Could Quantum Mechanical Properties Be Reflected on Classical Molecular Dynamics? The Case of Halogenated Organic Compounds of Biological Interest

Transport of phenoxyacetic acid herbicides by PIN-FORMED auxin transporters

Auxins are a group of phytohormones that control plant growth and development. Their crucial role in plant physiology has inspired development of potent synthetic auxins that can be used as herbicides. Phenoxyacetic acid derivatives are a widely used group of auxin herbicides in agriculture and research. Despite their prevalence, the identity of the transporters required for distribution of these herbicides in plants is both poorly understood and the subject of controversial debate. Here we show that PIN-FORMED auxin transporters transport a range of phenoxyacetic acid herbicides across the membrane. We go on to characterize the molecular determinants of substrate specificity using a variety of different substrates as well as protein mutagenesis to probe the binding site. Finally, we present cryogenic electron microscopy structures of Arabidopsis thaliana PIN8 bound to either 2,4-dichlorophenoxyacetic acid or 4-chlorophenoxyacetic acid. These structures represent five key states from the transport cycle, allowing us to describe conformational changes associated with the transport cycle. Overall, our results reveal that phenoxyacetic acid herbicides use the same export machinery as endogenous auxins and exemplify how transporter binding sites undergo transformations that dictate substrate specificity. These results provide a foundation for future development of novel synthetic auxins and for precision breeding of herbicide-resistant crop plants.

Automation of Drug Discovery through Cutting-edge In-silico Research in Pharmaceuticals: Challenges and Future Scope

The rapidity and high-throughput nature of in silico technologies make them advantageous for predicting the properties of a large array of substances. In silico approaches can be used for compounds intended for synthesis at the beginning of drug development when there is either no or very little compound available. In silico approaches can be used for impurities or degradation products. Quantifying drugs and related substances (RS) with pharmaceutical drug analysis (PDA) can also improve drug discovery (DD) by providing additional avenues to pursue. Potential future applications of PDA include combining it with other methods to make insilico predictions about drugs and RS. One possible outcome of this is a determination of the drug potential of nontoxic RS. ADME estimation, QSAR research, molecular docking, bioactivity prediction, and toxicity testing all involve impurity profiling. Before committing to DD, RS with minimal toxicity can be utilised in silico. The efficacy of molecular docking in getting a medication to market is still debated despite its refinement and improvement. Biomedical labs and pharmaceutical companies were hesitant to adopt molecular docking algorithms for drug screening despite their decades of development and improvement. Despite the widespread use of "force fields" to represent the energy exerted within and between molecules, it has been impossible to reliably predict or compute the binding affinities between proteins and potential binding medications.

Evaluation of autophagy inhibition to combat cancer: (vanadium complex)-protein interactions, parameterization, and validation of a new force field

Autophagy has drawn attention from the scientific community, mainly because of its significant advantages over chemotherapeutic processes. One of these advantages is its direct action on cancer cells, avoiding possible side effects, unlike chemotherapy, which reaches tumor cells and affects healthy cells in the body, leading to a great loss in the quality of life of patients. In this way, it is known that vanadium complex (VC) [VO(oda)(phen)] has proven inhibition effect on autophagy process in pancreatic cancer cells. Keeping that in mind, molecular dynamics (MD) simulations can be considered excellent strategies to investigate the interaction of metal complexes and their biological targets. However, simulations of this type are strongly dependent on the appropriate choice of force field (FF). Therefore, this work proposes the development of AMBER FF parameters for VC, having a minimum energy structure as a starting point, obtained through DFT calculations with B3LYP/def2-TZVP level of theory plus ECP for the vanadium atom. An MD simulation in vacuum was performed to validate the developed FF. From the structural analyses, satisfying values of VC bond lengths and angles were obtained, where a good agreement with the experimental data and the quantum reference was found. The RMSD analysis showed an average of only 0.3%. Finally, we performed docking and MD (120 ns) simulations with explicit solvent between VC and PI3K. Overall, our findings encourage new parameterizations of metal complexes with significant biological applications, as well as allow to contribute to the elucidation of the complex process of autophagy.

