Target shortage and less explored multiple targeting: hurdles in the development of novel antifungals but overcome/addressed effectively through structural bioinformatics

2020 ◽  
Author(s):  
Anubhuti Jha ◽  
Archana Vimal ◽  
Awanish Kumar
Keyword(s):  
Fungal Pathogen ◽  
Target Identification ◽  
Molecular Targets ◽  
Structural Bioinformatics ◽  
Antifungal Drugs ◽  
Patient Treatment ◽  
Effective Strategy ◽  
In Silico Screening ◽  
Limited Efficacy ◽  
Over Time

Abstract Billions of people are affected by fungal infection worldwide, which is a major cause of morbidity and mortality in humans. Regardless of development in the field of antifungal therapeutics over the last three decades, multidrug resistance and limited efficacy of available antifungal drugs are very prominent and still a great hurdle in the patient treatment. The current antifungal pipeline is dry, which is needed to be strengthened. Although several strategies have been implemented over time to discover novel promising antifungal leads, but very little emphasis has been given to address the gap of fungal target identification. Undeniably, the need for identifying novel cellular fungal targets is as vital as discovering novel antifungal leads and a structural bioinformatics approach could be an effective strategy in this regard. To address the issue, we have performed in silico screening to identify a few potent multiple targeting ligands and their respective antifungal targets. Thus, we offer a perspective on the phenomena of ‘target shortage’ and least explored ‘multiple targeting’ being the most underrated challenges in antifungal drug discovery. ‘Structural bioinformatics’ could be an effective approach in the recognition of new/innovative antifungal target and identification/development of novel antifungal lead molecule aiming multiple molecular targets of the fungal pathogen.

Forecasting Areawide Hospital Utilization: A Comparison of Five Univariate Time Series Techniques

1993 ◽  
Vol 6 (3) ◽  
pp. 178-190 ◽  
Author(s):  
Thomas W. Weiss ◽  
Carol M. Ashton ◽  
Nelda P. Wray
Keyword(s):  
Time Series ◽  
Average Length ◽  
Discharge Rate ◽  
Veterans Affairs ◽  
Economic Modeling ◽  
Hospital Utilization ◽  
Patient Treatment ◽  
Department Of Veterans Affairs ◽  
Univariate Time Series ◽  
Over Time

Time series analysis is one of the methods health services researchers, managers and planners have to examine and predict utilization over time. The focus of this study is univariate time series techniques, which model the change in a dependent variable over time, using time as the only independent variable. These techniques can be used with administrative healthcare databases, which typically contain reliable, time-specific utilization variables, but may lack adequate numbers of variables needed for behavioral or economic modeling. The inpatient discharge database of the Department of Veterans Affairs, the Patient Treatment File, was used to calculate monthly time series over a six-year period for the nation and across US Census Bureau regions for three hospital utilization indicators: Average length of stay, discharge rate, and multiple stay ratio, a measure of readmissions. The first purpose of this study was to determine the accuracy of forecasting these indicators 24 months into the future using five univariate time series techniques. In almost all cases, techniques were able to forecast the magnitude and direction of future utilization within a 10% mean monthly error. The second purpose of the study was to describe time series of the three hospital utilization indicators. This approach raised several questions concerning Department of Veterans Affairs hospital utilization.

Team Size, Team Role, Communication Modality, and Team Coordination in the Distributed Operation of Multiple Heterogeneous Unmanned Vehicles

2011 ◽  
Vol 5 (1) ◽  
pp. 106-131 ◽  
Author(s):  
Thomas Fincannon ◽  
Joseph R. Keebler ◽  
Florian Jentsch ◽  
Elizabeth Phillips ◽  
A. William Evans
Keyword(s):  
Instant Messaging ◽  
Target Identification ◽  
Unmanned Vehicles ◽  
Object Localization ◽  
Distributed Teams ◽  
Military Operations ◽  
Team Size ◽  
Communication Modality ◽  
Urban Terrain ◽  
Over Time

The aim of this study was to investigate the effects of team size, communication modality, and team role on measures of team process over time. As the use of semiautonomous, unmanned vehicles increases, it is pertinent to investigate issues associated with the human teams that will control them, including consideration of team roles and the design of systems to support these roles. Using a 1:35 scale facility for military operations in urban terrain, distributed teams of two or three operators used a simulated, unmanned aerial vehicle and a scaled, unmanned ground vehicle to complete two distinct phases of a mission. The teams used either audio or instant messaging for communication, and the analysis of communication assessed their discussion of target identification, target classification, object localization, and vehicle navigation. Findings indicate that the addition of a third teammate resulted in greater role specificity, and the use of audio increased communication of task-relevant content. The proper assignment of team roles can improve the ability of a team to both acquire and synthesize information from remote environments. Furthermore, proper system design can improve the flow of information between teammates over time.

