KEY, LOCK, and LOCKSMITH: complementary hydropathic map predictions of drug structure from a known receptor-receptor structure from known drugs

Conformation and electronic structure of Carbidopa. A QM/MD study

Carbidopa (CD) is a drug used in combination with L-dopa (LD) in treatment of Parkinson’s disease (PD). CD is an inhibitor for enzyme decarboxylase, yet its mode of action is not entirely known although it is believed to involve enzyme shape recognition. The present work attempts to investigate the conformational preferences of CD. Tight geometry optimization at the density functional theory (DFT)/B3LYP/6-311[Formula: see text]G** level of theory has been carried out. The shallow nature of the potential energy surface (PES) and the presence of several local minima within a small energy range necessitate the launching of DFT-based molecular dynamics (MD) simulations. Two MD experiments were submitted for 35,000 points each. The complete trajectory in time domain of 10.5 ps is analyzed and discussed. The global minimum energy structure of CD is localized and identified by subsequent frequency calculations. The quantum theory of atom in molecules (QTAIMs) is used to extract and compare the quantum chemical topology features of the electron density distribution in CD and LD. Bonding characteristics are analyzed and discussed within the natural bond orbital (NBO) framework.

How to deal with low-resolution target structures: using SAR, ensemble docking, hydropathic analysis, and 3D-QSAR to definitively map the αβ-tubulin colchicine site

αβ-Tubulin colchicine site inhibitors (CSIs) from four scaffolds that we previously tested for antiproliferative activity were modeled to better understand their effect on microtubules. Docking models, constructed by exploiting the SAR of a pyrrole subset and HINT scoring, guided ensemble docking of all 59 compounds. This conformation set and two variants having progressively less structure knowledge were subjected to CoMFA, CoMFA+HINT, and CoMSIA 3D-QSAR analyses. The CoMFA+HINT model (docked alignment) showed the best statistics: leave-one-out q(2) of 0.616, r(2) of 0.949, and r(2)pred (internal test set) of 0.755. An external (tested in other laboratories) collection of 24 CSIs from eight scaffolds were evaluated with the 3D-QSAR models, which correctly ranked their activity trends in 7/8 scaffolds for CoMFA+HINT (8/8 for CoMFA). The combination of SAR, ensemble docking, hydropathic analysis, and 3D-QSAR provides an atomic-scale colchicine site model more consistent with a target structure resolution much higher than the ~3.6 Å available for αβ-tubulin.

A new approach for investigating protein flexibility based on Constraint Logic Programming. The first application in the case of the estrogen receptor

We describe the potential of a novel method, based on Constraint Logic Programming (CLP), developed for an exhaustive sampling of protein conformational space. The CLP framework proposed here has been tested and applied to the estrogen receptor, whose activity and function is strictly related to its intrinsic, and well known, dynamics. We have investigated in particular the flexibility of H12, focusing on the pathways followed by the helix when moving from one stable crystallographic conformation to the others. Millions of geometrically feasible conformations were generated, selected and the traces connecting the different forms were determined by using a shortest path algorithm. The preliminary analyses showed a marked agreement between the crystallographic agonist-like, antagonist-like and hypothetical apo forms, and the corresponding conformations identified by the CLP framework. These promising results, together with the short computational time required to perform the analyses, make this constraint-based approach a valuable tool for the study of protein folding prediction. The CLP framework enables one to consider various structural and energetic scenarious, without changing the core algorithm. To show the feasibility of the method, we intentionally choose a pure geometric setting, neglecting the energetic evaluation of the poses, in order to be independent from a specific force field and to provide the possibility of comparing different behaviours associated with various energy models.

Using active site mapping and receptor-based pharmacophore tools: prelude to docking and de novo/fragment-based ligand design

Understanding the three-dimensional aspects of drug-receptor interactions and their specificity at the molecular level has become a focal point in modern drug discovery. Herein, we describe a set of methods by which the binding site on a protein can be located and mapped and the protein-ligand intermolecular interactions can be studied in the context of drug discovery. The methodology we describe is based on the empirical Hydropathic INTeraction (HINT) force field. Applications of the novel cavity detection algorithm, VICE, are demonstrated in delineating the binding pockets. The binding site environment is mapped using hydropathic "complementary map." The two binding sites are compared by calculating their 3D differences and the intermolecular interactions between a bound ligand and protein was further studied by HINT intermolecular maps. We illustrate the applications of these different types of HINT maps through an example from the development of selective COX-2 inhibitors.

