Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0001511 (Adhesion)
 5,955 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Four different colony morphologies were produced by Flavobacterium columnare strains on Shieh agar plate cultures: rhizoid and flat (type 1), non-rhizoid and hard (type 2), round and soft (type 3), and irregularly shaped and soft (type 4). Colonies produced on AO agar differed from these to some extent. The colony types formed on Shieh agar were studied according to molecular characteristics [Amplified Fragment Length Polymorphism (AFLP), Automated Ribosomal Intergenic Spacer Analysis (ARISA), and whole cell protein SDS-PAGE profiles], virulence on rainbow trout fingerlings, and adhesion on polystyrene and fish gills. There were no molecular differences between colony types within one strain. Type 2 was the most adherent on polystyrene, but type 1 was the most virulent. Adhesion of F. columnare strains used in this study was not connected to virulence. From fish infected with colony type 1, three colony types (types 1, 2 and 4) were isolated. Contrary to previous studies, our results suggest that strong adhesion capacity may not be the main virulence factor of F. columnare. Colony morphology change might be caused by phase variation, and different colony types isolated from infected fish may indicate different roles of the colony morphologies in the infection process of columnaris disease.
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PMID:Flavobacterium columnare colony types: connection to adhesion and virulence? 1898 35

The function of the protein is primarily dictated by its structure. Therefore it is far more logical to find the functional clues of the protein in its overall 3-dimensional fold or its global structure. In this paper, we have developed a novel Support Vector Machines (SVM) based prediction model for functional classification and prediction of proteins using features extracted from its global structure based on fragment libraries. Fragment libraries have been previously used for abintio modelling of proteins and protein structure comparisons. The query protein structure is broken down into a collection of short contiguous backbone fragments and this collection is discretized using a library of fragments. The input feature vector is frequency vector that counts the number of each library fragment in the collection of fragments by all-to-all fragment comparisons. SVM models were trained and optimised for obtaining the best 10-fold Cross validation accuracy for classification. As an example, this method was applied for prediction and classification of Cell Adhesion molecules (CAMs). Thirty-four different fragment libraries with sizes ranging from 4 to 400 and fragment lengths ranging from 4 to 12 were used for obtaining the best prediction model. The best 10-fold CV accuracy of 95.25% was obtained for library of 400 fragments of length 10. An accuracy of 87.5% was obtained on an unseen test dataset consisting of 20 CAMs and 20 NonCAMs. This shows that protein structure can be accurately and uniquely described using 400 representative fragments of length 10.
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PMID:Structure based function prediction of proteins using fragment library frequency vectors. 2314 57

The paper 'A C-Terminal Fragment of Adhesion Protein Fibulin-7 Inhibits Growth of Murine Breast Tumor by Regulating Macrophage Reprogramming' by Chakraborty et al. highlights that Fbln7-C could be explored as a potential immunomodulatory agent against various solid cancers and have shown its abilities to regulate tumor microenvironment reprogramming of TAMs in a breast cancer model. Fbln7, which is a secreted glycoprotein, has been shown to be anti-angiogenic and has an immunomodulatory role regulating various functional properties of monocytes, macrophages, and neutrophils, thereby influencing inflammation. In this study, the authors have shown that in a murine breast tumor model, intravenous administration of Fbln7-C significantly reduces the size of tumors via macrophage reprogramming. Comment on: https://doi.org/10.1111/febs.15333.
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PMID:Immunomodulation via macrophages to fight solid tumor malignancies. 3257 1