Antileishmanial Drug Development: A Review of Modern Molecular Chemical Tools and Research Strategies

2020 ◽  
Vol 28 ◽  
Author(s):  
Pavan K. Mantravadi ◽  
Anutthaman Parthasarathy ◽  
Karunakaran Kalesh
Keyword(s):  
Visceral Leishmaniasis ◽  
Drug Development ◽  
High Throughput Screening ◽  
Complex Disease ◽  
Geographic Location ◽  
Sequence Information ◽  
Research Strategies ◽  
Chemical Genetic ◽  
Compound Libraries ◽  
Antileishmanial Drug

: Leishmaniasis, a complex disease caused by at least 20 species of unicellular parasites of the genus Leishmania, disproportionately affects impoverished regions of about 90 tropical and sub-tropical countries. Currently available antileishmanial therapies, particularly for the visceral leishmaniasis, are severely limited, with treatment outcome depending on many factors including the immune status of the patient, comorbidities, malnutrition, and socio-economic conditions in the patient’s geographic location. There is an urgent need for new therapeutics, particularly new effective oral drugs, for visceral leishmaniasis. Despite the availability of the Leishmania genome sequence information and significant research into the biology of the parasites, antileishmanial drug development is hampered by the lack of knowledge about druggable targets in the parasite and difficulties in identifying the molecular targets of compounds that show activity. In this context, we analyse recent progress in antileishmanial drug development programmes, which take advantage of different powerful approaches such as high-throughput screening of compound libraries, recent developments in genetic methods for assessing essentiality of parasite genes and, chemical, genetic and proteomics-based target discovery and target validation methods.

scholarly journals Challenges in Chagas Disease Drug Development

Molecules ◽  
2020 ◽  
Vol 25 (12) ◽  
pp. 2799 ◽  
Author(s):  
Amanda F. Francisco ◽  
Shiromani Jayawardhana ◽  
Francisco Olmo ◽  
Michael D. Lewis ◽  
Shane R. Wilkinson ◽  
...  
Keyword(s):  
Drug Development ◽  
Chagas Disease ◽  
High Throughput Screening ◽  
Public Health Problem ◽  
Drug Repurposing ◽  
Current Status ◽  
Laboratory Research ◽  
Important Public Health Problem ◽  
Treatment Regimens ◽  
Compound Libraries

The protozoan parasite Trypanosoma cruzi causes Chagas disease, an important public health problem throughout Latin America. Current therapeutic options are characterised by limited efficacy, long treatment regimens and frequent toxic side-effects. Advances in this area have been compromised by gaps in our knowledge of disease pathogenesis, parasite biology and drug activity. Nevertheless, several factors have come together to create a more optimistic scenario. Drug-based research has become more systematic, with increased collaborations between the academic and commercial sectors, often within the framework of not-for-profit consortia. High-throughput screening of compound libraries is being widely applied, and new technical advances are helping to streamline the drug development pipeline. In addition, drug repurposing and optimisation of current treatment regimens, informed by laboratory research, are providing a basis for new clinical trials. Here, we will provide an overview of the current status of Chagas disease drug development, highlight those areas where progress can be expected, and describe how fundamental research is helping to underpin the process.

pLoc_bal-mEuk: Predict Subcellular Localization of Eukaryotic Proteins by General PseAAC and Quasi-balancing Training Dataset

2019 ◽  
Vol 15 (5) ◽  
pp. 472-485 ◽  
Author(s):  
Kuo-Chen Chou ◽  
Xiang Cheng ◽  
Xuan Xiao
Keyword(s):  
Drug Development ◽  
Subcellular Localization ◽  
Basic Research ◽  
The Other ◽  
Training Dataset ◽  
Sequence Information ◽  
Eukaryotic Proteins ◽  
Validation Tests ◽  
User Friendly ◽  
Better Than

