A new set of atomic radii for accurate estimation of solvation free energy by Poisson-Boltzmann solvent model

Insights from the molecular mechanism of pyrazinamide to mutated pyrazinamidase linked to the pncA gene in clinical isolates of Mycobacterium tuberculosis

This study aims to conduct a comprehensive molecular dynamics strategy to evaluate whether mutations found in pyrazinamide monoresistant (PZAMR) strains of Mycobacterium tuberculosis (MTB) can potentially reduce the effectiveness of pyrazinamide (PZA) for tuberculosis (TB) treatment. Five single point mutations of pyrazinamidase (PZAse), an enzyme which is responsible for the activation of prodrug PZA into pyrazinoic acid, found in MTB clinical isolates, namely His82Arg, Thr87Met, Ser66Pro, Ala171Val, and Pro62Leu, were analyzed by the dynamics simulations both in the apo state (unbound state) and in the PZA bound state. The results showed that the mutation of His82 to Arg, Thr87 to Met, and Ser66 to Pro in PZAse affects the coordination state of the Fe2+ ion, which is a cofactor required for enzyme activity. These mutations change the flexibility, stability, and fluctuation of His51, His57, and ASP49 amino acid residues around the Fe2+ ion, culminating in an unstable complex and dissociation of PZA from the PZAse binding site. However, mutations of Ala171 to Val and Pro62 to Leu were found to have no effect on the complex's stability. Based on the results, PZAse mutations of His82Arg, Thr87Met, and Ser66Pro culminated in weak binding affinity for PZA and caused significant structural deformations that led to PZA resistance. Future structural and functional studies, as well as investigations into other aspects of drug resistance in PZAse, will require experimental clarification.Communicated by Ramaswamy H. Sarma.

The Hydrolysis Rate of Paraoxonase-1 Q and R Isoenzymes: An In Silico Study Based on In Vitro Data

Human serum paraoxonase-1 (PON1) is an important hydrolase-type enzyme found in numerous tissues. Notably, it can exist in two isozyme-forms, Q and R, that exhibit different activities. This study presents an in silico (QSAR, Docking, MD and QM/MM) study of a set of compounds on the activity towards the PON1 isoenzymes (QPON1 and RPON1). Different rates of reaction for the Q and R isoenzymes were analyzed by modelling the effect of Q192R mutation on active sites. It was concluded that the Q192R mutation is not even close to the active site, while it is still changing the geometry of it. Using the combined genetic algorithm with multiple linear regression (GA-MLR) technique, several QSAR models were developed and relative activity rates of the isozymes of PON1 explained. From these, two QSAR models were selected, one each for the QPON1 and RPON1. Best selected models are four-variable MLR models for both Q and R isozymes with squared correlation coefficient R² values of 0.87 and 0.83, respectively. In addition, the applicability domain of the models was analyzed based on the Williams plot. The results were discussed in the light of the main factors that influence the hydrolysis activity of the PON1 isozymes.

Molecular Dynamics of Cobalt Protoporphyrin Antagonism of the Cancer Suppressor REV-ERBβ

Nuclear receptor REV-ERBβ is an overexpressed oncoprotein that has been used as a target for cancer treatment. The metal-complex nature of its ligand, iron protoporphyrin IX (Heme), enables the REV-ERBβ to be used for multiple therapeutic modalities as a photonuclease, a photosensitizer, or a fluorescence imaging agent. The replacement of iron with cobalt as the metal center of protoporphyrin IX changes the ligand from an agonist to an antagonist of REV-ERBβ. The mechanism behind that phenomenon is still unclear, despite the availability of crystal structures of REV-ERBβ in complex with Heme and cobalt protoporphyrin IX (CoPP). This study used molecular dynamic simulations to compare the effects of REV-ERBβ binding to Heme and CoPP, respectively. The initial poses of Heme and CoPP in complex with agonist and antagonist forms of REV-ERBβ were predicted using molecular docking. The binding energies of each ligand were calculated using the MM/PBSA method. The computed binding affinity of Heme to REV-ERBβ was stronger than that of CoPP, in agreement with experimental results. CoPP altered the conformation of the ligand-binding site of REV-ERBβ, disrupting the binding site for nuclear receptor corepressor, which is required for REV-ERBβ to regulate the transcription of downstream target genes. Those results suggest that a subtle change in the metal center of porphyrin can change the behavior of porphyrin in cancer cell signaling. Therefore, modification of porphyrin-based agents for cancer therapy should be conducted carefully to avoid triggering unfavorable effects.

