Evidence map›Paper›PMID 39312164›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

Approaching Pharmacological Space: Events and Components.

Giulio Vistoli, Carmine Talarico, Serena Vittorio, Filippo Lunghini, Angelica Mazzolari, Andrea Beccari, Alessandro Pedretti

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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Giulio VistoliDipartimento di Scienze Farmaceutiche, Università Degli Studi di Milano, Milan, Italy. giulio.vistoli@unimi.it.
Carmine TalaricoEXSCALATE, Dompé Farmaceutici SpA, Naples, Italy.
Serena VittorioDipartimento di Scienze Farmaceutiche, Università Degli Studi di Milano, Milan, Italy.
Filippo LunghiniEXSCALATE, Dompé Farmaceutici SpA, Naples, Italy.
Angelica MazzolariDipartimento di Scienze Farmaceutiche, Università Degli Studi di Milano, Milan, Italy.
Andrea BeccariEXSCALATE, Dompé Farmaceutici SpA, Naples, Italy.
Alessandro PedrettiDipartimento di Scienze Farmaceutiche, Università Degli Studi di Milano, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pharmacological space comprises all the dynamic events that determine the bioactivity (and/or the metabolism and toxicity) of a given ligand. The pharmacological space accounts for the structural flexibility and property variability of the two interacting molecules as well as for the mutual adaptability characterizing their molecular recognition process. The dynamic behavior of all these events can be described by a set of possible states (e.g., conformations, binding modes, isomeric forms) that the simulated systems can assume. For each monitored state, a set of state-dependent ligand- and structure-based descriptors can be calculated. Instead of considering only the most probable state (as routinely done), the pharmacological space proposes to consider all the monitored states. For each state-dependent descriptor, the corresponding space can be evaluated by calculating various dynamic parameters such as mean and range values.The reviewed examples emphasize that the pharmacological space can find fruitful applications in structure-based virtual screening as well as in toxicity prediction. In detail, in all reported examples, the inclusion of the pharmacological space parameters enhances the resulting performances. Beneficial effects are obtained by combining both different binding modes to account for ligand mobility and different target structures to account for protein flexibility/adaptability.The proposed computational workflow that combines docking simulations and rescoring analyses to enrich the arsenal of docking-based descriptors revealed a general applicability regardless of the considered target and utilized docking engine. Finally, the EFO approach that generates consensus models by linearly combining various descriptors yielded highly performing models in all discussed virtual screening campaigns.

Indexed as

Molecular Docking SimulationBinding SitesDrug DiscoveryHumansLigandsProtein BindingProteinsLigandsProteinsBinding spacehERGMolecular dockingMolecular flexibilityPharmacological spaceSars-CoV-2 M-ProToxicity predictionTRPM8Virtual screening

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What OpenQuestion holds

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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.