Evidence map›Paper›PMID 36993448›Full record

ArticlebioRxiv : the preprint server for biology2023

What Strengthens Protein-Protein Interactions: Analysis and Applications of Residue Correlation Networks.

Ta I Hung, Yun-Jung Hsieh, Wei-Lin Lu, Kuen-Phon Wu, Chia-En A Chang

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 2 countries.

Ta I HungDepartment of Chemistry, University of California, Riverside, United States.
Yun-Jung HsiehInstitute of Biological Chemistry, Academia Sinica, Taiwan.
Wei-Lin LuInstitute of Biological Chemistry, Academia Sinica, Taiwan.
Kuen-Phon WuInstitute of Biological Chemistry, Academia Sinica, Taiwan.
Chia-En A ChangDepartment of Chemistry, University of California, Riverside, United States.
National Taiwan University · TWUniversity of California, Riverside · USInstitute of Biological Chemistry, Academia Sinica · TW

Funding

Next-Generation GPU Computing Resource for Simulating Ligand-Protein Binding Kinetics/MechanismR01GM109045 · NIGMS · UNIVERSITY OF CALIFORNIA RIVERSIDE · PI CHANG, CHIA-EN · 2014 to 2023
$2.8M
NIGMS NIH HHS R01 GM109045
6 · The paper itself

Abstract

Identifying critical residues in protein-protein binding and efficiently designing stable and specific protein binders is challenging. In addition to direct contacts in a protein-protein binding interface, our study employs computation modeling to reveal the essential network of residue interaction and dihedral angle correlation critical in protein-protein recognition. We propose that mutating residues regions exhibited highly correlated motions within the interaction network can efficiently optimize protein-protein interactions to create tight and selective protein binders. We validated our strategy using ubiquitin (Ub) and MERS coronaviral papain-like protease (PLpro) complexes, where Ub is one central player in many cellular functions and PLpro is an antiviral drug target. Our designed UbV with 3 mutated residues resulted in a ~3,500-fold increase in functional inhibition, compared with the wild-type Ub. Further optimization by incorporating 2 more residues within the network, the 5-point mutant achieved a K

Indexed as

Dihedral correlation networknanomolar binderpapain-like proteaseprotein-based inhibitorsubiquitin variant

Identifiers

PMID36993448
PMCPMC10055079
OpenAlexW4324345085

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.