Diagnostic Stability of Psychotic Disorders: A Retrospective Study

2009 ◽  
Vol 24 (S1) ◽  
pp. 1-1
Author(s):  
C. Silveira ◽  
A. Norton ◽  
A. Martins ◽  
I. Domingues ◽  
R. Moreira ◽  
...  
Keyword(s):  
Retrospective Study ◽  
Psychotic Disorders ◽  
University Hospital ◽  
Patient Treatment ◽  
Psychotic Episode ◽  
List Type ◽  
Clinical Expertise ◽  
Drug Induced ◽  
Clinical Records ◽  
Over Time

Background:An essential condition to validate a diagnosis is its stability over time. Since there are no biological markers for psychiatric disorders, the diagnosis relies on clinical expertise, with several consequences in treatment planning, disease burden and disability, affecting outcome and public health.Objectives:The aims of this study were:1.the assessment of long term stability of the diagnosis of psychotic disorders,2.its implications in patient treatment, and3.the evaluation of eventual predictors of diagnosis stability.Methods:This was a retrospective study carried out in the Department of Psychiatry of a large University Hospital (Hospital S. João, Porto, Portugal). Patients enrolled were admitted in the inpatient unit from 2000 to 2003 (n=190, 12.41% of 1531 patients admitted), experienced a first psychotic episode, and fulfilled criteria for one of the following diagnosis: schizophrenia, schizoaffective disorder, bipolar disorder, drug induced psychosis, acute and transient psychotic disorders, schizophreniform disorder and psychosis NOS (ICD-10 classification). the diagnoses were extracted from clinical records, and reassessed five years after the initial diagnosis. the analysis focuses on diagnostic agreement over time; clinical and demographic variables were also collected and putative associations with diagnostic shift considered.Results:The study is now under statistic evaluation.

scholarly journals Tolerance to fluconazole in Candida albicans is regulated by temperature and aneuploidy

2021 ◽  
Vol 3 (12) ◽  
Author(s):  
FENG YANG ◽  
YUANYING JIANG ◽  
JUDITH BERMAN
Keyword(s):  
Candida Albicans ◽  
High Temperature ◽  
Fungal Pathogen ◽  
Drug Tolerance ◽  
Antifungal Drugs ◽  
Clinical Isolates ◽  
Human Fungal Pathogen ◽  
Genes Encoding ◽  
Aneuploid Chromosome ◽  
Definition Of

Candida albicans is a prevalent human fungal pathogen. Azoles are the most widely used antifungal drugs. Drug tolerance in bacteria is well defined and thoroughly studied, but in fungi, the definition of drug tolerance and the mechanism that drive it are not well understood. Here, we found that a large proportion of clinical isolates were intrinsically tolerant to fluconazole, and/or could be induced by high temperature (37°C) to become tolerant (conditionally tolerant). When treated with inhibitory doses of fluconazole, non-tolerant strains became tolerant by forming aneuploids involving different chromosomes, with chromosome R duplication as the most recurrent mechanism. Tolerance determines the ability to grow in the presence of fluconazole and other azoles, in a manner independent of the MIC. Both temperature conditional tolerance and the associated aneuploidy were sensitive to FK506, an inhibitor of calcineurin. Intrinsic and conditional tolerance were also abolished by deletions of genes encoding the calcineurin (CMP1 and CNB1). However, the dependence of tolerance on calcineurin could be bypassed by a different aneuploid chromosome. Thus, fluconazole tolerance in C. albicans is regulated by temperature and by aneuploidy and is dependent upon aneuploidy, but this dependence can be bypassed by an additional aneuploidy.

scholarly journals Kinase Inhibitor Library Screening Identifies the Cancer Therapeutic Sorafenib and Structurally Similar Compounds as Strong Inhibitors of the Fungal Pathogen Histoplasma capsulatum

Antibiotics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1223
Author(s):  
Charlotte Berkes ◽  
Jimmy Franco ◽  
Maxx Lawson ◽  
Katelynn Brann ◽  
Jessica Mermelstein ◽  
...  
Keyword(s):  
Fungal Pathogen ◽  
Kinase Inhibitors ◽  
Histoplasma Capsulatum ◽  
Kinase Inhibitor ◽  
Systemic Disease ◽  
Antifungal Drugs ◽  
Infection Model ◽  
Macrophage Infection ◽  
Pathogenic Yeast

