This work presents a robust and efficient algorithm for exhaustively determining the critical points (CPs) of the molecular electrostatic potential (MEP) in 3D space. By combining Newton's method with a systematic physical space sampling strategy, we locate all CPs (maxima, minima, and saddle points) for both exact quantum-chemical MEPs and their tricubic interpolated approximations. The method is validated using a test function with known CPs and applied to a diverse set of molecules, including neutral systems, ions, and noncovalent complexes from the S66 and IONIC-HB datasets. Our results demonstrate that the interpolated MEP faithfully reproduces the topology of the exact potential in most cases, with minor discrepancies arising near nuclear positions or in regions of low gradient. The algorithm's efficiency (2-7 × $$ \times $$ faster for interpolated calculations) and robustness make it suitable for large-scale analyses of MEP topologies, offering insights into chemical reactivity and noncovalent interactions.

Quantum chemical methods have been intensively applied to study the pyrolytic conversion of glucose into hydroxymethylfurfural (HMF) and furfural (FF). Herein, we collect the most relevant mechanistic proposals from the recent literature and organize them into a single reaction network. The transition structures (TSs) and intermediates are characterized using high level ab initio methods that predict relative energies within chemical accuracy. The reaction pathways are assessed in terms of the Gibbs free energy differences of the TSs and intermediates with respect to β-glucopyranose, selecting a 2D ideal-gas standard state at 773K to represent the usual pyrolysis conditions. After having scored all the possible pathways throughout the network assuming reversible reaction steps, several pathways, which present various changes with respect to the former proposals, can lead to the formation of both HMF and FF passing through rate-determining TSs that have ∆G‡ values of ~ 49-50 kcal/mol. Interestingly, the catalysis by auxiliary water molecules and the non-specific environmental effects as modelled by solvent continuum methods, have only a minor impact on the Gibbs free energy profiles of the most favoured routes. Since the HMF fragmentation (HMF→FF+CH2O) is predicted to have a small ∆rxnG value and an accessible ∆G‡ barrier, the HMF/FF molecular ratio may be partly determined by equilibrium conditions. In addition, the benchmark energies and structures are employed to study the performance of density functional methodologies. Finally, we show that the computational results are in consonance with the kinetic parameters derived from lumped models, the results of isotopic labelling experiments and the reported HMF/FF molecular ratios. Eventually, they could be useful in future computational studies focused on the kinetic modelling of the pyrolysis mechanisms including non-equilibrium kinetic effects, which could render much more detailed information about product yields and the importance of the various pathways.

Aptamers have proven useful for a wide variety of applications, such as drug delivery systems and analytical reagents for diagnosis or food safety control. Conventional aptamer selection methods typically produce sequences longer than necessary, which are optimized through a postselection trial and error process to obtain the shortest-length sequence that preserves binding affinity. Herein, we describe a general strategy to obtain the tridimensional structure of DNA aptamers using a semiautomated molecular dynamics protocol, which serves as a guide to rationally improve experimentally selected candidates. Based on this approach, we designed truncated aptamers from previously described ligands recognizing different peptides and proteins, which are 20-35% shorter than the original candidates and present similar or even improved binding affinities. Moreover, we also discriminate between energetically similar secondary structures in terms of the energetic scoring of the molecular dynamics trajectories and rationally explain the role of poly thymine spacers in the (de)stabilization of the structure. This work demonstrates how a protocol for generating the aptamers tridimensional structure can accelerate their optimization for obtaining better analytical reagents and therapeutic agents.

