scholarly journals Towards the routine use of in silico screenings for drug discovery using metabolic modelling

2020 ◽  
Vol 48 (3) ◽  
pp. 955-969
Author(s):  
Tamara Bintener ◽  
Maria Pires Pacheco ◽  
Thomas Sauter
Keyword(s):  
In Silico ◽  
Drug Targets ◽  
Model Building ◽  
Synthetic Lethality ◽  
Drug Efficacy ◽  
Metabolic Modelling ◽  
New Drug ◽  
Development Costs ◽  
Underlying Mechanisms ◽  
Genome Scale

Currently, the development of new effective drugs for cancer therapy is not only hindered by development costs, drug efficacy, and drug safety but also by the rapid occurrence of drug resistance in cancer. Hence, new tools are needed to study the underlying mechanisms in cancer. Here, we discuss the current use of metabolic modelling approaches to identify cancer-specific metabolism and find possible new drug targets and drugs for repurposing. Furthermore, we list valuable resources that are needed for the reconstruction of cancer-specific models by integrating various available datasets with genome-scale metabolic reconstructions using model-building algorithms. We also discuss how new drug targets can be determined by using gene essentiality analysis, an in silico method to predict essential genes in a given condition such as cancer and how synthetic lethality studies could greatly benefit cancer patients by suggesting drug combinations with reduced side effects.

scholarly journals In silicoidentification of metabolic enzyme drug targets inBurkholderia pseudomallei

2015 ◽  
Author(s):  
Jean F. Challacombe
Keyword(s):  
In Silico ◽  
Drug Targets ◽  
Culture Media ◽  
Metabolic Modeling ◽  
Host Cells ◽  
Natural Resistance ◽  
Metabolic Enzyme ◽  
Chronic Infections ◽  
Genome Scale ◽  
Nutrient Conditions

AbstractThe intracellular pathogenBurkholderia pseudomallei,which is endemic to parts of southeast Asia and northern Australia, causes the disease melioidosis. Although acute infections can be treated with antibiotics, melioidosis is difficult to cure, and some patients develop chronic infections or a recrudescence of the disease months or years after treatment of the initial infection.B. pseudomalleistrains have a high level of natural resistance to a variety of antibiotics, and with limited options for new antibiotics on the horizon, new alternatives are needed. The aim of the present study was to characterize the metabolic capabilities ofB. pseudomallei, identify metabolites crucial for pathogen survival, understand the metabolic interactions that occur between pathogen and host cells, and determine if metabolic enzymes produced by the pathogen might be potential antibacterial targets. This aim was accomplished through genome scale metabolic modeling under different external conditions: 1) including all nutrients that could be consumed by the model, and 2) providing only the nutrients available in culture media. Using this approach, candidate chokepoint enzymes were identified, then knocked outin silicounder the different nutrient conditions. The effect of each knockout on the metabolic network was examined. When five of the candidate chokepoints were knocked outin silico, the flux through theB. pseudomalleinetwork was decreased, depending on the nutrient conditions. These results demonstrate the utility of genome-scale metabolic modeling methods for drug target identification inB. pseudomallei.

In silico genome-scale modeling and analysis for identifying anti-tubercular drug targets

2010 ◽  
Vol 72 (2) ◽  
pp. 121-129 ◽  
Author(s):  
Dong-Yup Lee ◽  
Bevan Kai Sheng Chung ◽  
Faraaz N.K. Yusufi ◽  
Suresh Selvarasu
Keyword(s):  
In Silico ◽  
Drug Targets ◽  
Modeling And Analysis ◽  
Scale Modeling ◽  
Genome Scale

scholarly journals Genome-Scale Metabolic Model of the Human Pathogen Candida albicans: A Promising Platform for Drug Target Prediction

2020 ◽  
Vol 6 (3) ◽  
pp. 171
Author(s):  
Romeu Viana ◽  
Oscar Dias ◽  
Davide Lagoa ◽  
Mónica Galocha ◽  
Isabel Rocha ◽  
...  
Keyword(s):  
Candida Albicans ◽  
Drug Targets ◽  
Fungal Pathogens ◽  
Software Tool ◽  
Metabolic Model ◽  
New Drugs ◽  
Metabolic Reconstruction ◽  
Metabolic Potential ◽  
New Drug ◽  
Genome Scale

