Calculation Of Partial Charges Research Articles

Gas-phase ion mobility of protonated aldehydes in helium measured using a selected ion flow-drift tube.

In soft chemical ionization mass spectrometry, analyte ions are produced via ion-molecule reactions in the reactor. When an electric field E is imposed, the ion drift velocity vd determines the reaction time and the effective ion temperature. Agreement between experimental ion mobilities and theoretical predictions confirms the accuracy of the ion residence time measurement procedure. A selected ion flow-drift tube (SIFDT), an instrument with a chemical ionization source, was used to produce protonated aldehydes and selectively inject them into the resistive glass drift tube filled with He. Arrival-time distributions of ions were obtained using the Hadamard modulation. Reduced ion mobilities were then obtained at a pressure of 2hPa in the E/N range of 5-15 Td. Theoretical ion mobility values were calculated using two methods: hard-sphere approximation and trajectory modelling. The measured mobilities of three saturated and three unsaturated protonated aldehydes do not show substantial variation across the studied E/N range. Effective temperatures calculated using the Wannier formula from measured gas temperatures ranged from 300 to 315 K. Experimentally obtained values of the near-zero- E/N-reduced ion mobilities agree with both methods of calculations typically within ±3% standard deviation (maximum ±5%). The experimental SIFDT values of reduced mobilities in He of protonated aldehyde molecules generated from a chemical ionization source are in close agreement with two different theoretical methods based on the density functional theory calculations of ion geometries and partial atomic charges. Besides its fundamental importance, the ion mobility results validate the correct operation of the drift tube reactor and the ion residence time measurement procedure. Diffusion losses can also be determined from these results.

Unusual quadruple bonds featuring collective interaction-type σ bonds between first octal-row atoms in the alkaline-earth compounds AeOLi2 (Ae = Be-Ba).

Quantum chemical calculations are reported for the complexes of alkaline earth metals AeOLi2 (Ae = Be-Ba) at the BP86-D3(BJ)/def2-QZVPP and CCSD(T)/def2-QZVPPQZVPP levels. The nature of the Ae-OLi2 bond has been analyzed with a variety of methods. The AeOLi2 molecules exhibit an unprecedented σ donor bond Ae→OLi2 where the (n)s2 lone-pair electrons of the Ae atom are donated to vacant O-Li2 antibonding orbitals having the largest coefficient at lithium. This is a covalent bond where the accumulation of the associated electronic charge is located at two positions above and below the Ae-OLi2 axis. The bifurcated component of orbital interactions is structurally related to the recently proposed collective bonding model, but exhibits a completely different type of bonding. The most stable isomer of AeOLi2 has a C 2v geometry and a singlet (1A1) electronic ground state. The bond dissociation energy (BDE) of the Ae-OLi2 bonds exhibits a zig-zag trend from BeOLi2 to BaOLi2, with BeOLi2 having the largest BDE (D e = 73.0 kcal mol-1) and MgOLi2 possessing the lowest BDE (D e = 42.3 kcal mol-1) at the CCSD(T) level. The calculation of the atomic partial charges by the Hirshfeld and Voronoi methods suggests that Be and Mg carry small negative charges in the lighter molecules whereas the heavier atoms Ca-Ba have small positive charges. In contrast, the NBO and QTAIM methods give positive charges for all Ae atoms that are larger for Ca-Ba than that calculated by the Hirshfeld and Voronoi approaches. The molecules AeOLi2 have large dipole moments where the negative end is at the Ae atom with the polarity Ae→OLi2. The largest dipole moments are predicted for the lighter species BeOLi2 and MgOLi2 and the smallest value is calculated for BaOLi2. The calculation of the vibrational spectra shows a significant red-shift toward lower wave numbers for the Ae-OLi2 stretching mode in comparison to diatomic AeO. Besides the Ae→OLi2 σ-donor bonds there are also three dative bonds due to Ae←OLi2 backdonation which consist of one σ bond and two π bonds. The appearance of strong Ae→OLi2 σ donation leads to quadruple bonds AeOLi2 in all systems AeOLi2, even for the lightest species with Ae = Be, Mg. The valence orbitals of Ca, Sr, and Ba, which are involved in the dative interactions, are the (n)s and (n-1)d AOs whereas Be and Mg use their (n)s and (n)p AOs. The EDA-NOCV results are supported by the AdNDP calculations which give four 2c-2e bonding orbitals. Three bonding orbitals have occupation numbers ∼2. One σ orbital has smaller occupation numbers between 1.32 and 1.73 due to the delocalization to the lithium atoms. The analysis of the electronic structure with the ELF method suggests multicenter bonds with mainly trisynaptic and tetrasynaptic basins, which also support the results of the EDA-NOCV calculations.