Molecular Dynamics-Assisted Interaction of Vanadium Complex-AMPK: From Force Field Development to Biological Application for Alzheimer's Treatment

A large part of the world's population is affected by Alzheimer's disease (AD) and diabetes mellitus type 2, which cause both social and economic impacts. These two conditions are associated with one protein, AMPK. Studies have shown that vanadium complexes, such as bis(N',N'-dimethylbiguanidato)-oxovanadium(IV), VO(metf)₂·H₂O, are potential agents against AD. A crucial step in drug design studies is obtaining information about the structure and interaction of these complexes with the biological targets involved in the process through molecular dynamics (MD) simulations. However, MD simulations depend on the choice of a good force field that could present reliable results. Moreover, general force fields are not efficient for describing the properties of metal complexes, and a VO(metf)₂·H₂O-specific force field does not yet exist; thus, the proper development of a parameter set is necessary. Furthermore, this investigation is essential and relevant given the importance for both the scientific community and the population that is affected by this neurodegenerative disease. Therefore, the present work aims to develop and validate the AMBER force field parameters for VO(metf)₂·H₂O since the literature lacks such information on metal complexes and investigate through classical molecular dynamics the interactions made by the complex with the protein. The proposed force field proved to be effective for describing the vanadium complex (VC), supported by different analyses and validations. Moreover, it had a great performance when compared to the general AMBER force field. Beyond that, MD findings provided an in-depth perspective of vanadium complex-protein interactions that should be taken into consideration in future studies.

Accurate Quantum-Mechanically Derived Force-Fields through a Fragment-Based Approach: Balancing Specificity and Transferability in the Prediction of Self-Assembly in Soft Matter

The wide range of time/length scales covered by self-assembly in soft matter makes molecular dynamics (MD) the ideal candidate for simulating such a supramolecular phenomenon at an atomistic level. However, the reliability of MD outcomes heavily relies on the accuracy of the adopted force-field (FF). The spontaneous re-ordering in liquid crystalline materials stands as a clear example of such collective self-assembling processes, driven by a subtle and delicate balance between supramolecular interactions and single-molecule flexibility. General-purpose transferable FFs often dramatically fail to reproduce such complex phenomena, for example, the error on the transition temperatures being larger than 100 K. Conversely, quantum-mechanically derived force-fields (QMD-FFs), specifically tailored for the target system, were recently shown (J. Phys. Chem. Lett.2022,13, 243) to allow for the required accuracy as they not only well reproduced transition temperatures but also yielded a quantitative agreement with the experiment on a wealth of structural, dynamic, and thermodynamic properties. The main drawback of this strategy stands in the computational burden connected to the numerous quantum mechanical (QM) calculations usually required for a target-specific parameterization, which has undoubtedly hampered the routine application of QMD-FFs. In this work, we propose a fragment-based strategy to extend the applicability of QMD-FFs, in which the amount of QM calculations is significantly reduced, being a single-molecule-optimized geometry and its Hessian matrix the only QM information required. To validate this route, a new FF is assembled for a large mesogen, exploiting the parameters obtained for two smaller liquid crystalline molecules, in this and previous work. Lengthy MD simulations are carried out with the new transferred QMD-FF, observing again a spontaneous re-orientation in the correct range of temperatures, with good agreement with the available experimental measures. The present results strongly suggest that a partial transfer of QMD-FF parameters can be invoked without a significant loss of accuracy, thus paving the way to exploit the method's intrinsic predictive capabilities in the simulation of novel soft materials.

