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Article ; Online: KUALA: a machine learning-driven framework for kinase inhibitors repositioning.

De Simone, Giada / Sardina, Davide Stefano / Gulotta, Maria Rita / Perricone, Ugo

2022 Volume 12, Issue 1, Page(s) 17877

Abstract: The family of protein kinases comprises more than 500 genes involved in numerous functions. Hence, their physiological dysfunction has paved the way toward drug discovery for cancer, cardiovascular, and inflammatory diseases. As a matter of fact, Kinase ... ...

Abstract	The family of protein kinases comprises more than 500 genes involved in numerous functions. Hence, their physiological dysfunction has paved the way toward drug discovery for cancer, cardiovascular, and inflammatory diseases. As a matter of fact, Kinase binding sites high similarity has a double role. On the one hand it is a critical issue for selectivity, on the other hand, according to poly-pharmacology, a synergistic controlled effect on more than one target could be of great pharmacological interest. Another important aspect of binding similarity is the possibility of exploit it for repositioning of drugs on targets of the same family. In this study, we propose our approach called Kinase drUgs mAchine Learning frAmework (KUALA) to automatically identify kinase active ligands by using specific sets of molecular descriptors and provide a multi-target priority score and a repurposing threshold to suggest the best repurposable and non-repurposable molecules. The comprehensive list of all kinase-ligand pairs and their scores can be found at https://github.com/molinfrimed/multi-kinases .
MeSH term(s)	Drug Repositioning/methods ; Ligands ; Drug Discovery/methods ; Machine Learning ; Protein Kinases/genetics
Chemical Substances	Ligands ; Protein Kinases (EC 2.7.-)
Language	English
Publishing date	2022-10-25
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-022-22324-8
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: A Rational Design of α-Helix-Shaped Peptides Employing the Hydrogen-Bond Surrogate Approach: A Modulation Strategy for Ras-RasGRF1 Interaction in Neuropsychiatric Disorders.

Gulotta, Maria Rita / Brambilla, Riccardo / Perricone, Ugo / Brancale, Andrea

Pharmaceuticals (Basel, Switzerland)

2021 Volume 14, Issue 11

Abstract: In the last two decades, abnormal Ras (rat sarcoma protein)-ERK (extracellular signal-regulated kinase) signalling in the brain has been involved in a variety of neuropsychiatric disorders, including drug addiction, certain forms of intellectual ... ...

Abstract	In the last two decades, abnormal Ras (rat sarcoma protein)-ERK (extracellular signal-regulated kinase) signalling in the brain has been involved in a variety of neuropsychiatric disorders, including drug addiction, certain forms of intellectual disability, and autism spectrum disorder. Modulation of membrane-receptor-mediated Ras activation has been proposed as a potential target mechanism to attenuate ERK signalling in the brain. Previously, we showed that a cell penetrating peptide, RB3, was able to inhibit downstream signalling by preventing RasGRF1 (Ras guanine nucleotide-releasing factor 1), a neuronal specific GDP/GTP exchange factor, to bind Ras proteins, both in brain slices and in vivo, with an IC
Language	English
Publishing date	2021-10-28
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2193542-7
ISSN	1424-8247
ISSN	1424-8247
DOI	10.3390/ph14111099
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Article ; Online: KUALA

Giada De Simone / Davide Stefano Sardina / Maria Rita Gulotta / Ugo Perricone

Scientific Reports, Vol 12, Iss 1, Pp 1-

a machine learning-driven framework for kinase inhibitors repositioning

2022 Volume 16

Abstract: Abstract The family of protein kinases comprises more than 500 genes involved in numerous functions. Hence, their physiological dysfunction has paved the way toward drug discovery for cancer, cardiovascular, and inflammatory diseases. As a matter of fact, ...

