scholarly journals Computational Drug Repositioning for Chagas Disease Using Protein-Ligand Interaction Profiling

2020 ◽  
Vol 21 (12) ◽  
pp. 4270 ◽  
Author(s):  
Alfredo Juárez-Saldivar ◽  
Michael Schroeder ◽  
Sebastian Salentin ◽  
V. Joachim Haupt ◽  
Emma Saavedra ◽  
...  
Keyword(s):  
Chagas Disease ◽  
Dihydrofolate Reductase ◽  
Drug Repositioning ◽  
Treatment Options ◽  
Ligand Interaction ◽  
Starting Point ◽  
Protein Ligand Interaction ◽  
New Treatment ◽  
Approved Drugs ◽  
Human Dihydrofolate Reductase

Chagas disease, caused by Trypanosoma cruzi (T. cruzi), affects nearly eight million people worldwide. There are currently only limited treatment options, which cause several side effects and have drug resistance. Thus, there is a great need for a novel, improved Chagas treatment. Bifunctional enzyme dihydrofolate reductase-thymidylate synthase (DHFR-TS) has emerged as a promising pharmacological target. Moreover, some human dihydrofolate reductase (HsDHFR) inhibitors such as trimetrexate also inhibit T. cruzi DHFR-TS (TcDHFR-TS). These compounds serve as a starting point and a reference in a screening campaign to search for new TcDHFR-TS inhibitors. In this paper, a novel virtual screening approach was developed that combines classical docking with protein-ligand interaction profiling to identify drug repositioning opportunities against T. cruzi infection. In this approach, some food and drug administration (FDA)-approved drugs that were predicted to bind with high affinity to TcDHFR-TS and whose predicted molecular interactions are conserved among known inhibitors were selected. Overall, ten putative TcDHFR-TS inhibitors were identified. These exhibited a similar interaction profile and a higher computed binding affinity, compared to trimetrexate. Nilotinib, glipizide, glyburide and gliquidone were tested on T. cruzi epimastigotes and showed growth inhibitory activity in the micromolar range. Therefore, these compounds could lead to the development of new treatment options for Chagas disease.

scholarly journals Automatic discovery of transferable patterns in protein-ligand interaction networks

2018 ◽  
Author(s):  
Aida Mrzic ◽  
Dries Van Rompaey ◽  
Stefan Naulaerts ◽  
Hans De Winter ◽  
Wim Vanden Berghe ◽  
...  
Keyword(s):  
Drug Target ◽  
Bacterial Resistance ◽  
Resistance Mechanisms ◽  
Frequent Itemset ◽  
Interaction Patterns ◽  
Ligand Interaction ◽  
Attrition Rates ◽  
Stage Of Development ◽  
Protein Ligand Interaction ◽  
Approved Drugs

In recent years, the pharmaceutical industry has been confronted with rising R&D costs paired with decreasing productivity. Attrition rates for new molecules are tremendous, with a substantial number of molecules failing in an advanced stage of development. Repositioning previously approved drugs for new indications can mitigate these issues by reducing both risk and cost of development. Computational methods have been developed to allow for the prediction of drug-target interactions, but it remains difficult to branch out into new areas of application where information is scarce. Here, we present a proof-of-concept for discovering patterns in protein-ligand data using frequent itemset mining. Two key advantages of our method are the transferability of our patterns to different application domains and the facile interpretation of our recommendations. Starting from a set of known protein-ligand relationships, we identify patterns of molecular substructures and protein domains that lie at the basis of these interactions. We show that these same patterns also underpin metabolic pathways in humans. We further demonstrate how association rules mined from human protein-ligand interaction patterns can be used to predict antibiotics susceptible to bacterial resistance mechanisms.

