Publications by authors named "Fergal J Duffy"

16 Publications

  • Page 1 of 1

A contained Mycobacterium tuberculosis mouse infection model predicts active disease and containment in humans.

J Infect Dis 2021 Mar 10. Epub 2021 Mar 10.

Seattle Children's Research Institute, Seattle, WA, USA.

Previous studies have identified whole-blood transcriptional risk and disease signatures for Tuberculosis (TB); however, several lines of evidence suggest that these signatures primarily reflect bacterial burden, which increases prior to symptomatic disease. We found that the peripheral blood transcriptome of mice with contained Mycobacterium tuberculosis infection (CMTB) has striking similarities to that of humans with active TB and that a signature derived from these mice predicts human disease with comparable accuracy to signatures derived directly from humans. A set of genes associated with immune defense are upregulated in CMTB mice but not in humans with active TB suggesting that their upregulation is associated with bacterial containment. A signature comprised of these genes predicts both protection from TB disease and successful treatment at early time points where current signatures are not predictive. These results suggest that detailed study of the CMTB mouse model may enable identification of biomarkers for human TB.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/infdis/jiab130DOI Listing
March 2021

The Peripheral Blood Transcriptome Is Correlated With PET Measures of Lung Inflammation During Successful Tuberculosis Treatment.

Front Immunol 2020 10;11:596173. Epub 2021 Feb 10.

Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa.

Pulmonary tuberculosis (PTB) is characterized by lung granulomas, inflammation and tissue destruction. Here we used within-subject peripheral blood gene expression over time to correlate with the within-subject lung metabolic activity, as measured by positron emission tomography (PET) to identify biological processes and pathways underlying overall resolution of lung inflammation. We used next-generation RNA sequencing and [F]FDG PET-CT data, collected at diagnosis, week 4, and week 24, from 75 successfully cured PTB patients, with the [F]FDG activity as a surrogate for lung inflammation. Our linear mixed-effects models required that for each individual the slope of the line of [F]FDG data in the outcome and the slope of the peripheral blood transcript expression data correlate, i.e., the slopes of the outcome and explanatory variables had to be similar. Of 10,295 genes that changed as a function of time, we identified 639 genes whose expression profiles correlated with decreasing [F]FDG uptake levels in the lungs. Gene enrichment over-representation analysis revealed that numerous biological processes were significantly enriched in the 639 genes, including several well known in TB transcriptomics such as platelet degranulation and response to interferon gamma, thus validating our novel approach. Others not previously associated with TB pathobiology included smooth muscle contraction, a set of pathways related to mitochondrial function and cell death, as well as a set of pathways connecting transcription, translation and vesicle formation. We observed up-regulation in genes associated with B cells, and down-regulation in genes associated with platelet activation. We found 254 transcription factor binding sites to be enriched among the 639 gene promoters. In conclusion, we demonstrated that of the 10,295 gene expression changes in peripheral blood, only a subset of 639 genes correlated with inflammation in the lungs, and the enriched pathways provide a description of the biology of resolution of lung inflammation as detectable in peripheral blood. Surprisingly, resolution of PTB inflammation is positively correlated with smooth muscle contraction and, extending our previous observation on mitochondrial genes, shows the presence of mitochondrial stress. We focused on pathway analysis which can enable therapeutic target discovery and potential modulation of the host response to TB.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fimmu.2020.596173DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7902901PMC
February 2021

Ultra-low Dose Aerosol Infection of Mice with Mycobacterium tuberculosis More Closely Models Human Tuberculosis.

Cell Host Microbe 2021 01 2;29(1):68-82.e5. Epub 2020 Nov 2.

Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, WA 98109, USA; Department of Pediatrics, University of Washington, Seattle, WA 98109, USA; Department of Immunology, University of Washington, Seattle, WA 98109, USA. Electronic address:

Tuberculosis (TB) is a heterogeneous disease manifesting in a subset of individuals infected with aerosolized Mycobacterium tuberculosis (Mtb). Unlike human TB, murine infection results in uniformly high lung bacterial burdens and poorly organized granulomas. To develop a TB model that more closely resembles human disease, we infected mice with an ultra-low dose (ULD) of between 1-3 founding bacteria, reflecting a physiologic inoculum. ULD-infected mice exhibited highly heterogeneous bacterial burdens, well-circumscribed granulomas that shared features with human granulomas, and prolonged Mtb containment with unilateral pulmonary infection in some mice. We identified blood RNA signatures in mice infected with an ULD or a conventional Mtb dose (50-100 CFU) that correlated with lung bacterial burdens and predicted Mtb infection outcomes across species, including risk of progression to active TB in humans. Overall, these findings highlight the potential of the murine TB model and show that ULD infection recapitulates key features of human TB.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.chom.2020.10.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7854984PMC
January 2021

Contained Mycobacterium tuberculosis infection induces concomitant and heterologous protection.

PLoS Pathog 2020 07 16;16(7):e1008655. Epub 2020 Jul 16.

Seattle Children's Research Institute, Seattle, Washington, United States of America.

Progress in tuberculosis vaccine development is hampered by an incomplete understanding of the immune mechanisms that protect against infection with Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis. Although the M72/ASOE1 trial yielded encouraging results (54% efficacy in subjects with prior exposure to Mtb), a highly effective vaccine against adult tuberculosis remains elusive. We show that in a mouse model, establishment of a contained and persistent yet non-pathogenic infection with Mtb ("contained Mtb infection", CMTB) rapidly and durably reduces tuberculosis disease burden after re-exposure through aerosol challenge. Protection is associated with elevated activation of alveolar macrophages, the first cells that respond to inhaled Mtb, and accelerated recruitment of Mtb-specific T cells to the lung parenchyma. Systems approaches, as well as ex vivo functional assays and in vivo infection experiments, demonstrate that CMTB reconfigures tissue resident alveolar macrophages via low grade interferon-γ exposure. These studies demonstrate that under certain circumstances, the continuous interaction of the immune system with Mtb is beneficial to the host by maintaining elevated innate immune responses.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1371/journal.ppat.1008655DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7365393PMC
July 2020

Multinomial modelling of TB/HIV co-infection yields a robust predictive signature and generates hypotheses about the HIV+TB+ disease state.

PLoS One 2019 15;14(7):e0219322. Epub 2019 Jul 15.

Center for Infectious Disease Research (formerly Seattle Biomedical Research Institute), Seattle, WA, United States of America.

Background: Current diagnostics are inadequate to meet the challenges presented by co-infection with Mycobacterium tuberculosis (Mtb) and HIV, the leading cause of death for HIV-infected individuals. Improved characterization of Mtb/HIV coinfection as a distinct disease state may lead to better identification and treatment of affected individuals.

Methods: Four previously-published TB and HIV co-infection related datasets were used to train and validate multinomial machine learning classifiers that simultaneously predict TB and HIV status. Classifier predictive performance was measured using leave-one-out cross validation on the training set and blind predictive performance on multiple test sets using area under the ROC curve (AUC) as the performance metric. Linear modelling of signature gene expression was applied to systematically classify genes as TB-only, HIV-only or combined TB/HIV.

Results: The optimal signature discovered was a 10-gene random forest multinomial signature that robustly discriminated active tuberculosis (TB) from other non-TB disease states with improved performance compared with previously published signatures (AUC: 0.87), and specifically discriminated active TB/HIV co-infection from all other conditions (AUC: 0.88). Signature genes exhibited a variety of transcriptional patterns including both TB-only and HIV-only response genes and genes with expression patterns driven by interactions between HIV and TB infection states, including the CD8+ T-cell receptor LAG3 and the apoptosis-related gene CERKL.

Conclusions: By explicitly including distinct disease states within the machine learning analysis framework, we developed a compact and highly diagnostic signature that simultaneously discriminates multiple disease states associated with Mtb/HIV co-infection. Examination of the expression patterns of signature genes suggests mechanisms underlying the unique inflammatory conditions associated with active TB in the presence of HIV. In particular, we observed that dysregulation of CD8+ effector T-cell and NK-cell associated genes may be an important feature of Mtb/HIV co-infection.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0219322PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6629068PMC
March 2020

Detection of Tuberculosis Recurrence, Diagnosis and Treatment Response by a Blood Transcriptomic Risk Signature in HIV-Infected Persons on Antiretroviral Therapy.