αCharges: partial atomic charges for AlphaFold structures in high quality.

The AlphaFold2 prediction algorithm opened up the possibility of exploring proteins' structural space at an unprecedented scale. Currently, >200 million protein structures predicted by this approach are deposited in AlphaFoldDB, covering entire proteomes of multiple organisms, including humans. Predicted structures are, however, stored without detailed functional annotations describing their chemical behaviour. Partial atomic charges, which map electron distribution over a molecule and provide a clue to its chemical reactivity, are an important example of such data. We introduce the web application αCharges: a tool for the quick calculation of partial atomic charges for protein structures from AlphaFoldDB. The charges are calculated by the recent empirical method SQE+qp, parameterised for this class of molecules using robust quantum mechanics charges (B3LYP/6-31G*/NPA) on PROPKA3 protonated structures. The computed partial atomic charges can be downloaded in common data formats or visualised via the powerful Mol* viewer.The αCharges application is freely available at https://alphacharges.ncbr.muni.cz with no login requirement.

Computational Characterization of Zr-Oxide MOFs for Adsorption Applications.

Zr-oxide secondary building units construct metal-organic framework (MOF) materials with excellent gas adsorption properties and high mechanical, thermal, and chemical stability. These attributes have led Zr-oxide MOFs to be well-recognized for a wide range of applications, including gas storage and separation, catalysis, as well as healthcare domain. Here, we report structure search methods within the Cambridge Structural Database (CSD) to create a curated subset of 102 Zr-oxide MOFs synthesized to date, bringing a unique record for all researchers working in this area. For the identified structures, we manually corrected the proton topology of hydroxyl and water molecules on the Zr-oxide nodes and characterized their textural properties, Brunauer-Emmett-Teller (BET) area, and topology. Importantly, we performed systematic periodic density functional theory (DFT) calculations comparing 25 different combinations of basis sets and functionals to calculate framework partial atomic charges for use in gas adsorption simulations. Through experimental verification of CO2 adsorption in selected Zr-oxide MOFs, we demonstrate the sensitivity of CO2 adsorption predictions at the Henry's regime to the choice of the DFT method for partial charge calculations. We characterized Zr-MOFs for their CO2 adsorption performance via high-throughput grand canonical Monte Carlo (GCMC) simulations and revealed how the chemistry of the Zr-oxide node could have a significant impact on CO2 uptake predictions. We found that the maximum CO2 uptake is obtained for structures with the heat of adsorption values >25 kJ/mol and the largest cavity diameters of ca. 6-7 Å. Finally, we introduced augmented reality (AR) visualizations as a means to bring adsorption phenomena alive in porous adsorbents and to dynamically explore gas adsorption sites in MOFs.

Computational studies of caffeoylquinic acids from Brazilian green propolis and its anti-viral potential against SARS-CoV-2 Mpro

