scholarly journals Quinuclidine Derivatives as Potential Antiparasitics

2007 ◽  
Vol 51 (11) ◽  
pp. 4049-4061 ◽  
Author(s):  
Simon B. Cammerer ◽  
Carmen Jimenez ◽  
Simon Jones ◽  
Ludovic Gros ◽  
Silvia Orenes Lorente ◽  
...  
Keyword(s):  
Drug Target ◽  
Human African Trypanosomiasis ◽  
Leishmania Major ◽  
Sterol Biosynthesis ◽  
New Drugs ◽  
Causative Organism ◽  
Design And Synthesis ◽  
Human Enzyme ◽  
Key Enzyme ◽  
Potential Inhibitors

ABSTRACT There is an urgent need for the development of new drugs for the treatment of tropical parasitic diseases such as Chagas' disease and leishmaniasis. One potential drug target in the organisms that cause these diseases is sterol biosynthesis. This paper describes the design and synthesis of quinuclidine derivatives as potential inhibitors of a key enzyme in sterol biosynthesis, squalene synthase (SQS). A number of compounds that were inhibitors of the recombinant Leishmania major SQS at submicromolar concentrations were discovered. Some of these compounds were also selective for the parasite enzyme rather than the homologous human enzyme. The compounds inhibited the growth of and sterol biosynthesis in Leishmania parasites. In addition, we identified other quinuclidine derivatives that inhibit the growth of Trypanosoma brucei (the causative organism of human African trypanosomiasis) and Plasmodium falciparum (a causative agent of malaria), but through an unknown mode(s) of action.

scholarly journals The ubiquinone synthesis pathway is a promising drug target for Chagas disease

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0243855
Author(s):  
Takeshi Nara ◽  
Yukari Nakagawa ◽  
Keiko Tsuganezawa ◽  
Hitomi Yuki ◽  
Katsuhiko Sekimata ◽  
...  
Keyword(s):  
Chagas Disease ◽  
Latin American ◽  
Drug Target ◽  
Culture Medium ◽  
Protozoan Parasite ◽  
Redox Balance ◽  
New Drugs ◽  
Key Enzyme ◽  
2D And 3D ◽  
Similarity Searches

Chagas disease is caused by infection with the protozoan parasite Trypanosoma cruzi (T. cruzi). It was originally a Latin American endemic health problem, but now is expanding worldwide as a result of increasing migration. The currently available drugs for Chagas disease, benznidazole and nifurtimox, provoke severe adverse effects, and thus the development of new drugs is urgently required. Ubiquinone (UQ) is essential for respiratory chain and redox balance in trypanosomatid protozoans, therefore we aimed to provide evidence that inhibitors of the UQ biosynthesis have trypanocidal activities. In this study, inhibitors of the human COQ7, a key enzyme of the UQ synthesis, were tested for their trypanocidal activities because they were expected to cross-react and inhibit trypanosomal COQ7 due to their genetic homology. We show the trypanocidal activity of a newly found human COQ7 inhibitor, an oxazinoquinoline derivative. The structurally similar compounds were selected from the commercially available compounds by 2D and 3D ligand-based similarity searches. Among 38 compounds selected, 12 compounds with the oxazinoquinoline structure inhibited significantly the growth of epimastigotes of T. cruzi. The most effective 3 compounds also showed the significant antitrypanosomal activity against the mammalian stage of T. cruzi at lower concentrations than benznidazole, a commonly used drug today. We found that epimastigotes treated with the inhibitor contained reduced levels of UQ9. Further, the growth of epimastigotes treated with the inhibitors was partially rescued by UQ10 supplementation to the culture medium. These results suggest that the antitrypanosomal mechanism of the oxazinoquinoline derivatives results from inhibition of the trypanosomal UQ synthesis leading to a shortage of the UQ pool. Our data indicate that the UQ synthesis pathway of T. cruzi is a promising drug target for Chagas disease.