Fragment-based quantitative structure-activity relationship (FB-QSAR) for fragment-based drug design

In cooperation with the fragment-based design a new drug design method, the so-called "fragment-based quantitative structure-activity relationship" (FB-QSAR) is proposed. The essence of the new method is that the molecular framework in a family of drug candidates are divided into several fragments according to their substitutes being investigated. The bioactivities of molecules are correlated with the physicochemical properties of the molecular fragments through two sets of coefficients in the linear free energy equations. One coefficient set is for the physicochemical properties and the other for the weight factors of the molecular fragments. Meanwhile, an iterative double least square (IDLS) technique is developed to solve the two sets of coefficients in a training data set alternately and iteratively. The IDLS technique is a feedback procedure with machine learning ability. The standard Two-dimensional quantitative structure-activity relationship (2D-QSAR) is a special case, in the FB-QSAR, when the whole molecule is treated as one entity. The FB-QSAR approach can remarkably enhance the predictive power and provide more structural insights into rational drug design. As an example, the FB-QSAR is applied to build a predictive model of neuraminidase inhibitors for drug development against H5N1 influenza virus.

Multiple field three dimensional quantitative structure–activity relationship (MF-3D-QSAR)

A new drug design method, the multiple field three-dimensional quantitative structure-activity relationship (MF-3D-QSAR), is proposed. It is a combination and development of classical 2D-QSAR and traditional 3D-QSAR. In addition to the electrostatic and van der Waals potentials, more potential fields (such as lipophilic potential, hydrogen bonding potential, and nonthermodynamic factors) are integrated in the MF-3D-QSAR. Meanwhile, a principal component analysis (PCA) and iterative double least square (IDLS) technique is developed for predicting the bioactivity of query drug candidates. As an example, the MF-3D-QSAR is applied to the design of neuraminidase inhibitor and to prove its predictive power, and some useful findings are obtained for developing drugs against influenza virus.

Human cellular nucleic acid-binding protein Zn2+ fingers support replication of human immunodeficiency virus type 1 when they are substituted in the nucleocapsid protein

A family of cellular nucleic acid binding proteins (CNBPs) contains seven Zn(2+) fingers that have many of the structural characteristics found in retroviral nucleocapsid (NC) Zn(2+) fingers. The sequence of the NH(2)-terminal NC Zn(2+) finger of the pNL4-3 clone of human immunodeficiency virus type 1 (HIV-1) was replaced individually with sequences from each of the seven fingers from human CNBP. Six of the mutants were normal with respect to protein composition and processing, full-length genomic RNA content, and infectivity. One of the mutants, containing the fifth CNBP Zn(2+) finger (CNBP-5) packaged reduced levels of genomic RNA and was defective in infectivity. There appear to be defects in reverse transcription in the CNBP-5 infections. Models of Zn(2+) fingers were constructed by using computational methods based on available structural data, and atom-atom interactions were determined by the hydropathic orthogonal dynamic analysis of the protein method. Defects in the CNBP-5 mutant could possibly be explained, in part, by restrictions of a set of required atom-atom interactions in the CNBP-5 Zn(2+) finger compared to mutant and wild-type Zn(2+) fingers in NC that support replication. The present study shows that six of seven of the Zn(2+) fingers from the CNBP protein can be used as substitutes for the Zn(2+) finger in the NH(2)-terminal position of HIV-1 NC. This has obvious implications in antiviral therapeutics and DNA vaccines employing NC Zn(2+) finger mutants.

