Density Functional Theory calculations employed to describe the transport of medical gases

In nanomedicine, gas therapy has emerged as an innovative and promising approach for treating various pathological conditions, especially in the fight against cancer. Medical gases, such as carbon monoxide (CO), ammonia (NH₃), and hydrogen sulfide (H₂S), have shown significant therapeutic potential. They can complement conventional approaches or, in some cases, act independently.1 However, one of the main challenges of this strategy lies in the need for strict control over the administration of these gases once the gas concentrations directly influence their biological effects – while high concentrations can induce apoptosis in tumor cells, lower levels can stimulate metastatic progression.1 This reinforces the importance of developing controlled release systems, ensuring adequate bioavailability, and minimizing adverse effects.

Nanomaterials have proven essential in the development of efficient drug delivery systems,2 and hold great potential for the transport and controlled release of medical gases. Their unique physicochemical properties are key to overcoming the main challenges of this therapeutic approach. These properties include high specific surface area, favoring the adsorption of large quantities of gas; porosity, which allows encapsulation and control of the diffusion of gas molecules; and the possibility of chemical functionalization, allowing modulation of the interaction with the gas and the biological environment. In addition, biocompatibility and, in some cases, the ability to dissolve in physiological fluids are crucial to guaranteeing safety and therapeutic efficacy.3 Various types of nanomaterials have been explored for this purpose. For example, carbon nanotubes and graphene nanoflakes doped with alkali metals, have demonstrated a high capacity for storing hydrogen and other gaseous molecules, thanks to their conjugated structure and the possibility of electronic modification via doping.4 Metallic nanoparticles, such as gold and platinum, are effective for anchoring gaseous ligands and promoting release reactions under specific stimuli, such as light or pH.5,6 Biodegradable polymers, such as polylactic acid or polyethylene glycol-poly(lactic-co-glycolic acid) copolymers, enable the creation of biologically responsive systems that release the gas gradually and safely.4

Each class of nanomaterial offers distinct advantages but also presents challenges. Carbonaceous materials, for example, have high stability and adsorption capacity, but their controlled functionalization remains a challenge.7 Metal nanoparticles respond rapidly to stimuli but may pose risks related to toxicity and tissue accumulation. Biodegradable polymers, while highly biocompatible and easily eliminated by the body, can be limited in their gas-loading capacity and stability under certain physiological conditions. Selecting the appropriate nanomaterial is crucial, as different structures can significantly impact the stability, release kinetics, and selectivity of gases in the biological environment.7 Therefore, a detailed understanding of gas-nanomaterial interaction, diffusion, and stability mechanisms in the physiological environment is essential for advancing medical gas therapy. In this scenario, Density Functional Theory (DFT) has stood out as a fundamental computational tool for modeling gas-surface interactions in nanomaterials.8 This approach makes it possible to predict electronic and energetic properties, helping to identify the most promising materials for the transport and programmed release of therapeutic gas systems (Figure 1). In addition, DFT provides a detailed view of adsorption mechanisms, allowing the refinement of nanotechnological strategies to optimize the selective delivery of medical gases.

Figure 1.

Schematic representation of the interaction between a functionalized nanoparticle and a gas molecule, highlighting the role of the targeting system in the specific recognition of the tumor microenvironment.

Created with the assistance of artificial intelligence (ChatGPT, Open AI, 2025). The final content was verified and edited by the authors. DFT: Density Functional Theory.

As we have discussed in a recent review, DFT calculations have been widely employed to describe the interaction of nanomaterials with medical gases.8 However, these works focus more on detecting medical gases than transport and delivery. Nevertheless, the same procedure could be applied to propose nanomaterials for medical gas delivery, and even some results from works that dealt with detecting these gases can be useful for applications in delivery systems. This assumption makes sense once the same quantities (binding energy, charge transfer, and bonding distances) are important for both applications. First, these quantities are essential to determine whether an interaction between the nanomaterial and medical gas occurs or not. For both applications, the bonding must be strong enough that the gas can be detected or delivered. However, if the bonding is too strong the gas will not be released, which would not characterize a delivery system and cause issues with using a sensor more than once. An important difference appears when it comes to the materials employed. Indeed, it is a concern when considering a sensor that the materials will not be dangerous for human health and the environment. However, when we think about a delivery system that will enter the human body, there are additional concerns: the materials must be biodegradable and biocompatible. For this reason, a nanomaterial that shows potential as a sensor for a particular medical gas must meet these conditions to be proposed as a candidate for an efficient medical gas delivery system.