scholarly journals Novel Saccharomyces cerevisiae Screen Identifies WR99210 Analogues That Inhibit Mycobacterium tuberculosis Dihydrofolate Reductase

2002 ◽  
Vol 46 (11) ◽  
pp. 3362-3369 ◽  
Author(s):  
A'Lissa B. Gerum ◽  
Jonathan E. Ulmer ◽  
David P. Jacobus ◽  
Norman P. Jensen ◽  
David R. Sherman ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Mycobacterium Tuberculosis ◽  
Dihydrofolate Reductase ◽  
Drug Target ◽  
Multidrug Resistant ◽  
New Drugs ◽  
Treatment Regimens ◽  
Key Enzyme ◽  
Level 3

ABSTRACT The ongoing selection of multidrug-resistant strains of Mycobacterium tuberculosis has markedly reduced the effectiveness of the standard treatment regimens. Thus, there is an urgent need for new drugs that are potent inhibitors of M. tuberculosis, that exhibit favorable resistance profiles, and that are well tolerated by patients. One promising drug target for treatment of mycobacterial infections is dihydrofolate reductase (DHFR; EC 1.5.1.3), a key enzyme in folate utilization. DHFR is an important drug target in many pathogens, but it has not been exploited in the search for drugs effective against M. tuberculosis. The triazine DHFR inhibitor WR99210 has been shown to be effective against other mycobacteria. We show here that WR99210 is also a potent inhibitor of M. tuberculosis and Mycobacterium bovis BCG growth in vitro and that resistance to WR99210 occurred less frequently than resistance to either rifampin or isoniazid. Screening of drugs with M. tuberculosis cultures is slow and requires biosafety level 3 facilities and procedures. We have developed an alternative strategy: initial screening in an engineered strain of the budding yeast Saccharomyces cerevisiae that is dependent on the M. tuberculosis DHFR for its growth. Using this system, we have screened 19 compounds related to WR99210 and found that 7 of these related compounds are also potent inhibitors of the M. tuberculosis DHFR. These studies suggest that compounds of this class are excellent potential leads for further development of drugs effective against M. tuberculosis.

Design and synthesis of substrate mimetics based on an indole scaffold: potential inhibitors of 17β-HSD type 1

2011 ◽  
Vol 6 (1) ◽  
Author(s):  
Štefan Starčević ◽  
Polona Božnar ◽  
Samo Turk ◽  
Stanislav Gobec ◽  
Tea Lanišnik Rižner
Keyword(s):  
Breast Cancer ◽  
Indole Derivative ◽  
Hydroxysteroid Dehydrogenase ◽  
New Drugs ◽  
Indole Derivatives ◽  
Docking Simulations ◽  
Design And Synthesis ◽  
Steroid Substrate ◽  
Potential Inhibitors

AbstractHuman 17β-hydroxysteroid dehydrogenase type 1 (17β-HSD1) acts at a pre-receptor level. It catalyzes NADPH-dependent reduction of the weak estrogen estrone into the most potent estrogen estradiol, which exerts its proliferative effects via estrogen receptors. Overexpression of 17β-HSD1 in estrogen-responsive tissues is related to the development of hormone-dependent diseases, such as breast cancer and endometriosis. 17β-HSD1 thus represents an attractive target for development of new drugs.We designed and synthesized a series of 3-, 5- and 6-phenyl indole derivatives as mimetics of the steroid substrate estrone. All of these compounds were evaluated for inhibition of recombinant human 17β-HSD1 fromAmong 14 indole derivatives, compound 9 was an initial hit inhibitor of 17β-HSD1, with moderate inhibition (64% at 6 μM). Molecular docking into the crystal structure of 17β-HSD1 (1A27) revealed that this 5-phenyl indole derivative binds to 17β-HSD1 similarly to co-crystalized E2. Compound 9 forms two H-bonds with 17β-HSD1: one between the indole nitrogen and His222, and the second between the phenolic OH group and catalytic Tyr155.The indole scaffold is one of the possible starting points for the design of substrate mimetics of the steroid substrate estrone. Our study shows that these 6- and, especially, 5-phenol indole derivatives can act as moderate inhibitors of 17β-HSD1. Based on inhibition assays and docking simulations, we can infer further improvements of the 5-phenol indole derivatives that might result in better inhibition profiles.