<P>Background/Objective: Information of protein subcellular localization is crucially important for both basic research and drug development. With the explosive growth of protein sequences discovered in the post-genomic age, it is highly demanded to develop powerful bioinformatics tools for timely and effectively identifying their subcellular localization purely based on the sequence information alone. Recently, a predictor called “pLoc-mEuk” was developed for identifying the subcellular localization of eukaryotic proteins. Its performance is overwhelmingly better than that of the other predictors for the same purpose, particularly in dealing with multi-label systems where many proteins, called “multiplex proteins”, may simultaneously occur in two or more subcellular locations. Although it is indeed a very powerful predictor, more efforts are definitely needed to further improve it. This is because pLoc-mEuk was trained by an extremely skewed dataset where some subset was about 200 times the size of the other subsets. Accordingly, it cannot avoid the biased consequence caused by such an uneven training dataset. </P><P> Methods: To alleviate such bias, we have developed a new predictor called pLoc_bal-mEuk by quasi-balancing the training dataset. Cross-validation tests on exactly the same experimentconfirmed dataset have indicated that the proposed new predictor is remarkably superior to pLocmEuk, the existing state-of-the-art predictor in identifying the subcellular localization of eukaryotic proteins. It has not escaped our notice that the quasi-balancing treatment can also be used to deal with many other biological systems. </P><P> Results: To maximize the convenience for most experimental scientists, a user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/pLoc_bal-mEuk/. </P><P> Conclusion: It is anticipated that the pLoc_bal-Euk predictor holds very high potential to become a useful high throughput tool in identifying the subcellular localization of eukaryotic proteins, particularly for finding multi-target drugs that is currently a very hot trend trend in drug development.</P>

scholarly journals High-throughput screening of natural compounds and inhibition of a major therapeutic target HsGSK-3β for Alzheimer’s disease using computational approaches

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Rohit Shukla ◽  
Tiratha Raj Singh
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
High Throughput Screening ◽  
Complex Disease ◽  
Glycogen Synthase ◽  
Binding Free Energy ◽  
Drug Candidate ◽  
Pharmacokinetic Analysis ◽  
Pharmacokinetic Parameters ◽  
Computational Approaches

Abstract Background Alzheimer’s disease is a leading neurodegenerative disease worldwide and is the 6th leading cause of death in the USA. AD is a very complex disease and the drugs available in the market cannot fully cure it. The glycogen synthase kinase 3 beta plays a major role in the hyperphosphorylation of tau protein which forms the neurofibrillary tangles which is a major hallmark of AD. In this study, we have used a series of computational approaches to find novel inhibitors against GSK-3β to reduce the TAU hyperphosphorylation. Results We have retrieved a set of compounds (n=167,741) and screened against GSK-3β in four sequential steps. The resulting analysis of virtual screening suggested that 404 compounds show good binding affinity and can be employed for pharmacokinetic analysis. From here, we have selected 20 compounds those were good in terms of pharmacokinetic parameters. All these compounds were re-docked by using Autodock Vina followed by Autodock. Four best compounds were employed for MDS and here predicted RMSD, RMSF, Rg, hydrogen bonds, SASA, PCA, and binding-free energy. From all these analyses, we have concluded that out of 167,741 compounds, the ZINC15968620, ZINC15968622, and ZINC70707119 can act as lead compounds against HsGSK-3β to reduce the hyperphosphorylation. Conclusion The study suggested three compounds (ZINC15968620, ZINC15968622, and ZINC70707119) have great potential to be a drug candidate and can be tested using in vitro and in vivo experiments for further characterization and applications.

scholarly journals Identification of SARS-CoV-2 Receptor Binding Inhibitors by In Vitro Screening of Drug Libraries

Molecules ◽  
2021 ◽  
Vol 26 (11) ◽  
pp. 3213
Author(s):  
Alon Ben David ◽  
Eran Diamant ◽  
Eyal Dor ◽  
Ada Barnea ◽  
Niva Natan ◽  
...  
Keyword(s):  
Receptor Binding ◽  
High Throughput Screening ◽  
Cell Attachment ◽  
Drug Repurposing ◽  
Heparin Sodium ◽  
Compound Libraries ◽  
Global Pandemic ◽  
Ic50 Values ◽  
Binding Inhibitors

