ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025
Trustworthy Inverse Molecular Design via Alignment with Molecular Dynamics.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed.
- Trustworthy Inverse Molecular Design via Alignment with Molecular Dynamics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Data-driven inverse molecular design (IMD) has attracted significant attention in recent years. Despite the remarkable progress, existing IMD methods lag behind in terms of trustworthiness, as indicated by their misalignment to the ground-truth function that models the molecular dynamics. Here, TrustMol, an IMD method built to be trustworthy is proposed by inverting a reliable molecular property predictor. TrustMol first constructs a latent space with a novel variational autoencoder (VAE) and trains an ensemble of property predictors to learn the mapping from the latent space to the property space. The training samples for the ensemble are obtained from a new reacquisition method to ensure that the samples are representative of the latent space. To generate a desired molecule, TrustMol optimizes a latent design by minimizing both the predictive error and the uncertainty quantified by the ensemble. As a result, TrustMol achieves state-of-the-art performance in terms of IMD accuracy, and more importantly, it is aligned with the ground-truth function that indicates trustworthiness.
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Registered trials
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.