8 research outputs found

    Combining genetic algorithm with machine learning strategies for designing potent antimicrobial peptides

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    Background Current methods in machine learning provide approaches for solving challenging, multiple constraint design problems. While deep learning and related neural networking methods have state-of-the-art performance, their vulnerability in decision making processes leading to irrational outcomes is a major concern for their implementation. With the rising antibiotic resistance, antimicrobial peptides (AMPs) have increasingly gained attention as novel therapeutic agents. This challenging design problem requires peptides which meet the multiple constraints of limiting drug-resistance in bacteria, preventing secondary infections from imbalanced microbial flora, and avoiding immune system suppression. AMPs offer a promising, bioinspired design space to targeting antimicrobial activity, but their versatility also requires the curated selection from a combinatorial sequence space. This space is too large for brute-force methods or currently known rational design approaches outside of machine learning. While there has been progress in using the design space to more effectively target AMP activity, a widely applicable approach has been elusive. The lack of transparency in machine learning has limited the advancement of scientific knowledge of how AMPs are related among each other, and the lack of general applicability for fully rational approaches has limited a broader understanding of the design space. Methods Here we combined an evolutionary method with rough set theory, a transparent machine learning approach, for designing antimicrobial peptides (AMPs). Our method achieves the customization of AMPs using supervised learning boundaries. Our system employs in vitro bacterial assays to measure fitness, codon-representation of peptides to gain flexibility of sequence selection in DNA-space with a genetic algorithm and machine learning to further accelerate the process. Results We use supervised machine learning and a genetic algorithm to find a peptide active against S. epidermidis, a common bacterial strain for implant infections, with an improved aggregation propensity average for an improved ease of synthesis. Conclusions Our results demonstrate that AMP design can be customized to maintain activity and simplify production. To our knowledge, this is the first time when codon-based genetic algorithms combined with rough set theory methods is used for computational search on peptide sequences

    Mitigation of peri-implantitis by rational design of bifunctional peptides with antimicrobial properties

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    This document is the Accepted Manuscript version of a Published Work that appeared in final form in ACS Biomaterials Science and Engineering, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acsbiomaterials.9b01213.The integration of molecular and cell biology with materials science has led to strategies to improve the interface between dental implants with the surrounding soft and hard tissues in order to replace missing teeth and restore mastication. More than 3 million implants have been placed in the US alone and this number is rising by 500,000/year. Peri-implantitis, an inflammatory response to oral pathogens growing on the implant surface threatens to reduce service life leading to eventual implant failure, and such an outcome will have adverse impact on public health and create significant health care costs. Here we report a predictive approach to peptide design, which enabled us to engineer a bifunctional peptide to combat bacterial colonization and biofilm formation, reducing the adverse host inflammatory immune response that destroys the tissue surrounding implants and shortens their lifespans. This bifunctional peptide contains a titanium-binding domain that recognizes and binds with high affinity to titanium implant surfaces, fused through a rigid spacer domain with an antimicrobial domain. By varying the antimicrobial peptide domain, we were able to predict the properties of the resulting bifunctional peptides in their entirety by analyzing the sequence-structure-function relationship. These bifunctional peptides achieve: 1) nearly 100% surface coverage within minutes, a timeframe suitable for their clinical application to existing implants; 2) nearly 100% binding to a titanium surface even in the presence of contaminating serum protein; 3) durability to brushing with a commercially available electric toothbrush; and 4) retention of antimicrobial activity on the implant surface following bacterial challenge. A bifunctional peptide film can be applied to both new implants and/or repeatedly applied to previously placed implants to control bacterial colonization mitigating peri-implant disease that threatens dental implant longevity

