Reza Ghanavati

In this study, mixed matrix membranes (MMMs) consisting of a continuous polymer phase and a dispersed metal-organic framework (MOF) phase were designed to purify hydrogen from the solar water splitting process. We first identified 20 MOFs with a small pore limiting diameter of less than or equal to 3 Å to restrict the passage of larger molecules such as N2 and O2, thereby allowing the smaller H2 molecule to pass through. These MOFs were assessed for water stability, thermal stability, solvent removal stability, and to identify open-metal sites. We developed atomistic polarizable flexible force fields for these 20 MOFs and used these in molecular dynamics and Monte Carlo simulations to calculate diffusion constants and adsorption isotherms. Using these results, we selected stable MOFs with the highest permeability and ideal selectivity for hydrogen separation. We used experimental data for polymer permeability and selectivity. Finally, we used the Maxwell model to predict the permeability and ideal selectivity of each MMM. We observed that selectivity is primarily governed by polymer properties, and permeability increases by adding MOFs as the dispersed phase. Our computed results showed that MMMs have approximately a twofold reduction in required membrane area compared with pure polymers. Triptycene-based polybenzoxazole (TPBO)-1.0/ARIBOS performed the best, requiring the smallest membrane area.

Gemcitabine, a first-line nucleoside analogue chemotherapy drug, is rapidly inactivated in plasma by cytidine deaminase (CDA), severely limiting its therapeutic efficacy. Porous organic cages (POCs) have emerged as promising drug delivery vehicles due to their discrete, soluble architecture and tunable cavities. Here, we report a comprehensive computational structure-activity relationship (SAR) study of gemcitabine encapsulation across five CC3-based cage variants using molecular docking, molecular dynamics (MD) simulation, and MM-PBSA binding free energy analysis. AutoDock Vina blind docking yielded exclusively endohedral binding (20/20 poses, best ΔG = −5.7 kcal/mol) for pristine CC3. Three independent 200 ns GROMACS MD simulations of pristine CC3 at 300 K reveal stochastic encapsulation-release dynamics consistent with μM-affinity binding (ΔGbind = −13.44 ± 0.41 kcal/mol). A systematic SAR campaign across four additional cage variants establishes critical design rules: N-methyl endo-functionalization (CC3-methyl) eliminates encapsulation by reducing cavity volume; aromatic fluorination (CC3-F12) provides marginal electrostatic improvement but insufficient kinetic stabilization; exo-phenyl functionalization (CC3-exo-phenyl) blocks drug entry entirely; while lowering simulation temperature to 280 K achieves complete, reproducible endohedral encapsulation across all three independent replicas (100% endohedral, mean 2.25 ± 0.25 Å, no exit events in 200 ns each). Probability distribution analysis confirms the transformation from a broad bimodal distribution at 300 K (mean 9.4 Å, 46% endohedral) to a sharp unimodal peak at 280 K (mean 2.25 Å, 100% endohedral). Framework breathing analysis reveals that CC3 is more rigid at 280 K (Rg std = 0.07–0.08 Å) than at 300 K (Rg std = 0.17 Å), consistent with thermally-stabilized encapsulation. These results establish a robust multi-scale computational framework to guide the rational design of porous organic cages for targeted drug delivery applications.

Gemcitabine, a first-line nucleoside analogue chemotherapy drug, is rapidly inactivated in plasma by cytidine deaminase (CDA), severely limiting its therapeutic efficacy. Porous organic cages (POCs) have emerged as promising drug delivery vehicles due to their discrete, soluble architecture and tunable cavities. Here, we report a comprehensive computational structure-activity relationship (SAR) study of gemcitabine encapsulation across five CC3-based cage variants using molecular docking, molecular dynamics (MD) simulation, and MM-PBSA binding free energy analysis. AutoDock Vina blind docking yielded exclusively endohedral binding (20/20 poses, best ΔG = −5.7 kcal/mol) for pristine CC3. Three independent 200 ns GROMACS MD simulations of pristine CC3 at 300 K reveal stochastic encapsulation-release dynamics consistent with μM-affinity binding (ΔGbind = −13.44 ± 0.41 kcal/mol). A systematic SAR campaign across four additional cage variants establishes critical design rules: N-methyl endofunctionalization (CC3-methyl) eliminates encapsulation by reducing cavity volume; aromatic fluorination (CC3-F12) provides marginal electrostatic improvement but insufficient kinetic stabilization; exo-phenyl functionalization (CC3-exo-phenyl) blocks drug entry entirely; while lowering simulation temperature to 280 K achieves complete, reproducible endohedral encapsulation across all three independent replicas (100% endohedral, mean 2.25 ± 0.25 Å, no exit events in 181–190 ns each). Probability distribution analysis confirms the transformation from a broad bimodal distribution at 300 K (mean 9.4 Å, 46% endohedral) to a sharp unimodal peak at 280 K (mean 2.25 Å, 100% endohedral). Framework breathing analysis reveals that CC3 is more rigid at 280 K (Rg std = 0.07–0.08 Å) than at 300 K (Rg std = 0.17 Å), consistent with thermally-stabilized encapsulation. These results establish a robust multi-scale computational framework to guide the rational design of porous organic cages for targeted drug delivery applications.

Correction for ‘An automated protocol to construct flexibility parameters for classical forcefields: applications to metal–organic frameworks’ by Reza Ghanavati et al., RSC Adv., 2024, 14, 22714–22762, https://doi.org/10.1039/D4RA01859A.

In this work, forcefield flexibility parameters were constructed and validated for more than 100 metal–organic frameworks (MOFs). We used atom typing to identify bond types, angle types, and dihedral types associated with bond stretches, angle bends, dihedral torsions, and other flexibility interactions. Our work used Manz's angle-bending and dihedral-torsion model potentials. For a crystal structure containing N_atoms in its unit cell, the number of independent flexibility interactions is 3(N_atoms − 1). Because the number of bonds, angles, and dihedrals is normally much larger than 3(N_atoms − 1), these internal coordinates are redundant. To reduce (but not eliminate) this redundancy, our protocol prunes dihedral types in a way that preserves symmetry equivalency. Next, each dihedral type is classified as non-rotatable, hindered, rotatable, or linear. We introduce a smart selection method that identifies which particular torsion modes are important for each rotatable dihedral type. Then, we computed the force constants for all flexibility interactions together via LASSO regression (i.e., regularized linear least-squares fitting) of the training dataset. LASSO automatically identifies and removes unimportant forcefield interactions. For each MOF, the reference dataset was quantum-mechanically-computed in VASP via DFT with dispersion and included: (i) finite-displacement calculations along every independent atom translation mode, (ii) geometries randomly sampled via ab initio molecular dynamics (AIMD), (iii) the optimized ground-state geometry using experimental lattice parameters, and (iv) rigid torsion scans for each rotatable dihedral type. After training, the flexibility model was validated across geometries that were not part of the training dataset. For each MOF, we computed the goodness of fit (R-squared value) and the root-mean-squared error (RMSE) separately for the training and validation datasets. We compared flexibility models with and without bond–bond cross terms. Even without cross terms, the model yielded R-squared values of 0.910 (avg across all MOFs) ± 0.018 (st. dev.) for atom-in-material forces in the validation datasets. Our SAVESTEPS protocol should find widespread applications to parameterize flexible forcefields for material datasets. We performed molecular dynamics simulations using these flexibility parameters to compute heat capacities and thermal expansion coefficients for two MOFs.