Metal Complex Modeling Service

Metal complexes are ubiquitous and essential components of biological systems, exhibiting a remarkable diversity in their structure and function. Metal complex modeling, a core competency at CD ComputaBio, provides a powerful lens through which to investigate these intricate molecules, offering invaluable insights for understanding fundamental biological processes and for the discovery and design of novel therapeutic agents inspired by nature.

Introduction to Metal Complex

Metal complexes are chemical species comprising a central metal atom or ion that is bonded to a surrounding array of molecules or ions, known as ligands. These ligands, which can be inorganic or organic, donate one or more electron pairs to the central metal ion, forming coordinate covalent bonds. The nature of the central metal ion, its oxidation state, and the identity, number, and spatial arrangement of the ligands dictate the complex's overall charge, geometry, stability, and reactivity. In biological systems, metal complexes play indispensable roles in a myriad of processes, acting as catalytic centers in enzymes, structural components in proteins, and crucial agents in electron transfer and oxygen transport.

Fig 1. Structures and DFT studies of three mixed-ligand metal complexes. (Ibragimov A B, et al., 2021)

Metal Complex Modeling

Metal complex modeling encompasses a suite of computational methods aimed at predicting, analyzing, and visualizing the structural, electronic, and dynamic properties of molecules containing metal ions. These methods range from classical molecular mechanics approaches, which employ force fields to describe interatomic interactions, to sophisticated quantum mechanical methods, such as density functional theory (DFT) and ab initio calculations, which explicitly treat the electronic structure of the system. Molecular dynamics (MD) simulations further allow for the exploration of the time-dependent behavior of metal complexes, providing insights into their conformational flexibility, interactions with their biological environment (e.g., proteins, nucleic acids, membranes), and binding affinities.

Fig 2. Modeling Zinc complexes using neural networks. (Jin H, et al., 2022)

Our Services

CD ComputaBio leverages a diverse arsenal of computational tools and expertise to provide comprehensive metal complex modeling services, enabling our clients to gain a deeper understanding of these critical biomolecules. This includes predicting the coordination geometry around the metal center, calculating binding energies with potential drug targets, and elucidating reaction mechanisms involving metal-containing enzymes or cofactors.

By Types

By Modeling

Service Highlights

• Accurate Modeling System
  • Supports quantum mechanics (QM) and molecular mechanics (MM) modeling of transition metal and rare earth metal complexes.
  • Handles key parameters including coordination configuration, spin state analysis, and solvation effects.
  • Capable of modeling complex systems such as single/multi-core complexes and organometallic frameworks.
• Multi-Scale Simulation Scheme
  • Density Functional Theory (DFT) quantum calculations.
  • Molecular dynamics simulations (up to microsecond timescale).
  • QM/MM hybrid calculations (suitable for biological macromolecular systems).

CD ComputaBio's deep-rooted expertise in both computational and inorganic chemistry, coupled with cutting-edge tools and a client-centric approach, ensures transformative outcomes for drug discovery, energy solutions, and advanced materials. Whether optimizing a catalytic reaction or decoding metalloprotein mechanisms, CD ComputaBio delivers actionable insights that bridge the gap between simulation and reality. Partner with us to leverage computational power that accelerates innovation while minimizing risks and costs. Contact us today to learn more about how our services can empower your research.

References:

1. Ibragimov A B, Ashurov J M, Ibragimov A B, et al. Synthesis of the three mixed-ligand metal complexes and one organic salt of 3, 5-dinitrobenzoic acid for biopharmaceutical optimization through monoethanolamine: structures and DFT studies of complexes[J]. Journal of Chemical Crystallography, 2021, 51: 405-417.
2. Jin H, Merz Jr K M. Modeling Zinc Complexes Using Neural Networks[J]. Journal of Chemical Information and Modeling, 2024, 64(8): 3140-3148.

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