A Drug Target Interaction Prediction Based on LINE-RF Learning

2020 ◽  
Vol 15 (7) ◽  
pp. 750-757
Author(s):  
Jihong Wang ◽  
Yue Shi ◽  
Xiaodan Wang ◽  
Huiyou Chang
Keyword(s):  
Network Topology ◽  
Drug Target ◽  
Large Scale ◽  
Representation Learning ◽  
New Drugs ◽  
Combination Method ◽  
Learning Methods ◽  
Network Representation ◽  
On Line ◽  
Clinical Experiments

Background: At present, using computer methods to predict drug-target interactions (DTIs) is a very important step in the discovery of new drugs and drug relocation processes. The potential DTIs identified by machine learning methods can provide guidance in biochemical or clinical experiments. Objective: The goal of this article is to combine the latest network representation learning methods for drug-target prediction research, improve model prediction capabilities, and promote new drug development. Methods: We use large-scale information network embedding (LINE) method to extract network topology features of drugs, targets, diseases, etc., integrate features obtained from heterogeneous networks, construct binary classification samples, and use random forest (RF) method to predict DTIs. Results: The experiments in this paper compare the common classifiers of RF, LR, and SVM, as well as the typical network representation learning methods of LINE, Node2Vec, and DeepWalk. It can be seen that the combined method LINE-RF achieves the best results, reaching an AUC of 0.9349 and an AUPR of 0.9016. Conclusion: The learning method based on LINE network can effectively learn drugs, targets, diseases and other hidden features from the network topology. The combination of features learned through multiple networks can enhance the expression ability. RF is an effective method of supervised learning. Therefore, the Line-RF combination method is a widely applicable method.

scholarly journals Predicting drug–target interactions Based on the Ensemble Models of Multiple Feature Pairs

2021 ◽  
Vol 22 (12) ◽  
pp. 6598
Author(s):  
Cheng Wang ◽  
Jun Zhang ◽  
Peng Chen ◽  
Bing Wang
Keyword(s):  
Drug Target ◽  
Essential Feature ◽  
Characteristic Curve ◽  
Prediction Method ◽  
New Drugs ◽  
Good Prediction ◽  
Ensemble Model ◽  
Test Set ◽  
Multiple Feature ◽  
Validation Set

Backgroud: The prediction of drug–target interactions (DTIs) is of great significance in drug development. It is time-consuming and expensive in traditional experimental methods. Machine learning can reduce the cost of prediction and is limited by the characteristics of imbalanced datasets and problems of essential feature selection. Methods: The prediction method based on the Ensemble model of Multiple Feature Pairs (Ensemble-MFP) is introduced. Firstly, three negative sets are generated according to the Euclidean distance of three feature pairs. Then, the negative samples of the validation set/test set are randomly selected from the union set of the three negative sets in the validation set/test set. At the same time, the ensemble model with weight is optimized and applied to the test set. Results: The area under the receiver operating characteristic curve (area under ROC, AUC) in three out of four sub-datasets in gold standard datasets was more than 94.0% in the prediction of new drugs. The effectiveness of the proposed method is also shown with the comparison of state-of-the-art methods and demonstration of predicted drug–target pairs. Conclusion: The Ensemble-MFP can weigh the existing feature pairs and has a good prediction effect for general prediction on new drugs.

scholarly journals Chemical Validation of Phosphodiesterase C as a Chemotherapeutic Target in Trypanosoma cruzi, the Etiological Agent of Chagas' Disease

