Mechanism of non-phenolic substrate oxidation by the fungal laccase Type 1 copper site from Trametes versicolor: the case of benzo[a]pyrene and anthracene.

Laccases (EC 1.10.3.2) are multicopper oxidases with the capability to oxidize diverse phenolic and non-phenolic substrates. While the molecular mechanism of their activity towards phenolic substrates is well-established, their reactivity towards non-phenolic substrates, such as polycyclic aromatic hydrocarbons (PAHs), remains unclear. To elucidate the oxidation mechanism of PAHs, particularly the activation mechanism of the sp2 aromatic C-H bond, we conducted a density functional theory investigation on the oxidation of two PAHs (anthracene and benzo[a]pyrene) using an extensive model of the T1 copper catalytic site of the fungal laccase from Trametes versicolor.

Molecular Dynamics for the Optimal Design of Functionalized Nanodevices to Target Folate Receptors on Tumor Cells.

Atomistic details on the mechanism of targeting activity by biomedical nanodevices of specific receptors are still scarce in the literature, where mostly ligand/receptor pairs are modeled. Here, we use atomistic molecular dynamics (MD) simulations, free energy calculations, and machine learning approaches on the case study of spherical TiO2 nanoparticles (NPs) functionalized with folic acid (FA) as the targeting ligand of the folate receptor (FR). We consider different FA densities on the surface and different anchoring approaches, i.e., direct covalent bonding of FA γ-carboxylate or through polyethylene glycol spacers. By molecular docking, we first identify the lowest energy conformation of one FA inside the FR binding pocket from the X-ray crystal structure, which becomes the starting point of classical MD simulations in a realistic physiological environment. We estimate the binding free energy to be compared with the existing experimental data. Then, we increase complexity and go from the isolated FA to a nanosystem decorated with several FAs. Within the simulation time framework, we confirm the stability of the ligand-receptor interaction, even in the presence of the NP (with or without a spacer), and no significant modification of the protein secondary structure is observed. Our study highlights the crucial role played by the spacer, FA protonation state, and density, which are parameters that can be controlled during the nanodevice preparation step.

Assessing the Performance of Non-Equilibrium Thermodynamic Integration in Flavodoxin Redox Potential Estimation.

Flavodoxins are enzymes that contain the redox-active flavin mononucleotide (FMN) cofactor and play a crucial role in numerous biological processes, including energy conversion and electron transfer. Since the redox characteristics of flavodoxins are significantly impacted by the molecular environment of the FMN cofactor, the evaluation of the interplay between the redox properties of the flavin cofactor and its molecular surroundings in flavoproteins is a critical area of investigation for both fundamental research and technological advancements, as the electrochemical tuning of flavoproteins is necessary for optimal interaction with redox acceptor or donor molecules. In order to facilitate the rational design of biomolecular devices, it is imperative to have access to computational tools that can accurately predict the redox potential of both natural and artificial flavoproteins. In this study, we have investigated the feasibility of using non-equilibrium thermodynamic integration protocols to reliably predict the redox potential of flavodoxins. Using as a test set the wild-type flavodoxin from Clostridium Beijerinckii and eight experimentally characterized single-point mutants, we have computed their redox potential. Our results show that 75% (6 out of 8) of the calculated reaction free energies are within 1 kcal/mol of the experimental values, and none exceed an error of 2 kcal/mol, confirming that non-equilibrium thermodynamic integration is a trustworthy tool for the quantitative estimation of the redox potential of this biologically and technologically significant class of enzymes.

Selective events at individual sites underlie the evolution of monkeypox virus clades.

