ReviewQRB discovery2022
Towards design of drugs and delivery systems with the Martini coarse-grained model.
Review in QRB discovery, 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
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
16 citing papers in PubMed.
- Artificial intelligence in biologic drug discovery: A review of methodological evolution and therapeutic applications.Acta pharmaceutica Sinica. B · 2026Review
- An optimized contact map for GōMartini 3 enabling conformational changes in protein assemblies.Biophysical journal · 2026Article
- Martini Mapper: An Automated Fragment-Based Mapping Algorithm for Developing Coarse-Grained Models within the Martini 3 Framework.Journal of chemical information and modeling · 2026Article
- Bridging Scales: Coarse-Grained Protein Models in Computational Biology.Advances in experimental medicine and biology · 2026Review
- Automated parametrization of small molecules within the Martini 3 coarse-grained model guided by experimental log P values.Scientific reports · 2025Article
- Navigating chemical space: multi-level Bayesian optimization with hierarchical coarse-graining.Chemical science · 2025Article
- Challenges and opportunities in computational studies for lipid nanoparticle development.npj drug discovery · 2025Review
- Martini3-IDP: improved Martini 3 force field for disordered proteins.Nature communications · 2025Article
- Toward the Evolutionary Optimisation of Small Molecules Within Coarse-Grained Simulations: Training Molecules to Hide Behind Lipid Head Groups.The journal of physical chemistry. B · 2025Article
- Martini compatible coarse-grained model of polyethylenimine for pulmonary gene delivery.Scientific reports · 2025Article
- Recent computational advances in the identification of cryptic binding sites for drug discovery.Bioinformatics advances · 2025Review
- A millisecond coarse-grained simulation approach to decipher allosteric cannabinoid binding at the glycine receptor α1.Nature communications · 2024Article
- Revolutionizing Molecular Design for Innovative Therapeutic Applications through Artificial Intelligence.Molecules (Basel, Switzerland) · 2024Review
- Identification of inhibitors targeting the energy-coupling factor (ECF) transporters.Communications biology · 2023Article
- Alchemical Free Energy Calculations on Membrane-Associated Proteins.Journal of chemical theory and computation · 2023Review
- Effective Molecular Dynamics from Neural Network-Based Structure Prediction Models.Journal of chemical theory and computation · 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
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Coarse-grained (CG) modelling with the Martini force field has come of age. By combining a variety of bead types and sizes with a new mapping approach, the newest version of the model is able to accurately simulate large biomolecular complexes at millisecond timescales. In this perspective, we discuss possible applications of the Martini 3 model in drug discovery and development pipelines and highlight areas for future development. Owing to its high simulation efficiency and extended chemical space, Martini 3 has great potential in the area of drug design and delivery. However, several aspects of the model should be improved before Martini 3 CG simulations can be routinely employed in academic and industrial settings. These include the development of automatic parameterisation protocols for a variety of molecule types, the improvement of backmapping procedures, the description of protein flexibility and the development of methodologies enabling efficient sampling. We illustrate our view with examples on key areas where Martini could give important contributions such as drugs targeting membrane proteins, cryptic pockets and protein-protein interactions and the development of soft drug delivery systems.
Indexed as
Identifiers
What Socratic 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 Socratic graph.