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  1. Article: Barley in the Production of Cereal-Based Products.

    Lukinac, Jasmina / Jukić, Marko

    Plants (Basel, Switzerland)

    2022  Volume 11, Issue 24

    Abstract: Barley ( ...

    Abstract Barley (
    Language English
    Publishing date 2022-12-14
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2704341-1
    ISSN 2223-7747
    ISSN 2223-7747
    DOI 10.3390/plants11243519
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Machine Learning in Antibacterial Drug Design.

    Jukič, Marko / Bren, Urban

    Frontiers in pharmacology

    2022  Volume 13, Page(s) 864412

    Abstract: Advances in computer hardware and the availability of high-performance supercomputing platforms and parallel computing, along with artificial intelligence methods are successfully complementing traditional approaches in medicinal chemistry. In particular, ...

    Abstract Advances in computer hardware and the availability of high-performance supercomputing platforms and parallel computing, along with artificial intelligence methods are successfully complementing traditional approaches in medicinal chemistry. In particular, machine learning is gaining importance with the growth of the available data collections. One of the critical areas where this methodology can be successfully applied is in the development of new antibacterial agents. The latter is essential because of the high attrition rates in new drug discovery, both in industry and in academic research programs. Scientific involvement in this area is even more urgent as antibacterial drug resistance becomes a public health concern worldwide and pushes us increasingly into the post-antibiotic era. In this review, we focus on the latest machine learning approaches used in the discovery of new antibacterial agents and targets, covering both small molecules and antibacterial peptides. For the benefit of the reader, we summarize all applied machine learning approaches and available databases useful for the design of new antibacterial agents and address the current shortcomings.
    Language English
    Publishing date 2022-05-03
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2587355-6
    ISSN 1663-9812
    ISSN 1663-9812
    DOI 10.3389/fphar.2022.864412
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Identifying Metal Binding Sites in Proteins Using Homologous Structures, the MADE Approach.

    Ravnik, Vid / Jukič, Marko / Bren, Urban

    Journal of chemical information and modeling

    2023  Volume 63, Issue 16, Page(s) 5204–5219

    Abstract: In order to identify the locations of metal ions in the binding sites of proteins, we have developed a method named the MADE (MAcromolecular DEnsity and Structure Analysis) approach. The MADE approach represents an evolution of our previous toolset, the ... ...

    Abstract In order to identify the locations of metal ions in the binding sites of proteins, we have developed a method named the MADE (MAcromolecular DEnsity and Structure Analysis) approach. The MADE approach represents an evolution of our previous toolset, the ProBiS H
    MeSH term(s) Protein Conformation ; Proteins/chemistry ; Binding Sites ; Water ; Ions ; Software
    Chemical Substances Proteins ; Water (059QF0KO0R) ; Ions
    Language English
    Publishing date 2023-08-09
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 190019-5
    ISSN 1549-960X ; 0095-2338
    ISSN (online) 1549-960X
    ISSN 0095-2338
    DOI 10.1021/acs.jcim.3c00558
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1230: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  4. Article: Mechanistic Insights of Polyphenolic Compounds from Rosemary Bound to Their Protein Targets Obtained by Molecular Dynamics Simulations and Free-Energy Calculations.

    Lešnik, Samo / Jukič, Marko / Bren, Urban

    Foods (Basel, Switzerland)

    2023  Volume 12, Issue 2

    Abstract: Rosemary represents an important medicinal plant that has been attributed with various health-promoting properties, especially antioxidative, anti-inflammatory, and anticarcinogenic activities. Carnosic acid, carnosol, and rosmanol, as well as the ... ...

    Abstract Rosemary represents an important medicinal plant that has been attributed with various health-promoting properties, especially antioxidative, anti-inflammatory, and anticarcinogenic activities. Carnosic acid, carnosol, and rosmanol, as well as the phenolic acid ester rosmarinic acid, are the main compounds responsible for these actions. In our earlier research, we carried out an inverse molecular docking at the proteome scale to determine possible protein targets of the mentioned compounds. Here, we subjected the previously identified ligand-protein complexes with HIV-1 protease, K-RAS, and factor X to molecular dynamics simulations coupled with free-energy calculations. We observed that carnosic acid and rosmanol act as viable binders of the HIV-1 protease. In addition, carnosol represents a potential binder of the oncogene protein K-RAS. On the other hand, rosmarinic acid was characterized as a weak binder of factor X. We also emphasized the importance of water-mediated hydrogen-bond networks in stabilizing the binding conformation of the studied polyphenols, as well as in mechanistically explaining their promiscuous nature.
    Language English
    Publishing date 2023-01-14
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2704223-6
    ISSN 2304-8158
    ISSN 2304-8158
    DOI 10.3390/foods12020408
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article: Design of Tetra-Peptide Ligands of Antibody Fc Regions Using In Silico Combinatorial Library Screening.