Identification of FDA Approved Drugs Targeting COVID-19 Virus by Structure-Based Drug Repositioning (Version 2)

2020 ◽  
Author(s):  
Ayman Farag ◽  
Ping Wang ◽  
Mahmoud Ahmed ◽  
Hesham Sadek
Keyword(s):  
Drug Repositioning ◽  
Substrate Binding ◽  
Binding Pocket ◽  
Binding Energies ◽  
Binding Modes ◽  
Substrate Binding Pocket ◽  
Protease Enzyme ◽  
Starting Point ◽  
Approved Drugs ◽  
Fda Approved Drugs

The new strain of Coronaviruses (SARS-CoV-2), and the resulting Covid-19 disease has spread swiftly across the globe after its initial detection in late December 2019 in Wuhan, China, resulting in a pandemic status declaration by WHO within 3 months. Given the heavy toll of this pandemic, researchers are actively testing various strategies including new and repurposed drugs as well as vaccines. In the current brief report, we adopted a repositioning approach using insilico molecular modeling screening using FDA approved drugs with established safety profiles for potential inhibitory effects on Covid-19 virus. We started with structure based drug design by screening more than 2000 FDA approved drugs against Covid-19 virus main protease enzyme (Mpro) substrate-binding pocket focusing on two potential sites (central and terminal sites) to identify potential hits based on their binding energies, binding modes, interacting amino acids, and therapeutic indications. In addition, we elucidate preliminary pharmacophore features for candidates bound to Covid-19 virus Mpro substrate-binding pocket. The top hits bound to the central site of Mpro substrate-binding pocket include antiviral drugs such as Darunavir, Nelfinavir and Saquinavir, some of which are already being tested in Covid-19 patients. Interestingly, one of the most promising hits in our screen is the hypercholesterolemia drug Rosuvastatin. In addition, the top hits bound to the terminal site of Mpro substrate-binding pocket include the anti-asthma drug Montelukast and the anti-histaminic Fexofenadine among others. These results certainly do not confirm or indicate antiviral activity, but can rather be used as a starting point for further in vitro and in vivo testing, either individually or in combination.<br>

scholarly journals Identification of FDA Approved Drugs Targeting COVID-19 Virus by Structure-Based Drug Repositioning

2020 ◽  
Author(s):  
Ayman Farag ◽  
Ping Wang ◽  
Mahmoud Ahmed ◽  
Hesham Sadek
Keyword(s):  
Drug Repositioning ◽  
Binding Energies ◽  
Binding Modes ◽  
Structure Based Drug Design ◽  
Protease Enzyme ◽  
Starting Point ◽  
Approved Drugs ◽  
Fda Approved Drugs

<div>The new strain of Coronaviruses (SARS-CoV-2), and the resulting Covid-19 disease has spread swiftly across the globe after its initial detection in late December 2019 in Wuhan, China, resulting in a pandemic status declaration by WHO within 3 months. Given the heavy toll of this pandemic, researchers are actively testing various strategies including new and repurposed drugs as well as vaccines. In the current brief report, we adopted a repositioning approach using insilico molecular modeling screening using FDA approved drugs with established safety profiles for potential inhibitory effects on Covid-19 virus. We started with structure based drug design by screening more than 2000 FDA approved drugs</div><div>against Covid-19 virus main protease enzyme (Mpro) substrate-binding pocket to identify potential hits based on their binding energies, binding modes, interacting amino acids, and therapeutic indications. In addition, we elucidate preliminary pharmacophore features for candidates bound to Covid-19 virus Mpro substratebinding pocket. The top hits include anti-viral drugs such as Darunavir, Nelfinavirand Saquinavir, some of which are already being tested in Covid-19 patients. Interestingly, one of the most promising hits in our screen is the hypercholesterolemia drug Rosuvastatin. These results certainly do not confirm or indicate antiviral activity, but can rather be used as a starting point for further in vitro and in vivo testing, either individually or in combination.</div>

Signal Transduction Pathways as Therapeutic Target for Chagas Disease

2019 ◽  
Vol 26 (36) ◽  
pp. 6572-6589 ◽  
Author(s):  
Alejandra Cecilia Schoijet ◽  
Tamara Sternlieb ◽  
Guillermo Daniel Alonso
Keyword(s):  
Chagas Disease ◽  
New Technologies ◽  
Neglected Tropical Diseases ◽  
Drug Repositioning ◽  
Basic Research ◽  
Effector Proteins ◽  
Adenylyl Cyclases ◽  
Clinical Phase ◽  
Leishmania Spp ◽  
Approved Drugs