Candida albicans is one of the most impactful fungal pathogens and the most common cause of invasive candidiasis, which is associated with very high mortality rates. With the rise in the frequency of multidrug-resistant clinical isolates, the identification of new drug targets and new drugs is crucial in overcoming the increase in therapeutic failure. In this study, the first validated genome-scale metabolic model for Candida albicans, iRV781, is presented. The model consists of 1221 reactions, 926 metabolites, 781 genes, and four compartments. This model was reconstructed using the open-source software tool merlin 4.0.2. It is provided in the well-established systems biology markup language (SBML) format, thus, being usable in most metabolic engineering platforms, such as OptFlux or COBRA. The model was validated, proving accurate when predicting the capability of utilizing different carbon and nitrogen sources when compared to experimental data. Finally, this genome-scale metabolic reconstruction was tested as a platform for the identification of drug targets, through the comparison between known drug targets and the prediction of gene essentiality in conditions mimicking the human host. Altogether, this model provides a promising platform for global elucidation of the metabolic potential of C. albicans, possibly guiding the identification of new drug targets to tackle human candidiasis.

Discovery of Alzheimer's Molecular Pathway Reveals New Drug Targets

ASHA Leader ◽  
2013 ◽  
Vol 18 (3) ◽  
pp. 33-33
Keyword(s):  
Drug Targets ◽  
Molecular Pathway ◽  
New Drug

Discovery of Alzheimer's Molecular Pathway Reveals New Drug Targets

Identification of New Drug Targets in Multi-Drug Resistant Bacterial Infections

2013 ◽  
Author(s):  
Andrew M. Gulick ◽  
Thomas A. Russo ◽  
L. W. Schultz ◽  
Timothy C. Umland
Keyword(s):  
Drug Targets ◽  
Bacterial Infections ◽  
Drug Resistant ◽  
New Drug

Phytochemicals for drug discovery in Alzheimer’s disease: In silico Advances

2020 ◽  
Vol 26 ◽  
Author(s):  
Smriti Sharma ◽  
Vinayak Bhatia
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Drug Design ◽  
In Silico ◽  
Drug Targets ◽  
Development Process ◽  
Phytochemical Analysis ◽  
Computational Drug Design ◽  
Novel Drugs ◽  
Game Changer

: The search for novel drugs that can prevent or control Alzheimer’s disease has attracted lot of attention from researchers across the globe. Phytochemicals are increasingly being used to provide scaffolds to design drugs for AD. In silico techniques, have proven to be a game-changer in this drug design and development process. In this review, the authors have focussed on current advances in the field of in silico medicine, applied to phytochemicals, to discover novel drugs to prevent or cure AD. After giving a brief context of the etiology and available drug targets for AD, authors have discussed the latest advances and techniques in computational drug design of AD from phytochemicals. Some of the prototypical studies in this area are discussed in detail. In silico phytochemical analysis is a tool of choice for researchers all across the globe and helps integrate chemical biology with drug design.

Exploring PLAC1 Structure and Underlying Mechanisms to Design a Derivative Vaccine Against Breast Cancer Progression; In-Silico Study

2020 ◽  
Vol 17 (5) ◽  
pp. 379-391
Author(s):  
Farzaneh Afzali ◽  
Parisa Ghahremanifard ◽  
Mohammad Mehdi Ranjbar ◽  
Mahdieh Salimi
Keyword(s):  
Breast Cancer ◽  
Cancer Progression ◽  
In Silico ◽  
Tertiary Structure ◽  
Specific Antigen ◽  
Docking Simulation ◽  
Post Translational Modification ◽  
Intrinsically Disordered ◽  
Intrinsically Disordered Regions ◽  
Underlying Mechanisms