Abstract	Abstract The family of protein kinases comprises more than 500 genes involved in numerous functions. Hence, their physiological dysfunction has paved the way toward drug discovery for cancer, cardiovascular, and inflammatory diseases. As a matter of fact, Kinase binding sites high similarity has a double role. On the one hand it is a critical issue for selectivity, on the other hand, according to poly-pharmacology, a synergistic controlled effect on more than one target could be of great pharmacological interest. Another important aspect of binding similarity is the possibility of exploit it for repositioning of drugs on targets of the same family. In this study, we propose our approach called Kinase drUgs mAchine Learning frAmework (KUALA) to automatically identify kinase active ligands by using specific sets of molecular descriptors and provide a multi-target priority score and a repurposing threshold to suggest the best repurposable and non-repurposable molecules. The comprehensive list of all kinase-ligand pairs and their scores can be found at https://github.com/molinfrimed/multi-kinases .
Keywords	Medicine ; R ; Science ; Q
Language	English
Publishing date	2022-10-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Rational Design of α-Helix-Shaped Peptides Employing the Hydrogen-Bond Surrogate Approach

Maria Rita Gulotta / Riccardo Brambilla / Ugo Perricone / Andrea Brancale

Pharmaceuticals, Vol 14, Iss 1099, p

A Modulation Strategy for Ras-RasGRF1 Interaction in Neuropsychiatric Disorders

2021 Volume 1099

Abstract: In the last two decades, abnormal Ras (rat sarcoma protein)–ERK (extracellular signal-regulated kinase) signalling in the brain has been involved in a variety of neuropsychiatric disorders, including drug addiction, certain forms of intellectual ... ...

Abstract	In the last two decades, abnormal Ras (rat sarcoma protein)–ERK (extracellular signal-regulated kinase) signalling in the brain has been involved in a variety of neuropsychiatric disorders, including drug addiction, certain forms of intellectual disability, and autism spectrum disorder. Modulation of membrane-receptor-mediated Ras activation has been proposed as a potential target mechanism to attenuate ERK signalling in the brain. Previously, we showed that a cell penetrating peptide, RB3, was able to inhibit downstream signalling by preventing RasGRF1 (Ras guanine nucleotide-releasing factor 1), a neuronal specific GDP/GTP exchange factor, to bind Ras proteins, both in brain slices and in vivo, with an IC 50 value in the micromolar range. The aim of this work was to mutate and improve this peptide through computer-aided techniques to increase its inhibitory activity against RasGRF1. The designed peptides were built based on the RB3 peptide structure corresponding to the α-helix of RasGRF1 responsible for Ras binding. For this purpose, the hydrogen-bond surrogate (HBS) approach was exploited to maintain the helical conformation of the designed peptides. Finally, residue scanning, MD simulations, and MM-GBSA calculations were used to identify 18 most promising α-helix-shaped peptides that will be assayed to check their potential activity against Ras-RasGRF1 and prevent downstream molecular events implicated in brain disorders.
Keywords	Ras ; RasGRF1 ; hydrogen-bond surrogate ; computational residue scanning ; molecular dynamics ; MM-GBSA ; Medicine ; R ; Pharmacy and materia medica ; RS1-441
Subject code	500
Language	English
Publishing date	2021-10-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Computer-Based Methodology to Design Non-Standard Peptides Potentially Able to Prevent HOX-PBX1-Associated Cancer Diseases.

Gulotta, Maria Rita / De Simone, Giada / John, Justin / Perricone, Ugo / Brancale, Andrea

International journal of molecular sciences

2021 Volume 22, Issue 11

Abstract: In the last decades, HOX proteins have been extensively studied due to their pivotal role in transcriptional events. HOX proteins execute their activity by exploiting a cooperative binding to PBX proteins and DNA. Therefore, an increase or decrease in ... ...