Purpose: The present study evaluated the following caffeoylquinic acids, Neochlorogenic acid (3-CQA), Cryptochlorogenic acid (4-CQA), Chlorogenic Acid (5-CQA), Isochlorogenic acid A (3,5-DCQA) Isochlorogenic acid B (3,4-DCQA) and Isochlorogenic acid C (4,5-DCQA) found in Brazilian green propolis, regarding its physicochemical, pharmacokinetic and conformational characteristics. Additionally, the compounds were explored on the efficacy of inhibiting the pharmacological target SARS-CoV-2 Mpro, a protein involved in SARS-Cov-2 infection. Methods: The physicochemical and pharmacokinetic proprieties were obtained from the projected 2D structures of the respective compounds. The conformational characteristics were obtained from the three-dimensional models were subjected to geometric optimization by molecular mechanics under MMFF94 force field, subsequently, the calculation of partial atomic charges by employing AM1 semi-empirical methodology was performed. Molecular docking was performed, and the protein was loaded in PDB Data Bank (PDB ID 6LU7). Results: The physicochemical and pharmacokinetic results indicate that these phytochemicals have from medium to low potential for gastrointestinal tract absorption, principally in relation to the LogP values, and violated some druglikeness’ criteria. However molecular docking showed that the compounds 3-CQA, 4-CQA, 5-CQA, 3,5-DCQA, 3,4-DCQA and 4,5-DCQA potentially binds with the active site of the SARS-CoV-2 Mpro, through stables complexes, with a docking score of -6.44, -6.11, -6.48, -6.26, -7.01 and -7.40 kcal/mol, respectively. Conclusion: The physicochemical and pharmacokinetic parameters, as well as Hydrogen-bond formation, energy landscape, indicate that the compound with the greatest therapeutic potential are 5-CQA, 3,4-DCQA and 4,5-DCQA however this study necessitates further in vitro and in vivo experimental validation.

On the Value of Using 3D Shape and Electrostatic Similarities in Deep Generative Methods.

Multiparameter optimization, the heart of drug design, is still an open challenge. Thus, improved methods for automated compound design with multiple controlled properties are desired. Here, we present a significant extension to our previously described fragment-based reinforcement learning method (DeepFMPO) for the generation of novel molecules with optimal properties. As before, the generative process outputs optimized molecules similar to the input structures, now with the improved feature of replacing parts of these molecules with fragments of similar three-dimensional (3D) shape and electrostatics. We developed and benchmarked a new python package, ESP-Sim, for the comparison of the electrostatic potential and the molecular shape, allowing the calculation of high-quality partial charges (e.g., RESP with B3LYP/6-31G**) obtained using the quantum chemistry program Psi4. By performing comparisons of 3D fragments, we can simulate 3D properties while overcoming the notoriously difficult step of accurately describing bioactive conformations. The new improved generative (DeepFMPO v3D) method is demonstrated with a scaffold-hopping exercise identifying CDK2 bioisosteres. The code is open-source and freely available.

(Invited) A Multi-Scale Infrastructure for Automating Materials Science Computations

In this talk, I will present our group’s effort to build a high-throughput infrastructure for the automated execution of materials science computations and analysis. This work is an extension of open-source Python packages that have been developed in Materials Project [1]: (1) pymatgen [2] for structure representation and input/output files generation and handling, (2) FireWorks [3] for managing workflows over computing resources, and (3) Custodian [4] for monitoring inevitable errors during the simulations and applying on-the-fly fixes. In our work, we benefit from these three libraries to build well-tested workflows for speeding up the prediction and screening of materials properties relevant to various applications with a focus on battery systems. At the backend, the infrastructure interfaces with the Gaussian [5] software which enables electronic structure calculations of chemical systems, and LAMMPS [6] open-source code for molecular dynamics (MD) simulations. In addition to its ability to handle the generation of input/data files and parsing of output files from the mentioned computational software, the infrastructure allows management of the collected data and storing it in MongoDB [7], a NoSQL database program using JSON-like documents with flexible schema. Examples of implemented Gaussian-based workflows include the calculation of electrostatic partial charges, NMR chemical shift, binding energy, ionization potential, electron affinity, and bond dissociation energy. Each derived property is saved in its own collection with auxiliary information like molecular metadata (smiles representation, chemical formula, ...), which makes it easy to query and data-mine structure-property relationships. The user can tune the calculations by overriding default workflow parameters, for example, the functional and basis set, by-passing selected steps, or packing many jobs over multiple nodes for supercomputing resources. LAMMPS workflows allow the execution of MD simulations in different ensembles and analysis of the dumped trajectories for various dynamical and structural properties. The infrastructure enables coupling first-principles calculations with classical MD simulations to address chemical and physical phenomena occurring in a given system at different length and time scales. This approach aids in the development of databases required for training machine-learning models to accelerate the design and screening of materials with optimized properties for various materials science applications.References Jain, A., et al., Commentary: The Materials Project: A materials genome approach to accelerating materials innovation. Apl Materials, 2013. 1(1): p. 011002.Ong, S.P., et al., Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis. Computational Materials Science, 2013. 68: p. 314-319.Jain, A., et al., FireWorks: a dynamic workflow system designed for high‐throughput applications. Concurrency and Computation: Practice and Experience, 2015. 27(17): p. 5037-5059.Custodian. <https://github.com/materialsproject/custodian>.Frisch, M.J., et al., Gaussian 16 Rev. C.01. 2016: Wallingford, CT.Plimpton, S., Fast parallel algorithms for short-range molecular dynamics. 1993, Sandia National Labs., Albuquerque, NM (United States).MongoDB Inc., M., 2014.