Localization and quantification of hydrophobicity: the molecular free energy density (MolFESD) concept and its application to sweetness recognition

A method for the localization, the quantification, and the analysis of hydrophobicity of a molecule or a molecular fragment is presented. It is shown that the free energy of solvation for a molecule or the transfer free energy from one solvent to another can be represented by a surface integral of a scalar quantity, the molecular free energy surface density (MolFESD), over the solvent accessible surface of that molecule. This MolFESD concept is based on a model approach where the solvent molecules are considered to be small in comparison to the solute molecule, and the solvent can be represented by a continuous medium with a given dielectric constant. The transfer energy surface density for a 1-octanol/water system is empirically determined employing a set of atomic increment contributions and distance dependent membership functions measuring the contribution of the increments to the surface value of the MolFESD. The MolFESD concept can be well used for the quantification of the purely hydrophobic contribution to the binding constants of molecule-receptor complexes. This is demonstrated with the sweeteners sucrose and sucralose and various halogen derivatives. Therein the relative sweetness, which is assumed to be proportional to the binding constant, nicely correlates to the surface integral over the positive, hydrophobic part of the MolFESD, indicating that the sweetness receptor can be characterized by a highly flexible hydrophobic pocket instead of a localized binding site.

Hydrophobicity: is LogP(o/w) more than the sum of its parts?

The empirically calculated parameter LogP(o/w), the log(10) of the coefficient for solvent partitioning between 1-octanol and water, has been used to provide the key data for a unique non-covalent interaction force field called HINT (Hydropathic INTeractions). This experimentally-derived force field encodes entropic as well as enthalpic information and also includes some representation of solvation and desolvation energetics in biomolecular associations. The theoretical basis for the HINT model is discussed. This review includes: 1) discussion of calculational representation of the hydrophobic effect, 2) the rationale for describing the experimental LogP(o/w) based descriptors used in the HINT force field and model as free energy-like, 3) the relationship between hydrophobic fragment constants and partial group electrostatic charge, and 4) the implications of structurally-conserved water molecules on free energy of molecular association. Several recent applications of HINT in structure-based and ligand-based drug discovery are reviewed. Finally, future directions in the HINT model development are proposed.

Heuristic lipophilicity potential for computer-aided rational drug design

In this contribution we suggest a heuristic molecular lipophilicity potential (HMLP), which is a structure-based technique requiring no empirical indices of atomic lipophilicity. The input data used in this approach are molecular geometries and molecular surfaces. The HMLP is a modified electrostatic potential, combined with the averaged influences from the molecular environment. Quantum mechanics is used to calculate the electron density function rho(r) and the electrostatic potential V(r), and from this information a lipophilicity potential L(r) is generated. The HMLP is a unified lipophilicity and hydrophilicity potential. The interactions of dipole and multipole moments, hydrogen bonds, and charged atoms in a molecule are included in the hydrophilic interactions in this model. The HMLP is used to study hydrogen bonds and water-octanol partition coefficients in several examples. The calculated results show that the HMLP gives qualitatively and quantitatively correct, as well as chemically reasonable, results in cases where comparisons are available. These comparisons indicate that the HMLP has advantages over the empirical lipophilicity potential in many aspects. The HMLP is a three-dimensional and easily visualizable representation of molecular lipophilicity, suggested as a potential tool in computer-aided three-dimensional drug design.

Three-dimensional lipophilicity characterization of molecular pores and channel-like cavities

Molecular lipophilicity is a useful property for assessing molecular similarity or complementarity within the context of computer-aided drug design. As well, local contributions to solvent affinity help us to understand both dynamics and conformational stability in biomolecules. In this work, we discuss an approach to characterize the local contributions to hydrophobicity by using one- and two-dimensional representations of molecular channel-like cavities. The method monitors how a phenomenological lipophilicity potential (based on fragmental atom contributions) changes over a continuum of "molecular tubes" used for modeling channels and pores. Our results convey a relatively detailed picture of the spatial distribution of water affinity. The procedure can then be used as a complement to the hydrophobicity scales based on averaging contributions from single amino acids. In addition, we can study how the water affinity changes for inner and outer regions of the pores. As an application, we compute the 3D distribution of lipophilicity in the "pore conformation" of gramicidin A. The qualitative trends indicated by our results are broadly consistent with computer simulations of the gramicidin channel in the presence of hydrated ions. The behavior revealed by the simulations can then be incorporated to produce an improved, simple 2D model for water-channel interactions.

