ReviewCurrent opinion in structural biology2022
Recent progress in general force fields of small molecules.
Review in Current opinion in structural biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
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.
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Who cites it
16 citing papers in PubMed.
- Deep residual learning for molecular force fields.Nature communications · 2026Article
- Advances and opportunities for computational interrogation of plant proteins.The Plant journal : for cell and molecular biology · 2026Review
- Unravelling Rational Design of Molecularly Imprinted Polymer for Selective Mitragynine Isolation from Kratom: Quantum Mechanical, Molecular Dynamics, and Experimental Insights.Molecules (Basel, Switzerland) · 2026Article
- Computer Simulations of Multidrug Efflux Pumps of the Resistance-Nodulation-Cell Division Superfamily.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Ultrafast Optical Kerr Effect Spectroscopy Reveals the Vibrational Fingerprint of Acetate-Water Hydrogen Bonds.ACS omega · 2025Article
- Speed up Multi-Scale Force-Field Parameter Optimization by Substituting Molecular Dynamics Calculations with a Machine Learning Surrogate Model.Chemphyschem : a European journal of chemical physics and physical chemistry · 2025Article
- ABCG2: A Milestone Charge Model for Accurate Solvation Free Energy Calculation.Journal of chemical theory and computation · 2025Article
- Investigation of Solution Microstructure in Ferric Sulfate Coagulation-Assisted Precipitation of Fluoride Ions.Molecules (Basel, Switzerland) · 2025Article
- Accurate quantum-centric simulations of intermolecular interactions.Communications physics · 2025Article
- Review
- SPRank─A Knowledge-Based Scoring Function for RNA-Ligand Pose Prediction and Virtual Screening.Journal of chemical theory and computation · 2024Article
- Monte Carlo simulations for free energies of hydration: Past to present.The Journal of chemical physics · 2024Article
- The SAMPL9 host-guest blind challenge: an overview of binding free energy predictive accuracy.Physical chemistry chemical physics : PCCP · 2024Article
- On the potentials of sialic acid derivatives as inhibitors for the mumps virus: A molecular dynamics and quantum chemistry investigation.Virus research · 2023Article
- An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation.Journal of chemical information and modeling · 2023Review
- Piperazine Derivative Stabilizes Actin Filaments in Primary Fibroblasts and Binds G-Actin In Silico.Current issues in molecular biology · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Recent advances in computational hardware and free energy algorithms enable a broader application of molecular simulation of binding interactions between receptors and small-molecule ligands. The underlying molecular mechanics force fields (FFs) for small molecules have also achieved advancements in accuracy, user-friendliness, and speed during the past several years (2018-2020). Besides the expansion of chemical space coverage of ligand-like molecules among major popular classical additive FFs and polarizable FFs, new charge models have been proposed for better accuracy and transferability, new chemical perception of avoiding predefined atom types have been applied, and new automated parameterization toolkits, including machine learning approaches, have been developed for users' convenience.
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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.