In endemic regions (West Africa and the Congo Basin), the genetic diversity of monkeypox virus (MPXV) is geographically structured into two major clades (Clades I and II) that differ in virulence and host associations. Clade IIb is closely related to the B.1 lineage, which is dominating a worldwide outbreak initiated in 2022. Lineage B.1 has however accumulated mutations of unknown significance that most likely result from apolipoprotein B mRNA editing catalytic polypeptide-like 3 (APOBEC3) editing. We applied a population genetics-phylogenetics approach to investigate the evolution of MPXV during historical viral spread in Africa and to infer the distribution of fitness effects. We observed a high preponderance of codons evolving under strong purifying selection, particularly in viral genes involved in morphogenesis and replication or transcription. However, signals of positive selection were also detected and were enriched in genes involved in immunomodulation and/or virulence. In particular, several genes showing evidence of positive selection were found to hijack different steps of the cellular pathway that senses cytosolic DNA. Also, a few selected sites in genes that are not directly involved in immunomodulation are suggestive of antibody escape or other immune-mediated pressures. Because orthopoxvirus host range is primarily determined by the interaction with the host immune system, we suggest that the positive selection signals represent signatures of host adaptation and contribute to the different virulence of Clade I and II MPXVs. We also used the calculated selection coefficients to infer the effects of mutations that define the predominant human MPXV1 (hMPXV1) lineage B.1, as well as the changes that have been accumulating during the worldwide outbreak. Results indicated that a proportion of deleterious mutations were purged from the predominant outbreak lineage, whose spread was not driven by the presence of beneficial changes. Polymorphic mutations with a predicted beneficial effect on fitness are few and have a low frequency. It remains to be determined whether they have any significance for ongoing virus evolution.

Activation of the N2 molecule by means of low-valence complexes of calcium and magnesium.

Nitrogen gas is a highly inert molecule and its activation under mild conditions represents a crucial goal in current research. In a recent study, the discovery of low-valence Ca(I) compounds capable of coordinating and reducing N2 was reported [B. Rösch, T. X. Gentner, J. Langer, C. Färber, J. Eyselein, L. Zhao, C. Ding, G. Frenking and S. Harder, Science, 2021, 371, 1125]. The study of low-valence alkaline earth complexes represents a new horizon in inorganic chemistry and demonstrates examples of spectacular reactivity. For example, complexes of the [BDI]2Mg2 type are selective reducing reagents in both organic and inorganic synthesis reactions. To date, however, no activity of Mg(I) complexes in the activation of the nitrogen molecule has been reported. By computational studies, in the present work, we investigated the analogies and differences of low-valence Ca(I) and Mg(I) complexes in the coordination, activation and protonation of N2. We have shown that the possibility of alkaline earth metals to employ atomic orbitals of the d type is reflected in the differences in the N2 binding energy and its coordination mode (end-on vs. side-on), as well as in the spin state of the resulting adduct (singlet vs. triplet). These divergences are finally observed in the subsequent protonation reaction, which turned out to be prohibitive in the presence of Mg.

Recent Theoretical Insights into the Oxidative Degradation of Biopolymers and Plastics by Metalloenzymes.

Molecular modeling techniques have become indispensable in many fields of molecular sciences in which the details related to mechanisms and reactivity need to be studied at an atomistic level. This review article provides a collection of computational modeling works on a topic of enormous interest and urgent relevance: the properties of metalloenzymes involved in the degradation and valorization of natural biopolymers and synthetic plastics on the basis of both circular biofuel production and bioremediation strategies. In particular, we will focus on lytic polysaccharide monooxygenase, laccases, and various heme peroxidases involved in the processing of polysaccharides, lignins, rubbers, and some synthetic polymers. Special attention will be dedicated to the interaction between these enzymes and their substrate studied at different levels of theory, starting from classical molecular docking and molecular dynamics techniques up to techniques based on quantum chemistry.

Normal vs. Inverted Ordering of Reduction Potentials in [FeFe]-Hydrogenases Biomimetics: Effect of the Dithiolate Bulk.

Three hexacarbonyl diiron dithiolate complexes [Fe2 (CO)6 (µ-(SCH2 )2 X)] with different substituted bridgeheads (X=CH2 , CEt2 , CBn2 (Bn=CH2 C6 H5 )), have been studied under the same experimental conditions by cyclic voltammetry in dichloromethane [NBu4 ][PF6 ] 0.2 M. DFT calculations were performed to rationalize the mechanism of reduction of these compounds. The three complexes undergo a two-electron transfer whose the mechanism depends on the bulkiness of the dithiolate bridge, which involves a different timing of the structural changes (Fe-S bond cleavage, inversion of conformation and CO bridging) vs redox steps. The introduction of a bulky group in the dithiolate linker has obviously an effect on normally ordered (as for propanedithiolate (pdt)) or inverted (pdtEt2 , pdtBn2 ) reduction potentials. Et→Bn replacement is not theoretically predicted to alter the geometry and energy of the most stable mono-reduced and bi-reduced forms but such a replacement alters the kinetics of the electron transfer vs the structural changes.

