Electronic absorption spectra of pyridine and nicotine in aqueous solution with a combined molecular dynamics and polarizable QM/MM approach

The electronic absorption spectra of pyridine and nicotine in aqueous solution have been computed using a multistep approach. The computational protocol consists in studying the solute solvation with accurate molecular dynamics simulations, characterizing the hydrogen bond interactions, and calculating electronic transitions for a series of configurations extracted from the molecular dynamics trajectories with a polarizable QM/MM scheme based on the fluctuating charge model. Molecular dynamics simulations and electronic transition calculations have been performed on both pyridine and nicotine. Furthermore, the contributions of solute vibrational effect on electronic absorption spectra have been taken into account in the so called vertical gradient approximation. \ua9 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc

A quantitative structure-permeability relationship model for split-thickness skin absorption, reasoning for the choice of the database.

The skin is the largest organ in the human body, protecting the body from xenobiotic invasion (1). Local and systemic drugs may also be administered through the skin, therefore the need to measure the permeability of the skin to chemicals has long been apparent. The use of in vivo or in vitro techniques is time-consuming, since it is not only necessary to conduct a permeation study, but also to optimize experimental conditions and build analytical methods for each chemical. Moreover, it is not possible to assess the permeability of compounds not yet synthesised. An alternative option can be the development of Quantitative Structure-Permeability Relationships (QSPRs). These in silico models aim to form a relationship between the absorption of chemicals through the skin and their physico-chemical and/or structural properties (2). Knowing that permeability can be affected by different experimental conditions, the aim of this study is to build a QSPR based on uniform and consistent experimental conditions, but with a significant database size. Two different databases were compared: the first one was obtained only from Zhang et al (3), the second one was created from multiple literature sources, fulfilling the following conditions: - Data (log Kp values) were obtained by an in vitro diffusion system; - The membrane was human stratum corneum and viable epidermis; - The donor solvent was an aqueous solution; - No permeation enhancement technologies were used; - No association with other chemicals were considered. The geometrical structures of all chemicals were optimized with MM2 forcefield. Molecular descriptors and fingerprints were generated where possible. For each database, a wide range of Multi Linear Regression models were built using QSARins (4, 5) through a stepwise forward regression process. The models have been validated according to Golbraikh and Tropsha (6) criteria and the best ones have been selected according to the Multi-Criteria Decision Making (7). The model calculated from the data obtained from a single source shows better correlation, robustness, and predictivity, revealing a grade of uncertainty coming from an inter laboratory variability of the different sources used to build the database. REFERENCES 1. Baba H, Takahara J-i, Mamitsuka H. In Silico Predictions of Human Skin Permeability using Nonlinear Quantitative Structure–Property Relationship Models. Pharmaceutical Research. 2015;32(7):2360-71. 2. Moss GP, Cronin MTD. Quantitative structure–permeability relationships for percutaneous absorption: re-analysis of steroid data. International Journal of Pharmaceutics. 2002;238(1):105-9. 3. Zhang K, Chen M, Scriba GKE, Abraham MH, Fahr A, Liu X. Human Skin Permeation of Neutral Species and Ionic Species: Extended Linear Free Energy Relationship Analyses. Journal of Pharmaceutical Sciences. 2012;101(6):2034-44. 4. Gramatica P, Chirico N, Papa E, Cassani S, Kovarich S. QSARINS: A new software for the development, analysis, and validation of QSAR MLR models. Journal of Computational Chemistry. 2013;34(24):2121-32. 5. Gramatica P, Cassani S, Chirico N. QSARINS-chem: Insubria datasets and new QSAR/QSPR models for environmental pollutants in QSARINS. Journal of Computational Chemistry. 2014;35(13):1036-44. 6. Golbraikh A, Tropsha A. Beware of q2! Journal of Molecular Graphics and Modelling. 2002;20(4):269-76. 7. Keller HR, Massart DL, Brans JP. Multicriteria decision making: A case study. Chemometrics and Intelligent Laboratory Systems. 1991;11(2):175-89.Peer reviewedFinal Published versio