Antibiotic resistance is a growing global threat, with glycopeptides like vancomycin remaining critical for treating resistant infections. However, its narrow therapeutic index necessitates therapeutic drug monitoring (TDM). In this study, we present a disposable electrochemical aptasensor for cost-effective and rapid vancomycin monitoring. Novel high-affinity aptamers were identified via magnetic bead-based SELEX, with their binding confirmed by surface plasmon resonance and computational modeling. The aptasensor, developed on screen-printed gold electrodes using a multipulse-assisted immobilization method, demonstrated a linear response from 2.5 to 50 μM and a detection limit of 1.5 μM. This range encompasses clinically relevant trough (10-13.5 μM) concentrations. Validated in undiluted clinical samples, it showed performance comparable to gold-standard immunoassays, offering a promising tool for vancomycin TDM.

Herein, we present the results of molecular dynamics, potential of mean force (PMF) and quantum mechanical (QM) calculations aimed to investigate the cis-trans equilibria of short peptides: capped Ac-Z-NHMe, Ac-X-Z-NHMe, and zwitterionic Leu-Z with X = Gln, Leu, Tyr and Z = Pro, Ala. Both PMF free energies and average QM energies in aqueous solution consistently predict that the Ala → Pro substitution stabilizes the Ac/X-Z cis isomer in all the model compounds. Using the interacting quantum atoms method, we decomposed the average QM energies into physical components and performed a comparative analysis between the Pro-containing peptides and their Ala-substituted counterparts. The results point out that cis-trans isomerization is not controlled by a single steric or electronic contribution and unveil a mixture of electrostatic, steric and hyperconjugative effects that is modulated by the dipeptide sequence. It is also shown that solute-solvent interactions stabilize systematically the trans and cis isomer of the Ala- and Pro-containing capped peptides, respectively, suggesting thus that solvation plays a key role in the Pro cis effect observed in these systems in agreement with former proposals.

Quantum chemical methods have been intensively applied to study the pyrolytic conversion of glucose into hydroxymethylfurfural (HMF) and furfural (FF). Herein, we collect the most relevant mechanistic proposals from the recent literature and organize them into a single reaction network. The transition structures (TSs) and intermediates are characterized using high level ab initio methods that predict relative energies within chemical accuracy. The reaction pathways are assessed in terms of the Gibbs free energy differences of the TSs and intermediates with respect to β-glucopyranose, selecting a 2D ideal-gas standard state at 773K to represent the usual pyrolysis conditions. After having scored all the possible pathways throughout the network assuming reversible reaction steps, several pathways, which present various changes with respect to the former proposals, can lead to the formation of both HMF and FF passing through rate-determining TSs that have ∆G‡ values of ~ 49-50 kcal/mol. Interestingly, the catalysis by auxiliary water molecules and the non-specific environmental effects as modelled by solvent continuum methods, have only a minor impact on the Gibbs free energy profiles of the most favoured routes. Since the HMF fragmentation (HMF→FF+CH2O) is predicted to have a small ∆rxnG value and an accessible ∆G‡ barrier, the HMF/FF molecular ratio may be partly determined by equilibrium conditions. In addition, the benchmark energies and structures are employed to study the performance of density functional methodologies. Finally, we show that the computational results are in consonance with the kinetic parameters derived from lumped models, the results of isotopic labelling experiments and the reported HMF/FF molecular ratios. Eventually, they could be useful in future computational studies focused on the kinetic modelling of the pyrolysis mechanisms including non-equilibrium kinetic effects, which could render much more detailed information about product yields and the importance of the various pathways.