Abstract	In the last decades, HOX proteins have been extensively studied due to their pivotal role in transcriptional events. HOX proteins execute their activity by exploiting a cooperative binding to PBX proteins and DNA. Therefore, an increase or decrease in HOX activity has been associated with both solid and haematological cancer diseases. Thus, inhibiting HOX-PBX interaction represents a potential strategy to prevent these malignancies, as demonstrated by the patented peptide HTL001 that is being studied in clinical trials. In this work, a computational study is described to identify novel potential peptides designed by employing a database of non-natural amino acids. For this purpose, residue scanning of the HOX minimal active sequence was performed to select the mutations to be further processed. According to these results, the peptides were point-mutated and used for Molecular Dynamics (MD) simulations in complex with PBX1 protein and DNA to evaluate complex binding stability. MM-GBSA calculations of the resulting MD trajectories were exploited to guide the selection of the most promising mutations that were exploited to generate twelve combinatorial peptides. Finally, the latter peptides in complex with PBX1 protein and DNA were exploited to run MD simulations and the ΔG
MeSH term(s)	Antineoplastic Agents/chemistry ; Computer Simulation ; Drug Design ; Humans ; Neoplasms/drug therapy ; Neoplasms/metabolism ; Peptides/chemistry ; Pre-B-Cell Leukemia Transcription Factor 1/antagonists & inhibitors ; Pre-B-Cell Leukemia Transcription Factor 1/chemistry ; Pre-B-Cell Leukemia Transcription Factor 1/metabolism
Chemical Substances	Antineoplastic Agents ; Peptides ; Pre-B-Cell Leukemia Transcription Factor 1 ; PBX1 protein, human
Language	English
Publishing date	2021-05-26
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/ijms22115670
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Article ; Online: Exploring Molecular Contacts of MUC1 at CIN85 Binding Interface to Address Future Drug Design Efforts.

Gulotta, Maria Rita / Vittorio, Serena / Gitto, Rosaria / Perricone, Ugo / De Luca, Laura

International journal of molecular sciences

2021 Volume 22, Issue 4

Abstract: The modulation of protein-protein interactions (PPIs) by small molecules represents a valuable strategy for pharmacological intervention in several human diseases. In this context, computer-aided drug discovery techniques offer useful resources to ... ...

Abstract	The modulation of protein-protein interactions (PPIs) by small molecules represents a valuable strategy for pharmacological intervention in several human diseases. In this context, computer-aided drug discovery techniques offer useful resources to predict the network of interactions governing the recognition process between protein partners, thus furnishing relevant information for the design of novel PPI modulators. In this work, we focused our attention on the MUC1-CIN85 complex as a crucial PPI controlling cancer progression and metastasis. MUC1 is a transmembrane glycoprotein whose extracellular domain contains a variable number of tandem repeats (VNTRs) regions that are highly glycosylated in normal cells and under-glycosylated in cancer. The hypo-glycosylation fosters the exposure of the backbone to new interactions with other proteins, such as CIN85, that alter the intracellular signalling in tumour cells. Herein, different computational approaches were combined to investigate the molecular recognition pattern of MUC1-CIN85 PPI thus unveiling new structural information useful for the design of MUC1-CIN85 PPI inhibitors as potential anti-metastatic agents.
MeSH term(s)	Adaptor Proteins, Signal Transducing/chemistry ; Adaptor Proteins, Signal Transducing/metabolism ; Binding Sites ; Drug Design ; Molecular Docking Simulation ; Molecular Dynamics Simulation ; Mucin-1/chemistry ; Mucin-1/metabolism ; Peptide Fragments/chemistry ; Peptide Fragments/metabolism ; Protein Interaction Domains and Motifs ; Protein Multimerization ; Proto-Oncogene Proteins c-cbl/chemistry ; Proto-Oncogene Proteins c-cbl/metabolism ; src Homology Domains
Chemical Substances	Adaptor Proteins, Signal Transducing ; MUC1 protein, human ; Mucin-1 ; Peptide Fragments ; SH3KBP1 protein, human ; Proto-Oncogene Proteins c-cbl (EC 2.3.2.27) ; CBL protein, human (EC 6.3.2.-)
Language	English
Publishing date	2021-02-23
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/ijms22042208
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Article ; Online: Exploring the SARS-CoV-2 Proteome in the Search of Potential Inhibitors via Structure-based Pharmacophore Modeling/Docking Approach

Giulia Culletta / Maria Rita Gulotta / Ugo Perricone / Maria Zappalà / Anna Maria Almerico / Marco Tutone

Computation, Vol 8, Iss 77, p

2020 Volume 77

Abstract: To date, SARS-CoV-2 infectious disease, named COVID-19 by the World Health Organization (WHO) in February 2020, has caused millions of infections and hundreds of thousands of deaths. Despite the scientific community efforts, there are currently no ... ...