Optimized Atomic Partial Charges and Radii Defined by Radical Voronoi Tessellation of Bulk Phase Simulations.

We present a novel method for the computation of well-defined optimized atomic partial charges and radii from the total electron density. Our method is based on a two-step radical Voronoi tessellation of the (possibly periodic) system and subsequent integration of the total electron density within each Voronoi cell. First, the total electron density is partitioned into the contributions of each molecule, and subsequently the electron density within each molecule is assigned to the individual atoms using a second set of atomic radii for the radical Voronoi tessellation. The radii are optimized on-the-fly to minimize the fluctuation (variance) of molecular and atomic charges. Therefore, our method is completely free of empirical parameters. As a by-product, two sets of optimized atomic radii are produced in each run, which take into account many specific properties of the system investigated. The application of an on-the-fly interpolation scheme reduces discretization noise in the Voronoi integration. The approach is particularly well suited for the calculation of partial charges in periodic bulk phase systems. We apply the method to five exemplary liquid phase simulations and show how the optimized charges can help to understand the interactions in the systems. Well-known effects such as reduced ion charges below unity in ionic liquid systems are correctly predicted without any tuning, empiricism, or rescaling. We show that the basis set dependence of our method is very small. Only the total electron density is evaluated, and thus, the approach can be combined with any electronic structure method that provides volumetric total electron densities—it is not limited to Hartree–Fock or density functional theory (DFT). We have implemented the method into our open-source software tool TRAVIS.

Atomic Charge Calculator II: web-based tool for the calculation of partial atomic charges.

Partial atomic charges serve as a simple model for the electrostatic distribution of a molecule that drives its interactions with its surroundings. Since partial atomic charges are frequently used in computational chemistry, chemoinformatics and bioinformatics, many computational approaches for calculating them have been introduced. The most applicable are fast and reasonably accurate empirical charge calculation approaches. Here, we introduce Atomic Charge Calculator II (ACC II), a web application that enables the calculation of partial atomic charges via all the main empirical approaches and for all types of molecules. ACC II implements 17 empirical charge calculation methods, including the highly cited (QEq, EEM), the recently published (EQeq, EQeq+C), and the old but still often used (PEOE). ACC II enables the fast calculation of charges even for large macromolecular structures. The web server also offers charge visualization, courtesy of the powerful LiteMol viewer. The calculation setup of ACC II is very straightforward and enables the quick calculation of high-quality partial charges. The application is available at https://acc2.ncbr.muni.cz.

Isomers of Alkali Metal (Methylbenzyl)allylamides: A Theoretical Perspective.

Recent studies of alkali metal N-(α-methylbenzyl)allylamides containing lithium, sodium, and potassium have shown unique rearrangements in NMR experiments. It was found that lithium isomers favored the formation of aza-allyl and aza-enolate complexes that could exist in a solution for a substantial amount of time. As the radius of the metal ion increases going from lithium to potassium, so does the preference for the formation of the imine structure. For sodium, the aza-allyl complex could still be isolated, whereas the imine structure was only found to be stable on the scale of several hours for potassium. In this work, ab initio calculations were used to shed light on this phenomenon. Decomposition of intermolecular interaction energies of the aza-allyl, aza-enolate, and imine complexes showed that for lithium, the formation of aza-allyl and aza-enolate complexes was driven by electrostatic interactions. For potassium, the dispersion component of the metal interaction with the ligand proved to be more important for the stability of the imine structure. The presence of the imine formation in potassium and partially in sodium was found to be due to the reduced electrostatic nature of these larger metals. The assignment of the experimental NMR spectra was further confirmed with the natural bond order (NBO) analysis as well as the partial charge calculations. Analysis of orbital energies, specifically those of the highest occupied molecular orbitals (HOMOs), as well as the deformation energies of each of the ligands, were also considered. Through these procedures, an understanding of the tendency for each metal to have a unique isomerization pathway was gained.

