ReviewMolecules (Basel, Switzerland)2017
Dynamic Docking: A Paradigm Shift in Computational Drug Discovery.
Review in Molecules (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.
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Who cites it
72 citing papers in PubMed.
- Sartans and Bisartans: Expanding Therapeutic Horizons Through Broad Receptor Interactions and Repurposing Potential.International journal of molecular sciences · 2026Review
- In silico pipeline for GSK 3β inhibitor discovery in Alzheimer's disease using pharmacophore screening, docking, ADME filtering, and MD validation.Scientific reports · 2026Article
- Probing the binding stability of organic UV filters to human SLC transporters using AlphaFold and molecular dynamics simulations.Scientific reports · 2026Article
- Chemical Profiling, Pharmacological Activities, and Toxicity Assessment ofFood science & nutrition · 2026Article
- Critical Assessment of a Structure-Based Pipeline for Targeting the Long Noncoding RNA MALAT1.Journal of chemical information and modeling · 2026Article
- Integrative multi-omics and computational modeling reveal RPL22-driven skin aging mechanisms under PM2.5 exposure and identify high-stability natural inhibitors.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Mutation-Induced Resistance of SARS-CoV-2 MInternational journal of molecular sciences · 2026Article
- HEXB as a Candidate Target Gene in Keloid Radiotherapy: Based on Multi-Omics Analysis and Mendelian Randomization.Clinical, cosmetic and investigational dermatology · 2026Article
- Neuroprotective Effects of Triterpenoids From Rosa laevigata Root: Identification, Molecular Docking, and In Vitro Evaluation for Alzheimer's Disease Treatment.Chemistry & biodiversity · 2026Article
- Molecular dynamics simulation in traditional Chinese medicine research: from molecular mechanisms to multiscale validation.Frontiers in chemistry · 2026Review
- In Silico Identification of Natural-Product Aromatase (CYP19A1) Inhibitors via Integrated Molecular Docking and QSAR Modelling.Bioinformatics and biology insights · 2026Article
- Interaction of major monoterpenes fromFrontiers in pharmacology · 2026Article
- Network Pharmacology and Molecular Docking Identify Medicarpin as a Potent CASP3 and ESR1 Binder Driving Apoptotic and Hormone-Dependent Anticancer Activity.International journal of molecular sciences · 2025Article
- Boosting Drug Discovery: Expanding the Applicability of Fragment Dissolved Molecular Dynamics to Accelerate Binding Mode Elucidation.Journal of chemical information and modeling · 2025Article
- Antioxidant activity at the molecular level: exploring ways of action and computational tools to investigate them.Chemical science · 2025Review
- On Free Energy Calculations in Drug Discovery.Accounts of chemical research · 2025Article
- Theranostic Potential of Copper-64 ATSM Targeting MTHFD2: An In Silico Perspective on Hypoxia-Selective Imaging and Therapy.Cell biochemistry and biophysics · 2025Article
- Development of a Broad-Spectrum Pan-Mpox Vaccine via Immunoinformatic Approaches.International journal of molecular sciences · 2025Article
- Hidden GPCR structural transitions addressed by multiple walker supervised molecular dynamics (mwSuMD).eLife · 2025Article
- Molecular Modelling in Bioactive Peptide Discovery and Characterisation.Biomolecules · 2025Review
12 more citing papers are in PubMed but not listed here.
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5 authors.
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Abstract
Molecular docking is the methodology of choice for studying in silico protein-ligand binding and for prioritizing compounds to discover new lead candidates. Traditional docking simulations suffer from major limitations, mostly related to the static or semi-flexible treatment of ligands and targets. They also neglect solvation and entropic effects, which strongly limits their predictive power. During the last decade, methods based on full atomistic molecular dynamics (MD) have emerged as a valid alternative for simulating macromolecular complexes. In principle, compared to traditional docking, MD allows the full exploration of drug-target recognition and binding from both the mechanistic and energetic points of view (dynamic docking). Binding and unbinding kinetic constants can also be determined. While dynamic docking is still too computationally expensive to be routinely used in fast-paced drug discovery programs, the advent of faster computing architectures and advanced simulation methodologies are changing this scenario. It is feasible that dynamic docking will replace static docking approaches in the near future, leading to a major paradigm shift in in silico drug discovery. Against this background, we review the key achievements that have paved the way for this progress.
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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.