosis is proposed.•The host immune response is regulated by the interleukin-10 cytokine during disease ...progression.•Stability analysis of the model shows a possibility of dynamical stabilization of the disease-free steady state.•The occurrence of latent infection depends on the bacterial load for a reproduction number less than unity.•The time to switch from latent to active state is critically determined by the role of interferon gamma cytokine.
The use of mathematical tools to study biological processes is of necessity in determining the effects of these biological processes occurring at different levels. In this paper, we study the immune system’s response to infection with the bacteria Mycobacterium tuberculosis (the causative agent of tuberculosis). The response by the immune system is either global (lymph node, thymus, and blood) or local (at the site of infection). The response by the immune system against tuberculosis (TB) at the site of infection leads to the formation of spherical structures which comprised of cells, bacteria, and effector molecules known as granuloma. We developed a deterministic model capturing the dynamics of the immune system, macrophages, cytokines and bacteria. The hallmark of Mycobacterium tuberculosis (MTB) infection in the early stages requires a strong protective cell-mediated naive T cells differentiation which is characterised by antigen-specific interferon gamma (IFN-γ). The host immune response is believed to be regulated by the interleukin-10 cytokine by playing the critical role of orchestrating the T helper 1 and T helper 2 dominance during disease progression. The basic reproduction number is computed and a stability analysis of the equilibrium points is also performed. Through the computation of the reproduction number, we predict disease progression scenario including the latency state. The occurrence of latent infection is shown to depend on a number of effector function and the bacterial load for R0 < 1. The model predicts that endemically there is no steady state behaviour; rather it depicts the existence of the MTB to be a continuous process progressing over a differing time period. Simulations of the model predict the time at which the activated macrophages overcome the infected macrophages (switching time) and observed that the activation rate (ω) correlates negatively with it. The efficacy of potential host-directed therapies was determined by the use of the model.
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