Histoplasma capsulatum is a dimorphic fungal pathogen endemic to the midwestern and southern United States. It causes mycoses ranging from subclinical respiratory infections to severe systemic disease, and is of particular concern for immunocompromised patients in endemic areas. Clinical management of histoplasmosis relies on protracted regimens of antifungal drugs whose effectiveness can be limited by toxicity. In this study, we hypothesize that conserved biochemical signaling pathways in the eukaryotic domain can be leveraged to repurpose kinase inhibitors as antifungal compounds. We conducted a screen of two kinase inhibitor libraries to identify compounds inhibiting the growth of Histoplasma capsulatum in the pathogenic yeast form. Our approach identified seven compounds with an elongated hydrophobic polyaromatic structure, five of which share a molecular motif including a urea unit linking a halogenated benzene ring and a para-substituted polyaromatic group. The top hits include the cancer therapeutic Sorafenib, which inhibits growth of Histoplasma in vitro and in a macrophage infection model with low host cell cytotoxicity. Our results reveal the possibility of repurposing Sorafenib or derivatives thereof as therapy for histoplasmosis, and suggest that repurposing of libraries developed for human cellular targets may be a fruitful source of antifungal discovery.

scholarly journals The application of Hadoop in Structural Bioinformatics

2018 ◽  
Author(s):  
Jamie Alnasir ◽  
Hugh P. Shanahan
Keyword(s):  
High Throughput ◽  
Structural Alignment ◽  
Protein Docking ◽  
Structural Bioinformatics ◽  
Significant Barrier ◽  
Hadoop Platform ◽  
Hadoop Ecosystem ◽  
Over Time ◽  
Better Than

AbstractThe paper reviews the use of the Hadoop platform in Structural Bioinformatics applications. Specifically, we review a number of implementations using Hadoop of high-throughput analyses, e.g. ligand-protein docking and structural alignment, and their scalability in comparison with other batch schedulers and MPI. We find that these deployments for the most part use known executables called from MapReduce rather than rewriting the algorithms. The scalability exhibits a variable behaviour in comparison with other batch schedulers, particularly as direct comparisons on the same platform are generally not available. We do note there is some evidence that MPI implementations scale better than Hadoop. A significant barrier to the use of the Hadoop ecosystem is the difficulty of the interface and configuration of a resource to use Hadoop. This will improve over time as interfaces to Hadoop e.g. Spark improve, usage of cloud platforms (e.g. Azure and AWS) increases and approaches such as the Workflow Definition Language are taken up.

scholarly journals Interpreting Lived Experience through Writing Online in a Graduate Seminar

1944 ◽  
Vol 7 (1) ◽  
Author(s):  
Mary Clare Courtland ◽  
John Novak ◽  
Gail LaFleur ◽  
Ken McClelland ◽  
Steve R. Sider ◽  
...  
Keyword(s):  
Lived Experience ◽  
Literary Texts ◽  
Effective Strategy ◽  
Autobiographical Narratives ◽  
Interpretive Community ◽  
Graduate Seminar ◽  
Writing Strategy ◽  
Online Format ◽  
Over Time

Participants in an online doctoral seminar participated in the use of a writing strategy to explore the sociocultural contexts of their lived experience. Creating literary texts in three forms was an effective strategy in mediating participants' understanding. Each form provided a new lens through which to interpret experience. Participants functioned as an interpretive community. The final papers, autobiographical narratives, illuminated the complex relations among prediscursive experience, reflection on experience, distancing, and the iterative transformational quality of time. The online format embodied a virtual interpretive location which allowed participants to revisit texts and postings over time.

scholarly journals Echinocandins as Biotechnological Tools for Treating Candida auris Infections

2020 ◽  
Vol 6 (3) ◽  
pp. 185
Author(s):  
Elizabete de Souza Cândido ◽  
Flávia Affonseca ◽  
Marlon Henrique Cardoso ◽  
Octavio Luiz Franco
Keyword(s):  
Fungal Pathogen ◽  
Pathogenic Fungi ◽  
Antifungal Drugs ◽  
Healthcare Associated Infections ◽  
Candida Auris ◽  
High Interest ◽  
The Past ◽  
Recent Emergence ◽  
Echinocandin Resistance ◽  
Healthcare Associated

Candida auris has been reported in the past few years as an invasive fungal pathogen of high interest. Its recent emergence in healthcare-associated infections triggered the efforts of researchers worldwide, seeking additional alternatives to the use of traditional antifungals such as azoles. Lipopeptides, specially the echinocandins, have been reported as an effective approach to control pathogenic fungi. However, despite its efficiency against C. auris, some isolates presented echinocandin resistance. Thus, therapies focused on echinocandins’ synergism with other antifungal drugs were widely explored, representing a novel possibility for the treatment of C. auris infections.