    Repeatedly Applied Peptide Film Kills Bacteria on Dental Implants

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    This is a post-peer-review, pre-copyedit version of an article published in JOM Journal of the Minerals, Metals and Materials Society. The final authenticated version is available online at: http://dx.doi.org/10.1007/s11837-019-03334-w.The rising use of titanium dental implants has increased the prevalence of peri-implant disease that shortens their useful life. A growing view of peri-implant disease suggests that plaque accumulation and microbiome dysbiogenesis trigger a host immune inflammatory response that destroys soft and hard tissues supporting the implant. The incidence of peri-implant disease is difficult to estimate, but with over 3 million implants placed in the USA alone, and the market growing by 500,000 implants/year, such extensive use demands additional interceptive approaches. We report a water-based, nonsurgical approach to address peri-implant disease using a bifunctional peptide film, which can be applied during initial implant placement and later reapplied to existing implants to reduce bacterial growth. Bifunctional peptides are based upon a titanium binding peptide (TiBP) optimally linked by a spacer peptide to an antimicrobial peptide (AMP). We show herein that dental implant surfaces covered with a bifunctional peptide film kill bacteria. Further, using a simple protocol for cleaning implant surfaces fouled by bacteria, the surface can be effectively recoated with TiBP-AMP to regain an antimicrobial state. Fouling, cleansing, and rebinding was confirmed for up to four cycles with minimal loss of binding efficacy. After fouling, rebinding with a water-based peptide film extends control over the oral microbiome composition, providing a novel nonsurgical treatment for dental implants

    Controlling the Biomimetic Implant Interface: Modulating Antimicrobial Activity by Spacer Design

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    Surgical site infection is a common cause of post-operative morbidity, often leading to implant loosening, ultimately requiring revision surgery, increased costs and worse surgical outcomes. Since implant failure starts at the implant surface, creating and controlling the bio-material interface will play a critical role in reducing infection while improving host cell-to-implant interaction. Here, we engineered a biomimetic interface based upon a chimeric peptide that incorporates a titanium binding peptide (TiBP) with an antimicrobial peptide (AMP) into a single molecule to direct binding to the implant surface and deliver an antimicrobial activity against S. mutans and S. epidermidis, two bacteria which are linked with clinical implant infections. To optimize antimicrobial activity, we investigated the design of the spacer domain separating the two functional domains of the chimeric peptide. Lengthening and changing the amino acid composition of the spacer resulted in an improvement of minimum inhibitory concentration by a three-fold against S. mutans. Surfaces coated with the chimeric peptide reduced dramatically the number of bacteria, with up to a nine-fold reduction for S. mutans and a 48-fold reduction for S. epidermidis. Ab initio predictions of antimicrobial activity based on structural features were confirmed. Host cell attachment and viability at the biomimetic interface were also improved compared to the untreated implant surface. Biomimetic interfaces formed with this chimeric peptide offer interminable potential by coupling antimicrobial and improved host cell responses to implantable titanium materials, and this peptide based approach can be extended to various biomaterials surfaces

    Tocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

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    Background: In this study, we aimed to evaluate the effects of tocilizumab in adult patients admitted to hospital with COVID-19 with both hypoxia and systemic inflammation. Methods: This randomised, controlled, open-label, platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing several possible treatments in patients hospitalised with COVID-19 in the UK. Those trial participants with hypoxia (oxygen saturation <92% on air or requiring oxygen therapy) and evidence of systemic inflammation (C-reactive protein ≥75 mg/L) were eligible for random assignment in a 1:1 ratio to usual standard of care alone versus usual standard of care plus tocilizumab at a dose of 400 mg–800 mg (depending on weight) given intravenously. A second dose could be given 12–24 h later if the patient's condition had not improved. The primary outcome was 28-day mortality, assessed in the intention-to-treat population. The trial is registered with ISRCTN (50189673) and ClinicalTrials.gov (NCT04381936). Findings: Between April 23, 2020, and Jan 24, 2021, 4116 adults of 21 550 patients enrolled into the RECOVERY trial were included in the assessment of tocilizumab, including 3385 (82%) patients receiving systemic corticosteroids. Overall, 621 (31%) of the 2022 patients allocated tocilizumab and 729 (35%) of the 2094 patients allocated to usual care died within 28 days (rate ratio 0·85; 95% CI 0·76–0·94; p=0·0028). Consistent results were seen in all prespecified subgroups of patients, including those receiving systemic corticosteroids. Patients allocated to tocilizumab were more likely to be discharged from hospital within 28 days (57% vs 50%; rate ratio 1·22; 1·12–1·33; p<0·0001). Among those not receiving invasive mechanical ventilation at baseline, patients allocated tocilizumab were less likely to reach the composite endpoint of invasive mechanical ventilation or death (35% vs 42%; risk ratio 0·84; 95% CI 0·77–0·92; p<0·0001). Interpretation: In hospitalised COVID-19 patients with hypoxia and systemic inflammation, tocilizumab improved survival and other clinical outcomes. These benefits were seen regardless of the amount of respiratory support and were additional to the benefits of systemic corticosteroids. Funding: UK Research and Innovation (Medical Research Council) and National Institute of Health Research

    Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

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    Background: Many patients with COVID-19 have been treated with plasma containing anti-SARS-CoV-2 antibodies. We aimed to evaluate the safety and efficacy of convalescent plasma therapy in patients admitted to hospital with COVID-19. Methods: This randomised, controlled, open-label, platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]) is assessing several possible treatments in patients hospitalised with COVID-19 in the UK. The trial is underway at 177 NHS hospitals from across the UK. Eligible and consenting patients were randomly assigned (1:1) to receive either usual care alone (usual care group) or usual care plus high-titre convalescent plasma (convalescent plasma group). The primary outcome was 28-day mortality, analysed on an intention-to-treat basis. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936. Findings: Between May 28, 2020, and Jan 15, 2021, 11558 (71%) of 16287 patients enrolled in RECOVERY were eligible to receive convalescent plasma and were assigned to either the convalescent plasma group or the usual care group. There was no significant difference in 28-day mortality between the two groups: 1399 (24%) of 5795 patients in the convalescent plasma group and 1408 (24%) of 5763 patients in the usual care group died within 28 days (rate ratio 1·00, 95% CI 0·93–1·07; p=0·95). The 28-day mortality rate ratio was similar in all prespecified subgroups of patients, including in those patients without detectable SARS-CoV-2 antibodies at randomisation. Allocation to convalescent plasma had no significant effect on the proportion of patients discharged from hospital within 28 days (3832 [66%] patients in the convalescent plasma group vs 3822 [66%] patients in the usual care group; rate ratio 0·99, 95% CI 0·94–1·03; p=0·57). Among those not on invasive mechanical ventilation at randomisation, there was no significant difference in the proportion of patients meeting the composite endpoint of progression to invasive mechanical ventilation or death (1568 [29%] of 5493 patients in the convalescent plasma group vs 1568 [29%] of 5448 patients in the usual care group; rate ratio 0·99, 95% CI 0·93–1·05; p=0·79). Interpretation: In patients hospitalised with COVID-19, high-titre convalescent plasma did not improve survival or other prespecified clinical outcomes. Funding: UK Research and Innovation (Medical Research Council) and National Institute of Health Research

    eIF3d is an mRNA cap-binding protein that is required for specialized translation initiation

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    Eukaryotic mRNAs contain a 5′ cap structure that is crucial for recruitment of the translation machinery and initiation of protein synthesis. mRNA recognition is thought to require direct interactions between eukaryotic initiation factor 4E (eIF4E) and the mRNA cap. However, translation of numerous capped mRNAs remains robust during cellular stress, early development, and cell cycle progression despite inactivation of eIF4E. Here we describe a cap-dependent pathway of translation initiation in human cells that relies on a previously unknown cap-binding activity of eIF3d, a subunit of the 800-kilodalton eIF3 complex. A 1.4 Å crystal structure of the eIF3d cap-binding domain reveals unexpected homology to endonucleases involved in RNA turnover, and allows modelling of cap recognition by eIF3d. eIF3d makes specific contacts with the cap, as exemplified by cap analogue competition, and these interactions are essential for assembly of translation initiation complexes on eIF3-specialized mRNAs such as the cell proliferation regulator c-Jun (also known as JUN). The c-Jun mRNA further encodes an inhibitory RNA element that blocks eIF4E recruitment, thus enforcing alternative cap recognition by eIF3d. Our results reveal a mechanism of cap-dependent translation that is independent of eIF4E, and illustrate how modular RNA elements work together to direct specialized forms of translation initiation
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