Front Microbiol 2019 26;10:1441. Epub 2019 Jun 26.

South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology and Department of Pathology, University of Cape Town, Cape Town, South Africa.

HIV-infected individuals are at high risk of tuberculosis disease and those with prior tuberculosis episodes are at even higher risk of disease recurrence. A non-sputum biomarker that identifies individuals at highest tuberculosis risk would allow targeted microbiological testing and appropriate treatment and also guide need for prolonged therapy. We determined the utility of a previously developed whole blood transcriptomic correlate of risk (COR) signature for (1) predicting incident recurrent tuberculosis, (2) tuberculosis diagnosis and (3) its potential utility for tuberculosis treatment monitoring in HIV-infected individuals. We retrieved cryopreserved blood specimens from three previously completed clinical studies and measured the COR signature by quantitative microfluidic real-time-PCR. The signature differentiated recurrent tuberculosis progressors from non-progressors within 3 months of diagnosis with an area under the Receiver-operating characteristic (ROC) curve (AUC) of 0.72 (95% confidence interval (CI), 0.58-0.85) amongst HIV-infected individuals on antiretroviral therapy (ART). Twenty-five of 43 progressors (58%) were asymptomatic at microbiological diagnosis and thus had subclinical disease. The signature showed excellent diagnostic discrimination between HIV-uninfected tuberculosis cases and controls (AUC 0.97; 95%CI 0.94-1). Performance was lower in HIV-infected individuals (AUC 0.83; 95%CI 0.81-0.96) and signature scores were directly associated with HIV viral loads. Tuberculosis treatment response in HIV-infected individuals on ART with a new recurrent tuberculosis diagnosis was also assessed. Signature scores decreased significantly during treatment. However, pre-treatment scores could not differentiate between those who became sputum negative before and after 2 months. Direct application of the unmodified blood transcriptomic COR signature detected subclinical and active tuberculosis by blind validation in HIV-infected individuals. However, prognostic performance for recurrent tuberculosis, and performance as diagnostic and as treatment monitoring tool in HIV-infected persons was inferior to published results from HIV-negative cohorts. Our results suggest that performance of transcriptomic signatures comprising interferon stimulated genes are negatively affected in HIV-infected individuals, especially in those with incompletely suppressed viral loads.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fmicb.2019.01441DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6608601PMC
June 2019

Immunometabolic Signatures Predict Risk of Progression to Active Tuberculosis and Disease Outcome.

Front Immunol 2019 22;10:527. Epub 2019 Mar 22.

Center for Infectious Disease Research, Seattle, WA, United States.

There remains a pressing need for biomarkers that can predict who will progress to active tuberculosis (TB) after exposure to Mycobacterium tuberculosis (MTB) bacterium. By analyzing cohorts of household contacts of TB index cases (HHCs) and a stringent non-human primate (NHP) challenge model, we evaluated whether integration of blood transcriptional profiling with serum metabolomic profiling can provide new understanding of disease processes and enable improved prediction of TB progression. Compared to either alone, the combined application of pre-existing transcriptome- and metabolome-based signatures more accurately predicted TB progression in the HHC cohorts and more accurately predicted disease severity in the NHPs. Pathway and data-driven correlation analyses of the integrated transcriptional and metabolomic datasets further identified novel immunometabolomic signatures significantly associated with TB progression in HHCs and NHPs, implicating cortisol, tryptophan, glutathione, and tRNA acylation networks. These results demonstrate the power of multi-omics analysis to provide new insights into complex disease processes.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fimmu.2019.00527DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6440524PMC
August 2020

Metabolite changes in blood predict the onset of tuberculosis.

Nat Commun 2018 12 6;9(1):5208. Epub 2018 Dec 6.