    Jukič, Marko / Kralj, Sebastjan / Kolarič, Anja / Bren, Urban

    Pharmaceuticals (Basel, Switzerland)

    2023  Volume 16, Issue 8

    Abstract: Peptides, or short chains of amino-acid residues, are becoming increasingly important as active ingredients of drugs and as crucial probes and/or tools in medical, biotechnological, and pharmaceutical research. Situated at the interface between small ... ...

    Abstract Peptides, or short chains of amino-acid residues, are becoming increasingly important as active ingredients of drugs and as crucial probes and/or tools in medical, biotechnological, and pharmaceutical research. Situated at the interface between small molecules and larger macromolecular systems, they pose a difficult challenge for computational methods. We report an in silico peptide library generation and prioritization workflow using CmDock for identifying tetrapeptide ligands that bind to Fc regions of antibodies that is analogous to known in vitro recombinant peptide libraries' display and expression systems. The results of our in silico study are in accordance with existing scientific literature on in vitro peptides that bind to antibody Fc regions. In addition, we postulate an evolving in silico library design workflow that will help circumvent the combinatorial problem of in vitro comprehensive peptide libraries by focusing on peptide subunits that exhibit favorable interaction profiles in initial in silico peptide generation and testing.
    Language English
    Publishing date 2023-08-17
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2193542-7
    ISSN 1424-8247
    ISSN 1424-8247
    DOI 10.3390/ph16081170
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Naive Prediction of Protein Backbone Phi and Psi Dihedral Angles Using Deep Learning.

    Broz, Matic / Jukič, Marko / Bren, Urban

    Molecules (Basel, Switzerland)

    2023  Volume 28, Issue 20

    Abstract: Protein structure prediction represents a significant challenge in the field of bioinformatics, with the prediction of protein structures using backbone dihedral angles recently achieving significant progress due to the rise of deep neural network ... ...

    Abstract Protein structure prediction represents a significant challenge in the field of bioinformatics, with the prediction of protein structures using backbone dihedral angles recently achieving significant progress due to the rise of deep neural network research. However, there is a trend in protein structure prediction research to employ increasingly complex neural networks and contributions from multiple models. This study, on the other hand, explores how a single model transparently behaves using sequence data only and what can be expected from the predicted angles. To this end, the current paper presents data acquisition, deep learning model definition, and training toward the final protein backbone angle prediction. The method applies a simple fully connected neural network (FCNN) model that takes only the primary structure of the protein with a sliding window of size 21 as input to predict protein backbone ϕ and ψ dihedral angles. Despite its simplicity, the model shows surprising accuracy for the ϕ angle prediction and somewhat lower accuracy for the ψ angle prediction. Moreover, this study demonstrates that protein secondary structure prediction is also possible with simple neural networks that take in only the protein amino-acid residue sequence, but more complex models are required for higher accuracies.
    MeSH term(s) Deep Learning ; Proteins/chemistry ; Amino Acid Sequence ; Neural Networks, Computer ; Protein Structure, Secondary
    Chemical Substances Proteins
    Language English
    Publishing date 2023-10-12
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 1413402-0
    ISSN 1420-3049 ; 1431-5165 ; 1420-3049
    ISSN (online) 1420-3049
    ISSN 1431-5165 ; 1420-3049
    DOI 10.3390/molecules28207046
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.MO 81: Show issues

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  7. Article: Long-Term Consequences of War Captivity in Military Veterans.

    Jukić, Melita / Malenica, Luka / Đuričić, Vanja / Talapko, Jasminka / Lukinac, Jasmina / Jukić, Marko / Škrlec, Ivana

    Healthcare (Basel, Switzerland)

    2023  Volume 11, Issue 14

    Abstract: Numerous studies on the health and functioning of veterans and former prisoners of war have shown that the experience of war captivity is one of the most difficult human experiences. Captivity is often characterized by extremely difficult and inhumane ... ...

    Abstract Numerous studies on the health and functioning of veterans and former prisoners of war have shown that the experience of war captivity is one of the most difficult human experiences. Captivity is often characterized by extremely difficult and inhumane conditions, as well as exposure to various forms of both psychological and physical abuse. Such traumatic experiences can lead to serious psychological consequences that can last for years, even decades after release from captivity. The aim of this paper is to present a brief overview of research that points to the specifics of wartime captivity and the long-term psychological consequences in veterans of former camp detainees, as well as the consequences suffered by their families and factors that, apart from the intensity of the trauma, contribute to the emergence and persistence of psychological disorders. From the presented research, it can be concluded that former prisoners of the camp represent an extremely vulnerable group of the social community and require long-term appropriate treatment, while the needs of veterans' families should not be neglected, with the necessity of including spouses and children in psychological and psychosocial treatments.
    Language English
    Publishing date 2023-07-10
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2721009-1
    ISSN 2227-9032
    ISSN 2227-9032
    DOI 10.3390/healthcare11141993
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Molecular Filters in Medicinal Chemistry

    Sebastjan Kralj / Marko Jukič / Urban Bren

    Encyclopedia, Vol 3, Iss 35, Pp 501-

    2023  Volume 511

    Abstract: Efficient chemical library design for high-throughput virtual screening and drug design requires a pre-screening filter pipeline capable of labeling aggregators, pan-assay interference compounds (PAINS), and rapid elimination of swill (REOS); identifying ...