Organic Antifungal Drugs and Targets of Their Action

2021 ◽  
Vol 21 ◽  
Author(s):  
Alexander Yu. Maksimov ◽  
Svetlana Yu. Balandina ◽  
Pavel A. Topanov ◽  
Irina V. Mashevskaya ◽  
Sandeep Chaudhary
Keyword(s):  
Molecular Design ◽  
Fungal Infections ◽  
Wide Spectrum ◽  
Molecular Targets ◽  
Antifungal Drugs ◽  
The Body ◽  
Fungal Diseases ◽  
Fungal Cell ◽  
Genomics And Proteomics

: In recent decades, there has been a significant increase in the number of fungal diseases. This is due to a wide spectrum of action, immunosuppressants and other group drugs. In terms of frequency, rapid spread and globality, fungal infections are approaching acute respiratory infections. Antimycotics are medicinal substances endorsed with fungicidal or fungistatic properties. For the treatment of fungal diseases, several groups of compounds are used that differ in their origin (natural or synthetic), molecular targets and mechanism of action, antifungal effect (fungicidal or fungistatic), indications for use (local or systemic infections), methods of administration (parenteral, oral, outdoor). Several efforts have been made by various medicinal chemists around the world for the development of antifungal drugs with high efficacy with least toxicity and maximum selectivity in the area of antifungal chemotherapy. The pharmacokinetic properties of the new antimycotics are also important: the ability to penetrate biological barriers, be absorbed and distributed in tissues and organs, get accumulated in tissues affected by micromycetes, drug metabolism in the intestinal microflora and human organs, and in the kinetics of excretion from the body. There are several ways to search for new effective antimycotics: - Obtaining new derivatives of the already used classes of antimycotics with improved activity properties. - Screening of new chemical classes of synthetic antimycotic compounds. - Screening of natural compounds. - Identification of new unique molecular targets in the fungal cell. - Development of new compositions and dosage forms with effective delivery vehicles. The methods of informatics, bioinformatics, genomics and proteomics were extensively investigated for the development of new antimycotics. These techniques were employed in finding and identification of new molecular proteins in a fungal cell; in the determination of the selectivity of drug-protein interactions, evaluation of drug-drug interactions and synergism of drugs; determination of the structure-activity relationship (SAR) studies; determination of the molecular design of the most active, selective and safer drugs for the humans, animals and plants. In medical applications, the methods of information analysis and pharmacogenomics allows to take into account the individual phenotype of the patient, the level of expression of the targets of antifungal drugs when choosing antifungal agents and its dosage. This review article incorporates some of the most significant studies covering the basic structures and approaches for the synthesis of antifungal drugs and the directions for their further development.

Docking studies with multiple molecular targets associated with SARSCoV-2 for drug repurposing

Coronaviruses ◽  
2020 ◽  
Vol 01 ◽  
Author(s):  
Shiwani Rana ◽  
Meghali Panwar ◽  
Kalyan Sundar Ghosh
Keyword(s):  
Viral Infections ◽  
Molecular Targets ◽  
Drug Repurposing ◽  
Docking Studies ◽  
New Drugs ◽  
In Silico Screening ◽  
Angiotensin Converting Enzyme 2 ◽  
Viral Proteases ◽  
Free Energy Of Binding ◽  
3Cl Protease

Background: The current pandemic outbreak of COVID-19 due to viral infections by SARS-CoV-2 is now become associated with severe commotion on global healthcare and economy. Objective: In this extreme situation when vaccine or effective new drugs against COVID-19 are not available, the only quick and feasible therapeutic alternative would be the drug repurposing approach. Method: In the present work, in silico screening of some antiviral and antiprotozoal drugs was performed based on docking using Autodock. Results: Two known antiviral drugs sorivudine and noricumazole B are predicted to bind to the active site of the viral proteases namely cysteine like protease or 3CL protease (3CLpro) and papain like protease (PLpro) respectively with a highly favorable free energy of binding. Further, the promising molecules were subjected for checking their activity on other molecular targets in SARS-CoV-2 like spike protein S1, RNA dependent RNA polymerase (RdRp) and angiotensin converting enzyme 2 (ACE2) receptor. But the compounds were found non-effective on rest other molecular targets. Conclusion: Sorivudine alone or a combination of sorivudine and noricumazole B may be administered to impede viral replication though the predicted drug likeliness of noricumazole B is not very much satisfactory. These observations are solely based on the results from blind docking with protein molecules and that need to be further corroborated with experimental results.

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