Evidence map›Paper›PMID 42045222›Full record

ArticleNature communications2026

FMOPhore for hotspot identification and efficient fragment-to-lead growth strategies.

Peter E G F Ibrahim, Simone Altmann, Ulrich Zachariae, David Horn, Ian H Gilbert, Michael J Bodkin

Abstract read
In one paragraph

Article in Nature communications, 2026. 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.

No citing paper in PubMed yet.

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.

Peter E G F IbrahimDrug Discovery Unit, Wellcome Centre for Anti-Infectives Research, School of Life Sciences, University of Dundee, Dundee, UK. peteregfi@gmail.com.
Simone AltmannSchool of Life Sciences, University of Dundee, Dundee, UK.ORCID http://orcid.org/0000-0001-8268-0916
Ulrich ZachariaeSchool of Life Sciences, University of Dundee, Dundee, UK.ORCID http://orcid.org/0000-0003-3287-8494
David HornSchool of Life Sciences, University of Dundee, Dundee, UK.ORCID http://orcid.org/0000-0001-5173-9284
Ian H GilbertDrug Discovery Unit, Wellcome Centre for Anti-Infectives Research, School of Life Sciences, University of Dundee, Dundee, UK.ORCID http://orcid.org/0000-0002-5238-1314
Michael J BodkinDrug Discovery Unit, Wellcome Centre for Anti-Infectives Research, School of Life Sciences, University of Dundee, Dundee, UK.

Funding

Wellcome TrustWellcome Trust (Wellcome) 203134/A/16/Z
6 · The paper itself

Abstract

Fragment based drug design is like a chess game in that a good or a bad move can dramatically influence the outcome. In the design process, it is important to identify the key binding site residues (hotspots) that can have a substantial impact on ligand potency and efficiency. Here, we introduce FMOPhore algorithm represented with a scoring function named FP-score, which combines Quantum Mechanics Fragment Molecular Orbital calculations with 3D-protein-ligand pharmacophore models. FP-score accurately classifies binding site residues in two classes: 1) Hotspot residues (Delineated into three categories; Anchor, Transient, and Accessible) and 2) non-hotspot residues. We apply our algorithm in two different scenarios: holo-complex and apo-structure, testing its robustness on 46 different protein targets including an experimental case study on drug-resistance hotspots across 829 protein-ligand complexes. We handle protein binding site flexibility using Dy-FMOPhore which improves the detection of hotspots. FMOPhore provides valuable insight for efficient, selective fragment growing and lead optimization strategies.

Indexed as

Drug DesignProteinsAlgorithmsBinding SitesLigandsModels, MolecularPharmacophoreProtein BindingLigandsProteins

Identifiers

PMID42045222
PMCPMC13328607

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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.