Utilizing metal-organic framework porosity for efficient antibiotic separation and sustained release

Metal-organic frameworks (MOFs) have emerged as a revolutionary class of nanoporous materials due to their highly tunable porosity and functionality. With the vast number of MOFs being discovered, traditional experimental techniques to identify the best candidates for various applications, including water treatment and drug delivery become time-consuming and expensive. This is where computational screening offers a powerful solution. We present a computational screening strategy using Monte Carlo (MC) simulation to identify the promising MOFs among over 14,000 MOFs for efficient absorption, membrane separation, and sustained delivery of antibiotics (e.g., azithromycin, AZ). The MC simulation was used to calculate the loading capacity and isosteric heat of the AZ absorption. These absorption properties were correlated with several structural characteristics of the MOF, including the largest cavity diameter, pore limiting diameter, accessible volume, helium void fraction, etc. Critical evaluation of the correlation results identified the best MOFs for AZ absorption, separation, and delivery. The results recommended a total of 578 MOFs, with 126 identified as suitable for use as AZ adsorbents or drug carriers, and 452 for use as membranes to separate AZ from water. Furthermore, the adsorption mechanism of the top MOF was analyzed using molecular dynamics simulation and non-covalent interactions. The solvation-free energy of AZ was evaluated in various solvents to identify the most effective solvent for extracting AZ from MOFs, thereby facilitating the regeneration of the MOF.