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the coronavirus disease 2019 (COVID-19) global pandemic. The first step of viral infection is cell attachment, which is mediated by the binding of the SARS-CoV-2 receptor binding domain (RBD), part of the virus spike protein, to human angiotensin-converting enzyme 2 (ACE2). Therefore, drug repurposing to discover RBD-ACE2 binding inhibitors may provide a rapid and safe approach for COVID-19 therapy. Here, we describe the development of an in vitro RBD-ACE2 binding assay and its application to identify inhibitors of the interaction of the SARS-CoV-2 RBD to ACE2 by the high-throughput screening of two compound libraries (LOPAC®1280 and DiscoveryProbeTM). Three compounds, heparin sodium, aurintricarboxylic acid (ATA), and ellagic acid, were found to exert an effective binding inhibition, with IC50 values ranging from 0.6 to 5.5 µg/mL. A plaque reduction assay in Vero E6 cells infected with a SARS-CoV-2 surrogate virus confirmed the inhibition efficacy of heparin sodium and ATA. Molecular docking analysis located potential binding sites of these compounds in the RBD. In light of these findings, the screening system described herein can be applied to other drug libraries to discover potent SARS-CoV-2 inhibitors.

scholarly journals High-Throughput Screening and Drug Development to Fix RyR Pathology

2021 ◽  
Vol 120 (3) ◽  
pp. 148a-149a
Author(s):  
Robyn T. Rebbeck ◽  
Kaja Rozman ◽  
Gabrielle M. Evans ◽  
Jacob Schwarz ◽  
Marzena Baran ◽  
...  
Keyword(s):  
Drug Development ◽  
High Throughput ◽  
High Throughput Screening

scholarly journals Nicho ecológico actual y futuro de la Leishmaniasis (Kinetoplastida: Trypanosomatidae) en la región Neotropical

2016 ◽  
Vol 64 (3) ◽  
Author(s):  
David A. Moo-Llanes
Keyword(s):  
Climate Change ◽  
Visceral Leishmaniasis ◽  
Complex Disease ◽  
Protozoan Parasite ◽  
Neotropical Region ◽  
World Health ◽  
Climate Change Scenarios ◽  
Rcp Scenarios ◽  
Bioclimatic Variables ◽  
Health Organization

The leishmaniasis is a complex disease system, caused by the protozoan parasite Leishmania and transmitted to humans by the vector Lutzomyia spp. Since it is listed as a neglected disease according to the World Health Organization, the aim of this study was to determine the current and future niche of cutaneous and visceral leishmaniasis in the Neotropical region. We built the ecological niche model (ENM) of cutaneous (N= 2 910 occurrences) and visceral (N= 851 occurrences) leishmaniasis using MaxEnt algorithm. Nine bioclimatic variables (BIO1, BIO4, BIO5, BIO6, BIO7, BIO12, BIO13, BIO14, BIO15 (downloaded from the Worldclim) and disease occurrences data were used for the construction of ENM for three periods (current, 2050 and 2070) and four climate change scenarios (RCP 2.6, 4.5, 6.0 y 8.5). We analyzed the number of pixels occupied, identity niche, modified niche (stable, loss, and gain) and seasonality. Our analyses indicated the expansion for cutaneous leishmaniasis (CL), a comparison for visceral leishmaniasis (VL). We rejected the null hypothesis of niche identity between CL and VL with Hellinger’s index = 0.91 (0.92-0.98) and Schoener’s Index = 0.67 (0.85-1.00) but with an overlap niche of 56.3 %. The differences between the two leishmaniasis types were detected in relation to RCP scenarios and niche shifts (area gained / loss). Seasonality was more important for CL. We provided a current picture of CL and VL distributions and the predicted distributional changes associated to different climate change scenarios for the Neotropical region. We can anticipate that increasing range is likely although it will depend locally on the future trends in weather seasonality.

scholarly journals A Fully Automated High-Throughput Flow Cytometry Screening System Enabling Phenotypic Drug Discovery

2018 ◽  
Vol 23 (7) ◽  
pp. 697-707 ◽  
Author(s):  
John Joslin ◽  
James Gilligan ◽  
Paul Anderson ◽  
Catherine Garcia ◽  
Orzala Sharif ◽  
...  
Keyword(s):  
Flow Cytometry ◽  
Drug Discovery ◽  
High Throughput ◽  
High Throughput Screening ◽  
Screening System ◽  
Preclinical Development ◽  
Drug Identification ◽  
Therapeutic Setting ◽  
Compound Libraries ◽  
Automated Platform

