Evidence map›Paper›PMID 37697630›Full record

ArticleProteins2023

Accurate ligand-protein docking in CASP15 using the ClusPro LigTBM server.

Sergei Kotelnikov, Ryota Ashizawa, Konstantin I Popov, Omeir Khan, Mikhail Ignatov, Stan Xiaogang Li, Mosavverul Hassan, Evangelos A Coutsias, Gennady Poda, Dzmitry Padhorny and 3 more

Open access · bronzeAbstract read
In one paragraph

Article in Proteins, 2023. 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
1.2field-weighted citation impact, top 18% 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, 6 citations in OpenAlex.

  1. Article
  2. Recent Progress of Protein Tertiary Structure Prediction.Molecules (Basel, Switzerland) · 2024
    Review
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

13 authors at 4 institutions in 2 countries.

Sergei KotelnikovDepartment of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA.
Ryota AshizawaDepartment of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA.
Konstantin I PopovDepartment of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Omeir KhanDepartment of Chemistry, Boston University, Boston, Massachusetts, USA.
Mikhail IgnatovDepartment of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA.
Stan Xiaogang LiDepartment of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA.
Mosavverul HassanDepartment of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA.ORCID 0000-0002-9540-0490
Evangelos A CoutsiasDepartment of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA.ORCID 0000-0003-2910-9125
Gennady PodaDrug Discovery Program, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
Dzmitry PadhornyLaufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York, USA.ORCID 0000-0002-7840-8677
Alexander TropshaEshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Sandor VajdaDepartment of Chemistry, Boston University, Boston, Massachusetts, USA.ORCID 0000-0003-1540-8220
Dima KozakovDepartment of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA.ORCID 0000-0003-0464-4500
Stony Brook University · USBoston University · USUniversity of North Carolina at Chapel Hill · USOntario Institute for Cancer Research · CA

Funding

Analysis and Prediction of Molecular InteractionsR35GM118078 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI SANDOR VAJDA · 2016 to 2026
$6.5M
Solvation modeling for next-gen biomolecule simulationsRM1GM135136 · NIGMS · STATE UNIVERSITY NEW YORK STONY BROOK · PI COUTSIAS, EVANGELOS A., DILL, KEN A · 2020 to 2024
$6.0M
Mechanism of Slow Onset Enzyme Inhibition and Translation to Time-Dependent Drug ActivityR01GM102864 · NIGMS · STATE UNIVERSITY NEW YORK STONY BROOK · PI TONGE, PETER J · 2012 to 2021
$2.6M
Simulation of Multi-Protein systemsR01GM140098 · NIGMS · STATE UNIVERSITY NEW YORK STONY BROOK · PI KOZAKOV, DMYTRO · 2021 to 2024
$1.4M
NIGMS NIH HHS R01 GM102864NIGMS NIH HHS R01GM102864NIGMS NIH HHS R01 GM140098NIGMS NIH HHS R01GM140098NIGMS NIH HHS R35 GM118078NIGMS NIH HHS R35GM118078NIGMS NIH HHS RM1135136
6 · The paper itself

Abstract

In the ligand prediction category of CASP15, the challenge was to predict the positions and conformations of small molecules binding to proteins that were provided as amino acid sequences or as models generated by the AlphaFold2 program. For most targets, we used our template-based ligand docking program ClusPro ligTBM, also implemented as a public server available at https://ligtbm.cluspro.org/. Since many targets had multiple chains and a number of ligands, several templates, and some manual interventions were required. In a few cases, no templates were found, and we had to use direct docking using the Glide program. Nevertheless, ligTBM was shown to be a very useful tool, and by any ranking criteria, our group was ranked among the top five best-performing teams. In fact, all the best groups used template-based docking methods. Thus, it appears that the AlphaFold2-generated models, despite the high accuracy of the predicted backbone, have local differences from the x-ray structure that make the use of direct docking methods more challenging. The results of CASP15 confirm that this limitation can be frequently overcome by homology-based docking.

Indexed as

ProteinsSoftwareBinding SitesLigandsMolecular Docking SimulationProtein BindingProtein ConformationLigandsProteinsAlphaFold2 modelsBRIKARD macrocycle modelingClusPro docking programFTMap protein mappingtemplate-based ligand docking

Identifiers

PMID37697630
PMCPMC10947245
OpenAlexW4386623903

What OpenQuestion holds

Textmetadata
LicenceTDM
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.