Macromolecule-Macromolecule Interaction Service
Understanding macromolecular interactions is critical for unraveling biological processes, designing effective therapies, and optimizing protein engineering. Determining these interactions experimentally is challenging, time-consuming, and costly. Computational methods such as molecular dynamics simulations have emerged as powerful tools to complement experimental studies. CD ComputaBio can provide a variety of algorithms to observe the motion and interactions of atoms and molecules in macromolecular interactions over time, allowing us to observe and analyze the dynamic behavior of macromolecules at the atomic level.
Introduction to Macromolecule-Macromolecule Interaction
Biomolecular interactions mediated by macromolecules, including proteins, nucleic acids, enzymes and ligands, form the basis of biochemistry and coordinate different biological pathways. Therefore, understanding macromolecular interactions such as protein-protein interactions, protein-DNA interactions, protein-RNA interactions and protein-ligand interactions helps to deeply understand biological processes and develop and design new treatments. The development of computational biology provides powerful tools for the study of macromolecular interactions, allowing scientists to study these interactions with higher resolution and a wider range, thereby supporting:
Fig. 1 Different paradigms for studying protein-RNA interactions with deep learning. (Wei J, et al.; 2022)
New Drug Development
Computational models can accelerate the drug discovery process, improve R&D efficiency and reduce costs through virtual screening and optimization.
Disease Mechanism Research
Simulate the effects of mutants on the structure and function of macromolecules, and help reveal the molecular mechanisms of genetic diseases and cancer.
Protein Engineering
Design proteins and enzymes with specific functions for industrial, biomedical and environmental applications.
Systems Biology
Establish computational models of complex processes in cells, predict the behavior of biological systems, and guide experimental design.
Our Services
Thanks to advanced algorithms and high-performance computing analysis platforms, CD ComputaBio provides comprehensive and customized solutions for macromolecule-macromolecule interaction analysis. Our high-performance computing analysis platform is equipped with a series of advanced analysis tools and software, providing one-stop services from data preparation, simulation operation to result analysis, including but not limited to:
Protein-Ligand Interaction Modeling Service
We fully support modeling and simulation activities of interactions between proteins and macromolecular ligands, such as proteins, DNA, RNA, and enzymes. By predicting how ligands bind to target proteins, we help you understand binding sites, binding modes, and affinity. This critical information can support the screening and optimization of potential drug molecules and the understanding of key biological processes.
Antibody-Antigen Interaction Modeling Service
Our antibody-antigen interaction modeling service focuses on simulating the interaction between antibodies and their antigens. By building an antibody-antigen complex model, we can help you analyze binding sites, identify key amino acid residues, and understand the binding mechanism to support your antibody drug design, vaccine development, and immune response research.
Protein-Protein Interaction Modeling Service
Our protein-protein interaction modeling service focuses on simulating and predicting the interaction relationship between proteins. Molecular docking and computational simulation methods are used to predict the possible interaction modes and binding sites between two or more proteins, helping you understand the structural basis and functional mechanism of protein interaction, thereby supporting signal transduction research and drug development.
Protein-DNA/RNA Interaction Modeling Service
Our scientists simulate the interaction between proteins and DNA or RNA. By constructing a three-dimensional model of the protein-nucleic acid complex, the binding sites and sequence specificity of proteins on DNA or RNA are predicted, and the spatial structure of their interaction is revealed.
Protein-Peptide Interaction Modeling Service
Peptides can act as signal molecules, receptor ligands, enzyme inhibitors, etc., and participate in regulating the function and activity of proteins. Our protein-peptide interaction modeling service aims to accurately predict the binding mode and affinity of proteins and peptides through computational simulation, helping you to deeply understand their interaction mechanism, and support new drug development and basic research.
Protein-Enzyme Interaction Modeling Service
Enzymes are key biomacromolecules that catalyze biochemical reactions. They interact with protein substrates, inhibitors, activators, etc., and regulate various biochemical reactions in life processes. Our scientists use advanced computational simulation technology to deeply analyze the binding mode between proteins and enzymes and identify active sites and key residues.