Trypanosomatids are a group of flagellated unicellular eukaryotes, causing serious human diseases including Chagas disease (Trypanosoma cruzi), sleeping sickness (Trypanosoma brucei spp.) and Leishmaniasis (Leishmania spp.). The second messenger cAMP is involved in numerous and fundamental processes in these parasites including differentiation between stages, proliferation, osmoregulation, oxidative stress and quorum sensing. Interestingly, its signaling pathway is quite different from that of mammals, including structurally different adenylyl cyclases, the shortage of orthologous effector proteins and the absence of G-protein-coupled-receptors, among others. These characteristics make the proteins involved in these transduction pathways good candidates for therapeutic targets. However, the identification of new unknown druggable targets involves extensive research time and is economically very expensive, making difficult the transition from basic research to the clinical phase. Trypanosomatid PDEs have characteristic binding pockets that allow for a differential inhibition from their human orthologs. Modification in the approved drugs for human to convert them into trypanocidal treatments could lead to more effective therapies, shorter lab time and lower costs. In view of the fact that kinetoplastid PDEs are highly conserved with their mammalian counterparts, and since there are already numerous drugs on the market against human PDEs, the drug repositioning approach is highly promising. The development of new technologies, higher government and industrial involvement and more scientists committed to basic investigation, are the key to ultimately find an effective treatment and cure for the neglected tropical diseases.

scholarly journals Drug Repositioning for COVID-19

2020 ◽  
Author(s):  
Vicente Benavides-Cordoba
Keyword(s):  
Monoclonal Antibodies ◽  
Drug Development ◽  
Drug Repositioning ◽  
Quality Criteria ◽  
Regulatory Agencies ◽  
Double Blind ◽  
Starting Point ◽  
Potential Activity ◽  
Approved Drugs ◽  
Selection Of

Drug repositioning is a strategy that identifies new uses of approved drugs, to treat conditions different from their original purpose. With the advance of COVID-19 and the declaration of a pandemic; It has become the closest alternative to slow the advance of the virus. Antimalarial, antiviral drugs, antibiotics, glucocorticoids, monoclonal antibodies, among others, are being studied; his findings, although preliminary, could establish a starting point in the search for a solution. In this article, we present a selection of drugs, of different classes and with potential activity to combat COVID-19, whose trials are ongoing; and as proofs of concept, double blind, event-driven add-on, would allow proposing research that generates results in less time and preserving the quality criteria for drug development and approval by regulatory agencies.

scholarly journals Antiprotozoal Activity Profiling of Approved Drugs: A Starting Point toward Drug Repositioning

PLoS ONE ◽  
2015 ◽  
Vol 10 (8) ◽  
pp. e0135556 ◽  
Author(s):  
Marcel Kaiser ◽  
Pascal Mäser ◽  
Leela Pavan Tadoori ◽  
Jean-Robert Ioset ◽  
Reto Brun
Keyword(s):  
Drug Repositioning ◽  
Antiprotozoal Activity ◽  
Activity Profiling ◽  
Starting Point ◽  
Approved Drugs

scholarly journals Prediction of Drug Indications Based on Chemical Interactions and Chemical Similarities

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Guohua Huang ◽  
Yin Lu ◽  
Changhong Lu ◽  
Mingyue Zheng ◽  
Yu-Dong Cai
Keyword(s):  
Drug Development ◽  
Large Scale ◽  
Cross Validation ◽  
Drug Repositioning ◽  
Accuracy Rate ◽  
Computational Approaches ◽  
Starting Point ◽  
Independent Test ◽  
Approved Drugs ◽  
Fold Cross Validation

Discovering potential indications of novel or approved drugs is a key step in drug development. Previous computational approaches could be categorized into disease-centric and drug-centric based on the starting point of the issues or small-scaled application and large-scale application according to the diversity of the datasets. Here, a classifier has been constructed to predict the indications of a drug based on the assumption that interactive/associated drugs or drugs with similar structures are more likely to target the same diseases using a large drug indication dataset. To examine the classifier, it was conducted on a dataset with 1,573 drugs retrieved from Comprehensive Medicinal Chemistry database for five times, evaluated by 5-fold cross-validation, yielding five 1st order prediction accuracies that were all approximately 51.48%. Meanwhile, the model yielded an accuracy rate of 50.00% for the 1st order prediction by independent test on a dataset with 32 other drugs in which drug repositioning has been confirmed. Interestingly, some clinically repurposed drug indications that were not included in the datasets are successfully identified by our method. These results suggest that our method may become a useful tool to associate novel molecules with new indications or alternative indications with existing drugs.