    Abstract Efficient chemical library design for high-throughput virtual screening and drug design requires a pre-screening filter pipeline capable of labeling aggregators, pan-assay interference compounds (PAINS), and rapid elimination of swill (REOS); identifying or excluding covalent binders; flagging moieties with specific bio-evaluation data; and incorporating physicochemical and pharmacokinetic properties early in the design without compromising the diversity of chemical moieties present in the library. This adaptation of the chemical space results in greater enrichment of hit lists, identified compounds with greater potential for further optimization, and efficient use of computational time. A number of medicinal chemistry filters have been implemented in the Konstanz Information Miner (KNIME) software and analyzed their impact on testing representative libraries with chemoinformatic analysis. It was found that the analyzed filters can effectively tailor chemical libraries to a lead-like chemical space, identify protein–protein inhibitor-like compounds, prioritize oral bioavailability, identify drug-like compounds, and effectively label unwanted scaffolds or functional groups. However, one should be cautious in their application and carefully study the chemical space suitable for the target and general medicinal chemistry campaign, and review passed and labeled compounds before taking further in silico steps.
    Keywords medicinal chemistry ; filtering chemical libraries ; chemical space ; HTVS ; virtual screening ; computer aided drug-design ; Science ; Q
    Subject code 540
    Language English
    Publishing date 2023-04-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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  9. Article: Novel Small-Molecule Inhibitors of the SARS-CoV-2 Spike Protein Binding to Neuropilin 1.

    Kolarič, Anja / Jukič, Marko / Bren, Urban

    Pharmaceuticals (Basel, Switzerland)

    2022  Volume 15, Issue 2

    Abstract: Furin cleavage of the SARS-CoV-2 spike protein results in a polybasic terminal sequence termed the C-end rule (CendR), which is responsible for the binding to neuropilin 1 (NRP1), enhancing viral infectivity and entry into the cell. Here we report the ... ...

    Abstract Furin cleavage of the SARS-CoV-2 spike protein results in a polybasic terminal sequence termed the C-end rule (CendR), which is responsible for the binding to neuropilin 1 (NRP1), enhancing viral infectivity and entry into the cell. Here we report the identification of 20 small-molecule inhibitors that emerged from a virtual screening of nearly 950,000 drug-like compounds that bind with high probability to the CendR-binding pocket of NRP1. In a spike NRP1 binding assay, two of these compounds displayed a stronger inhibition of spike protein binding to NRP1 than the known NRP1 antagonist
    Language English
    Publishing date 2022-01-28
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2193542-7
    ISSN 1424-8247
    ISSN 1424-8247
    DOI 10.3390/ph15020165
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Comparative Analyses of Medicinal Chemistry and Cheminformatics Filters with Accessible Implementation in Konstanz Information Miner (KNIME).

    Kralj, Sebastjan / Jukič, Marko / Bren, Urban

    International journal of molecular sciences

    2022  Volume 23, Issue 10

    Abstract: High-throughput virtual screening (HTVS) is, in conjunction with rapid advances in computer hardware, becoming a staple in drug design research campaigns and cheminformatics. In this context, virtual compound library design becomes crucial as it ... ...

    Abstract High-throughput virtual screening (HTVS) is, in conjunction with rapid advances in computer hardware, becoming a staple in drug design research campaigns and cheminformatics. In this context, virtual compound library design becomes crucial as it generally constitutes the first step where quality filtered databases are essential for the efficient downstream research. Therefore, multiple filters for compound library design were devised and reported in the scientific literature. We collected the most common filters in medicinal chemistry (PAINS, REOS, Aggregators, van de Waterbeemd, Oprea, Fichert, Ghose, Mozzicconacci, Muegge, Egan, Murcko, Veber, Ro3, Ro4, and Ro5) to facilitate their open access use and compared them. Then, we implemented these filters in the open platform Konstanz Information Miner (KNIME) as a freely accessible and simple workflow compatible with small or large compound databases for the benefit of the readers and for the help in the early drug design steps.
    MeSH term(s) Cheminformatics ; Chemistry, Pharmaceutical ; High-Throughput Screening Assays ; Software ; Workflow
    Language English
    Publishing date 2022-05-20
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2019364-6
    ISSN 1422-0067 ; 1422-0067 ; 1661-6596
    ISSN (online) 1422-0067
    ISSN 1422-0067 ; 1661-6596
    DOI 10.3390/ijms23105727
    Database MEDical Literature Analysis and Retrieval System OnLINE

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