A De Novo-Designed Type 3 Copper Protein Tunes Catechol Substrate Recognition and Reactivity.

De novo metalloprotein design is a remarkable approach to shape protein scaffolds toward specific functions. Here, we report the design and characterization of Due Rame 1 (DR1), a de novo designed protein housing a di-copper site and mimicking the Type 3 (T3) copper-containing polyphenol oxidases (PPOs). To achieve this goal, we hierarchically designed the first and the second di-metal coordination spheres to engineer the di-copper site into a simple four-helix bundle scaffold. Spectroscopic, thermodynamic, and functional characterization revealed that DR1 recapitulates the T3 copper site, supporting different copper redox states, and being active in the O2 -dependent oxidation of catechols to o-quinones. Careful design of the residues lining the substrate access site endows DR1 with substrate recognition, as revealed by Hammet analysis and computational studies on substituted catechols. This study represents a premier example in the construction of a functional T3 copper site into a designed four-helix bundle protein.

Conjugation of gold nanoparticles with multidentate surfactants for enhanced stability and biological properties.

This work originated from the need to functionalize surfactant-coated inorganic nanoparticles for biomedical applications, a process that is limited by excess unbound surfactant. These limitations are connected to the bioconjugation of targeting molecules that are often in equilibrium between the free aliquot in solution and that which binds the surface of the nanoparticles. The excess in solution can play a role in the biocompatability in vitro and in vivo of the final nanoparticles stock. For this purpose, we tested the ability of common surfactants - monothiolated polyethylene glycol and amphiphilic polymers - to colloidally stabilize nanoparticles as excess surfactant is removed and compared them to newly appearing multidentate surfactants endowed with high avidity for inorganic nanoparticles. Our results showed that monothiolated polyethylene glycol or amphiphilic polymers have an insufficient affinity to the nanoparticles and as the excess surfactant is removed the colloidal stability is lost, while multidentate high-avidity surfactants excel in the same regard, possibly allowing improvement in an array of nanoparticle applications, especially in those stated.

Exome Sequencing in an ADSHE Family: VUS Identification and Limits.

Autosomal dominant sleep-related hypermotor epilepsy (ADSHE) is the familial form of a focal epilepsy characterized by hyperkinetic focal seizures, mainly arising during non-rapid eye movements (NREM) sleep. Mutations associated with ADSHE account for a small proportion of the genetically determined cases, suggesting the existence of other disease-causing genes. Here, we reported the results obtained by performing trio-based whole-exome sequencing (WES) in an Italian family showing ADSHE and investigated the structural impact of putative variants by in silico modeling analysis. We identified a p.(Trp276Gly) variant in MOXD1 gene encoding the monooxigenase DBH like 1 protein, cosegregating with the disease and annotated as VUS under the ACMG recommendations. Structural bioinformatic analysis predicted a high destabilizing effect of this variant, due to the loss of important hydrophilic bonds and an expansion of cavity volume in the protein hydrophobic core. Although our data support a functional effect of the p.(Trp276Gly) variant, we highlight the need to identify additional families carrying MOXD1 mutations or functional analyses in suitable models to clarify its role in ADSHE pathogenesis. Moreover, we discuss the importance of VUS reporting due to the low rate of pathogenic variant identification by NGS in epilepsy and for future reinterpretation studies.

Machine Learning for Efficient Prediction of Protein Redox Potential: The Flavoproteins Case.

Determining the redox potentials of protein cofactors and how they are influenced by their molecular neighborhoods is essential for basic research and many biotechnological applications, from biosensors and biocatalysis to bioremediation and bioelectronics. The laborious determination of redox potential with current experimental technologies pushes forward the need for computational approaches that can reliably predict it. Although current computational approaches based on quantum and molecular mechanics are accurate, their large computational costs hinder their usage. In this work, we explored the possibility of using more efficient QSPR models based on machine learning (ML) for the prediction of protein redox potential, as an alternative to classical approaches. As a proof of concept, we focused on flavoproteins, one of the most important families of enzymes directly involved in redox processes. To train and test different ML models, we retrieved a dataset of flavoproteins with a known midpoint redox potential (Em) and 3D structure. The features of interest, accounting for both short- and long-range effects of the protein matrix on the flavin cofactor, have been automatically extracted from each protein PDB file. Our best ML model (XGB) has a performance error below 1 kcal/mol (∼36 mV), comparing favorably to more sophisticated computational approaches. We also provided indications on the features that mostly affect the Em value, and when possible, we rationalized them on the basis of previous studies.