Identification of FDA Approved Drugs Targeting COVID-19 Virus by Structure-Based Drug Repositioning (Version 2)

2020 ◽  
Author(s):  
Ayman Farag ◽  
Ping Wang ◽  
Mahmoud Ahmed ◽  
Hesham Sadek
Keyword(s):  
Drug Repositioning ◽  
Substrate Binding ◽  
Binding Pocket ◽  
Binding Energies ◽  
Binding Modes ◽  
Substrate Binding Pocket ◽  
Protease Enzyme ◽  
Starting Point ◽  
Approved Drugs ◽  
Fda Approved Drugs

The new strain of Coronaviruses (SARS-CoV-2), and the resulting Covid-19 disease has spread swiftly across the globe after its initial detection in late December 2019 in Wuhan, China, resulting in a pandemic status declaration by WHO within 3 months. Given the heavy toll of this pandemic, researchers are actively testing various strategies including new and repurposed drugs as well as vaccines. In the current brief report, we adopted a repositioning approach using insilico molecular modeling screening using FDA approved drugs with established safety profiles for potential inhibitory effects on Covid-19 virus. We started with structure based drug design by screening more than 2000 FDA approved drugs against Covid-19 virus main protease enzyme (Mpro) substrate-binding pocket focusing on two potential sites (central and terminal sites) to identify potential hits based on their binding energies, binding modes, interacting amino acids, and therapeutic indications. In addition, we elucidate preliminary pharmacophore features for candidates bound to Covid-19 virus Mpro substrate-binding pocket. The top hits bound to the central site of Mpro substrate-binding pocket include antiviral drugs such as Darunavir, Nelfinavir and Saquinavir, some of which are already being tested in Covid-19 patients. Interestingly, one of the most promising hits in our screen is the hypercholesterolemia drug Rosuvastatin. In addition, the top hits bound to the terminal site of Mpro substrate-binding pocket include the anti-asthma drug Montelukast and the anti-histaminic Fexofenadine among others. These results certainly do not confirm or indicate antiviral activity, but can rather be used as a starting point for further in vitro and in vivo testing, either individually or in combination.<br>

scholarly journals Repositioned Drugs for Chagas Disease Unveiled via Structure-Based Drug Repositioning

2020 ◽  
Vol 21 (22) ◽  
pp. 8809
Author(s):  
Melissa F. Adasme ◽  
Sarah Naomi Bolz ◽  
Lauren Adelmann ◽  
Sebastian Salentin ◽  
V. Joachim Haupt ◽  
...  
Keyword(s):  
Chagas Disease ◽  
Neglected Tropical Diseases ◽  
Ex Vivo ◽  
Drug Repositioning ◽  
Protein Structures ◽  
New Drugs ◽  
Drug Candidates ◽  
Growth Inhibitory ◽  
Growth Inhibitory Activity ◽  
Approved Drugs

Chagas disease, caused by the parasite Trypanosoma cruzi, affects millions of people in South America. The current treatments are limited, have severe side effects, and are only partially effective. Drug repositioning, defined as finding new indications for already approved drugs, has the potential to provide new therapeutic options for Chagas. In this work, we conducted a structure-based drug repositioning approach with over 130,000 3D protein structures to identify drugs that bind therapeutic Chagas targets and thus represent potential new Chagas treatments. The screening yielded over 500 molecules as hits, out of which 38 drugs were prioritized following a rigorous filtering process. About half of the latter were already known to have trypanocidal activity, while the others are novel to Chagas disease. Three of the new drug candidates—ciprofloxacin, naproxen, and folic acid—showed a growth inhibitory activity in the micromolar range when tested ex vivo on T. cruzi trypomastigotes, validating the prediction. We show that our drug repositioning approach is able to pinpoint relevant drug candidates at a fraction of the time and cost of a conventional screening. Furthermore, our results demonstrate the power and potential of structure-based drug repositioning in the context of neglected tropical diseases where the pharmaceutical industry has little financial interest in the development of new drugs.

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