Parameterization of Large Ligands for Gromacs Molecular Dynamics Simulation with LigParGen

Molecular dynamics (MD) simulation is a powerful method of investigating the interaction between molecular species. Defining the mechanical properties and topologies for all components involved is critical. While parameters for proteins are well established, those for the wide range of ligands and substrates are not. Here we introduce a very useful service which is designed for small organic molecules. We describe a protocol to extend this tool to beyond its current size (200 atoms) and formal charge (2+ to 2-) limits.

An overview of albumin and alpha-1-acid glycoprotein main characteristics: highlighting the roles of amino acids in binding kinetics and molecular interactions

Although Albumin (ALB) and alpha-1-acid glycoprotein (AGP) have distinctive structural and functional characteristics, they both play a key role in binding a large variety of endogenous and exogenous ligands. An extensive binding to these plasma proteins could have a potential impact on drugs disposition (e.g. bioavailability, distribution and clearance), on their innocuity and their efficacy. This review summarizes the common knowledge about the structural and molecular characteristics of both ALB and AGP in humans, and about the most involved amino acids in their high-affinity binding pockets. However, the variability in residues found in binding pockets, for the same species, allows each plasma protein to interact differently with the ligands. The protein-ligand interaction influences differently the disposition of drugs that bind to either of these plasma proteins. The content of this review is useful for the design of new drug entities with high-binding characteristics, in qualitative and quantitative modelling (e.g. in vitro-in vivo extrapolations, 3D molecular docking, interspecies extrapolations), and for other interdisciplinary research.

Antioxidant defence system is responsible for the toxicological interactions of mixtures: A case study on PFOS and PFOA in Daphnia magna

Perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) are two types of perfluorinated compounds (PFCs) frequently studied in recent years due to their potential for bioaccumulation and toxicity to humans. Usually, PFCs can co-exist in various environment. Therefore, over- or under-estimated risk assessments would result if antagonism or synergism occurred in mixture toxicity. In the present study, the acute and chronic toxicities of single and mixtures of PFOA and PFOS to Daphnia magna were investigated. PFOS was more toxic than PFOA, both in 48-h acute toxicity and 21-d chronic toxicity. In acute toxicity tests, mixture toxicities showed strong synergistic effects on mortality. The experimental EC₅₀ of the mixture is 4.44 × 10^-5 mol/L, whereas the predicted EC₅₀ is 8.19 × 10^-5 mol/L by Concentration Addition Model and 9.73 × 10^-5 mol/L by Independent Action Model. In chronic toxicity tests, synergistic effects were also found in the aspects of offspring. The offspring rate is reduced significantly to 39.8% at the 9.61 × 10^-7 mol/L of mixture, while, PFOS and PFOA do not have effects when they are tested individually at corresponding concentrations. To explore the potential mechanism of the synergistic effect, the interactions between PFCs and proteins, including acetylcholinesterase, superoxide dismutase, catalase, ecdysone receptor and glutathione-S-transferase, were investigated by the Molecular Docking. The docking results revealed that the driving forces for the binding of PFCs with proteins were predominantly hydrophobic and hydrogen-bonding interactions. Based on the binding models, we deduced that the potential mechanism of synergism is that PFOS and PFOA have similar binding modes with catalase and have different binding modes with superoxide dismutase. Overall, these data provide experimental evidence that there is strong synergism in acute and chronic toxicity of mixtures to D. magna and demonstrate that molecular structure of some components of the antioxidant defence system contributes to the synergistic interaction.

Receptor pharmacophore ensemble (REPHARMBLE): a probabilistic pharmacophore modeling approach using multiple protein-ligand complexes

Ensemble methods are gaining more importance in structure-based approaches as single protein-ligand complexes strongly influence the outcomes of virtual screening. Structure-based pharmacophore modeling based on a single protein-ligand complex with complex feature combinations is often limited to certain chemical classes. The REPHARMBLE (receptor pharmacophore ensemble) approach presented here examines the ability of an ensemble of selected protein-ligand complexes to populate pharmacophore space in the ligand binding site, rigorously assesses the importance of pharmacophore features using Poisson statistic and information theory-based entropy calculations, and generates pharmacophore models with high probabilities. In addition, an ensemble scoring function that combines all the resultant high-scoring pharmacophore models to score molecules is derived. The REPHARMBLE approach was evaluated on ten DUD-E benchmark datasets and afforded good screening performance, as measured by receiver operating characteristic, enrichment factor and Güner-Henry score. Although one of the high-scoring models achieved superior statistical results in each dataset, the ensemble scoring function balanced the shortcomings of each model and passed with close performance measures. This approach offers a reliable way of choosing the best-scoring features to build four-feature pharmacophore queries and customize a target-biased 'pharmacophore ensemble' scoring function for subsequent virtual screening.

Native Top-Down Mass Spectrometry and Ion Mobility MS for Characterizing the Cobalt and Manganese Metal Binding of α-Synuclein Protein

Structural characterization of intrinsically disordered proteins (IDPs) has been a major challenge in the field of protein science due to limited capabilities to obtain full-length high-resolution structures. Native ESI-MS with top-down MS was utilized to obtain structural features of protein-ligand binding for the Parkinson's disease-related protein, α-synuclein (αSyn), which is natively unstructured. Binding of heavy metals has been implicated in the accelerated formation of αSyn aggregation. Using high-resolution Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry, native top-down MS with various fragmentation methods, including electron capture dissociation (ECD), collisional activated dissociation (CAD), and multistage tandem MS (MS³), deduced the binding sites of cobalt and manganese to the C-terminal region of the protein. Ion mobility MS (IM-MS) revealed a collapse toward compacted states of αSyn upon metal binding. The combination of native top-down MS and IM-MS provides structural information of protein-ligand interactions for intrinsically disordered proteins. Graphical Abstract ᅟ.