Characterization of the p.L145F and p.S135N Mutations in SOD1: Impact on the Metabolism of Fibroblasts Derived from Amyotrophic Lateral Sclerosis Patients.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the loss of the upper and lower motor neurons (MNs). About 10% of patients have a family history (familial, fALS); however, most patients seem to develop the sporadic form of the disease (sALS). SOD1 (Cu/Zn superoxide dismutase-1) is the first studied gene among the ones related to ALS. Mutant SOD1 can adopt multiple misfolded conformation, lose the correct coordination of metal binding, decrease structural stability, and form aggregates. For all these reasons, it is complicated to characterize the conformational alterations of the ALS-associated mutant SOD1, and how they relate to toxicity. In this work, we performed a multilayered study on fibroblasts derived from two ALS patients, namely SOD1L145F and SOD1S135N, carrying the p.L145F and the p.S135N missense variants, respectively. The patients showed diverse symptoms and disease progression in accordance with our bioinformatic analysis, which predicted the different effects of the two mutations in terms of protein structure. Interestingly, both mutations had an effect on the fibroblast energy metabolisms. However, while the SOD1L145F fibroblasts still relied more on oxidative phosphorylation, the SOD1S135N fibroblasts showed a metabolic shift toward glycolysis. Our study suggests that SOD1 mutations might lead to alterations in the energy metabolism.

Dating the Emergence of Human Endemic Coronaviruses.

Four endemic coronaviruses infect humans and cause mild symptoms. Because previous analyses were based on a limited number of sequences and did not control for effects that affect molecular dating, we re-assessed the timing of endemic coronavirus emergence. After controlling for recombination, selective pressure, and molecular clock model, we obtained similar tMRCA (time to the most recent common ancestor) estimates for the four coronaviruses, ranging from 72 (HCoV-229E) to 54 (HCoV-NL63) years ago. The split times of HCoV-229E and HCoV-OC43 from camel alphacoronavirus and bovine coronavirus were dated ~268 and ~99 years ago. The split times of HCoV-HKU1 and HCoV-NL63 could not be calculated, as their zoonoticic sources are unknown. To compare the timing of coronavirus emergence to that of another respiratory virus, we recorded the occurrence of influenza pandemics since 1500. Although there is no clear relationship between pandemic occurrence and human population size, the frequency of influenza pandemics seems to intensify starting around 1700, which corresponds with the initial phase of exponential increase of human population and to the emergence of HCoV-229E. The frequency of flu pandemics in the 19th century also suggests that the concurrence of HCoV-OC43 emergence and the Russian flu pandemic may be due to chance.

Homology-based classification of accessory proteins in coronavirus genomes uncovers extremely dynamic evolution of gene content.

Coronaviruses (CoVs) have complex genomes that encode a fixed array of structural and nonstructural components, as well as a variety of accessory proteins that differ even among closely related viruses. Accessory proteins often play a role in the suppression of immune responses and may represent virulence factors. Despite their relevance for CoV phenotypic variability, information on accessory proteins is fragmentary. We applied a systematic approach based on homology detection to create a comprehensive catalogue of accessory proteins encoded by CoVs. Our analyses grouped accessory proteins into 379 orthogroups and 12 super-groups. No orthogroup was shared by the four CoV genera and very few were present in all or most viruses in the same genus, reflecting the dynamic evolution of CoV genomes. We observed differences in the distribution of accessory proteins in CoV genera. Alphacoronaviruses harboured the largest diversity of accessory open reading frames (ORFs), deltacoronaviruses the smallest. However, the average number of accessory proteins per genome was highest in betacoronaviruses. Analysis of the evolutionary history of some orthogroups indicated that the different CoV genera adopted similar evolutionary strategies. Thus, alphacoronaviruses and betacoronaviruses acquired phosphodiesterases and spike-like accessory proteins independently, whereas horizontal gene transfer from reoviruses endowed betacoronaviruses and deltacoronaviruses with fusion-associated small transmembrane (FAST) proteins. Finally, analysis of accessory ORFs in annotated CoV genomes indicated ambiguity in their naming. This complicates cross-communication among researchers and hinders automated searches of large data sets (e.g., PubMed, GenBank). We suggest that orthogroup membership is used together with a naming system to provide information on protein function.