Docking-Based Virtual Screening and Molecular Dynamics Simulations of Quercetin Analogs as Enoyl-Acyl Carrier Protein Reductase (InhA) Inhibitors of Mycobacterium tuberculosis

The emergence of multidrug-resistant Mycobacterium tuberculosis (MTB) has become a major problem in treating tuberculosis (TB) and shows the need to develop new and efficient drugs for better TB control. This study aimed to use in silico techniques to discover potential inhibitors to the Enoyl-[acyl-carrier-protein] reductase (InhA), which controls mycobacterial cell wall construction. Initially, 391 quercetin analogs present in the KNApSAck_3D database were selected, filters were sequentially applied by docking-based virtual screening. After recategorizing the variables (bond energy prediction and molecular interaction, including hydrogen bond and hydrophobic bond), compounds C00013874, C00006532, and C00013887 were selected as hit ligands. These compounds showed great hydrophobic contributions, and for each hit ligand, 100 ns of molecular dynamic simulations were performed, and the binding free energy was calculated. C00013874 demonstrated the greatest capacity for the InhA enzyme inhibition with ΔGbind = −148.651 kcal/mol compare to NAD (native ligand) presented a ΔGbind = −87.570 kcal/mol. These data are preliminary studies and might be a suitable candidate for further experimental analysis.

Implicit Solvents for the Polarizable Atomic Multipole AMOEBA Force Field

Computational protein design, ab initio protein/RNA folding, and protein-ligand screening can be too computationally demanding for explicit treatment of solvent. For these applications, implicit solvent offers a compelling alternative, which we describe here for the polarizable atomic multipole AMOEBA force field based on three treatments of continuum electrostatics: numerical solutions to the nonlinear and linearized versions of the Poisson-Boltzmann equation (PBE), the domain-decomposition conductor-like screening model (ddCOSMO) approximation to the PBE, and the analytic generalized Kirkwood (GK) approximation. The continuum electrostatics models are combined with a nonpolar estimator based on novel cavitation and dispersion terms. Electrostatic model parameters are numerically optimized using a least-squares style target function based on a library of 103 small-molecule solvation free energy differences. Mean signed errors for the adaptive Poisson-Boltzmann solver (APBS), ddCOSMO, and GK models are 0.05, 0.00, and 0.00 kcal/mol, respectively, while the mean unsigned errors are 0.70, 0.63, and 0.58 kcal/mol, respectively. Validation of the electrostatic response of the resulting implicit solvents, which are available in the Tinker (or Tinker-HP), OpenMM, and Force Field X software packages, is based on comparisons to explicit solvent simulations for a series of proteins and nucleic acids. Overall, the emergence of performative implicit solvent models for polarizable force fields opens the door to their use for folding and design applications.

Multidimensional Global Optimization and Robustness Analysis in the Context of Protein-Ligand Binding