Bothrops species are the main cause of snake bites in rural communities of tropical developing countries of Central and South America. Envenomation by Bothrops snakes is characterized by prominent local inflammation, hemorrhage and necrosis as well as systemic hemostatic disturbances. These pathological effects are mainly caused by the major toxins of the viperidae venoms, the snake venom metalloproteinases (SVMPs). Despite the antivenom therapy efficiency to block the main toxic effects on bite victims, this treatment shows limited efficacy to prevent tissue necrosis. Thus, drug-like inhibitors of these toxins have the potential to aid serum therapy of accidents inflicted by viper snakes. Broad-spectrum metalloprotease inhibitors bearing a hydroxamate zinc-binding group are potential candidates to improve snake bites therapy and could also be used to study toxin-ligand interactions. Therefore, in this work, we used both docking calculations and molecular dynamics simulations to assess the interactions between six hydroxamate inhibitors and two P-I SVMPs selected as models: Atroxlysin-I (hemorrhagic) from Bothrops atrox, and Leucurolysin-a (nonhemorrhagic) from Bothrops leucurus. We also employed a large variety of end-point free energy methods in combination with entropic terms to produce scoring functions of the relative affinities of the inhibitors for the toxins. Then we identified the scoring functions that best correlated with experimental data obtained from kinetic activity assays. In addition, to the characterization of these six molecules as inhibitors of the toxins, this study sheds light on the main enzyme-inhibitor interactions, explaining the broad-spectrum behavior of the inhibitors, and identifies the energetic and entropic terms that improve the performance of the scoring functions.

In this perspective, we review some recent advances in the concept of atoms-in-molecules from a real space perspective. We first introduce the general formalism of atomic weight factors that allows unifying the treatment of fuzzy and non-fuzzy decompositions under a common algebraic umbrella. We then show how the use of reduced density matrices and their cumulants allows partitioning any quantum mechanical observable into atomic or group contributions. This circumstance provides access to electron counting as well as energy partitioning, on the same footing. We focus on how the fluctuations of atomic populations, as measured by the statistical cumulants of the electron distribution functions, are related to general multi-center bonding descriptors. Then we turn our attention to the interacting quantum atom energy partitioning, which is briefly reviewed since several general accounts on it have already appeared in the literature. More attention is paid to recent applications to large systems. Finally, we consider how a common formalism to extract electron counts and energies can be used to establish an algebraic justification for the extensively used bond order-bond energy relationships. We also briefly review a path to recover one-electron functions from real space partitions. Although most of the applications considered will be restricted to real space atoms taken from the quantum theory of atoms in molecules, arguably the most successful of all the atomic partitions devised so far, all the take-home messages from this perspective are generalizable to any real space decompositions.

The interacting quantum atoms (IQA) method decomposes the quantum mechanical (QM) energy of a molecular system in terms of one- and two-center (atomic) contributions within the context of the quantum theory of atoms in molecules. Here, we demonstrate that IQA, enhanced with molecular mechanics (MM) and Poisson-Boltzmann surface-area (PBSA) solvation methods, is naturally extended to the realm of hybrid QM/MM methodologies, yielding intra- and inter-residue energy terms that characterize all kinds of covalent and noncovalent bonding interactions. To test the robustness of this approach, both metal-water interactions and QM/MM boundary artifacts are characterized in terms of the IQA descriptors derived from QM regions of varying size in Zn(II)- and Mg(II)-water clusters. In addition, we analyze a homologous series of inhibitors in complex with a matrix metalloproteinase (MMP-12) by carrying out QM/MM-PBSA calculations on their crystallographic structures followed by IQA energy decomposition. Overall, these applications not only show the advantages of the IQA QM/MM approach but also address some of the challenges lying ahead for expanding the QM/MM methodology.

The absolute entropy of a flexible molecule can be approximated by the sum of a rigid-rotor-harmonic-oscillator (RRHO) entropy and a Gibbs-Shannon entropy associated to the Boltzmann distribution for the occupation of the conformational energy levels. Herein, we show that such partitioning, which has received renewed interest, leads to accurate entropies of single molecules of increasing size provided that the conformational part is estimated by means of a set of discretization and expansion techniques that are able to capture the significant correlation effects among the torsional motions. To ensure a reliable entropy estimation, we rely on extensive sampling as that produced by classical molecular dynamics simulations on the microsecond time scale, which is currently affordable for small- and medium-sized molecules. According to test calculations, the gas-phase entropy of simple organic molecules is predicted with a mean unsigned error of 0.9 cal/(mol K) when the RRHO entropies are computed at the B3LYP-D3/cc-pVTZ level. Remarkably, the same protocol gives small errors [<1 cal/(mol K)] for the extremely flexible linear alkane molecules (CnH2n+2, n = 14, 16, and 18). Similarly, we obtain well-converged entropies for a more challenging test of drug molecules, which exhibit more pronounced correlation effects. We also perform equivalent entropy calculations on a 76 amino acid protein, ubiquitin, by taking advantage of the cutoff-dependent formulation of an expansion technique (correlation-consistent multibody local approximation, CC-MLA), which incorporates genuine correlation effects among the neighboring dihedral angles. Moreover, we show that insightful descriptors of the coupled torsional motions can be obtained with the CC-MLA approach.