Max Planck Institute for Infection Biology, 10117, Berlin, Germany.

New biomarkers of tuberculosis (TB) risk and disease are critical for the urgently needed control of the ongoing TB pandemic. In a prospective multisite study across Subsaharan Africa, we analyzed metabolic profiles in serum and plasma from HIV-negative, TB-exposed individuals who either progressed to TB 3-24 months post-exposure (progressors) or remained healthy (controls). We generated a trans-African metabolic biosignature for TB, which identifies future progressors both on blinded test samples and in external data sets and shows a performance of 69% sensitivity at 75% specificity in samples within 5 months of diagnosis. These prognostic metabolic signatures are consistent with development of subclinical disease prior to manifestation of active TB. Metabolic changes associated with pre-symptomatic disease are observed as early as 12 months prior to TB diagnosis, thus enabling timely interventions to prevent disease progression and transmission.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-018-07635-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6283869PMC
December 2018

A Serum Circulating miRNA Signature for Short-Term Risk of Progression to Active Tuberculosis Among Household Contacts.

Front Immunol 2018 13;9:661. Epub 2018 Apr 13.

DST/NRF Centre of Excellence for Biomedical TB Research and MRC Centre for TB Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa.

Biomarkers that predict who among recently (MTB)-exposed individuals will progress to active tuberculosis are urgently needed. Intracellular microRNAs (miRNAs) regulate the host response to MTB and circulating miRNAs (c-miRNAs) have been developed as biomarkers for other diseases. We performed machine-learning analysis of c-miRNA measurements in the serum of adult household contacts (HHCs) of TB index cases from South Africa and Uganda and developed a c-miRNA-based signature of risk for progression to active TB. This c-miRNA-based signature significantly discriminated HHCs within 6 months of progression to active disease from HHCs that remained healthy in an independent test set [ROC area under the ROC curve (AUC) 0.74, progressors < 6 Mo to active TB and ROC AUC 0.66, up to 24 Mo to active TB], and complements the predictions of a previous cellular mRNA-based signature of TB risk.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3389/fimmu.2018.00661DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5908968PMC
June 2019

Four-Gene Pan-African Blood Signature Predicts Progression to Tuberculosis.

Am J Respir Crit Care Med 2018 May;197(9):1198-1208

South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and.

Contacts of patients with tuberculosis (TB) constitute an important target population for preventive measures because they are at high risk of infection with and progression to disease. We investigated biosignatures with predictive ability for incident TB. In a case-control study nested within the Grand Challenges 6-74 longitudinal HIV-negative African cohort of exposed household contacts, we employed RNA sequencing, PCR, and the pair ratio algorithm in a training/test set approach. Overall, 79 progressors who developed TB between 3 and 24 months after diagnosis of index case and 328 matched nonprogressors who remained healthy during 24 months of follow-up were investigated. A four-transcript signature derived from samples in a South African and Gambian training set predicted progression up to two years before onset of disease in blinded test set samples from South Africa, the Gambia, and Ethiopia with little population-associated variability, and it was also validated in an external cohort of South African adolescents with latent infection. By contrast, published diagnostic or prognostic TB signatures were predicted in samples from some but not all three countries, indicating site-specific variability. meta-analysis identified a single gene pair, / (complement C1q C-chain / T-cell receptor-α variable gene 27) that would consistently predict TB progression in household contacts from multiple African sites but not in infected adolescents without known recent exposure events. Collectively, we developed a simple whole blood-based PCR test to predict TB in recently exposed household contacts from diverse African populations. This test has potential for implementation in national TB contact investigation programs.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1164/rccm.201711-2340OCDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6019933PMC
May 2018

GlycoProfileAssigner: automated structural assignment with error estimation for glycan LC data.

Bioinformatics 2015 Jul 26;31(13):2220-1. Epub 2015 Feb 26.

National Institute for Bioprocessing Research and Training, Fosters Avenue, Mount Merrion, Co. Dublin, Ireland.