Modifying the CHARMM36 Lipid Force Field for LJ-PME Simulations

Long-range Lennard-Jones (LJ) interactions were historically excluded from energy calculations in Molecular Dynamics (MD) simulations due to high computational cost. However, these interactions have a significant impact on the properties of nonpolar systems. The LJ particle-mesh Ewald (LJ-PME) method offers a solution to this problem and retains good efficiency. Here we introduce a modification to the additive all-atom CHARMM lipid force field (FF) which makes it compatible with the LJ-PME method. The last generation of the CHARMM36 (C36) lipid FF is suitable for NPT simulations of lipid bilayer systems using the PME method for the nonbonded interactions but systematically yields lower values of surface area per lipid compared to experimental estimates when the long-range LJ interactions are included. Here we develop an automated workflow to optimize the parameters of the nonbonded interactions (partial atomic charges and Lennard-Jones parameters). 1,2-dipalmitoyl-sn-phosphatidylcholine (DPPC) is used as the prototype and various structural properties (surface area per lipid, NMR deuterium order parameters, radial distribution functions of water for selected atoms) are used as targets. In each optimization step, free energy perturbation theory is used to estimate the properties from trajectories generated by the optimal parameters in the previous step. QM calculations of partial atomic charges are also used to guide the optimization. The parametrization improves the above-mentioned properties significantly with small changes to the C36 lipid FF and allows MD simulations of lipid systems to use the LJ-PME method.

Ab Initio Calculations of Partial Charges at Kaolinite Edge Sites and Molecular Dynamics Simulations of Cation Adsorption in Saline Solutions at and above the pH of Zero Charge

Molecular dynamics simulations are used to study adsorption of cations on the (010) kaolinite edge surface at and above the pH of zero charge. The cation solutions are highly concentrated and inclu...

Benchmark of different charges for prediction of the partitioning coefficient through the hydrophilic/lipophilic index.

A few different theoretical methods for assigning the partial atomic charges were benchmarked for calculation of the hydrophilic/lipophilic index (HLI). The coefficients were selected to produce the best correlation of the HLI values with the experimental octanol-water partition. Different parameters were checked in calculations of partial charges to get the best performance of the HLI values obtained. Thus, four partitioning schemes (Coulson, Mulliken, Merz-Kollman, Ford-Wang) were benchmarked for calculations of atomic charges with six semiempirical methods (AM1, PM3, RM1, PM6, PM6-D3H4, PM7). Moreover, five distinct types of partial atomic charges (Mulliken, Hirshfeld, Löwdin, CHELPG, NPA), obtained at the Hartree-Fock and DFT levels of theory with three basis sets, were tested for their ability to produce the HLI values with the best correlation to experimental logP coefficients of 50 mono-charged organic anions. In the case of the semiempirical methods, the best correlation between the HLI and logP values (the correlation coefficient r = 0.9216) was obtained with the AM1 Ford-Wang parametric electrostatic potential charges. The Mulliken and Coulson charges calculated with the PM7 method can be used as an alternative to AM1, with the r values of 0.9107 and 0.8984, respectively. In the case of the DFT, the PBE/def2-TZVP natural population analysis charges produce the best correlation (r = 0.9220). Nevertheless, in spite of a marginally lower performance (r = 0.9159), the NPA charges computed at the PBE/def2-SVP level are more robust and can be regarded as the optimum choice for calculating the HLI values. Graphical abstract The hydrophilic/lipophilic index (HLI).