Fluorescence of KCl Aqueous Solution: A Possible Spectroscopic Signature of Nucleation.

Ion pairing in water solutions alters both the water hydrogen-bond network and ion solvation, modifying the dynamics and properties of electrolyte water solutions. Here, we report an anomalous intrinsic fluorescence of KCl aqueous solution at room temperature and show that its intensity increases with the salt concentration. From the ab initio density functional theory (DFT) and time-dependent DFT modeling, we propose that the fluorescence emission could originate from the stiffening of the hydrogen bond network in the hydration shell of solvated ion-pairs that suppresses the fast nonradiative decay and allows the slower radiative channel to become a possible decay pathway. Because computations suggest that the fluorophores are the local ion-water structures present in the prenucleation phase, this band could be the signature of the incoming salt precipitation.

Adaptation of the endemic coronaviruses HCoV-OC43 and HCoV-229E to the human host.

Four coronaviruses (HCoV-OC43, HCoV-HKU1, HCoV-NL63, and HCoV-229E) are endemic in human populations. All these viruses are seasonal and generate short-term immunity. Like the highly pathogenic coronaviruses, the endemic coronaviruses have zoonotic origins. Thus, understanding the evolutionary dynamics of these human viruses might provide insight into the future trajectories of SARS-CoV-2 evolution. Because the zoonotic sources of HCoV-OC43 and HCoV-229E are known, we applied a population genetics-phylogenetic approach to investigate which selective events accompanied the divergence of these viruses from the animal ones. Results indicated that positive selection drove the evolution of some accessory proteins, as well as of the membrane proteins. However, the spike proteins of both viruses and the hemagglutinin-esterase (HE) of HCoV-OC43 represented the major selection targets. Specifically, for both viruses, most positively selected sites map to the receptor-binding domains (RBDs) and are polymorphic. Molecular dating for the HCoV-229E spike protein indicated that RBD Classes I, II, III, and IV emerged 3-9 years apart. However, since the appearance of Class V (with much higher binding affinity), around 25 years ago, limited genetic diversity accumulated in the RBD. These different time intervals are not fully consistent with the hypothesis that HCoV-229E spike evolution was driven by antigenic drift. An alternative, not mutually exclusive possibility is that strains with higher affinity for the cellular receptor have out-competed strains with lower affinity. The evolution of the HCoV-OC43 spike protein was also suggested to undergo antigenic drift. However, we also found abundant signals of positive selection in HE. Whereas such signals might result from antigenic drift, as well, previous data showing co-evolution of the spike protein with HE suggest that optimization for human cell infection also drove the evolution of this virus. These data provide insight into the possible trajectories of SARS-CoV-2 evolution, especially in case the virus should become endemic.

The Multi-Level Mechanism of Action of a Pan-Ras Inhibitor Explains its Antiproliferative Activity on Cetuximab-Resistant Cancer Cells.

Ras oncoproteins play a crucial role in the onset, maintenance, and progression of the most common and deadly human cancers. Despite extensive research efforts, only a few mutant-specific Ras inhibitors have been reported. We show that cmp4-previously identified as a water-soluble Ras inhibitor- targets multiple steps in the activation and downstream signaling of different Ras mutants and isoforms. Binding of this pan-Ras inhibitor to an extended Switch II pocket on HRas and KRas proteins induces a conformational change that down-regulates intrinsic and GEF-mediated nucleotide dissociation and exchange and effector binding. A mathematical model of the Ras activation cycle predicts that the inhibitor severely reduces the proliferation of different Ras-driven cancer cells, effectively cooperating with Cetuximab to reduce proliferation even of Cetuximab-resistant cancer cell lines. Experimental data confirm the model prediction, indicating that the pan-Ras inhibitor is an appropriate candidate for medicinal chemistry efforts tailored at improving its currently unsatisfactory affinity.

First-Principles Calculations on Ni,Fe-Containing Carbon Monoxide Dehydrogenases Reveal Key Stereoelectronic Features for Binding and Release of CO2 to/from the C-Cluster.

