Pramod C. Nair

An Automated Force Field Topology Builder (ATB) and Repository: Version 1.0

The Automated force field Topology Builder (ATB, http://compbio.biosci.uq.edu.au/atb ) is a Web-accessible server that can provide topologies and parameters for a wide range of molecules appropriate for use in molecular simulations, computational drug design, and X-ray refinement. The ATB has three primary functions: (1) to act as a repository for molecules that have been parametrized as part of the GROMOS family of force fields, (2) to act as a repository for pre-equilibrated systems for use as starting configurations in molecular dynamics simulations (solvent mixtures, lipid systems pre-equilibrated to adopt a specific phase, etc.), and (3) to generate force field descriptions of novel molecules compatible with the GROMOS family of force fields in a variety of formats (GROMOS, GROMACS, and CNS). Force field descriptions of novel molecules are derived using a multistep process in which results from quantum mechanical (QM) calculations are combined with a knowledge-based approach to ensure compatibility (as far as possible) with a specific parameter set of the GROMOS force field. The ATB has several unique features: (1) It requires that the user stipulate the protonation and tautomeric states of the molecule. (2) The symmetry of the molecule is analyzed to ensure that equivalent atoms are assigned identical parameters. (3) Charge groups are assigned automatically. (4) Where the assignment of a given parameter is ambiguous, a range of possible alternatives is provided. The ATB also provides several validation tools to assist the user to assess the degree to which the topology generated may be appropriate for a given task. In addition to detailing the steps involved in generating a force field topology compatible with a specific GROMOS parameter set (GROMOS 53A6), the challenges involved in the automatic generation of force field parameters for atomic simulations in general are discussed.

Comparison of enveloping distribution sampling and thermodynamic integration to calculate binding free energies of phenylethanolamine N-methyltransferase inhibitors.

The relative binding free energy between two ligands to a specific protein can be obtained using various computational methods. The more accurate and also computationally more demanding techniques are the so-called free energy methods which use conformational sampling from molecular dynamics or Monte Carlo simulations to generate thermodynamic averages. Two such widely applied methods are the thermodynamic integration (TI) and the recently introduced enveloping distribution sampling (EDS) methods. In both cases relative binding free energies are obtained through the alchemical perturbations of one ligand into another in water and inside the binding pocket of the protein. TI requires many separate simulations and the specification of a pathway along which the system is perturbed from one ligand to another. Using the EDS approach, only a single automatically derived reference state enveloping both end states needs to be sampled. In addition, the choice of an optimal pathway in TI calculations is not trivial and a poor choice may lead to poor convergence along the pathway. Given this, EDS is expected to be a valuable and computationally efficient alternative to TI. In this study, the performances of these two methods are compared using the binding of ten tetrahydroisoquinoline derivatives to phenylethanolamine N-transferase as an example. The ligands involve a diverse set of functional groups leading to a wide range of free energy differences. In addition, two different schemes to determine automatically the EDS reference state parameters and two different topology approaches are compared.

Missing Fragments: Detecting Cooperative Binding in Fragment-Based Drug Design

The aim of fragment-based drug design (FBDD) is to identify molecular fragments that bind to alternate subsites within a given binding pocket leading to cooperative binding when linked. In this study, the binding of fragments to human phenylethanolamine N-methyltransferase is used to illustrate how (a) current protocols may fail to detect fragments that bind cooperatively, (b) theoretical approaches can be used to validate potential hits, and (c) apparent false positives obtained when screening against cocktails of fragments may in fact indicate promising leads.

A novel function for UDP glycosyltransferase 8: galactosidation of bile acids.

The human UDP glycosyltransferase (UGT) superfamily comprises four families of enzymes that catalyze the addition of sugar residues to small lipophilic chemicals. The UGT1 and UGT2 enzymes use UDP-glucuronic acid, and UGT3 enzymes use UDP-N-acetylglucosamine, UDP-glucose, and UDP-xylose to conjugate xenobiotics, including drugs and endobiotics such as metabolic byproducts, hormones, and signaling molecules. This metabolism renders the substrate more polar and more readily excreted from the body and/or functionally inactive. The fourth UGT family, called UGT8, contains only one member that, unlike other UGTs, is considered biosynthetic. UGT8 uses UDP galactose to galactosidate ceramide, a key step in the synthesis of brain sphingolipids. To date other substrates for this UGT have not been identified and there has been no suggestion that UGT8 is involved in metabolism of endo- or xenobiotics. We re-examined the functions of UGT8 and discovered that it efficiently galactosidates bile acids and drug-like bile acid analogs. UGT8 conjugates bile acids ∼60-fold more efficiently than ceramide based on in vitro assays with substrate preference deoxycholic acid > chenodeoxycholic acid > cholic acid > hyodeoxycholic acid > ursodeoxycholic acid. Activities of human and mouse UGT8 are qualitatively similar. UGT8 is expressed at significant levels in kidney and gastrointestinal tract (intestine, colon) where conjugation of bile acids is likely to be metabolically significant. We also investigate the structural determinants of UDP-galactose selectivity. Our novel findings suggest a new role for UGT8 as a modulator of bile acid homeostasis and signaling.