Discriminating D1 and D2 agonists with a hydrophobic similarity index

Currently, methods for calculating molecular similarity indices have been developed for comparing steric, charge density, and molecular electrostatic potential (MEP) properties. Much of the existing technology may, however, be applied to the quantitative comparison of molecular hydrophobicities. In this article we present an empirical hydrophobic similarity index. We utilize atomic hydrophobic parameters derived from a quantum mechanical semiempirical wavefunction. Hydrophobicity at points on a grid is computed with a recently introduced "molecular lipophilicity potential." The overlap of pairs of molecules is calculated with the metric introduced by Carbó. This approach is applied to a case in which steric and electrostatic criteria have already been shown to be inadequate in rationalizing selectivity, namely, requirements for recognition at the dopamine D1 and D2 receptors. We demonstrate that, for a set of dopamine agonists, D1 ligands show higher similarity in this property that D2 analogs. This indicator of similarity is more successful at accounting for D1 selectivity than previous methods.

Interactions at the alpha 1 beta 1 interface in hemoglobin: a single amino acid change affects dimer ratio in transgenic mice expressing human hemoglobin

The erythrocytes of transgenic mice expressing human hemoglobin contain mouse, human, and two hybrid hemoglobins. These hybrids include a predominant one, the human-alpha/mouse-beta and one found at lower levels, the human-beta/mouse-alpha. We used molecular modeling-aided hydropathic analysis of the globin alpha 1 beta 1 interface to identify a residue partly or wholly responsible for this distribution. Hemoglobin containing a single amino acid change [beta 112(G14)Cys-->Val] was expressed in transgenic mice. The hybrid ratio was reversed in transgenic mice expressing this mutated human hemoglobin as compared to the control transgenic mice expressing native human hemoglobin. These results demonstrate the importance of subunit assembly in the expression of hybrids in transgenic animals and may lead to successful design approaches for optimal expression of hemoglobin in larger animals such as the pig.

The effect of physical organic properties on hydrophobic fields

Physical organic structural properties of small molecules and macromolecules such as bond count, branching and proximity between multiple polar fragments contribute significantly to measured hydrophobicity (log P). These structural properties are encoded in the Rekker and Leo methods of calculating log P as structural-dependent factors. Regardless of the size of the atom primitive set, methods predicting log P with only atom primitives can miss subtle structural detail within series of related compounds. The HINT (Hydropathic INTeractions) model for inter- and intramolecular noncovalent interactions calculates atom-based hydrophobic constants, but uses all Leo-type factors in the calculation rather than a large set of atom primitives. Two types of applications of HINT are discussed: evaluation of the binding of an inhibitor (A74704) to HIV-1 protease, where it is shown that modeling of the protonation state (i.e., Asp25, Asp125) in the protein can strongly influence perceived substrate binding; and the use of HINT to calculate a third (hydropathic) field for CoMFA can yield a statistically enhanced and predictive model for molecular design.

A new approach to analysis and display of local lipophilicity/hydrophilicity mapped on molecular surfaces

A new method for display and analysis of lipophilic/hydrophilic properties on molecular surfaces is presented. The present approach is based on the concept of Crippen and coworkers that the overall hydrophobicity of a molecule (measured as the logarithm of the partition coefficient in an octanol/water system) can be obtained as a superposition of single atom contributions. It is also based on the concept of molecular lipophilicity potentials (MLP) first introduced by Audry and coworkers in order to establish a 3D lipophilicity potential profile in the molecular environment. Instead of using a l/r- or an exponential distance law between the atomic coordinates and a point on the molecular surface, a new distance dependency is introduced for the calculation of an MLP-value on the solvent-accessible surface of the molecule. In the present formalism the Crippen values (introduced for atoms in their characteristic structural environment) are 'projected' onto the van der Waals surface of the molecule by a special weighting procedure. This guarantees that only those atomic fragments contribute significantly to the surface values that are in the close neighbourhood of the surface point. This procedure not only works for small molecules but also allows the characterization of the surfaces of biological macromolecules by means of local lipophilicity. Lipophilic and hydrophilic domains can be recognized by visual inspection of computer-generated images or by computational procedures using fuzzy logic strategies. Local hydrophobicities on different molecular surfaces can be quantitatively compared on the basis of the present approach.