Abstract	To date, SARS-CoV-2 infectious disease, named COVID-19 by the World Health Organization (WHO) in February 2020, has caused millions of infections and hundreds of thousands of deaths. Despite the scientific community efforts, there are currently no approved therapies for treating this coronavirus infection. The process of new drug development is expensive and time-consuming, so that drug repurposing may be the ideal solution to fight the pandemic. In this paper, we selected the proteins encoded by SARS-CoV-2 and using homology modeling we identified the high-quality model of proteins. A structure-based pharmacophore modeling study was performed to identify the pharmacophore features for each target. The pharmacophore models were then used to perform a virtual screening against the DrugBank library (investigational, approved and experimental drugs). Potential inhibitors were identified for each target using XP docking and induced fit docking. MM-GBSA was also performed to better prioritize potential inhibitors. This study will provide new important comprehension of the crucial binding hot spots usable for further studies on COVID-19. Our results can be used to guide supervised virtual screening of large commercially available libraries.
Keywords	COVID-19 ; SARS-CoV-2 ; computational chemistry ; structure-based ; pharmacophore ; docking ; Electronic computers. Computer science ; QA75.5-76.95 ; covid19
Subject code	540
Language	English
Publishing date	2020-09-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Computer-Based Methodology to Design Non-Standard Peptides Potentially Able to Prevent HOX-PBX1-Associated Cancer Diseases

Maria Rita Gulotta / Giada De Simone / Justin John / Ugo Perricone / Andrea Brancale

International Journal of Molecular Sciences, Vol 22, Iss 5670, p

2021 Volume 5670

Abstract	In the last decades, HOX proteins have been extensively studied due to their pivotal role in transcriptional events. HOX proteins execute their activity by exploiting a cooperative binding to PBX proteins and DNA. Therefore, an increase or decrease in HOX activity has been associated with both solid and haematological cancer diseases. Thus, inhibiting HOX-PBX interaction represents a potential strategy to prevent these malignancies, as demonstrated by the patented peptide HTL001 that is being studied in clinical trials. In this work, a computational study is described to identify novel potential peptides designed by employing a database of non-natural amino acids. For this purpose, residue scanning of the HOX minimal active sequence was performed to select the mutations to be further processed. According to these results, the peptides were point-mutated and used for Molecular Dynamics (MD) simulations in complex with PBX1 protein and DNA to evaluate complex binding stability. MM-GBSA calculations of the resulting MD trajectories were exploited to guide the selection of the most promising mutations that were exploited to generate twelve combinatorial peptides. Finally, the latter peptides in complex with PBX1 protein and DNA were exploited to run MD simulations and the ΔG binding average values of the complexes were calculated. Thus, the analysis of the results highlighted eleven combinatorial peptides that will be considered for further assays.
Keywords	HOX ; PBX ; Protein-Protein Interactions ; Residue Scanning ; Molecular Dynamics ; MM-GBSA ; Biology (General) ; QH301-705.5 ; Chemistry ; QD1-999
Subject code	540
Language	English
Publishing date	2021-05-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Exploring Molecular Contacts of MUC1 at CIN85 Binding Interface to Address Future Drug Design Efforts

Maria Rita Gulotta / Serena Vittorio / Rosaria Gitto / Ugo Perricone / Laura De Luca