Background: The tolerogenic homeostasis in Breast Cancer (BC) can be surpassed by rationally designed immune-encouraging constructs against tumor-specific antigens through immunoinformatics approach. Objective: Availability of high throughput data providing the underlying concept of diseases and awarded computational simulations, lead to screening the potential medications and strategies in less time and cost. Despite the extensive effects of Placenta Specific 1 (PLAC1) in BC progression, immune tolerance, invasion, cell cycle regulation, and being a tumor-specific antigen the fundamental mechanisms and regulatory factors were not fully explored. It is also worth to design an immune response inducing construct to surpass the hurdles of traditional anti-cancer treatments. Methods and Result: The study was initiated by predicting and modelling the PLAC1 secondary and tertiary structures and then engineering the fusion pattern of PLAC1 derived immunodominant predicted CD8+ and B-cell epitopes to form a multi-epitope immunogenic construct. The construct was analyzed considering the physiochemical characterization, safety, antigenicity, post-translational modification, solubility, and intrinsically disordered regions. After modelling its tertiary structure, proteinprotein docking simulation was carried out to ensure the attachment of construct with Toll-Like Receptor 4 (TLR4) as an immune receptor. To guarantee the highest expression of the designed construct in E. coli k12 as an expressional host, the codon optimization and in-silico cloning were performed. The PLAC1 related miRNAs in BC were excavated and validated through TCGA BC miRNA-sequencing and databases; the common pathways then were introduced as other probable mechanisms of PLAC1 activity. Conclusion: Regarding the obtained in-silico results, the designed anti-PLAC1 multi-epitope construct can probably trigger humoral and cellular immune responses and inflammatory cascades, therefore may have the potential of halting BC progression and invasion engaging predicted pathways.

In silico discovery of novel flavonoids as poly ADP ribose polymerase (PARP) inhibitors

2020 ◽  
Vol 16 ◽  
Author(s):  
Ashish Shah ◽  
Ghanshyam Parmar ◽  
Avinash Kumar Seth
Keyword(s):  
Virtual Screening ◽  
In Silico ◽  
Synthetic Lethality ◽  
Parp Inhibitor ◽  
Parp Inhibitors ◽  
Docking Studies ◽  
Docking Score ◽  
Docking Method ◽  
Anti Cancer ◽  
In Silico Toxicity

Background: The concept of synthetic lethality is emerging field in the treatment of cancer and can be applied for new drug development of cancer as it has been already represented by Poly (ADP-ribose) polymerase (PARPs) inhibitors. Objectives: In this study we performed virtual screening of 329 flavonoids obtained from Naturally Occurring Plant-based Anti-cancer Compound-Activity-Target (NPACT) database to identify novel PARP inhibitors. Materials and methods: Virtual screening carried out using different In Silico methods which includes molecular docking studies, prediction of druglikeness and In Silico toxicity studies. Results: Fifteen out of 329 flavonoids achieved better docking score as compared to rucaparib which is an FDA approved PARP inhibitor. These 15 hits were again rescored using accurate docking mode and drug-likeliness properties were evaluated. Accuracy of docking method was checked using re-docking. Finally NPACT00183 and NPACT00280 were identified as potential PARP inhibitors with docking score of -139.237 and -129.36 respectively. These two flavonoids were also showed no AMES toxicity and no carcinogenicity which was predicted using admetSAR. Conclusion: Our finding suggests that NPACT00183 and NPACT00280 have promising potential to be further explored as PARP inhibitors.

scholarly journals Intrinsically Disordered Proteins as Regulators of Transient Biological Processes and as Untapped Drug Targets

Molecules ◽  
2021 ◽  
Vol 26 (8) ◽  
pp. 2118
Author(s):  
Yusuke Hosoya ◽  
Junko Ohkanda
Keyword(s):  
Drug Targets ◽  
Intrinsically Disordered Proteins ◽  
Dynamic Control ◽  
Disordered Proteins ◽  
Biological Processes ◽  
Phase Separations ◽  
Cellular Processes ◽  
Intrinsically Disordered ◽  
New Drug ◽  
Liquid Phase Separations

Intrinsically disordered proteins (IDPs) are critical players in the dynamic control of diverse cellular processes, and provide potential new drug targets because their dysregulation is closely related to many diseases. This review focuses on several medicinal studies that have identified low-molecular-weight inhibitors of IDPs. In addition, clinically relevant liquid–liquid phase separations—which critically involve both intermolecular interactions between IDPs and their posttranslational modification—are analyzed to understand the potential of IDPs as new drug targets.

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