Insights into the Chemical Mechanism for CO2(aq) and H+ in Aqueous Diamine Solutions - An Experimental Stopped-Flow Kinetic and 1H/13C NMR Study of Aqueous Solutions of N,N-Dimethylethylenediamine for Postcombustion CO2 Capture.

In an effort to advance the understanding of multiamine based CO2 capture process absorbents, we report here the determination of the kinetic and equilibrium constants for a simple linear diamine N,N-dimethylethylenediamine (DMEDA) via stopped-flow spectrophotometric kinetic measurements and 1H/13C NMR titrations at 25.0 °C. From the kinetic data, the formation of monocarbamic acid (DMEDACOOH) from the reaction of DMEDA with CO2(aq) is the dominant reaction at high pH > 9.0 (k7 = 6.99 × 103 M-1·s-1). Below this pH, the formation of protonated monocarbamic acid (DMEDACOOH2) via the pathway involving DMEDAH+ and CO2(aq) becomes active and contributes to the kinetics despite the 107-fold decrease in the rate constant between the two pathways. 1H and 13C NMR spectra as a function of decreasing pH (increasing HCl concentration) at 25.0 °C have been evaluated here to confirm the protonation events in DMEDA. Calculations of the respective DMEDA nitrogen partial charges have also been undertaken to support the NMR protonation study. A comparison of the DMEDA kinetic constants with the corresponding data for piperazine (PZ) reveals that despite the larger basicity of DMEDA, the enhanced and superior kinetic performance of PZ with CO2(aq) above its predicted Bronsted reactivity is not observed in DMEDA.

Effect of hydrostatic strain on the electronic transport properties of CsPbI3

We conducted ballistic conductance calculations to study the effect of hydrostatic strain on the electronic transport properties of α-CsPbI3. We found that the strain has a profound effect on the electronic transport in the system. For example, for a given value of applied voltage bias the current decreases almost linearly with increasing the tensile strain. On the contrary, compression increases the charge transport and reduces the band gap of the material. The obtained results are explained by strain-induced spatial variations of electronic density in the system, as revealed in our density-derived electrostatic and chemical partial charge calculations. The obtained results can be useful in enhancing photovoltaic performance of lead-halide perovskites by strain engineering.

General Force-Field Parametrization Scheme for Molecular Dynamics Simulations of Conjugated Materials in Solution.

We describe a general scheme to obtain force-field parameters for classical molecular dynamics simulations of conjugated polymers. We identify a computationally inexpensive methodology for calculation of accurate intermonomer dihedral potentials and partial charges. Our findings indicate that the use of a two-step methodology of geometry optimization and single-point energy calculations using DFT methods produces potentials which compare favorably to high level theory calculation. We also report the effects of varying the conjugated backbone length and alkyl side-chain lengths on the dihedral profiles and partial charge distributions and determine the existence of converged lengths above which convergence is achieved in the force-field parameter sets. We thus determine which calculations are required for accurate parametrization and the scope of a given parameter set for variations to a given molecule. We perform simulations of long oligomers of dioctylfluorene and hexylthiophene in explicit solvent and find peristence lengths and end-length distributions consistent with experimental values.

Molecular descriptors as proxies for the modeling of the materials and their environmental impact

For the prediction of material's properties and of interaction of molecules with the surroundings, one needs to know their properties. Usually, the molecular properties are revealed through experimental measurements. It can be a tedious, time-consuming, and costly work. On the other hand, computational chemistry readily generates a huge number of data which can provide various molecular descriptors. These can be various observable properties (bond lengths and angles, dipole moments, etc...), but also the unobservable properties (partial atomic charges, electronegativity, various latent variables ....). There is an urgent need to develop accurate and economical screening tools that predict potential toxicity and environmental burden of various chemicals. Equally important is the design of safer alternatives. Molecular modeling methods offer one of several complementary approaches to evaluate the risk to human health and the environment as a result of exposure to environmental chemicals. These tools can streamline the hazard assessment process by simulating possible modes of action and providing virtual screening tools that can help prioritize bioassay requirements. Tailoring these strategies to the particular challenges presented by environmental chemical interactions make them even more effective. Advances in the fields of computational chemistry and molecular toxicology in recent decades allow the development of predictive models that inform the design of molecules with reduced potential to be toxic to humans or to the environment. As an example we present the novel methodology for the computational evaluation of pKa values of various organic bases, based on calculation of partial atomic charges by a simple semiempirical QM method.