In view of the depletion of fossil fuel reserves and climatic effects of greenhouse gas emissions, Ni,Fe-containing carbon monoxide dehydrogenase (Ni-CODH) enzymes have attracted increasing interest in recent years for their capability to selectively catalyze the reversible reduction of CO2 to CO (CO2 + 2H+ + 2e- ⇌ CO + H2O). The possibility of converting the greenhouse gas CO2 into useful materials that can be used as synthetic building blocks or, remarkably, as carbon fuels makes Ni-CODH a very promising target for reverse-engineering studies. In this context, in order to provide insights into the chemical principles underlying the biological catalysis of CO2 activation and reduction, quantum mechanics calculations have been carried out in the framework of density functional theory (DFT) on different-sized models of the Ni-CODH active site. With the aim of uncovering which stereoelectronic properties of the active site (known as the C-cluster) are crucial for the efficient binding and release of CO2, different coordination modes of CO2 to different forms and redox states of the C-cluster have been investigated. The results obtained from this study highlight the key role of the protein environment in tuning the reactivity and the geometry of the C-cluster. In particular, the protonation state of His93 is found to be crucial for promoting the binding or the dissociation of CO2. The oxidation state of the C-cluster is also shown to be critical. CO2 binds to Cred2 according to a dissociative mechanism (i.e., CO2 binds to the C-cluster after the release of possible ligands from Feu) when His93 is doubly protonated. CO2 can also bind noncatalytically to Cred1 according to an associative mechanism (i.e., CO2 binding is preceded by the binding of H2O to Feu). Conversely, CO2 dissociates when His93 is singly protonated and the C-cluster is oxidized at least to the Cint redox state.

On the propagation of the OH radical produced by Cu-amyloid beta peptide model complexes. Insight from molecular modelling.

Oxidative stress and metal dyshomeostasis are considered as crucial factors in the pathogenesis of Alzheimer's disease (AD). Indeed, transition metal ions such as Cu(ii) can generate Reactive Oxygen Species (ROS) via O2 Fenton-like reduction, catalyzed by Cu(ii) coordinated to the Amyloid beta (Aß) peptide. Despite intensive effort, the mechanisms of ROS-induced molecular damage remain poorly understood. In the present paper, we investigate on the basis of molecular modelling computations the mechanism of OH radical propagation toward the Aß peptide, starting from the end-product of OH radical generation by Cu(ii)·Aß. We evaluate (i) the OH oxidative capacity, as well as the energetics of the possible Aß oxidation target residues, by quantum chemistry Density Functional Theory (DFT) on coordination models of Cu(ii)/OH/Aß and (ii) the motion of the OH˙ approaching the Aß target residues by classical Molecular Dynamics (MD) on the full peptide Cu(ii)/OH/Aß(1-16). The results show that the oxidative capacity of OH coordinated Cu(ii)Aß is significantly lower than that of the free OH radical and that propagation toward Aß Asp and His residues is favoured over Tyr residues. These results are discussed on the basis of the recent literature on in vitro Aß metal-catalyzed oxidation and on the possible implications for the AD oxidative stress mechanism.

Rational Design of Fe2 (µ-PR2 )2 (L)6 Coordination Compounds Featuring Tailored Potential Inversion.

It was recently discovered that some redox proteins can thermodynamically and spatially split two incoming electrons towards different pathways, resulting in the one-electron reduction of two different substrates, featuring reduction potential respectively higher and lower than the parent reductant. This energy conversion process, referred to as electron bifurcation, is relevant not only from a biochemical perspective, but also for the ground-breaking applications that electron-bifurcating molecular devices could have in the field of energy conversion. Natural electron-bifurcating systems contain a two-electron redox centre featuring potential inversion (PI), i. e. with second reduction easier than the first. With the aim of revealing key factors to tailor the span between first and second redox potentials, we performed a systematic density functional study of a 26-molecule set of models with the general formula Fe2 (µ-PR2 )2 (L)6 . It turned out that specific features such as i) a Fe-Fe antibonding character of the LUMO, ii) presence of electron-donor groups and iii) low steric congestion in the Fe's coordination sphere, are key ingredients for PI. In particular, the synergic effects of i)-iii) can lead to a span between first and second redox potentials larger than 700 mV. More generally, the "molecular recipes" herein described are expected to inspire the synthesis of Fe2 P2 systems with tailored PI, of primary relevance to the design of electron-bifurcating molecular devices.