RNA-RNA Interaction Modeling Service
Our RNA-RNA interaction modeling service focuses on using computational biology methods to help you predict and analyze key interactions, conformational changes, hydrogen bond networks, stacking effects, etc., between RNA molecules. These informations are strong support for gene expression regulation research, and new drug development, such as antisense oligonucleotide design and RNA interference (RNAi) therapy development.
DNA-DNA Interaction Modeling Service
The service is designed to use computational biology and computational chemistry methods to simulate and analyze the interactions between DNA molecules, including the formation of DNA double helix, triplex, quadruplex, and DNA superhelix structures. This allows you to deeply understand the interaction mechanism in biological processes such as gene regulation, genetic recombination, and DNA repair.
Methods for Macromolecule-Macromolecule Interaction Analysis
Molecular Docking
Molecular docking algorithms are designed to predict how two macromolecules bind to each other, as well as their binding conformations and binding energies. Our team of experts uses advanced computational tools such as ZDOCK, HADDOCK, and ClusPro to provide strong support for studying macromolecular interactions. These tools can help you simulate and predict how macromolecules interact, find possible binding sites and optimal binding conformations.
Molecular Dynamics Simulations
Our scientists use first-class tools such as GROMACS, AMBER, NAMD, etc., to study the dynamic process and stability of macromolecular interactions by simulating the movement of molecules over time. Importantly, we also can use advanced enhanced sampling techniques to overcome energy barriers and sample the conformational space of macromolecule-macromolecule interactions on a longer time scale.
Binding Free Energy Calculations
Our computational biologists use rigorous methods such as MM/PBSA and MM/GBSA to calculate accurate binding free energies. These calculations provide a quantitative understanding of binding affinity and can be used for virtual screening and lead compound optimization.
Homology Modeling
Homology modeling provides reliable models for the study of macromolecules, such as proteins and nucleic acids, that lack experimentally resolved three-dimensional structures. Our scientific team combines homology modeling with molecular docking and molecular dynamics simulation to build and optimize complex models and deeply explore the details of macromolecule-macromolecule interactions.
Coarse-Grained Modeling
Coarse-grained modeling simplifies complex macromolecular systems by reducing the number of particles and interactions that need to be considered. Our team utilizes advanced coarse-grained simulation tools and force fields like MARTINI to study large-scale conformational changes and assembly processes in macromolecule-macromolecule interactions. This method provides valuable insights into the collective behaviors and dynamics of macromolecular complexes, complementing the detailed views obtained from all-atom simulations.
Service Highlights
Precision and Insight
Our detailed analyses provide a comprehensive understanding of molecular interactions, guiding rational drug design decisions with precision.
Time and Cost Efficiency
By leveraging computational methods, we accelerate the drug discovery process, saving time and resources compared to traditional experimental approaches.
Fast Turnaround Time
We endeavor to deliver results as quickly as possible, without compromising the quality of service.
CD ComputaBio utilizes state-of-the-art tools, algorithms, and expertise to provide comprehensive services for macromolecule-macromolecule interactions. By utilizing MD simulations, we provide insight into protein-protein interactions, protein-peptide interactions, and protein-enzyme interactions. Our services contribute to drug discovery, protein engineering, and basic biology research, helping scientists gain a deeper understanding of macromolecular interactions. Please don't hesitate to contact us if you are interested in our services.
References:
- Wei J, et al. Protein-RNA interaction prediction with deep learning: structure matters. Brief Bioinform. 2022;23(1):bbab540.
- Rizzuti B. Molecular simulations of proteins: From simplified physical interactions to complex biological phenomena. Biochim Biophys Acta Proteins Proteom. 2022;1870(3):140757.
- Kumar V, et al. Protein-Protein Interaction Studies Using Molecular Dynamics Simulation. Methods Mol Biol. 2023;2652:269-283.
- Sriramulu DK, et al. Analysis of protein-protein interface with incorporating low-frequency molecular interactions in molecular dynamics simulation. J Mol Graph Model. 2023;122:108461.
* For Research Use Only.
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