Theoretical studies on farnesyl transferase: Evidence for thioether product coordination to the active-site zinc sphere

Theoretical Studies on Catalysis Mechanisms of Serum Paraoxonase 1 and Phosphotriesterase Diisopropyl Fluorophosphatase Suggest the Alteration of Substrate Preference from Paraoxonase to DFP

The calcium-dependent β-propeller proteins mammalian serum paraoxonase 1 (PON1) and phosphotriesterase diisopropyl fluorophosphatase (DFPase) catalyze the hydrolysis of organophosphorus compounds and enhance hydrolysis of various nerve agents. In the present work, the phosphotriesterase activity development between PON1 and DFPase was investigated by using the hybrid density functional theory method B3LYP. Based on the active-site difference between PON1 and DFPase, both the wild type and the mutant (a water molecule replacing Asn270 in PON1) models were designed. The results indicated that the substitution of a water molecule for Asn270 in PON1 had little effect on the enzyme activity in kinetics, while being more efficient in thermodynamics, which is essential for DFP hydrolysis. Structure comparisons of evolutionarily related enzymes show that the mutation of Asn270 leads to the catalytic Ca²⁺ ion indirectly connecting the buried structural Ca²⁺ ion via hydrogen bonds in DFPase. It can reduce the plasticity of enzymatic structure, and possibly change the substrate preference from paraoxon to DFP, which implies an evolutionary transition from mono- to dinuclear catalytic centers. Our studies shed light on the investigation of enzyme catalysis mechanism from an evolutionary perspective.

Molecular dynamic simulations and structure-based pharmacophore development for farnesyltransferase inhibitors discovery

Farnesyltransferase is one of the enzyme targets for the development of drugs for diseases, including cancer, malaria, progeria, etc. In the present study, the structure-based pharmacophore models have been developed from five complex structures (1LD7, 1NI1, 2IEJ, 2ZIR and 2ZIS) obtained from the protein data bank. Initially, molecular dynamic (MD) simulations were performed for the complexes for 10 ns using AMBER 12 software. The conformers of the complexes (75) generated from the equilibrated protein were undergone protein-ligand interaction fingerprint (PLIF) analysis. The results showed that some important residues, such as LeuB96, TrpB102, TrpB106, ArgB202, TyrB300, AspB359 and TyrB361, are predominantly present in most of the complexes for interactions. These residues form side chain acceptor and surface (hydrophobic or π-π) kind of interactions with the ligands present in the complexes. The structure-based pharmacophore models were generated from the fingerprint bits obtained from PLIF analysis. The pharmacophore models have 3-4 pharmacophore contours consist of acceptor and metal ligation (Acc & ML), hydrophobic (HydA) and extended acceptor (Acc2) features with the radius ranging between 1-3 Å for Acc & ML and 1-2 Å for HydA. The excluded volumes of the pharmacophore contours radius are between 1-2 Å. Further, the distance between the interacting groups, root mean square deviation (RMSD), root mean square fluctuation (RMSF) and radial distribution function (RDF) analysis were performed for the MD-simulated proteins using PTRAJ module. The generated pharmacophore models were used to screen a set of natural compounds and database compounds to select significant HITs. We conclude that the developed pharmacophore model can be a significant model for the identification of HITs as FTase inhibitors.

In Silico–Based Structural Analysis of Arylthiophene Derivatives for FTase Inhibitory Activity, hERG, and Other Toxic Effects

In the present investigation, the authors have performed an in silico–based analysis on a series of arylthiophene derivatives for the determination of their structural features responsible for farnesyltransferase (FTase) inhibitory activity, hERG blocking activity, and toxicity by quantitative structure–activity relationship and pharmacophore analysis techniques. The statistically significant models derived through multiple linear regression analysis were validated by different validation methods. The applicability of the descriptors contributed in the selected models show that the polar and polarizable properties on the van der Waals (vdW) surface area of the molecules are important for the FTase inhibitory and hERG blocking activities, while being detrimental for the toxicity of the molecules. It is interesting to note that the topological properties, molecular flexibility, and connectivity of the molecules are positively correlated to all the activities (FTase inhibition, hERG blocking, and toxicity). This implies that the flexibility of the molecules is the common feature for interaction in all targets, whereas the presence of polar groups on the molecular surface (vdW) is a determinant for the favorable (FTase inhibition) or unwanted effect (hERG blocking and toxicity) of the molecules. The pharmacophore analysis of the molecules demonstrated that the aromatic/hydrophobicity and polarizability features are important pharmacophore contours favorable for these activities.