Characterizing the potentially neuronal acetylcholinesterase reactivity toward chiral pyraclofos: Enantioselective insights from spectroscopy, in silico docking, molecular dynamics simulation and per-residue energy decomposition studies

Chiral organophosphorus agents are distributed ubiquitously in the environment, but the neuroactivity of these asymmetric chemicals to humans remains uncertain. This scenario was to explore the stereoselective neurobiological response of human acetylcholinesterase (AChE) to chiral pyraclofos at the enantiomeric scale, and then decipher the microscopic basis of enantioselective neurotoxicity of pyraclofos enantiomers. The results indicated that (R)-/(S)-pyraclofos can form the bioconjugates with AChE with a stoichiometric ratio of 1:1, but the neuronal affinity of (R)-pyraclofos (K = 6.31 × 10⁴ M^-1) with AChE was larger than that of (S)-pyraclofos (K = 1.86 × 10⁴ M^-1), and significant enantioselectivity was existed in the biochemical reaction. The modes of neurobiological action revealed that pyraclofos enantiomers were situated at the substrate binding domain, and the strength of the overall noncovalent bonds between (S)-pyraclofos and the residues was weaker than that of (R)-pyraclofos, resulting in the high inhibitory effect of (R)-pyraclofos toward the activity of AChE. Dynamic enantioselective biointeractions illustrated that the intervention of inherent conformational flexibility in the AChE-(R)-pyraclofos was greater than that of the AChE-(S)-pyraclofos, which arises from the big spatial displacement and the conformational flip of the binding domain composed of the residues Thr-64～Asn-89, Gly-122～Asp-134, and Thr-436～Tyr-449. Energy decomposition exhibited that the Gibbs free energies of the AChE-(R)-/(S)-pyraclofos were ΔG° = －37.4/－30.2 kJ mol^-1, respectively, and the disparity comes from the electrostatic energy during the stereoselective neurochemical reactions. Quantitative conformational analysis further confirmed the atomic-scale computational chemistry conclusions, and the perturbation of (S)-pyraclofos on the AChE's ordered conformation was lower than that of (R)-pyraclofos, which is germane to the interaction energies of the crucial residues, e.g. Tyr-124, Tyr-337, Asp-74, Trp-86, and Tyr-119. Evidently, this attempt will contribute mechanistic information to uncovering the neurobiological effects of chiral organophosphates on the body.

Automated Parameterization of Quantum Mechanically Derived Force Fields for Soft Materials and Complex Fluids: Development and Validation

The reliability of molecular dynamics (MD) simulations in predicting macroscopic properties of complex fluids and soft materials, such as liquid crystals, colloidal suspensions, or polymers, relies on the accuracy of the adopted force field (FF). We present an automated protocol to derive specific and accurate FFs, fully based on ab initio quantum mechanical (QM) data. The integration of the Joyce and Picky procedures, recently proposed by our group to provide an accurate description of simple liquids, is here extended to larger molecules, capable of exhibiting more complex fluid phases. While the standard Joyce protocol is employed to parameterize the intramolecular FF term, a new automated procedure is here proposed to handle the computational cost of the QM calculations required for the parameterization of the intermolecular FF term. The latter is thus obtained by integrating the old Picky procedure with a fragmentation reconstruction method (FRM) that allows for a reliable, yet computationally feasible sampling of the intermolecular energy surface at the QM level. The whole FF parameterization protocol is tested on a benchmark liquid crystal, and the performances of the resulting quantum mechanically derived (QMD) FF were compared with those delivered by a general-purpose, transferable one, and by the third, "hybrid" FF, where only the bonded terms were refined against QM data. Lengthy atomistic MD simulations are carried out with each FF on extended 5CB systems in both isotropic and nematic phases, eventually validating the proposed protocol by comparing the resulting macroscopic properties with other computational models and with experiments. The QMD-FF yields the best performances, reproducing both phases in the correct range of temperatures and well describing their structure, dynamics, and thermodynamic properties, thus providing a clear protocol that may be explored to predict such properties on other complex fluids or soft materials.