Human UDP-Glucuronosyltransferase (UGT) 2B10: Validation of Cotinine as a Selective Probe Substrate, Inhibition by UGT Enzyme-Selective Inhibitors and Antidepressant and Antipsychotic Drugs, and Structural Determinants of Enzyme Inhibition

Although there is evidence for an important role of UGT2B10 in the N-glucuronidation of drugs and other xenobiotics, the inhibitor selectivity of this enzyme is poorly understood. This study sought primarily to characterize the inhibition selectivity of UGT2B10 by UDP-glucuronosyltransferase (UGT) enzyme-selective inhibitors used for reaction phenotyping, and 34 antidepressant and antipsychotic drugs that contain an amine functional group. Initial studies demonstrated that cotinine is a highly selective substrate of human liver microsomal UGT2B10. The kinetics of cotinine N-glucuronidation by recombinant UGT and human liver microsomes (± bovine serum albumin) were consistent with the involvement of a single enzyme. Of the UGT enzyme-selective inhibitors employed for reaction phenotyping, only the UGT2B4/7 inhibitor fluconazole reduced recombinant UGT2B10 activity to an appreciable extent. The majority of antidepressant and antipsychotic drugs screened for effects on UGT2B10 inhibited enzyme activity with IC50 values <100 µM. The most potent inhibition was observed with the tricyclic antidepressants amitriptyline and doxepin and the tetracyclic antidepressant mianserin, and the structurally related compounds desloratadine and loratadine. Molecular modeling using a ligand-based approach indicated that hydrophobic and charge interactions are involved in inhibitor binding, whereas spatial features influence the potency of UGT2B10 inhibition. Respective mean Ki,u (± S.D.) values for amitriptyline, doxepin, and mianserin inhibition of human liver microsomal UGT2B10 were 0.61 ± 0.05, 0.95 ± 0.18, and 0.43 ± 0.01 µM. In vitro–in vivo extrapolation indicates that these drugs may perpetrate inhibitory drug-drug interactions when coadministered with compounds that are cleared predominantly by UGT2B10.

Cytochrome P450 structure–function: insights from molecular dynamics simulations

Abstract Cytochrome P450 (CYP) family 1, 2, and 3 enzymes play an essential role in the metabolic clearance and detoxification of a myriad of structurally and chemically diverse drugs and non-drug xenobiotics. The individual CYP enzymes exhibit distinct substrate and inhibitor selectivities, and hence differing patterns of inhibitory drug–drug interactions. In addition, CYP enzymes differ in terms of regulation of expression, genetic polymorphism, and environmental factors that alter activity. The availability of three-dimensional structures from X-ray crystallography have been invaluable for understanding the structural basis of the ligand selectivity of CYP enzymes. Moreover, the X-ray crystal structures demonstrate that CYP proteins exhibit marked flexibility, particularly around the active site, and the principle of ligand-induced conformational changes is now well accepted. Recent studies have demonstrated that molecular dynamics simulations (MDS) provide an additional approach for modeling the structural flexibility of CYP enzymes, both in the presence and absence of bound ligand, and understanding the functional consequences of plasticity. However, most of the MDS studies reported to date have utilized short simulation time scales, and few have validated the computationally-generated data experimentally (e.g. by site-directed mutagenesis and enzyme kinetic approaches). Although modeling approaches require further development and validation, MDS has the potential to provide a deeper understanding of CYP structure–function than is available from experimental techniques such as X-ray crystallography alone.

Molecular dynamics simulations: from structure function relationships to drug discovery

Molecular dynamics (MD) simulation is an emerging in silico technique with potential applications in diverse areas of pharmacology. Over the past three decades MD has evolved as an area of importance for understanding the atomic basis of complex phenomena such as molecular recognition, protein folding, and the transport of ions and small molecules across membranes. The application of MD simulations in isolation and in conjunction with experimental approaches have provided an increased understanding of protein structure-function relationships and demonstrated promise in drug discovery.

