Nov 28, 2025
Molecular Dynamics Simulations for Understanding Protein–Ligand Binding Mechanisms: A Systematic Review protocol
- JABRI Zineb1,
- AMRANI Nisrine1,
- LAABOUDI Ouafae1,
- TABEK Hanae1,
- KACIMI Ghita1
- 1École d'Ingénieur Biomedtech
- Systematic_Study
Protocol Citation: JABRI Zineb, AMRANI Nisrine, LAABOUDI Ouafae, TABEK Hanae, KACIMI Ghita 2025. Molecular Dynamics Simulations for Understanding Protein–Ligand Binding Mechanisms: A Systematic Review protocol. protocols.io https://dx.doi.org/10.17504/protocols.io.4r3l21wp4g1y/v1
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
Created: November 27, 2025
Last Modified: November 28, 2025
Protocol Integer ID: 233643
Keywords: molecular dynamics simulations for understanding protein, ligand binding mechanism, molecular dynamics simulation, ligand binding, systematic review protocol molecular dynamic, computational drug discovery, ligand interaction, analyzing md simulation, binding pathway, md simulation, stability of biomolecular complex, md simulations in this context, cornerstone in computational biophysics, ligand, biomolecular complex, molecular mechanisms at an atomic scale, computational biophysics, molecular mechanism, studying protein, understanding protein, simulation, protein
Abstract
Molecular dynamics (MD) simulations make it possible to explore how proteins and ligands interact at the atomic level, offering insights that experimental methods alone often cannot provide. Over the past decades, MD has become a cornerstone in computational biophysics, providing valuable information about conformational flexibility, binding pathways, and the stability of biomolecular complexes under near-physiological conditions. MD simulations are widely recognized as powerful tools for studying protein–ligand interactions and are frequently applied in computational drug discovery to predict binding affinities and explore molecular mechanisms at an atomic scale. However, it is still unclear how different simulation parameters, software, and methodological choices influence the results and their comparability across studies. There may also be a lack of consensus on the best practices for setting up and analyzing MD simulations in this context. For these reasons, this systematic review aims to collect, analyze, and compare existing MD-based approaches used to study protein–ligand binding. By identifying methodological trends and reporting differences, this work seeks to provide a clearer overview of current practices and help improve reproducibility and standardization in future studies.
Guidelines
Study Design
- Primary computational studies.
- Comparative computational studies.
- Method development studies.
- Validation studies.
- Exclusions:
- Narrative reviews.
- Clinical study designs (RCTs, Cohort studies, case-control studies, cross-sectional studies).
- Reviews or meta-analysis.
- Non-peer-reviewed sources.
- Computational studies unrelated to MD.
Time Frame
No particular time frame, we will select pertinent articles regardless of the time frame. However, we will focus more on the recent ones, published in the last 10 years.
Language
Articles written in English.
- Exclusions:
- Articles that are not written in English.
Setting
In silico studies.
- Exclusions:
- In vitro studies.
Article Specifications
- Only studies with well-defined, experimentally validated protein-ligand complexes are to be considered.
- Results should present quantitative or interpretable outcomes, such as binding energies, affinity constants, or stability metrics of the complex.
- The methodology must be clearly explained, including system preparation, simulation protocols, duration, software, and parameters to ensure reproducibility.
- The publication should be recent, peer-reviewed, and the full text must be accessible for thorough evaluation.
- Exclusions:
- No access to full text or incomplete data.
- Studies with undefined or poorly characterized protein-ligand complexes.
- Studies with unclear or incomplete methodology.
- Non-peer-reviewed publications.
- Studies reporting only qualitative results without quantitative or interpretable outcomes.
Troubleshooting
Objectives
Primary Objective: Our systematic review aims to provide a comprehensive overview of the different molecular dynamics methods and strategies used to simulate and understand protein–ligand binding mechanisms, highlighting their respective strengths and limitations.
Secondary Objective: To critically compare and contrast the available molecular dynamics approaches, and outline future perspectives and emerging trends in the field.
Research Question(s)
PICO:
Population (P): Protein-ligand complexes studied in silico.
Intervention (I): Molecular Dynamics (MD) simulations methods.
Comparison (C): Comparison between the different methods used to studying protein-ligand binding mechanisms in molecular dynamics.
Outcomes: An evaluation of the strengths and limitations of the different molecular dynamics (MD) methods available, as well as the identification of the most optimal approaches for studying protein–ligand binding mechanisms.
- What are the different MD methods used for the simulation of protein-ligand binding mechanisms?
- What are the strengths and limitations of each MD method?
- What are the emerging molecular dynamics (MD) simulation methods currently under development for studying protein–ligand binding mechanisms?
- Among the existing MD approaches, which ones can be considered the most optimal and insightful for accurately characterizing protein–ligand interactions?
Eligibility Criteria (Inclusion/Exclusion)
A) Inclusion Criteria:
Category: Population/Participants
Criteria: MD methods used for the simulation of protein-ligand binding mechanisms.
Category: Intervention/Exposure
Criteria: Use of molecular dynamics (MD) simulations, including both explicit and implicit solvent models, to study the binding mechanisms and molecular interactions between proteins and ligands.
Category: Comparator
Criteria: Comparison between the MD methods
Category: Outcomes
Criteria: - Provide an overview of molecular dynamics (MD) simulation methods for protein–ligand binding. - Critically compare the different MD methods. - Evaluate the strengths and limitations of each method. - Identify the most optimal and effective methods for thorough evaluation.
B) Exclusion Criteria:
Acknowledgements
Module: Research Methodology. Professor: Pr. BOUTIB Amal.