Automated parameterization of quantum-mechanically derived force-fields including explicit sigma holes: A pathway to energetic and structural features of halogen bonds in gas and condensed phase

In classical molecular dynamics, general purpose atomistic force-fields (FFs) often deliver inaccurate results when dealing with halogen bonds (XBs), notwithstanding their crucial role in many fields of science, ranging from material design to drug development. Given the large dimensions of the systems of interest, it would be therefore desirable to increase the FF accuracy maintaining the simplicity of the standard Lennard-Jones (LJ) plus point charge description to avoid an excessive computational cost. A simple yet effective strategy consists in introducing a number of virtual sites able to mimic the so-called "explicit σ-hole." In this work, we present an automated FF parameterization strategy based on a global optimization of both LJ and charge parameters with respect to accurate quantum mechanical data, purposely computed for the system under investigation. As a test case, we report on two homologue series, characterized either by weak or strong XBs, namely, the di-halogenated methanes and the mono-, di-, and tri-substituted acetonitriles, taking into consideration Cl, Br, and I substituents. The resulting quantum mechanically derived FFs are validated for each compound in the gas and in the condensed phase by comparing them to general purpose and specific FFs without virtual sites and to highly accurate reference quantum mechanical data. The results strongly support the adoption of the specific FFs with virtual sites, which overcome the other investigated models in representing both gas phase energetics and the structural patterns of the liquid phase structure related to the presence of XBs.

Iron's Wake: The Performance of Quantum Mechanical-Derived Versus General-Purpose Force Fields Tested on a Luminescent Iron Complex

Recently synthetized iron complexes have achieved long-lived excited states and stabilities which are comparable, or even superior, to their ruthenium analogues, thus representing an eco-friendly and cheaper alternative to those materials based on rare metals. Most of computational tools which could help unravel the origin of this large efficiency rely on ab-initio methods which are not able, however, to capture the nanosecond time scale underlying these photophysical processes and the influence of their realistic environment. Therefore, it exists an urgent need of developing new low-cost, but still accurate enough, computational methodologies capable to deal with the steady-state and transient spectroscopy of transition metal complexes in solution. Following this idea, here we focus on the comparison between general-purpose transferable force-fields (FFs), directly available from existing databases, and specific quantum mechanical derived FFs (QMD-FFs), obtained in this work through the Joyce procedure. We have chosen a recently reported Fe^III complex with nanosecond excited-state lifetime as a representative case. Our molecular dynamics (MD) simulations demonstrated that the QMD-FF nicely reproduces the structure and the dynamics of the complex and its chemical environment within the same precision as higher cost QM methods, whereas general-purpose FFs failed in this purpose. Although in this particular case the chemical environment plays a minor role on the photo physics of this system, these results highlight the potential of QMD-FFs to rationalize photophysical phenomena provided an accurate QM method to derive its parameters is chosen.

Trends in the Recent Patent Literature on Cholinesterase Reactivators (2016-2019)

Acetylcholinesterase (AChE) is the key enzyme responsible for deactivating the ACh neurotransmitter. Irreversible or prolonged inhibition of AChE, therefore, elevates synaptic ACh leading to serious central and peripheral adverse effects which fall under the cholinergic syndrome spectra. To combat the toxic effects of some AChEI, such as organophosphorus (OP) nerve agents, many compounds with reactivator effects have been developed. Within the most outstanding reactivators, the substances denominated oximes stand out, showing good performance for reactivating AChE and restoring the normal synaptic acetylcholine (ACh) levels. This review was developed with the purpose of covering the new advances in AChE reactivation. Over the past years, researchers worldwide have made efforts to identify and develop novel active molecules. These researches have been moving farther into the search for novel agents that possess better effectiveness of reactivation and broad-spectrum reactivation against diverse OP agents. In addition, the discovery of ways to restore AChE in the aged form is also of great importance. This review will allow us to evaluate the major advances made in the discovery of new acetylcholinesterase reactivators by reviewing all patents published between 2016 and 2019. This is an important step in continuing this remarkable research so that new studies can begin.