Fingerprint Directed Scaffold Hopping for Identification of CCR2 Antagonists

Chemokine receptors have evolved as attractive targets for disease conditions which arise due to immunomodulation involving host-defense mechanisms. CCR2, a chemokine receptor, is targeted for diseases like arthritis, multiple sclerosis, vascular disease, obesity, and type 2 diabetes. This study provides a new strategy of a ligand based technique which exploits fingerprint led fragment features in conjunction with structure-guided design for identifying new scaffolds for CCR2. A fragment based mining (FBM) technique was employed on a chemical database to identify novel scaffold hops. The hits were subjected to 3-point pharmacophore fingerprint procedures with Tanimoto similarity metric to compare pharmacophoric fingerprints. The final 66 hits generated by these exercises were predicted by the validated HQSAR model, and the top predicted were suggested as probable scaffolds for CCR2 antagonism. The identified scaffolds were validated through molecular docking studies. The ligands were docked by providing receptor flexibility in the extra cellular domain (1 and 3), N terminal domain, and in the transmembrane (TM1 & TM7) helix region with IFD approach. Some of the scaffolds showed H-bonding potential which was not explored by the data set molecules. All identified scaffolds highlighted a key hydrogen bonding interaction with Thr292 as supported by mutational studies. The observed pi stacking interaction with Tyr188 in data set molecules was also produced by the new scaffolds. Taking the advantage of receptor flexibility the scaffolds explored the hydrophobic binding cleft between helix 1 and 7 occupied by residues Leu44, Leu45, Leu48 and Ile300, Ile303, Ile304, respectively. Two of the identified molecules have promising outcomes and can be considered as novel scaffolds for CCR2 binding.

Using Theory to Reconcile Experiment: The Structural and Thermodynamic Basis of Ligand Recognition by Phenylethanolamine N-Methyltransferase (PNMT)

A fundamental challenge in computational drug design is the availability of reliable and validated experimental binding and structural data against which theoretical calculations can be compared. In this work a combination of molecular dynamics (MD) simulations and free energy calculations has been used to analyze the structural and thermodynamic basis of ligand recognition by phenylethanolamine N-methyltransferase (PNMT) in an attempt to resolve uncertainties in the available binding and structural data. PNMT catalyzes the conversion of norepinephrine into epinephrine (adrenaline), and inhibitors of PNMT are of potential therapeutic importance in Alzheimers and Parkinsons disease. Excellent agreement between the calculated and recently revised relative binding free energies to human PNMT was obtained with the average deviation between the calculated and the experimentally determined values being only 0.8 kJ/mol. In this case, the variation in the experimental data over time is much greater than the uncertainties in the theoretical estimates. The calculations have also enabled the refinement of structure-activity relationships in this system, to understand the basis of enantiomeric selectivity of substitution at position three of tetrahydroisoquinoline and to identify the role of specific structural waters. Finally, the calculations suggest that the preferred binding mode of trans-(1S,2S)-2-amino-1-tetralol is similar to that of its epimer cis-(1R,2S)-2-amino-1-tetralol and that the ligand does not adopt the novel binding mode proposed in the pdb entry 2AN5 . The work demonstrates how MD simulations and free energy calculations can be used to resolve uncertainties in experimental binding affinities, binding modes, and other aspects related to X-ray refinement and computational drug design.

QSAR studies on CCR2 antagonists with chiral sensitive hologram descriptors

Chemokines are small molecular weight water-soluble proteins playing a key role in immunomodulation and host-defense mechanisms. CCR2 receptor is targeted for diseases like arthritis, multiple sclerosis, vascular disease, obesity, and type 2 diabetes. Reported, herein are the QSAR studies performed on a diverse set of enantiopure analogues reported as CCR2 antagonists by hologram analysis. The best model highlights the importance of chirality feature in comparison with the other models developed without the chirality. The validated model showed high internal and external predictive power. The robustness of the model was achieved with good statistical r(2) of 0.945 and cross-validated r(cv)(2) of 0.837. The challenging test predictivity of the model was confirmed with r(pred)(2) of 0.807. The fragment fingerprints help in understanding essential pharmacophoric features for CCR2 antagonism and provide basis for SAR of the molecules. The 2D contribution maps with fragment information will be useful for the design of novel CCR2 antagonists having improved efficacy.