Evaluation of the novel algorithm of flexible ligand docking with moveable target-protein atoms

We present the novel docking algorithm based on the Tensor Train decomposition and the TT-Cross global optimization. The algorithm is applied to the docking problem with flexible ligand and moveable protein atoms. The energy of the protein-ligand complex is calculated in the frame of the MMFF94 force field in vacuum. The grid of precalculated energy potentials of probe ligand atoms in the field of the target protein atoms is not used. The energy of the protein-ligand complex for any given configuration is computed directly with the MMFF94 force field without any fitting parameters. The conformation space of the system coordinates is formed by translations and rotations of the ligand as a whole, by the ligand torsions and also by Cartesian coordinates of the selected target protein atoms. Mobility of protein and ligand atoms is taken into account in the docking process simultaneously and equally. The algorithm is realized in the novel parallel docking SOL-P program and results of its performance for a set of 30 protein-ligand complexes are presented. Dependence of the docking positioning accuracy is investigated as a function of parameters of the docking algorithm and the number of protein moveable atoms. It is shown that mobility of the protein atoms improves docking positioning accuracy. The SOL-P program is able to perform docking of a flexible ligand into the active site of the target protein with several dozens of protein moveable atoms: the native crystallized ligand pose is correctly found as the global energy minimum in the search space with 157 dimensions using 4700 CPU ∗ h at the Lomonosov supercomputer.

Optimization of Electrospray Ionization by Statistical Design of Experiments and Response Surface Methodology: Protein-Ligand Equilibrium Dissociation Constant Determinations

Electrospray ionization mass spectrometry (ESI-MS) binding studies between proteins and ligands under native conditions require that instrumental ESI source conditions are optimized if relative solution-phase equilibrium concentrations between the protein-ligand complex and free protein are to be retained. Instrumental ESI source conditions that simultaneously maximize the relative ionization efficiency of the protein-ligand complex over free protein and minimize the protein-ligand complex dissociation during the ESI process and the transfer from atmospheric pressure to vacuum are generally specific for each protein-ligand system and should be established when an accurate equilibrium dissociation constant (KD) is to be determined via titration. In this paper, a straightforward and systematic approach for ESI source optimization is presented. The method uses statistical design of experiments (DOE) in conjunction with response surface methodology (RSM) and is demonstrated for the complexes between Plasmodium vivax guanylate kinase (PvGK) and two ligands: 5'-guanosine monophosphate (GMP) and 5'-guanosine diphosphate (GDP). It was verified that even though the ligands are structurally similar, the most appropriate ESI conditions for KD determination by titration are different for each. Graphical Abstract ᅟ.

Protoss: a holistic approach to predict tautomers and protonation states in protein-ligand complexes

The calculation of hydrogen positions is a common preprocessing step when working with crystal structures of protein-ligand complexes. An explicit description of hydrogen atoms is generally needed in order to analyze the binding mode of particular ligands or to calculate the associated binding energies. Due to the large number of degrees of freedom resulting from different chemical moieties and the high degree of mutual dependence this problem is anything but trivial. In addition to an efficient algorithm to take care of the complexity resulting from complicated hydrogen bonding networks, a robust chemical model is needed to describe effects such as tautomerism and ionization consistently. We present a novel method for the placement of hydrogen coordinates in protein-ligand complexes which takes tautomers and protonation states of both protein and ligand into account. Our method generates the most probable hydrogen positions on the basis of an optimal hydrogen bonding network using an empirical scoring function. The high quality of our results could be verified by comparison to the manually adjusted Astex diverse set and a remarkably low rate of undesirable hydrogen contacts compared to other tools.

Quantum Mechanics Approaches to Drug Research in the Era of Structural Chemogenomics

The rapid growth of the available crystallographic information about proteins and binding pockets creates remarkable opportunities for enriching the drug research pipelines with computational prediction of novel protein-ligand interactions. While ab initio quantum mechanical approaches are known to provide unprecedented accuracy in structure-based binding energy calculations, they are limited to only small systems of dozens of atoms. In the structural chemogenomics era, it is critical that new approaches are developed that enable application of QM methodologies to non-covalent interactions in systems as large as protein-ligand complexes and conformational ensembles. This perspective highlights recent advances towards bridging the gap between high accuracy and high volume computations in drug research.

Free Energy Calculations of Mutations Involving a Tightly Bound Water Molecule and Ligand Substitutions in a Ligand-Protein Complex

The accurate calculation of the free energy of interaction of protein-water-ligand systems has an important role in molecular recognition and drug design that is often not fully considered. We report free energy thermodynamic integration calculations used to evaluate the effects of inclusion, neglect, and targeting and removal (i.e., systematic substitution by ligand functional groups) of an important, tightly bound, water molecule in the SH3 domain of Abl tyrosine kinase. The effects of this water molecule on the free energies of interaction of several Abl-SH3 domain-ligand systems reveal that there is an unfavourable free energy change associated with its removal into the bulk solvent. Only three substitutions by an additional functional group (out of methyl, ethyl, hydroxyl, amino, and amide groups) in the phenyl ring of a tyrosine in the peptide ligand resulted in a favourable change in the free energy of binding upon replacement of the ordered water molecule. This computational approach provides a direct route to the systematic and rigorous prediction of the thermodynamic influence of ordered, structural water molecules on ligand modification and optimization in drug design by calculating free energy changes in protein-water-ligand systems.