The goal of high-throughput screening is to enable screening of compound libraries in an automated manner to identify quality starting points for optimization. This often involves screening a large diversity of compounds in an assay that preserves a connection to the disease pathology. Phenotypic screening is a powerful tool for drug identification, in that assays can be run without prior understanding of the target and with primary cells that closely mimic the therapeutic setting. Advanced automation and high-content imaging have enabled many complex assays, but these are still relatively slow and low throughput. To address this limitation, we have developed an automated workflow that is dedicated to processing complex phenotypic assays for flow cytometry. The system can achieve a throughput of 50,000 wells per day, resulting in a fully automated platform that enables robust phenotypic drug discovery. Over the past 5 years, this screening system has been used for a variety of drug discovery programs, across many disease areas, with many molecules advancing quickly into preclinical development and into the clinic. This report will highlight a diversity of approaches that automated flow cytometry has enabled for phenotypic drug discovery.

scholarly journals Drug discovery from Nature: automated high-quality sample preparation

2000 ◽  
Vol 22 (5) ◽  
pp. 149-157 ◽  
Author(s):  
Ralf Thiericke
Keyword(s):  
Drug Discovery ◽  
Sample Preparation ◽  
High Throughput ◽  
High Throughput Screening ◽  
Solid Phase ◽  
Structural Diversity ◽  
Synthetic Compound ◽  
Natural Origin ◽  
Screening Programs ◽  
Compound Libraries

Secondary metabolites from plants, animals and microorganisms have been proven to be an outstanding source for new and innovative drugs and show a striking structural diversity that supplements chemically synthesized compounds or libraries in drug discovery programs. Unfortunately, extracts from natural sources are usually complex mixtures of compounds:: often generated in time consuming and for the most part manual processes. As quality and quantity of the provided samples play a pivotal role in the success of high-throughput screening programs this poses serious problems. In order to make samples of natural origin competitive with synthetic compound libraries, we devised a novel, automated sample preparation procedure based on solid-phase extraction (SPE). By making use of a modified Zymark RapidTrace®SPE workstation an easy-to-handle and effective fractionation method has been developed which allows the generation of highquality samples from natural origin, fulfilling the requirements of an integration into high-throughput screening programs.

scholarly journals Multidimensional Profiling of CSF1R Screening Hits and Inhibitors

2011 ◽  
Vol 16 (9) ◽  
pp. 1007-1017 ◽  
Author(s):  
Joost C. M. Uitdehaag ◽  
Cecile M. Sünnen ◽  
Antoon M. van Doornmalen ◽  
Nikki de Rouw ◽  
Arthur Oubrie ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Screening ◽  
Active Form ◽  
Dissociation Rate ◽  
The Past ◽  
Compound Libraries ◽  
Competitive Kinetics ◽  
Homogeneous Assay ◽  
High Throughput Assay ◽  
Stimulating Factor

Over the past years, improvements in high-throughput screening (HTS) technology and compound libraries have resulted in a dramatic increase in the amounts of good-quality screening hits, and there is a growing need for follow-on hit profiling assays with medium throughput to further triage hits. Here the authors present such assays for the colony-stimulating factor 1 receptor (CSF1R, Fms), including tests for cellular activity and a homogeneous assay to measure affinity for inactive CSF1R. They also present a high-throughput assay to measure target residence time, which is based on competitive binding kinetics. To better fit koff rates, they present a modified mathematical model for competitive kinetics. In all assays, they profiled eight reference inhibitors (imatinib, sorafenib, sunitinib, tandutinib, dasatinib, GW2580, Ki20227, and J&J’s pyrido[2,3-d]pyrimidin-5-one). Using the known biochemical selectivities of these inhibitors, which can be quantified using metrics such as the selectivity entropy, the authors have determined which assay readout best predicts hit selectivity. Their profiling shows surprisingly that imatinib has a preference for the active form of CSF1R and that Ki20227 has an unusually slow target dissociation rate. This confirms that follow-on hit profiling is essential to ensure that the best hits are selected for lead optimization.

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