2010 ◽  
Vol 54 (9) ◽  
pp. 3738-3745 ◽  
Author(s):  
Sharon King-Keller ◽  
Minyong Li ◽  
Alyssa Smith ◽  
Shilong Zheng ◽  
Gurpreet Kaur ◽  
...  
Keyword(s):  
Trypanosoma Cruzi ◽  
Chagas Disease ◽  
Catalytic Domain ◽  
Polypeptide Chain ◽  
Inflammatory Diseases ◽  
New Drugs ◽  
Volume Recovery ◽  
Chronic Pulmonary Diseases ◽  
Potential Inhibitors

ABSTRACT Trypanosoma cruzi phosphodiesterase (PDE) C (TcrPDEC), a novel and rather unusual PDE in which, unlike all other class I PDEs, the catalytic domain is localized in the middle of the polypeptide chain, is able to hydrolyze cyclic GMP (cGMP), although it prefers cyclic AMP (cAMP), and has a FYVE-type domain in its N-terminal region (S. Kunz et al., FEBS J. 272:6412-6422, 2005). TcrPDEC shows homology to the mammalian PDE4 family members. PDE4 inhibitors are currently under development for the treatment of inflammatory diseases, such as asthma, chronic pulmonary diseases, and psoriasis, and for treating depression and serving as cognitive enhancers. We therefore tested a number of compounds originally synthesized as potential PDE4 inhibitors on T. cruzi amastigote growth, and we obtained several useful hits. We then conducted homology modeling of T. cruzi PDEC and identified other compounds as potential inhibitors through virtual screening. Testing of these compounds against amastigote growth and recombinant TcrPDEC activity resulted in several potent inhibitors. The most-potent inhibitors were found to increase the cellular concentration of cAMP. Preincubation of cells in the presence of one of these compounds stimulated volume recovery after hyposmotic stress, in agreement with their TcrPDEC inhibitory activity in vitro, providing chemical validation of this target. The compounds found could be useful tools in the study of osmoregulation in T. cruzi. In addition, their further optimization could result in the development of new drugs against Chagas' disease and other trypanosomiases.

scholarly journals Prediction of Anti-COVID 19 Therapeutic Power of Medicinal Moroccan Plants Using Molecular Docking

2021 ◽  
Vol 15 ◽  
pp. 117793222110091
Author(s):  
Badreddine Nouadi ◽  
Abdelkarim Ezaouine ◽  
Mariame El Messal ◽  
Mohamed Blaghen ◽  
Faiza Bennis ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Medicinal Plants ◽  
Drug Target ◽  
Cost Effective ◽  
Current Medical Research ◽  
New Drugs ◽  
Binding Affinities ◽  
Global Public Health ◽  
Public Health Challenge ◽  
Ucsf Chimera

The emerging pathogen SARS-CoV2 causing coronavirus disease 2019 (COVID-19) is a global public health challenge. To the present day, COVID-19 had affected more than 40 million people worldwide. The exploration and the development of new bioactive compounds with cost-effective and specific anti-COVID 19 therapeutic power is the prime focus of the current medical research. Thus, the exploitation of the molecular docking technique has become essential in the discovery and development of new drugs, to better understand drug-target interactions in their original environment. This work consists of studying the binding affinity and the type of interactions, through molecular docking, between 54 compounds from Moroccan medicinal plants, dextran sulfate and heparin (compounds not derived from medicinal plants), and 3CLpro-SARS-CoV-2, ACE2, and the post fusion core of 2019-nCoV S2 subunit. The PDB files of the target proteins and prepared herbal compounds (ligands) were subjected for docking to AutoDock Vina using UCSF Chimera, which provides a list of potential complexes based on the criteria of form complementarity of the natural compound with their binding affinities. The results of molecular docking revealed that Taxol, Rutin, Genkwanine, and Luteolin-glucoside have a high affinity with ACE2 and 3CLpro. Therefore, these natural compounds can have 2 effects at once, inhibiting 3CLpro and preventing recognition between the virus and ACE2. These compounds may have a potential therapeutic effect against SARS-CoV2, and therefore natural anti-COVID-19 compounds.