Biosynthesis via carbocations: theoretical studies on terpene formation

This review describes applications of quantum chemical calculations in the field of terpene biosynthesis, with a focus on insights into the mechanisms of terpene-forming carbocation rearrangements arising from theoretical studies.

Systematic Derivation of AMBER Force Field Parameters Applicable to Zinc-Containing Systems

Metal ions are indispensable for maintaining the structural stability and catalytic activity of metalloproteins. Molecular modeling studies of such proteins with force fields, however, are often hampered by the "missing parameter" problem. In this study, we have derived bond-stretching and angle-bending parameters applicable to zinc-containing systems which are compatible with the AMBER force field. A total of 18 model systems were used to mimic the common coordination configurations observed in the complexes formed by zinc-containing metalloproteins. The Hessian matrix of each model system computed at the B3LYP/6-311++G(2d,2p) level was then analyzed by Seminario's method to derive the desired force constants. These parameters were validated extensively in structural optimizations and molecular dynamics simulations of four selected model systems as well as one protein-ligand complex formed by carbonic anhydrase II. The best performance was achieved by a bonded model in combination with the atomic partial charges derived by the restrained electrostatic potential method. After some minor optimizations, this model was also able to reproduce the vibrational frequencies computed by quantum mechanics. This study provides a comprehensive set of force field parameters applicable to a variety of zinc-containing molecular systems. In principle, our approach can be applied to other molecular systems with missing force field parameters.

QM/MM methods for biomolecular systems

Combined quantum-mechanics/molecular-mechanics (QM/MM) approaches have become the method of choice for modeling reactions in biomolecular systems. Quantum-mechanical (QM) methods are required for describing chemical reactions and other electronic processes, such as charge transfer or electronic excitation. However, QM methods are restricted to systems of up to a few hundred atoms. However, the size and conformational complexity of biopolymers calls for methods capable of treating up to several 100,000 atoms and allowing for simulations over time scales of tens of nanoseconds. This is achieved by highly efficient, force-field-based molecular mechanics (MM) methods. Thus to model large biomolecules the logical approach is to combine the two techniques and to use a QM method for the chemically active region (e.g., substrates and co-factors in an enzymatic reaction) and an MM treatment for the surroundings (e.g., protein and solvent). The resulting schemes are commonly referred to as combined or hybrid QM/MM methods. They enable the modeling of reactive biomolecular systems at a reasonable computational effort while providing the necessary accuracy.

Computational enzymatic catalysis

Computational methodologies are playing increasingly important roles in elucidating and presenting the complete and detailed mechanisms of enzymatic reactions because of their capacity to determine and characterize intermediates and transition states from both structural and energetics points of view, independent of their reduced lifetimes and without interfering with the natural reactional flux. These features are turning the field into an active and interesting area of research, involving a diverse range of studies, mostly directed at understanding the ways in which enzymes function under certain circumstances and predicting how they will behave under others. The accuracy of the computational data obtained for a given mechanistic hypothesis depends essentially on three mutually exclusive factors: the accuracy of the Hamiltonian of the reaction mechanism, consideration of the modulating aspect of the enzyme's structure in the energetics of the active center, and consideration of the enzyme's conformational fluctuations and dynamics. Although, unfortunately, it is impossible at present to optimize these crucial factors simultaneously, the success of any enzymatic mechanistic study depends on the level of equilibrium achieved among them. Different authors adopt different solutions, and this Account summarizes the most favored, with emphasis placed on our own preferences. Another crucial aspect in computational enzymatic catalysis is the model used in the calculations. Our aim is to build the simplest model that captures the essence of the catalytic power of an enzyme, allowing us to apply the highest possible theoretical level and minimize accidental errors. The choice is, however, far from obvious, ranging from simple models containing tens of atoms up to models of full enzymes plus solvent. Many factors underlie the choice of an appropriate model; here, examples are presented of very different modeling strategies that have been employed to obtain meaningful results. One particular case study, that of enzyme ribonucleotide reductase (RNR), a radical enzyme that catalyzes the reduction of ribonucleotides into deoxyribonucleotides, is one of the examples illustrating how the successive increase of the system's size does not dramatically change the thermodynamics and kinetics of the reaction. The values obtained and presented speak for themselves in that the only ones that are distinctly different are those calculated using an exceedingly small model, which omitted the amino acids that establish hydrogen bonds with the reactive unit of the substrate. This Account also describes our computational analysis of the mechanism of farnesyltransferase, a heterodimeric zinc metalloenzyme that is currently one of the most fascinating targets in cancer research. We focus on the present methodologies that we have been using, our models and understanding of the problem, and the accuracy of results and associated problems within this area of research.