Motivation: Sequencing glycan structures is a difficult problem that requires the use of multiple experimental approaches. One powerful approach to glycan sequencing is the combination of liquid chromatography with sequential exoglycosidase digestions; however, interpreting this can be difficult and time-consuming. To aid this process, we introduce GlycoProfileAssigner, software for automated structural assignment of glycan profile data from liquid chromatography experiments.

Results: GlycoProfileAssigner has been tested on human IgG data, and can retrieve the correct structure in 14 out of 16 peaks tested.

Availability And Implementation: The programme and its source code is available at https://bitbucket.org/fergaljd/glycoprofileassigner

Contact: : [email protected]

Supplementary Information: Supplementary data are available at Bioinformatics online.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/bioinformatics/btv129DOI Listing
July 2015

Virtual screening using combinatorial cyclic peptide libraries reveals protein interfaces readily targetable by cyclic peptides.

J Chem Inf Model 2015 Mar 20;55(3):600-13. Epub 2015 Feb 20.

†School of Medicine and Medical Science, ‡Complex and Adaptive Systems Laboratory, ¶Conway Institute of Biomolecular and Biomedical Research, and §School of Biomolecular and Biomedical Science, University College Dublin, Dublin 4, Ireland, and.

Protein-protein and protein-peptide interactions are responsible for the vast majority of biological functions in vivo, but targeting these interactions with small molecules has historically been difficult. What is required are efficient combined computational and experimental screening methods to choose among a number of potential protein interfaces worthy of targeting lead macrocyclic compounds for further investigation. To achieve this, we have generated combinatorial 3D virtual libraries of short disulfide-bonded peptides and compared them to pharmacophore models of important protein-protein and protein-peptide structures, including short linear motifs (SLiMs), protein-binding peptides, and turn structures at protein-protein interfaces, built from 3D models available in the Protein Data Bank. We prepared a total of 372 reference pharmacophores, which were matched against 108,659 multiconformer cyclic peptides. After normalization to exclude nonspecific cyclic peptides, the top hits notably are enriched for mimetics of turn structures, including a turn at the interaction surface of human α thrombin, and also feature several protein-binding peptides. The top cyclic peptide hits also cover the critical "hot spot" interaction sites predicted from the interaction crystal structure. We have validated our method by testing cyclic peptides predicted to inhibit thrombin, a key protein in the blood coagulation pathway of important therapeutic interest, identifying a cyclic peptide inhibitor with lead-like activity. We conclude that protein interfaces most readily targetable by cyclic peptides and related macrocyclic drugs may be identified computationally among a set of candidate interfaces, accelerating the choice of interfaces against which lead compounds may be screened.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1021/ci500431qDOI Listing
March 2015

Computational approaches to developing short cyclic peptide modulators of protein-protein interactions.

Methods Mol Biol 2015 ;1268:241-71

School of Medicine and Medical Science, University College Dublin, Belfield, Dublin 4, Ireland.

Cyclic peptides are a promising class of bioactive molecules potentially capable of modulating "difficult" targets, such as protein-protein interactions. Cyclic peptides have long been used as therapeutics derived from natural product derivatives, but remain an underexplored class of compounds from the perspective of rational drug design, possibly due to the known weaknesses of peptide drugs in general. While cyclic peptides are non"druglike" by the accepted empirical rules, their unique structure may lend itself to both membrane permeability and proteolytic resistance-the main barriers to oral delivery. The constrained shape of cyclic peptides also lends itself better to virtual screening approaches, and new tools and successes in this area have been recently noted. An increasing number of strategies are available, both to generate and screen cyclic peptide libraries, and best practises and current successes are described within. This chapter will describe various computational strategies for virtual screening cyclic peptides, along with known implementations and applications. We will explore the generation and screening of diverse combinatorial virtual libraries, incorporating a range of cyclization strategies and structural modifications. More advanced approaches covered include evolutionary algorithms designed to aid in screening large structural libraries, machine learning approaches, and harnessing bioinformatics resources to bias cyclic peptide virtual libraries towards known bioactive structures.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/978-1-4939-2285-7_11DOI Listing
August 2015

Computational survey of peptides derived from disulphide-bonded protein loops that may serve as mediators of protein-protein interactions.