International Journal of Molecular Sciences, Vol 22, Iss 4, p

2021 Volume 2208

Abstract	The modulation of protein-protein interactions (PPIs) by small molecules represents a valuable strategy for pharmacological intervention in several human diseases. In this context, computer-aided drug discovery techniques offer useful resources to predict the network of interactions governing the recognition process between protein partners, thus furnishing relevant information for the design of novel PPI modulators. In this work, we focused our attention on the MUC1-CIN85 complex as a crucial PPI controlling cancer progression and metastasis. MUC1 is a transmembrane glycoprotein whose extracellular domain contains a variable number of tandem repeats (VNTRs) regions that are highly glycosylated in normal cells and under-glycosylated in cancer. The hypo-glycosylation fosters the exposure of the backbone to new interactions with other proteins, such as CIN85, that alter the intracellular signalling in tumour cells. Herein, different computational approaches were combined to investigate the molecular recognition pattern of MUC1-CIN85 PPI thus unveiling new structural information useful for the design of MUC1-CIN85 PPI inhibitors as potential anti-metastatic agents.
Keywords	protein-protein interactions ; MUC1-CIN85 ; SH3 domain ; molecular dynamics ; protein-peptide docking ; MM-GBSA ; Biology (General) ; QH301-705.5 ; Chemistry ; QD1-999
Subject code	500
Language	English
Publishing date	2021-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: In-silico guided chemical exploration of KDM4A fragments hits.

Lombino, Jessica / Vallone, Rosario / Cimino, Maura / Gulotta, Maria Rita / De Simone, Giada / Morando, Maria Agnese / Sabbatella, Raffaele / Di Martino, Simona / Fogazza, Mario / Sarno, Federica / Coronnello, Claudia / De Rosa, Maria / Cipollina, Chiara / Altucci, Lucia / Perricone, Ugo / Alfano, Caterina

Clinical epigenetics

2023 Volume 15, Issue 1, Page(s) 197

Abstract: Background: Lysine demethylase enzymes (KDMs) are an emerging class of therapeutic targets, that catalyse the removal of methyl marks from histone lysine residues regulating chromatin structure and gene expression. KDM4A isoform plays an important role ... ...

Abstract	Background: Lysine demethylase enzymes (KDMs) are an emerging class of therapeutic targets, that catalyse the removal of methyl marks from histone lysine residues regulating chromatin structure and gene expression. KDM4A isoform plays an important role in the epigenetic dysregulation in various cancers and is linked to aggressive disease and poor clinical outcomes. Despite several efforts, the KDM4 family lacks successful specific molecular inhibitors. Results: Herein, starting from a structure-based fragments virtual screening campaign we developed a synergic framework as a guide to rationally design efficient KDM4A inhibitors. Commercial libraries were used to create a fragments collection and perform a virtual screening campaign combining docking and pharmacophore approaches. The most promising compounds were tested in-vitro by a Homogeneous Time-Resolved Fluorescence-based assay developed for identifying selective substrate-competitive inhibitors by means of inhibition of H3K9me3 peptide demethylation. 2-(methylcarbamoyl)isonicotinic acid was identified as a preliminary active fragment, displaying inhibition of KDM4A enzymatic activity. Its chemical exploration was deeply investigated by computational and experimental approaches which allowed a rational fragment growing process. The in-silico studies guided the development of derivatives designed as expansion of the primary fragment hit and provided further knowledge on the structure-activity relationship. Conclusions: Our study describes useful insights into key ligand-KDM4A protein interaction and provides structural features for the development of successful selective KDM4A inhibitors.
MeSH term(s)	Humans ; Jumonji Domain-Containing Histone Demethylases/genetics ; Jumonji Domain-Containing Histone Demethylases/metabolism ; Lysine/metabolism ; DNA Methylation ; Histones/metabolism ; Structure-Activity Relationship
Chemical Substances	Jumonji Domain-Containing Histone Demethylases (EC 1.14.11.-) ; Lysine (K3Z4F929H6) ; Histones ; KDM4A protein, human (EC 1.5.-)
Language	English
Publishing date	2023-12-21
Publishing country	Germany
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2553921-8
ISSN	1868-7083 ; 1868-7075
ISSN (online)	1868-7083
ISSN	1868-7075
DOI	10.1186/s13148-023-01613-7
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