Additive CHARMM force field for naturally occurring modified ribonucleotides

International audienceMore than 100 naturally occurring modified nucleotides have been found in RNA molecules, in particular in tRNAs. We have determined molecular mechanics force field parameters compatible with the CHARMM36 all-atom additive force field for all these modifications using the CHARMM force field parametrization strategy. Emphasis was placed on fine tuning of the partial atomic charges and torsion angle parameters. Quantum mechanics calculations on model compounds provided the initial set of target data, and extensive molecular dynamics simulations of nucleotides and oligonucleotides in aqueous solutions were used for further refinement against experimental data. The presented parameters will allow for computational studies of a wide range of RNAs containing modified nucleotides, including the ribosome and transfer RNAs. (C) 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc

GIAO-PCM Calculations on Alanine Diamide Models Aimed at Predicting Protein Secondary Structures

In this paper we extend our theoretical studies dealing with the dependence of relative proton and carbon chemical shifts (CSs) of protein backbone atoms on their conformational position. In an earlier paper (A. Czajlik, I. Hudáky, A. Perczel, J Comp Chem 2011, 32, 3362) we reported on a fair agreement between calculated and observed backbone CSs as a function of backbone conformation. Applying the polarizable continuum model (PCM) in this work, we compare relative CSs of fully optimized alanine diamide conformers with gas phase calculations and experimental results. Along a path on the Ramachandran surface, we collated calculated relative CSs obtained with and without explicit water molecules, as well as with and without considering the PCM reaction field. Furthermore, we traced the energetically relevant reaction paths along the torsional angle ψ connecting the lowest energy minima (helical, extended, polyproline II and inverse γ-turn) on the Ramachandran plot, with the prospect to facilitate identifying them by their relative CSs. We found that consideration of the solvent effect of the environment around a diamide model improves the agreement with experimental findings on abundant conformers. This agreement is of the level achieved previously by a thorough gas phase investigation on considerably larger oligoalanine models. By relating DeltaδCα, DeltaδHα and DeltaδCβ values of polyproline II and inverse γ-turn to the experimentally well characterized helical and extended data, our calculations contribute to protein secondary structure prediction based on nuclear magnetic CS

A Deeper Insight into Strain for the Sila-bi[6]prismane (Si\u3csub\u3e18\u3c/sub\u3eH\u3csub\u3e12\u3c/sub\u3e) Cluster with its Endohedrally Trapped Silicon Atom, Si\u3csub\u3e19\u3c/sub\u3eH\u3csub\u3e12\u3c/sub\u3e

A new family of over-coordinated hydrogenated silicon nanoclusters with outstanding optical and mechanical properties has recently been proposed. For one member of this family, namely the highly symmetric Si19H12 nanocrystal, strain calculations have been presented with the goal to question its thermal stability and the underlying mechanism of ultrastability and electron-deficiency aromaticity. Here, the invalidity of these strain energy (SE) calculations is demonstrated mainly based on a fundamentally wrong usage of homodesmotic reactions, the miscounting of atomic bonds, and arithmetic errors. Since the article in question is entirely anchored on those erroneous SE values, all of its conclusions and predictions become without meaning. We provide evidence here that the nanocrystal in question suffers from such low levels of strain that its thermodynamical stability should be largely sufficient for device fabrication in a realistic plasma reactor. Most remarkably, the two “alternative,” irregular isomers explicitly proposed in the aforementioned article are also electron-deficient, nontetrahedral, ultrastable, and aromatic nicely underlining the universality of the ultrastability concept for nanometric hydrogenated silicon clusters. © 2015 Wiley Periodicals, Inc

A Continuum Poisson-Boltzmann Model for Membrane Channel Proteins

Membrane proteins constitute a large portion of the human proteome and perform a variety of important functions as membrane receptors, transport proteins, enzymes, signaling proteins, and more. The computational studies of membrane proteins are usually much more complicated than those of globular proteins. Here we propose a new continuum model for Poisson-Boltzmann calculations of membrane channel proteins. Major improvements over the existing continuum slab model are as follows: 1) The location and thickness of the slab model are fine-tuned based on explicit-solvent MD simulations. 2) The highly different accessibility in the membrane and water regions are addressed with a two-step, two-probe grid labeling procedure, and 3) The water pores/channels are automatically identified. The new continuum membrane model is optimized (by adjusting the membrane probe, as well as the slab thickness and center) to best reproduce the distributions of buried water molecules in the membrane region as sampled in explicit water simulations. Our optimization also shows that the widely adopted water probe of 1.4 {\AA} for globular proteins is a very reasonable default value for membrane protein simulations. It gives an overall minimum number of inconsistencies between the continuum and explicit representations of water distributions in membrane channel proteins, at least in the water accessible pore/channel regions that we focus on. Finally, we validate the new membrane model by carrying out binding affinity calculations for a potassium channel, and we observe a good agreement with experiment results.Comment: 40 pages, 6 figures, 5 table

