Marco Franco-Pérez

By taking advantage of the fundamental convexity of the exact energy as a function of the number of electrons, we extrapolate the straight-line segments connecting the N and N + 1 states and N – 2 and N – 1 states in a four-state ensemble-inspired model. These segments intersect at a unique point that determines a fractional charge transfer condition,ΔNint−=−λ, which naturally contemplates the reactivity of the cation and neutral forms in terms of their hardness. The energy evaluated at the intersection point, Ni, and the energy evaluated at −λ in the ensemble segment,Nl, give rise to our proposed descriptors that contribute to the electronic panorama of the donation process and describe the reactivity of a set of molecules in specific conditions. The performance of the indicators as nucleophilic indices was evaluated in five chemical reactions: the oxidation of metals, the proton affinity of amines, the stability of coordinated metals that follow the Irving–Williams series, and the kinetic substitution of indoles and alkenes. The nucleophilicity indices proposed are an important complement to the electrophilicity index because they are based on a different response that, although they may lead to similar results with respect to the correlation with a given property, they may be used to recognize dominant aspects of the electronic structure in a chemical interaction. The results obtained support their use as complementary descriptors of the intrinsic electronic contribution to nucleophilic reactivity within specified reaction families.

Psychedelic compounds have shown promising efficacy in the treatment of psychiatric disorders, yet the electronic features of their recognition by the serotonin 2A receptor (5-HT _2A ) remain poorly characterized. Here, we present a quantum-chemical analysis of local ligand–receptor models derived from the experimental 5-HT _2A structures of six ligands: serotonin, psilocin, lysergic acid diethylamide (LSD), lisuride, lumateperone and IHCH-7086. First-sphere (4.5 Å) models were used to benchmark density-functional and MP2-based methods against DLPNO-CCSD(T) for both protonated and neutral ligands, and second-sphere (5.5 Å) models were used to evaluate the effect of extending the receptor environment. Protonation increases the interaction energies by approximately 100–120 kcal/mol and defines two interaction regimes: the range-separated hybrids ωB97X-D3 and ωB97M-V perform best for the protonated complexes, whereas RIJCOSX-SCS-MP2 ^BWI−DZ provides the most uniform agreement for the neutral ones. QTAIM and NCI analyses show that protonation and model expansion mainly redistribute the strength of existing contacts, centered on ASP155, rather than reorganizing the interaction network. Expansion of the model stabilizes all six complexes, with expansion energies ranging from − 7.47 kcal/mol (serotonin) to − 33.10 kcal/mol (IHCH-7086). Within the two structurally related pairs, the psychedelic ligands psilocin and LSD respond more strongly to model expansion than serotonin and lisuride, although this observation does not establish a link with hallucinogenic activity. These results illustrate how interaction energies and electron-density descriptors can be combined to characterize the local electronic environment of serotonergic ligand–receptor complexes.

Paracetamol is a widely used analgesic and antipyretic agent; however, its use is limited by minimal anti‐inflammatory activity and the risk of hepatotoxicity from prolonged oral use or in acute overdose. To address these limitations, four novel phosphorylated paracetamol analogs (2a–2d) were synthesized via a UV‐radical methodology and evaluated through integrated in silico, in vitro, and in vivo for anti‐inflammatory dermal approaches. Molecular docking suggested plausible binding interactions with COX‐1 and COX‐2 for all analogs. In vitro cytotoxicity assays in THP‐1 cells showed that 2a and 2b did not affect cell viability at 100 μM over 24 h. In a TPA‐induced acute ear edema model in CD1 male mice, 2a produced about 50% inhibition of edema at the lowest tested quantity (0.5 mg/ear), representing a fourfold potency advantage over indomethacin at the same amount, while 2b displayed significant anti‐inflammatory and vasoregulatory activity at higher quantities. Computational ADME profiling indicated that all analogs satisfy Lipinski’s drug‐likeness criteria and exhibit low predicted hERG channel risk. These results support N‐phosphorylation of 4‐aminophenol as a viable strategy to improve the topical anti‐inflammatory efficacy of paracetamol analogs.

First order perturbation of the chemical potential and hardness of interacting species is translated into the language of conceptual density functional theory (CDFT), leading to important insights into the possible dominant effects in a reaction.

The accurate identification of static (non-dynamical) electron correlation remains a fundamental challenge in quantum chemistry, particularly for systems that exhibit pronounced multireference (MR) character. In this work, we derive two diagnostics, R MAX and Δ ε MAX , for quantifying the MR nature of molecular systems. Both indices are rigorously derived from the Grand Potential of Fermions (GPFs) and are dependent on natural orbitals, offering complementary perspectives on the degree of static correlation in electronic species. Univocal numerical thresholds are provided to identify cases where static correlation significantly impacts the electronic structure. An evaluation was also performed using two well-established diagnostics, I ND MAX and D2[MP2] , as benchmarks. Our results reveal excellent agreement between the proposed and reference diagnostics, with Pearson correlation coefficients exceeding 0.93 across a customized dataset of 1925 chemical systems, extracted from the GMTKN55 database. The strong correspondence between R MAX , Δ ε MAX and I ND MAX , D2[MP2] confirms that the GPFs provides a physically meaningful and transferable foundation for diagnosing MR character. Their balance of interpretability, computational efficiency, and diagnostic accuracy makes them promising tools for guiding the selection of electronic structure methods and identifying cases where single-reference approaches may be insufficient.