BMC Bioinformatics 2014 Sep 17;15:305. Epub 2014 Sep 17.

School of Medicine and Medical Science, University College Dublin, Belfield, Dublin 4, Ireland.

Background: Bioactive cyclic peptides derived from natural sources are well studied, particularly those derived from non-ribosomal synthetases in fungi or bacteria. Ribosomally synthesised bioactive disulphide-bonded loops represent a large, naturally enriched library of potential bioactive compounds, worthy of systematic investigation.

Results: We examined the distribution of short cyclic loops on the surface of a large number of proteins, especially membrane or extracellular proteins. Available three-dimensional structures highlighted a number of disulphide-bonded loops responsible for the majority of the likely binding interactions in a variety of protein complexes, due to their location at protein-protein interfaces. We find that disulphide-bonded loops at protein-protein interfaces may, but do not necessarily, show biological activity independent of their parent protein. Examining the conservation of short disulphide bonded loops in proteins, we find a small but significant increase in conservation inside these loops compared to surrounding residues. We identify a subset of these loops that exhibit a high relative conservation, particularly among peptide hormones.

Conclusions: We conclude that short disulphide-bonded loops are found in a wide variety of biological interactions. They may retain biological activity outside their parent proteins. Such structurally independent peptides may be useful as biologically active templates for the development of novel modulators of protein-protein interactions.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/1471-2105-15-305DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4262234PMC
September 2014

TIN-a combinatorial compound collection of synthetically feasible multicomponent synthesis products.

J Chem Inf Model 2011 May 15;51(5):986-95. Epub 2011 Apr 15.

Molecular and Cellular Therapeutics Department, Royal College of Surgeons in Ireland , 123 St. Stephen's Green, Dublin 2, Ireland.

The synthetic feasibility of any compound library used for virtual screening is critical to the drug discovery process. TIN, a recursive acronym for 'TIN Is Not commercial', is a virtual combinatorial database enumeration of diversity-orientated multicomponent syntheses (MCR). Using a 'one-pot' synthetic technique, 12 unique small molecule scaffolds were developed, predominantly styrylisoxazoles and bis-acetylenic ketones, with extensive derivatization potential. Importantly, the scaffolds were accessible in a single operation from commercially available sources containing R-groups which were then linked combinatorially. This resulted in a combinatorial database of over 28 million product structures, each of which is synthetically feasible. These structures can be accessed through a free Web-based 2D structure search engine or downloaded in SMILES, MOL2, and SDF formats. Subsets include a 10% diversity subset, a drug-like subset, and a lead-like subset that are also freely available for download and virtual screening ( http://mmg.rcsi.ie:8080/tin ).
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1021/ci100443xDOI Listing
May 2011

CycloPs: generating virtual libraries of cyclized and constrained peptides including nonnatural amino acids.

J Chem Inf Model 2011 Apr 24;51(4):829-36. Epub 2011 Mar 24.

UCD Complex and Applied Systems Laboratory, Conway Institute of Biomolecular and Biomedical Sciences, and School of Medicine and Medical Sciences, University College Dublin, Belfield, Dublin 4, Ireland.

We introduce CycloPs, software for the generation of virtual libraries of constrained peptides including natural and nonnatural commercially available amino acids. The software is written in the cross-platform Python programming language, and features include generating virtual libraries in one-dimensional SMILES and three-dimensional SDF formats, suitable for virtual screening. The stand-alone software is capable of filtering the virtual libraries using empirical measurements, including peptide synthesizability by standard peptide synthesis techniques, stability, and the druglike properties of the peptide. The software and accompanying Web interface is designed to enable the rapid generation of large, structurally diverse, synthesizable virtual libraries of constrained peptides quickly and conveniently, for use in virtual screening experiments. The stand-alone software, and the Web interface for evaluating these empirical properties of a single peptide, are available at http://bioware.ucd.ie .
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1021/ci100431rDOI Listing
April 2011