One good example was provided by Abd-Elkader et al.,9 who studied the adsorption of various gases, namely CO, carbon dioxide (CO₂), sulfur dioxide (SO₂), H₂S, nitrogen dioxide (NO₂). NH₃, and ozone (O₃), on titanium dioxide (TiO₂) quantum dots (QDs) via DFT calculations.9 By employing the hybrid functional M06-2X with a 6–31G basis set, the authors have shown that the proposed QDs are stable. To understand the interaction between the gases and the QDs, the binding energy, charge transfer, recovery time, as well as the influence of each gas on the electronic and optical properties of the QDs were investigated. Although the focus was to explore the applicability of TiO₂-QDs as gas sensors, the results can be interpreted to propose these nanomaterials as efficient gas transport systems. For instance, CO and H₂S present binding energies of –0.38 and –0.44 eV, which enables the gases to be released, while ammonia, another medical gas, presents a higher binding energy of –1.27 eV. These negative values mean that the gas adsorption is energetically favorable, and the values are small enough to permit the gases to be released, which is essential for the reusability of a sensor. Regarding a gas transport system, the binding energy must also be small enough to guarantee the gas release, so the results obtained by Abd-Elkader et al.9 could lead to the proposed TiO₂-QDs as a promising medical gas transport system.

Another example was provided by a computational and experimental study on releasing CO from aryl-propargyl dicobalt(0) hexacarbonyl derivatives.10 The authors demonstrated that these compounds are effective CO-releasing molecules by employing hybrid functionals and basis sets optimized for transition metal systems. Key parameters such as bond dissociation energy, charge transfer, and reaction kinetics were investigated to understand CO release mechanisms. The results suggest that these cobalt-based complexes provide a tunable platform for CO delivery, with binding energies that facilitate controlled gas release under physiological conditions.

DFT calculations revealed the nature of the metal-carbonyl bonding in dicobalt hexacarbonyl derivatives, showing that the substituents with a negative mesomeric effect (-M), such as the –NO₂ group, facilitate CO release. This occurs due to a reduction in the interaction between the cobalt d-electrons and the non-bonding π* orbitals of the carbonyl groups, weakening the back-donation effect and making CO dissociation more favorable. Furthermore, computational models predict that CO release is an endothermic process, with a bond dissociation energy of around 25 kcal/mol, indicating that spontaneous release is unlikely without the presence of a specific acceptor, such as myoglobin.

Energy profiles and reaction mechanisms predicted via DFT align with experimental findings, confirming the role of electronic effects in tuning CO release. Additionally, implicit and explicit solvation models were used to refine the computational predictions, demonstrating that the presence of nucleophilic species in the medium significantly enhances CO release. These insights reinforce the importance of computational approaches in rationalizing experimental observations and optimizing molecular designs for biomedical applications.

Although the main objective was to evaluate the CO release capabilities of these complexes, the findings can be extended to propose such molecules as potential gas carriers in biomedical applications. The calculated binding energies indicate that CO release can be precisely modulated, a crucial factor for therapeutic gas delivery. Future research should focus on refining computational methodologies, incorporating dynamic effects, and integrating multi-scale modeling approaches to enhance the predictive power of DFT in medical gas transport studies.

Even though DFT can provide a good description of the interaction between nanomaterials and medical gases, some concerns should be addressed. Medical gases generally interact in environments where solvent effects and pH play an important role. Some DFT implementations allow for the implicit inclusion of the solvent, leading to a more accurate and realistic description of nanomaterial–medical gas conjugates. Another important concern is that DFT is not able to attest to the biocompatibility of new nanomaterials. Moreover, a biocompatible material in bulk form may not necessarily retain this property when confined in one or more dimensions as a nanomaterial. Even in such cases, however, DFT remains a valuable tool for guiding both theoretical and experimental research. Furthermore, an effective medical gas delivery system must ensure that the conjugated nanomaterial reaches the target region, such as a tumor. Therefore, DFT simulations should also include target molecules to evaluate whether their presence affects the adsorption of medical gases onto nanomaterials. Finally, when using DFT to propose nanomaterials as gas sensors, calculations typically consider only a single gas molecule. This approach is valid for sensor applications, as the goal is to detect even a small gas concentration. However, high gas concentrations are often required in therapeutic applications to achieve effective treatment and minimize undesirable effects. Consequently, when employing DFT to design medical gas delivery systems, multiple gas molecules should be considered to predict the influence of gas concentration on adsorption.

Once the transport of medical gas by nanomaterials to improve the efficiency and safety of cancer disease treatment is an emerging field of investigation, we believe that DFT calculations should be employed to describe the mechanism of interaction in these conjugated systems. It is known that developing and approbating new medications and treatment protocols take a lot of time, in some cases a few years. DFT calculations can provide valuable insights to guide further research, starting with the characterization of biodegradable and biocompatible nanomaterials, which can be achieved by determining the most stable structure and describing their electronic properties. The interaction between a nanomaterial and a medical gas can be investigated as a next step. Binding energy values can show whether the conjugated system is favorable and indicate which configuration is more probable to occur. Additional analyses like bonding distances, charge transfer, projected density of states, and localized density of states can be employed to confirm the interaction. These procedures could provide valuable results, which would reduce costs and time in the search for an effective and harmless cancer treatment.