Evidence map›Paper›PMID 38456842›Full record

ArticleJournal of chemical information and modeling2024

Expanding FTMap for Fragment-Based Identification of Pharmacophore Regions in Ligand Binding Sites.

Omeir Khan, George Jones, Maria Lazou, Diane Joseph-McCarthy, Dima Kozakov, Dmitri Beglov, Sandor Vajda

Abstract read
In one paragraph

Article in Journal of chemical information and modeling, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

7 authors.

Omeir KhanDepartment of Chemistry, Boston University, Boston, Massachusetts 02215, United States.ORCID 0000-0002-5822-1549
George JonesDepartment of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York 11794, United States.
Maria LazouDepartment of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, United States.
Diane Joseph-McCarthyDepartment of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, United States.
Dima KozakovDepartment of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York 11794, United States.
Dmitri BeglovDepartment of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, United States.
Sandor VajdaDepartment of Chemistry, Boston University, Boston, Massachusetts 02215, United States.ORCID 0000-0003-1540-8220

Funding

Analysis and Prediction of Molecular InteractionsR35GM118078 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI SANDOR VAJDA · 2016 to 2026
$6.5M
Simulation of Multi-Protein systemsR01GM140098 · NIGMS · STATE UNIVERSITY NEW YORK STONY BROOK · PI KOZAKOV, DMYTRO · 2021 to 2024
$1.4M
Deep learning augmented protein mapping software to screen large compound librariesR43GM144992 · NIGMS · ACPHARIS, INC. · PI BEGLOV, DMITRI · 2022 to 2022
$173k
NIGMS NIH HHS R01 GM140098NIGMS NIH HHS R35 GM118078NIGMS NIH HHS R43 GM144992
6 · The paper itself

Abstract

The knowledge of ligand binding hot spots and of the important interactions within such hot spots is crucial for the design of lead compounds in the early stages of structure-based drug discovery. The computational solvent mapping server FTMap can reliably identify binding hot spots as consensus clusters, free energy minima that bind a variety of organic probe molecules. However, in its current implementation, FTMap provides limited information on regions within the hot spots that tend to interact with specific pharmacophoric features of potential ligands. E-FTMap is a new server that expands on the original FTMap protocol. E-FTMap uses 119 organic probes, rather than the 16 in the original FTMap, to exhaustively map binding sites, and identifies pharmacophore features as atomic consensus sites where similar chemical groups bind. We validate E-FTMap against a set of 109 experimentally derived structures of fragment-lead pairs, finding that highly ranked pharmacophore features overlap with the corresponding atoms in both fragments and lead compounds. Additionally, comparisons of mapping results to ensembles of bound ligands reveal that pharmacophores generated with E-FTMap tend to sample highly conserved protein-ligand interactions. E-FTMap is available as a web server at https://eftmap.bu.edu.

Indexed as

Drug DiscoveryPharmacophoreBinding SitesLigandsProtein BindingLigands

Identifiers

PMID38456842
PMCPMC11694573

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Registered trials

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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.