Evidence map›Paper›PMID 32061934›Full record

ArticleJournal of molecular biology2020

HMI-PRED: A Web Server for Structural Prediction of Host-Microbe Interactions Based on Interface Mimicry.

Emine Guven-Maiorov, Asma Hakouz, Sukejna Valjevac, Ozlem Keskin, Chung-Jung Tsai, Attila Gursoy, Ruth Nussinov

Abstract read
In one paragraph

Article in Journal of molecular biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Review
  6. Bioinformatics approaches for unveiling virus-host interactions.Computational and structural biotechnology journal · 2023
    Review
  7. Article
  8. Article
  9. Article
  10. AlphaFold, Artificial Intelligence (AI), and Allostery.The journal of physical chemistry. B · 2022
    Review
  11. Article
  12. Article
  13. Article
  14. Host-pathogen protein-nucleic acid interactions: A comprehensive review.Computational and structural biotechnology journal · 2022
    Review
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Emine Guven-MaiorovComputational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA. Electronic address: emine.guven-maiorov@nih.gov.
Asma HakouzDepartment of Computer Engineering, Koc University, Istanbul, 34450, Turkey. Electronic address: ahakouz17@ku.edu.tr.
Sukejna ValjevacDepartment of Computer Engineering, Koc University, Istanbul, 34450, Turkey. Electronic address: svaljevac18@ku.edu.tr.
Ozlem KeskinDepartment of Chemical and Biological Engineering, Koc University, Istanbul, 34450, Turkey. Electronic address: okeskin@ku.edu.tr.
Chung-Jung TsaiComputational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA. Electronic address: tsaic@mail.nih.gov.
Attila GursoyDepartment of Computer Engineering, Koc University, Istanbul, 34450, Turkey. Electronic address: agursoy@ku.edu.tr.
Ruth NussinovComputational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA; Sackler Inst. of Molecular Medicine, Department of Human Genetics and Molecular Medicine, Sackler School of Medicine, Tel Aviv University, Tel Aviv, 69978, Israel. Electronic address: NussinoR@mail.nih.gov.

Funding

Protein Structure, Stability, and Amyloid FormationZIABC010440 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI NUSSINOV, RUTH · 2009 to 2025
$11.8M
Biomolecular Recognition and Binding MechanismsZIABC010441 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI NUSSINOV, RUTH · 2009 to 2025
$9.4M
Method Development: Efficient Computer Vision Based AlgorithmsZIABC010442 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI NUSSINOV, RUTH · 2009 to 2025
$2.4M
Method Development: Efficient Computer Vision Based AlgorithmsZ01BC010442 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI NUSSINOV, RUTH · 2002 to 2008
$454k
CCR NIH HHS HHSN261200800001CIntramural NIH HHS Z01 BC010442NCI NIH HHS HHSN261200800001E
6 · The paper itself

Abstract

Microbes, commensals, and pathogens, control the numerous functions in the host cells. They can alter host signaling and modulate immune surveillance by interacting with the host proteins. For shedding light on the contribution of microbes to health and disease, it is vital to discern how microbial proteins rewire host signaling and through which host proteins they do this. Host-Microbe Interaction PREDictor (HMI-PRED) is a user-friendly web server for structural prediction of protein-protein interactions (PPIs) between the host and a microbial species, including bacteria, viruses, fungi, and protozoa. HMI-PRED relies on "interface mimicry" through which the microbial proteins hijack host binding surfaces. Given the structure of a microbial protein of interest, HMI-PRED will return structural models of potential host-microbe interaction (HMI) complexes, the list of host endogenous and exogenous PPIs that can be disrupted, and tissue expression of the microbe-targeted host proteins. The server also allows users to upload homology models of microbial proteins. Broadly, it aims at large-scale, efficient identification of HMIs. The prediction results are stored in a repository for community access. HMI-PRED is free and available at https://interactome.ku.edu.tr/hmi.

Indexed as

Protein Interaction MappingSoftwareBacteriaHost Microbial InteractionsHumansInternetcomputational predictionHMIhost-microbe interactionhost-pathogen interactionHPIinterface mimicrymodelingprotein-protein interactionstructure

Identifiers

PMID32061934
PMCPMC7261632

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.