Antiapoptotic proteins represent a major obstacle to the success of anticancer therapies, as they promote the survival of malignant cells and contribute to treatment resistance.

Context: Copper is an essential trace element that plays a central role in redox chemistry and electron transfer processes in biological systems. To gain a deeper understanding of the electronic behavior of copper species, we carried out a comparative evaluation of the Cu ₂ and CuO molecules, focusing on key properties such as ionization energy, electron affinity, vibrational frequencies, bond lengths, and dissociation energies. Cu ₂ serves as a model for dinuclear copper sites present in metalloproteins like tyrosinase and hemocyanin, while CuO captures the essential features of copper-oxygen bonding relevant to copper-dependent oxidases and oxygen-activating enzymes. By systematically benchmarking density functional approximations (DFAs) against high-level CCSD(T) reference calculations or experimental data, we identify the methodologies that best reproduce the electronic and structural properties of these prototypical copper systems. The functional PBE, in particular, demonstrates the most consistent performance across both species. Insights obtained from Cu ₂ and CuO serve as a foundation for understanding more complex copper coordination environments. In this context, we extend our analysis to the Cu(II)/indomethacin complex, illustrating how the lessons learned from the fundamental systems can be applied to biologically relevant copper-ligand interactions. Overall, this study provides a systematic assessment of the accuracy of different DFAs for describing copper-containing species, establishing a solid framework for future investigations of bioinorganic copper chemistry and copper-based drug candidates. Methods: This study employed density functional theory (DFT) alongside thermodynamic cycles to assess the stability of Cu(Indo)₂ and Cu₂(Indo)₄ complexes in ethanol solution. To select suitable computational methods, a benchmark was conducted using Cu(II)/acetate complexes as reference systems. A total of fifteen DFT functionals—BPW91, PBE, B97D, revTPSS, M06-L, M11-L, B3LYP, BHandHLYP, PBE0, ωB97XD, APDF, M06, M06-2X, M06-HF, and TPSSh—were tested in combination with four basis sets: Def2-SVP, Def2-TZVP, 6–31 + G(d,p), and 6–311 + G(d,p). The most reliable functional-basis set combinations were then applied to the copper-indomethacin complexes. In addition, electronic and structural properties of Cu₂ and CuO—such as ionization potentials, electron affinities, vibrational frequencies, equilibrium bond lengths, and spin or magnetic coupling constants—were calculated. Computational results were validated through comparison with available experimental data.

In this study, we introduce a set of novel computational strategies based on second-order Mo̷ller-Plesset perturbation theory (MP2), enhanced through acceleration techniques, such as the resolution of the identity (RI). These approaches are further refined via spin-component scaling (SCS), following Grimme's methodology, and are specifically calibrated for the quantitatively accurate prediction of weak interaction energiesinteractions that play a critical role in biological systems. Among the developed methods, three variants exhibit outstanding performance, surpassing the accuracy of several state-of-the-art, nondynamical electronic structure techniques. Benchmarking against a comprehensive data set of 274 dimerization energies, computed at the CCSD-(T)/CBS level of theory, reveals that these models deliver quantitatively accurate interaction energies. In particular, the RIJCOSX-SCS-MP2^BWI‑DZ method, employing uniquely optimized scaling parameters, demonstrates exceptional accuracy (errors below 1 kcal/mol) while maintaining computational efficiency superior to widely used hybrid and meta-GGA density functional approximations (DFAs). This method reliably captures a range of biologically relevant interactions, including π-π stacking between nucleotide base pairs, halogen bonding, and dissociation energy profiles, showcasing its robustness and predictive power. Given its accuracy, efficiency, and versatility, RI-SCS-MP2^BWI‑DZ, RIJK-SCS-MP2^BWI‑DZ, and RIJCOSX-SCS-MP2^BWI‑DZ emerge as promising and reliable alternatives for modeling weak interactions in complex biological environments.

Recently, Miranda-Quintana, Heidar-Zadeh, and Ayers have elaborated a simple proof of the “Δμ big is good” rule for reactions that are dominated by charge transfer, making use of the smooth quadratic interpolation for fractional electron number and the analysis of several derivatives. In this work, we extend this approach, showing that one can derive a direct relationship of the change in the energy as a function of the change in the absolute value of the chemical potential that implies the “Δμ big is good” rule. In addition, we show that this rule plays an important role in the fulfillment of the hard and soft acids and bases (HSAB), the maximum hardness, and the minimum electrophilicity principles, as anticipated intuitively by Parr.