Knowledge about the existence and stability of different species of organoarsenicals in solution is of the most significant interest for fields so different as chemical, environmental, biological, toxicological and forensic. This work provides a comparative evaluation of the Raman spectra of four organoarsenicals (o-arsanilic acid, parsanilic acid, roxarsone and cacodylic acid) in aqueous solutions under acidic, neutral and alkaline conditions. Speciation of some of these organoarsenicals is possible by Raman spectrometry at different selected pHs. Further, we examine the proficiency of computational chemistry to obtain the theoretical Raman spectra of the four organoarsenicals compounds. To this end, we employ a computational protocol that includes explicit water molecules and conformational sampling, finding that the calculated organoarsenicals spectra agree reasonably well with those experimentally obtained in an aqueous solution in the whole pH range covered. Finally, we highlight the effectiveness of quantum chemical calculations to identify organoarsenicals in an aqueous solution.

Reliably knowledge of the arsenic oxoacids in solution and solid-state and any possible relationship between them at different pHs is of concern in various scientific fields. This work compares the experimental Raman spectra of the inorganic arsenic oxoacids in aqueous solutions under acidic, neutral and alkaline conditions with the dry precipitates obtained from the corresponding aqueous solutions. Further, we explore the ability of quantum chemical methods to model the Raman spectra of the arsenic oxoacids in solution by considering explicit water molecules and conformational sampling, fitting reasonably well with the experimental spectra in the whole pH range covered. Hydrogen bridges and the coexistence of arsenic oxoacids facilitate strong overlapping in the Raman spectra of the As(III) aqueous samples compared with the As(V) ones. Some Raman shifts of the dry arsenic precipitates correlate well with the corresponding Raman spectra of the same arsenic species in aqueous solutions, allowing a practical use of the Raman spectrometry for indirect screening purposes of arsenic speciation in both condensed phases.

Amphiphilic cyclodextrins spontaneously aggregate to form different supramolecular assemblies with potential applications in drug release. Herein, we employ extended molecular dynamics simulations in order to characterize the structure and dynamics in explicit solvent of several amphiphilic derivatives of the beta-cyclodextrin (beta-CD) molecule, with aliphatic chains ester-bound to the wide rim of the hydrophobic cavity. We also study the binding properties considering a typical guest (diazepam) and the dimerization of these macrocyclic systems, assessing the relative stability of the complexes by means of end-point free energy methods. Different lengths (C-4, C-10, and C-14 atoms) are considered for the alkyl side chains included in the amphiphilic beta-CD-C-n molecules. According to the simulations, the length of these C-n moieties determines the complexing and aggregation capabilities of the beta-CD-C-n systems. Compared to the native beta-CD, the alkyl side chains in the beta-CD-C-n molecules destabilize the inclusion complexes with diazepam and hinder the access of guest molecules to the hydrophobic cavity. In turn, dimerization is favored in the largest amphiphilic derivatives associated to the hydrophobic interaction between the C-n fragments. (C) 2022 The Authors. Published by Elsevier B.V.

While the state-of-the-art computational simulations support the neutral state for the catalytic dyad of the SARS-CoV-2 main protease, the recently-reported neutron structure exhibits a zwitterionic form. To better compare the structural and dynamical features of the two charge configurations, we perform a Molecular Dynamics study of the dimeric enzyme in complex with a peptide substrate. The simulations show that the enzyme charge configuration from the neutron structure is not compatible with a catalytically-competent binding mode for peptide substrates.

