ArticleThe journal of physical chemistry letters2021
Machine Learning Prediction of Allosteric Drug Activity from Molecular Dynamics.
Article in The journal of physical chemistry letters, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
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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.
The trial behind it
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Who cites it
25 citing papers in PubMed.
- The Evolving Landscape of Protein Allostery: From Computational and Experimental Perspectives.Journal of molecular biology · 2025Review
- Special Issue: "Advanced Research on Molecular Modeling of Protein Structure and Functions".International journal of molecular sciences · 2025Article
- STINGAllo: a web server for high-throughput prediction of allosteric site-forming residues using internal protein nanoenvironment descriptors.Briefings in bioinformatics · 2025Article
- Neural Network Models for Prediction of Biological Activity using Molecular Dynamics Data: A Case of Photoswitchable Peptides.Molecular informatics · 2025Article
- Using Machine Learning to Analyze Molecular Dynamics Simulations of Biomolecules.The journal of physical chemistry. B · 2025Article
- The structural and functional dynamics of BiP and Grp94: opportunities for therapeutic discovery.Trends in pharmacological sciences · 2025Review
- Elucidating the role of artificial intelligence in drug development from the perspective of drug-target interactions.Journal of pharmaceutical analysis · 2025Review
- Genetic evidence informs the direction of therapeutic modulation in drug development.npj drug discovery · 2025Article
- Allostery Illuminated: Harnessing AI and Machine Learning for Drug Discovery.ACS medicinal chemistry letters · 2024Review
- G Protein-Coupled Receptor-Ligand Pose and Functional Class Prediction.International journal of molecular sciences · 2024Article
- A Study on the Robustness and Stability of Explainable Deep Learning in an Imbalanced Setting: The Exploration of the Conformational Space of G Protein-Coupled Receptors.International journal of molecular sciences · 2024Article
- Machine Learning Integrating Protein Structure, Sequence, and Dynamics to Predict the Enzyme Activity of Bovine Enterokinase Variants.Journal of chemical information and modeling · 2024Article
- ATLAS: protein flexibility description from atomistic molecular dynamics simulations.Nucleic acids research · 2024Article
- Unsupervised deep learning for molecular dynamics simulations: a novel analysis of protein-ligand interactions in SARS-CoV-2 MRSC advances · 2023Article
- Protein conformational ensembles in function: roles and mechanisms.RSC chemical biology · 2023Review
- Discovery of Nonretinoid Inhibitors of CRBP1: Structural and Dynamic Insights for Ligand-Binding Mechanisms.ACS chemical biology · 2023Article
- Predicting allosteric pockets in protein biological assemblages.Bioinformatics (Oxford, England) · 2023Article
- Beyond sequence: Structure-based machine learning.Computational and structural biotechnology journal · 2023Review
- Specifics of Metabolite-Protein Interactions and Their Computational Analysis and Prediction.Methods in molecular biology (Clifton, N.J.) · 2023Review
- Combined DFT, SCAPS-1D, and wxAMPS frameworks for design optimization of efficient CsRSC advances · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Allosteric drugs have been attracting increasing interest over the past few years. In this context, it is common practice to use high-throughput screening for the discovery of non-natural allosteric drugs. While the discovery stage is supported by a growing amount of biological information and increasing computing power, major challenges still remain in selecting allosteric ligands and predicting their effect on the target protein's function. Indeed, allosteric compounds can act both as inhibitors and activators of biological responses. Computational approaches to the problem have focused on variations on the theme of molecular docking coupled to molecular dynamics with the aim of recovering information on the (long-range) modulation typical of allosteric proteins.
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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.