Evidence map›Paper›PMID 41652165›Full record

ReviewAdvances in experimental medicine and biology2026

Ligand-Binding Free Energy Simulations of Membrane Proteins.

Han Zhang, Wonpil Im

Abstract readReview
PubMed Publisher
In one paragraph

Review in Advances in experimental medicine and biology, 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

2 authors.

Han ZhangDepartment of Biological Sciences, Lehigh University, Bethlehem, PA, USA.
Wonpil ImDepartment of Biological Sciences, Lehigh University, Bethlehem, PA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular modeling and simulations of biomolecular systems are crucial for understanding their structure, dynamics, and function. They also play a key role in drug discovery and design, since protein-ligand affinity is a critical factor in developing new drugs. This chapter primarily focuses on computational methods for predicting ligand-binding affinity in membrane proteins. It highlights the major challenges associated with calculating ligand affinities in membrane protein environments and discusses potential solutions. Various membrane protein systems are presented to demonstrate the capabilities of both geometric and alchemical approaches in accurately estimating ligand-binding affinities. Free energy methods such as free energy perturbation (FEP), thermodynamic integration (TI), the alchemical transfer method (AToM), umbrella sampling (US), and weighted ensemble (WE) have been successfully applied to GPCRs, ion channels, and transporters, with representative examples discussed throughout the chapter.

Indexed as

Membrane ProteinsMolecular Dynamics SimulationAnimalsHumansLigandsProtein BindingProtein ConformationThermodynamicsLigandsMembrane ProteinsBinding affinityFree energyMembrane proteinsMolecular dynamics

Identifiers

What OpenQuestion holds

Textmetadata
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.