Construction and functionalization of pyranone ring fused with pyran moiety: Design and synthesis of novel pyrano[4,3-b]pyran-5(4H)-ones as potential inhibitors of sirtuins

2013 ◽  
Vol 23 (14) ◽  
pp. 4195-4205 ◽  
Author(s):  
Ali Nakhi ◽  
Md. Shafiqur Rahman ◽  
Sivakumar Archana ◽  
Ravada Kishore ◽  
G.P.K. Seerapu ◽  
...  
Keyword(s):  
Design And Synthesis ◽  
Potential Inhibitors

scholarly journals cDNA cloning of human and rat brain myo-inositol monophosphatase. Expression and characterization of the human recombinant enzyme

1992 ◽  
Vol 284 (3) ◽  
pp. 749-754 ◽  
Author(s):  
G McAllister ◽  
P Whiting ◽  
E A Hammond ◽  
M R Knowles ◽  
J R Atack ◽  
...  
Keyword(s):  
Rat Brain ◽  
Cell Signalling ◽  
Biochemical Properties ◽  
Recombinant Enzyme ◽  
Cdna Clones ◽  
Coding Region ◽  
Inositol Monophosphatase ◽  
Human Enzyme ◽  
Key Enzyme

Inositol monophosphatase (EC 3.1.3.25) is a key enzyme in the phosphoinositide cell-signalling system. Its role is to provide inositol required for the resynthesis of phosphatidylinositol and polyphosphoinositides. It is the probable pharmacological target for lithium action in brain. Using probes derived from the bovine inositol monophosphatase cDNA we have isolated cDNA clones encoding the human and rat brain enzymes. The enzyme is highly conserved in all three species (79% identical). The coding region of the human cDNA was inserted into a bacterial expression vector. The expressed recombinant enzyme was purified and its biochemical properties examined. The human enzyme is very similar to the bovine enzyme.

scholarly journals PROMISCUOUS 2.0: a resource for drug-repositioning

2020 ◽  
Vol 49 (D1) ◽  
pp. D1373-D1380
Author(s):  
Kathleen Gallo ◽  
Andrean Goede ◽  
Andreas Eckert ◽  
Barbara Moahamed ◽  
Robert Preissner ◽  
...  
Keyword(s):  
Side Effects ◽  
Small Molecules ◽  
User Experience ◽  
Drug Target ◽  
Drug Repositioning ◽  
Dynamic Network ◽  
Structural Similarity ◽  
New Drugs ◽  
Entry Level ◽  
Development Costs

Abstract The development of new drugs for diseases is a time-consuming, costly and risky process. In recent years, many drugs could be approved for other indications. This repurposing process allows to effectively reduce development costs, time and, ultimately, save patients’ lives. During the ongoing COVID-19 pandemic, drug repositioning has gained widespread attention as a fast opportunity to find potential treatments against the newly emerging disease. In order to expand this field to researchers with varying levels of experience, we made an effort to open it to all users (meaning novices as well as experts in cheminformatics) by significantly improving the entry-level user experience. The browsing functionality can be used as a global entry point to collect further information with regards to small molecules (∼1 million), side-effects (∼110 000) or drug-target interactions (∼3 million). The drug-repositioning tab for small molecules will also suggest possible drug-repositioning opportunities to the user by using structural similarity measurements for small molecules using two different approaches. Additionally, using information from the Promiscuous 2.0 Database, lists of candidate drugs for given indications were precomputed, including a section dedicated to potential treatments for COVID-19. All the information is interconnected by a dynamic network-based visualization to identify new indications for available compounds. Promiscuous 2.0 is unique in its functionality and is publicly available at http://bioinformatics.charite.de/promiscuous2.

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