ArticleQRB discovery2022
Challenges and frontiers of computational modelling of biomolecular recognition.
Article in QRB discovery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed, 14 citations in OpenAlex.
- Aptamer Engineering: Strategies for Discovering Functional Nucleic Acids for Next-Generation Diagnostics and Biosensing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Conformational Dynamics and Binding Interactions of SARS-CoV-2 Spike Protein Variants: Omicron, XBB.1.9.2, and EG.5.Journal of chemical information and modeling · 2025Article
- A beginner's approach to deep learning applied to VS and MD techniques.Journal of cheminformatics · 2025Review
- Synthesis, crystal structure, and antiviral evaluation of new imidazopyridine-schiff base derivatives:RSC advances · 2024Article
- Enhanced Sampling for Conformational Changes and Molecular Mechanisms of Human NTHL1.The journal of physical chemistry letters · 2024Article
- Predicting Biomolecular Binding Kinetics: A Review.Journal of chemical theory and computation · 2023Review
- Editorial: Mechanisms, thermodynamics and kinetics of ligand binding revealed from molecular simulations and machine learning.Frontiers in molecular biosciences · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Biomolecular recognition including binding of small molecules, peptides and proteins to their target receptors plays a key role in cellular function and has been targeted for therapeutic drug design. However, the high flexibility of biomolecules and slow binding and dissociation processes have presented challenges for computational modeling. Here, we review the challenges and computational approaches developed to characterize biomolecular binding, including molecular docking, Molecular Dynamics (MD) simulations (especially enhanced sampling) and Machine Learning. Further improvements are still needed in order to accurately and efficiently characterize binding structures, mechanisms, thermodynamics and kinetics of biomolecules in the future.
Indexed as
Identifiers
What OpenQuestion holds
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.