Synthesis and biochemical evaluation of 3,7-disubstituted farnesyl diphosphate analogues

Farnesyl diphosphate (FPP) analogues have proven to be both potent inhibitors of protein-farnesyltransferase (FTase) and valuable probes for the investigation of the function of prenylated proteins. Previously, we have demonstrated that certain 3-substituted and 7-substituted FPP analogues can act as inhibitors of FTase, while others are effective alternative substrates. We have now utilized our vinyl triflate-mediated route to synthesize the first seven FPP variants bearing substituents in both the 3- and 7-positions of the isoprene unit. Despite their exceptional steric bulk with respect to FPP itself, six of the seven analogues bind to FTase. Two of the analogues are potent inhibitors of the enzyme, but a more striking finding is that three FPP variants (4a, 4b, and 4f) are efficient alternative substrates for FTase.

Analysis of zinc-ligand bond lengths in metalloproteins: Trends and patterns

Zinc is one of the biologically most abundant and important metal elements, present in a plethora of enzymes from a broad array of species of all phyla. In this study we report a thorough analysis of the geometrical properties of Zinc coordination spheres performed on a dataset of 994 high quality protein crystal structures from the Protein Data Bank, and complemented with Quantum mechanical calculations at the DFT level of theory (B3LYP/SDD) on mononuclear model systems. The results allowed us to draw interesting conclusions on the structural characteristics of Zn centres and to evaluate the importance of such effects as the resolution of X-ray crystallographic structures, the enzyme class in which the Zn centre is included, and the identity of the ligands at the Zn coordination sphere. Altogether, the set of results obtained provides useful data for the enhancement of the atomic models normally applied to the theoretical and computational study of zinc enzymes at the quantum mechanical level (in particular enzymatic mechanisms), and for the development of molecular mechanical parameters for the treatment of zinc coordination spheres with molecular mechanics or molecular dynamics in studies with the full enzyme.

Comparative assessment of theoretical methods for the determination of geometrical properties in biological zinc complexes

In the present study, we have compared the performance of the density functional theory (DFT) functionals B1B95, B3LYP, B97-2, BP86, and BPW91 with MP2 for geometry determination in biological mononuclear Zn complexes. A total of 15 different basis sets, of rather diverse complexity, were tested, several which included also three different types of common effective-core potentials: Los Alamos, Steven-Basch-Krauss, and Stuttgart-Dresden. In addition, the ability to describe mononuclear Zn biological systems using relatively simple models of the metal coordination sphere, comprising only the metal atom and a simplified representation of the ligands at the first coordination sphere, starting from a set of high-resolution X-ray crystallographic structures, is evaluated for 90 combinations of method/basis set. The results show that the use of such models allows for a relatively accurate description of the Zn-ligand bond lengths, although failing to correctly represent the topology of the metal coordination sphere (namely, the angles involving the metal atom) if constraints at the Calpha atoms are not considered. Globally, B3LYP had the best average performance in the test, closely followed by MP2, whereas B1B95 was the least accurate method. The study also points out B3LYP/CEP-121G and B3LYP/SDD, which use, respectively, the Steven-Basch-Krauss and the Stuttgart-Dresden effective-core potentials, as the best compromise between accuracy and CPU time for the geometrical characterization of metal-ligand bond lengths in Zn biological systems.