High-quality and universal empirical atomic charges for chemoinformatics applications.

BackgroundPartial atomic charges describe the distribution of electron density in a molecule and therefore provide clues to the chemical behaviour of molecules. Recently, these charges have become popular in chemoinformatics, as they are informative descriptors that can be utilised in pharmacophore design, virtual screening, similarity searches etc. Especially conformationally-dependent charges perform very successfully. In particular, their fast and accurate calculation via the Electronegativity Equalization Method (EEM) seems very promising for chemoinformatics applications. Unfortunately, published EEM parameter sets include only parameters for basic atom types and they often miss parameters for halogens, phosphorus, sulphur, triple bonded carbon etc. Therefore their applicability for drug-like molecules is limited.ResultsWe have prepared six EEM parameter sets which enable the user to calculate EEM charges in a quality comparable to quantum mechanics (QM) charges based on the most common charge calculation schemes (i.e., MPA, NPA and AIM) and a robust QM approach (HF/6-311G, B3LYP/6-311G). The calculated EEM parameters exhibited very good quality on a training set (R^2 > 0.9) and also on a test set (R^2 > 0.93). They are applicable for at least 95 % of molecules in key drug databases (DrugBank, ChEMBL, Pubchem and ZINC) compared to less than 60 % of the molecules from these databases for which currently used EEM parameters are applicable.ConclusionsWe developed EEM parameters enabling the fast calculation of high-quality partial atomic charges for almost all drug-like molecules. In parallel, we provide a software solution for their easy computation (http://ncbr.muni.cz/eem_parameters). It enables the direct application of EEM in chemoinformatics.Electronic supplementary materialThe online version of this article (doi:10.1186/s13321-015-0107-1) contains supplementary material, which is available to authorized users.

Molecular dynamics simulation studies of p-xylene on graphene surface: effect of partial charge calculation method on adsorption energies

We report the results of molecular dynamics (MD) simulations of the adsorption of p-xylene on graphene nanosheet in a canonical (NVT) ensemble at 293.15 K. The high adsorption energy is expected to result mainly from the π–π stacking interactions, because of the attraction between the π orbital on the graphene and the electronic density in the p-xylene aromatic rings. In this study, a developed intermolecular force field for the interaction between graphene and p-xylene is used. The improved performance of the developed potential function is shown to reproduce more accurate adsorption energies. Molecular dynamics simulations are also accomplished for investigating the wettability of the graphene surface by the organic liquid. Our findings denote a strong adhesion between the surface and the p-xylene liquid, and the low contact angle obtained θ = 49.16°, indicates strong liquid–surface intermolecular interactions and reflects the high wettability of the graphene surface by the liquid droplet, and thus increases the tendency of the liquid to spread over a large area of the surface.

Structure based 3D-QSAR studies of Interleukin-2 inhibitors: Comparing the quality and predictivity of 3D-QSAR models obtained from different alignment methods and charge calculations

Interleukin-2 is an essential cytokine in an innate immune response, and is a promising drug target for several immunological disorders. In the present study, structure-based 3D-QSAR modeling was carried out via Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA) methods. Six different partial charge calculation methods were used in combination with two different alignment methods to scrutinize their effects on the predictive power of 3D-QSAR models. The best CoMFA and CoMSIA models were obtained with the AM1 charges when used with co-conformer based substructure alignment (CCBSA) method. The obtained models posses excellent correlation coefficient value and also exhibited good predictive power (for CoMFA: q2=0.619; r2=0.890; r2Pred=0.765 and for CoMSIA: q2=0.607; r2=0.884; r2Pred=0.655). The developed models were further validated by using a set of another sixteen compounds as external test set 2 and both models showed strong predictive power with r2Pred=>0.8. The contour maps obtained from these models better interpret the structure activity relationship; hence the developed models would help to design and optimize more potent IL-2 inhibitors. The results might have implications for rational design of specific anti-inflammatory compounds with improved affinity and selectivity.