Evidence map›Paper›PMID 36358939›Full record

ArticleBiomolecules2022

HBcompare: Classifying Ligand Binding Preferences with Hydrogen Bond Topology.

Justin Z Tam, Zhaoming Kong, Omar Ahmed, Lifang He, Brian Y Chen

Open access · goldAbstract read
In one paragraph

Article in Biomolecules, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact, top 84% of its field
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

2 citing papers in PubMed, 0 citations in OpenAlex.

  1. Article
  2. 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

5 authors at 1 institution in 1 country.

Justin Z TamDepartment Computer Science and Engineering, Lehigh University, 113 Research Drive, Bethlehem, PA 19004, USA.ORCID 0000-0003-3280-7397
Zhaoming KongDepartment Computer Science and Engineering, Lehigh University, 113 Research Drive, Bethlehem, PA 19004, USA.ORCID 0000-0001-9252-911X
Omar AhmedDepartment Computer Science and Engineering, Lehigh University, 113 Research Drive, Bethlehem, PA 19004, USA.
Lifang HeDepartment Computer Science and Engineering, Lehigh University, 113 Research Drive, Bethlehem, PA 19004, USA.ORCID 0000-0001-7810-9071
Brian Y ChenDepartment Computer Science and Engineering, Lehigh University, 113 Research Drive, Bethlehem, PA 19004, USA.ORCID 0000-0001-9025-0107
Lehigh University · US

Funding

Algorithmic identification of binding specificity mechanisms in proteinsR01GM123131 · NIGMS · LEHIGH UNIVERSITY · PI CHEN, BRIAN YUAN · 2019 to 2022
$1.1M
NIH HHS R01GM123131
6 · The paper itself

Abstract

This paper presents HBcompare, a method that classifies protein structures according to ligand binding preference categories by analyzing hydrogen bond topology. HBcompare excludes other characteristics of protein structure so that, in the event of accurate classification, it can implicate the involvement of hydrogen bonds in selective binding. This approach contrasts from methods that represent many aspects of protein structure because holistic representations cannot associate classification with just one characteristic. To our knowledge, HBcompare is the first technique with this capability. On five datasets of proteins that catalyze similar reactions with different preferred ligands, HBcompare correctly categorized proteins with similar ligand binding preferences 89.5% of the time. Using only hydrogen bond topology, classification accuracy with HBcompare surpassed standard structure-based comparison algorithms that use atomic coordinates. As a tool for implicating the role of hydrogen bonds in protein function categories, HBcompare represents a first step towards the automatic explanation of biochemical mechanisms.

Indexed as

AlgorithmsProteinsBinding SitesHydrogen BondingLigandsModels, MolecularProtein BindingLigandsProteinsfunction annotationspecificity annotationstructural bioinformatics

Identifiers

PMID36358939
PMCPMC9687905
OpenAlexW4308502962

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.