Improvements to the APBS biomolecular solvation software suite

The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that has provided impact in the study of a broad range of chemical, biological, and biomedical applications. APBS addresses three key technology challenges for understanding solvation and electrostatics in biomedical applications: accurate and efficient models for biomolecular solvation and electrostatics, robust and scalable software for applying those theories to biomolecular systems, and mechanisms for sharing and analyzing biomolecular electrostatics data in the scientific community. To address new research applications and advancing computational capabilities, we have continually updated APBS and its suite of accompanying software since its release in 2001. In this manuscript, we discuss the models and capabilities that have recently been implemented within the APBS software package including: a Poisson-Boltzmann analytical and a semi-analytical solver, an optimized boundary element solver, a geometry-based geometric flow solvation model, a graph theory based algorithm for determining p$K_a$ values, and an improved web-based visualization tool for viewing electrostatics

Extension of the QuickFF force field protocol for an improved accuracy of structural, vibrational, mechanical and thermal properties of metal-organic frameworks

QuickFF was originally launched in 2015 to derive accurate force fields for isolated and complex molecular systems in a quick and easy way. Apart from the general applicability, the functionality was especially tested for metal-organic frameworks (MOFs), a class of hybrid materials consisting of organic and inorganic building blocks. Herein, we launch a new release of the QuickFF protocol which includes new major features to predict structural, vibrational, mechanical and thermal properties with greater accuracy, without compromising its robustness and transparent workflow. First, the ab initio data necessary for the fitting procedure may now also be derived from periodic models for the molecular system, as opposed to the earlier cluster-based models. This is essential for an accurate description of MOFs with one-dimensional metal-oxide chains. Second, cross terms that couple internal coordinates (ICs) and anharmonic contributions for bond and bend terms are implemented. These features are essential for a proper description of vibrational and thermal properties. Third, the fitting scheme was modified to improve robustness and accuracy. The new features are tested on MIL-53(Al), MOF-5, CAU-13 and NOTT-300. As expected, periodic input data are proven to be essential for a correct description of structural, vibrational and thermodynamic properties of MIL-53(Al). Bulk moduli and thermal expansion coefficients of MOF-5 are very accurately reproduced by static and dynamic simulations using the newly derived force fields which include cross terms and anharmonic corrections. For the flexible materials CAU-13 and NOTT-300, the transition pressure is accurately predicted provided cross terms are taken into account

Atomic radius and charge parameter uncertainty in biomolecular solvation energy calculations

Atomic radii and charges are two major parameters used in implicit solvent electrostatics and energy calculations. The optimization problem for charges and radii is under-determined, leading to uncertainty in the values of these parameters and in the results of solvation energy calculations using these parameters. This paper presents a new method for quantifying this uncertainty in implicit solvation calculations of small molecules using surrogate models based on generalized polynomial chaos (gPC) expansions. There are relatively few atom types used to specify radii parameters in implicit solvation calculations; therefore, surrogate models for these low-dimensional spaces could be constructed using least-squares fitting. However, there are many more types of atomic charges; therefore, construction of surrogate models for the charge parameter space requires compressed sensing combined with an iterative rotation method to enhance problem sparsity. We demonstrate the application of the method by presenting results for the uncertainties in small molecule solvation energies based on these approaches. The method presented in this paper is a promising approach for efficiently quantifying uncertainty in a wide range of force field parameterization problems, including those beyond continuum solvation calculations.The intent of this study is to provide a way for developers of implicit solvent model parameter sets to understand the sensitivity of their target properties (solvation energy) on underlying choices for solute radius and charge parameters