Evidence map›Paper›PMID 34257885›Full record

ArticleChemical science2021

Rapid and accurate estimation of protein-ligand relative binding affinities using site-identification by ligand competitive saturation.

Himanshu Goel, Anthony Hazel, Vincent D Ustach, Sunhwan Jo, Wenbo Yu, Alexander D MacKerell

Open access · diamondAbstract read
In one paragraph

Article in Chemical science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
5.7field-weighted citation impact, top 4% 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

35 citing papers in PubMed, 48 citations in OpenAlex.

  1. Article
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  5. The journal of physical chemistry. B · 2026
    Article
  6. Sampling the Grand Canonical Ensemble with Multisite λ Dynamics.The journal of physical chemistry letters · 2026
    Article
  7. Article
  8. Computational Ligand-Binding Site Prediction.Advances in experimental medicine and biology · 2026
    Review
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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

6 authors at 2 institutions in 2 countries.

Himanshu GoelComputer Aided Drug Design Center, Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy 20, Penn St. Baltimore Maryland 21201 USA alex@outerbanks.umaryland.edu +1-410-706-5017 +1-410-706-7442.ORCID https://orcid.org/0000-0002-0313-7040
Anthony HazelComputer Aided Drug Design Center, Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy 20, Penn St. Baltimore Maryland 21201 USA alex@outerbanks.umaryland.edu +1-410-706-5017 +1-410-706-7442.ORCID https://orcid.org/0000-0002-8195-7909
Vincent D UstachComputer Aided Drug Design Center, Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy 20, Penn St. Baltimore Maryland 21201 USA alex@outerbanks.umaryland.edu +1-410-706-5017 +1-410-706-7442.ORCID https://orcid.org/0000-0001-8299-3998
Sunhwan JoSilcsBio LLC 8 Market Place, Suite 300 Baltimore Maryland 21201 USA.ORCID https://orcid.org/0000-0002-4104-6473
Wenbo YuComputer Aided Drug Design Center, Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy 20, Penn St. Baltimore Maryland 21201 USA alex@outerbanks.umaryland.edu +1-410-706-5017 +1-410-706-7442.
Alexander D MacKerellComputer Aided Drug Design Center, Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy 20, Penn St. Baltimore Maryland 21201 USA alex@outerbanks.umaryland.edu +1-410-706-5017 +1-410-706-7442.ORCID https://orcid.org/0000-0001-8287-6804
University of Maryland, Baltimore · USSilcsBio (United States) · US

Funding

Macromolecular Conformational HeterogeneityR35GM131710 · NIGMS · UNIVERSITY OF MARYLAND BALTIMORE · PI ALEXANDER D MACKERELL · 2019 to 2026
$6.2M
Pre-computed free energy maps for rapid structure-based ligand designR44GM109635 · NIGMS · SILCSBIO, LLC · PI LAKKARAJU, SIRISH KAUSHIK, MACKERELL, ALEXANDER D · 2016 to 2018
$1.3M
NIGMS NIH HHS R35 GM131710NIGMS NIH HHS R44 GM109635
6 · The paper itself

Abstract

Predicting relative protein-ligand binding affinities is a central pillar of lead optimization efforts in structure-based drug design. The site identification by ligand competitive saturation (SILCS) methodology is based on functional group affinity patterns in the form of free energy maps that may be used to compute protein-ligand binding poses and affinities. Presented are results obtained from the SILCS methodology for a set of eight target proteins as reported originally in Wang

Identifiers

PMID34257885
PMCPMC8246086
OpenAlexW3164060112

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.