Basing on the interacting quantum atoms approach, we present a conceptual and theoretical framework of short-range electrostatic interactions, whose accurate description is still a challenging problem in molecular modeling. For all the non-covalent complexes in the S66 database, the fragment and atomic decomposition of the electrostatic binding energies is performed using both the charge density of the dimers and the unrelaxed densities of the monomers. This energy decomposition together with dispersion corrections gives rise to a pairwise approximation to the total binding energy. It also provides energetic descriptors at varying distance that directly address the atomic and molecular electrostatic interactions as described by point-charge or multipole-based potentials. Additionally, we propose a consistent definition of the charge penetration energy within quantum chemical topology, which is mainly characterized in terms of the intramolecular electrostatic energy. Finally, we discuss some practical implications of our results for the design and validation of electrostatic potentials.

Knowledge about the theoretical relationship between the analyte properties and the critical chromatographic parameters is mandatory for a better interpretation of the separation mechanism and a more leisurely development of quantitative studies. In a preliminary stage of this work, we introduce the Gumbel distribution, the extreme value distribution type-I widely used in other fields, as a novel tool for modelling the chromatographic peak shape. Further, we develop mathematical models to evaluate the effect of the experimental variables and various quantum parameters on the chromatographic indices, such as the retention time, capacity factor, asymmetry factor, tailing factor and number of theoretical plates. Finally, we propose a mechanistic behaviour for the chromatographic separation process based on the structure-retention relationship of fifteen selected drugs involving several molecular quantum parameters.

We provide results from a molecular dynamics simulation of the SARS-CoV-2 main protease in the monomer and dimer states of the native enzyme and also bound to a peptide substrate.

Detecting specific protein glycoforms is attracting particular attention due to its potential to improve the performance of current cancer biomarkers. Although natural receptors such as lectins and antibodies have served as powerful tools for the detection of protein-bound glycans, the development of effective receptors able to integrate in the recognition both the glycan and peptide moieties is still challenging. Here we report a method for selecting aptamers toward the glycosylation site of a protein. It allows identification of an aptamer that binds with nM affinity to prostate-specific antigen, discriminating it from proteins with a similar glycosylation pattern. We also computationally predict the structure of the selected aptamer and characterize its complex with the glycoprotein by docking and molecular dynamics calculations, further supporting the binary recognition event. This study opens a new route for the identification of aptamers for the binary recognition of glycoproteins, useful for diagnostic and therapeutic applications.

In this work, we investigate the conformational properties of unguisin A, a natural macrocyclic heptapeptide that incorporates a γ-aminobutyric acid (Gaba), and four of its difluorinated stereoisomers at the Gaba residue. According to nuclear magnetic resonance (NMR) experiments, their secondary structure depends dramatically on the stereochemistry of the fluorinated carbon atoms. However, many molecular details of the structure and flexibility of these systems remain unknown, so that a rationale of the conformational changes induced by the fluorine atoms in the macrocycle is still missing. To fill this gap, we apply enhanced molecular dynamics (MD) techniques to explore the peptide conformational space in dimethyl sulfoxide solution followed by 4-8 μs of conventional MD simulations that provide extensive equilibrium sampling. The simulations, which compare reasonably well with the NMR-based observations, show that the secondary structure of the macrocycle is altered substantially upon fluorination, except for the (S,S) diastereomer. It also turns out that the conformations of the fluorinated peptides are visited during the enhanced MD simulation of natural unguisin A, suggesting thus that conformations accessible to the unsubstituted macrocyclic peptide may be selected by fluorination. Therefore, computational characterization of the macrocyclic peptides could be helpful in the rational design of stereoselective fluorinated peptides with fine-tuned conformation and activity.