Accuracy of protein-ligand binding free energy calculations utilizing implicit solvent models is critically affected by parameters of the underlying dielectric boundary, specifically, the atomic and water probe radii. Here, a global multidimensional optimization pipeline is developed to find optimal atomic radii specifically for protein-ligand binding calculations in implicit solvent. The computational pipeline has these three key components: (1) a massively parallel implementation of a deterministic global optimization algorithm (VTDIRECT95), (2) an accurate yet reasonably fast generalized Born implicit solvent model (GBNSR6), and (3) a novel robustness metric that helps distinguish between nearly degenerate local minima via a postprocessing step of the optimization. A graph-based "kT-connectivity" approach to explore and visualize the multidimensional energy landscape is proposed: local minima that can be reached from the global minimum without exceeding a given energy threshold (kT) are considered to be connected. As an illustration of the capabilities of the optimization pipeline, we apply it to find a global optimum in the space of just five radii: four atomic (O, H, N, and C) radii and water probe radius. The optimized radii, ρW = 1.37 Å, ρC = 1.40 Å, ρH = 1.55 Å, ρN = 2.35 Å, and ρO = 1.28 Å, lead to a closer agreement of electrostatic binding free energies with the explicit solvent reference than two commonly used sets of radii previously optimized for small molecules. At the same time, the ability of the optimizer to find the global optimum reveals fundamental limits of the common two-dielectric implicit solvation model: the computed electrostatic binding free energies are still almost 4 kcal/mol away from the explicit solvent reference. The proposed computational approach opens the possibility to further improve the accuracy of practical computational protocols for binding free energy calculations.

Tackling Halogenated Species with PBSA: Effect of Emulating the σ-Hole

To model halogen-bond phenomena using classical force fields, an extra point (EP) of charge is frequently introduced at a given distance from the halogen (X) to emulate the σ-hole. The resulting molecular dynamics (MD) trajectories can be used in subsequent molecular mechanics (MM) combined with Poisson-Boltzmann and surface area calculations (PBSA) to estimate protein-ligand binding free energies (Δ G_bind). While EP addition improves the MM/MD description of halogen-containing systems, its effect on the calculation of solvation free energies (Δ G_solv) using the PBSA approach is yet to be assessed. As the PBSA calculations depend, among other parameters, on the empirical assignment of radii (PB radii), a problematic issue arises, since standard halogen radii are smaller than the typical X···EP distances, thus placing the EP within the solvent dielectric. Herein, we took a common literature EP parametrization scheme, which uses X···EP = R_min and RESP charges in the context of GAFF, and performed a comprehensive study on the performance of PBSA (using three different setups) in the calculation of Δ G_solv values for 142 halogenated compounds (bearing Cl, Br, or I) for which the experimental values are known. By conducting an optimization (minimizing the error against experimental values), we provide a new optimized set of halogen PB radii, for each PBSA setup, that should be used in the context of the aforementioned scenario. A simultaneous optimization of PB radii and X···EP distances shows that a wide range of distance/radius pairs can be used without significant loss of accuracy, therefore laying the basis for expanding this halogen radii optimization strategy to other force fields and EP implementations. As ligand Δ G_solv estimation is an important term in the determination of protein-ligand Δ G_bind, this work is particularly relevant in the framework of structure-based virtual screening and related computer-aided drug design routines.

Combining the polarizable Drude force field with a continuum electrostatic Poisson-Boltzmann implicit solvation model

In this work, we have combined the polarizable force field based on the classical Drude oscillator with a continuum Poisson-Boltzmann/solvent-accessible surface area (PB/SASA) model. In practice, the positions of the Drude particles experiencing the solvent reaction field arising from the fixed charges and induced polarization of the solute must be optimized in a self-consistent manner. Here, we parameterized the model to reproduce experimental solvation free energies of a set of small molecules. The model reproduces well-experimental solvation free energies of 70 molecules, yielding a root mean square difference of 0.8 kcal/mol versus 2.5 kcal/mol for the CHARMM36 additive force field. The polarization work associated with the solute transfer from the gas-phase to the polar solvent, a term neglected in the framework of additive force fields, was found to make a large contribution to the total solvation free energy, comparable to the polar solute-solvent solvation contribution. The Drude PB/SASA also reproduces well the electronic polarization from the explicit solvent simulations of a small protein, BPTI. Model validation was based on comparisons with the experimental relative binding free energies of 371 single alanine mutations. With the Drude PB/SASA model the root mean square deviation between the predicted and experimental relative binding free energies is 3.35 kcal/mol, lower than 5.11 kcal/mol computed with the CHARMM36 additive force field. Overall, the results indicate that the main limitation of the Drude PB/SASA model is the inability of the SASA term to accurately capture non-polar solvation effects. © 2018 Wiley Periodicals, Inc.