Ligand Entropy in Gas-Phase, Upon Solvation and Protein Complexation. Fast Estimation with Quasi-Newton Hessian

A method of rapid entropy estimation for small molecules in vacuum, solution, and inside a protein receptor is proposed. We show that the Hessian matrix of second derivatives built by a quasi-Newton optimizer during geometry optimization of a molecule with a classical molecular potential in these three environments can be used to predict vibrational entropies. We also show that a simple analytical solvation model allows for no less accurate entropy estimation of molecules in solution than a physically rigorous but computationally more expensive model based on Poisson's equation. Our work also suggests that scaled particle theory more precisely estimates the hydrophobic part of solvation entropy than the using a simple surface area term.

Automated ligand placement and refinement with a combined force field and shape potential

An automated computational procedure for fitting a ligand into its electron density with the use of the MMFF94 force field and a Gaussian shape description has been developed. It employs a series of adiabatic optimizations of gradually increasing shape potential. Starting from a set of energy-relaxed ligand conformations, the final results are structures realistically strained to fit the crystallographic data.

DOCK 4.0: search strategies for automated molecular docking of flexible molecule databases

In this paper we describe the search strategies developed for docking flexible molecules to macomolecular sites that are incorporated into the widely distributed DOCK software, version 4.0. The search strategies include incremental construction and random conformation search and utilize the existing Coulombic and Lennard-Jones grid-based scoring function. The incremental construction strategy is tested with a panel of 15 crystallographic testcases, created from 12 unique complexes whose ligands vary in size and flexibility. For all testcases, at least one docked position is generated within 2 A of the crystallographic position. For 7 of 15 testcases, the top scoring position is also within 2 A of the crystallographic position. The algorithm is fast enough to successfully dock a few testcases within seconds and most within 100 s. The incremental construction and the random search strategy are evaluated as database docking techniques with a database of 51 molecules docked to two of the crystallographic testcases. Incremental construction outperforms random search and is fast enough to reliably rank the database of compounds within 15 s per molecule on an SGI R10000 cpu.

Design, docking, and evaluation of multiple libraries against multiple targets

We present a general approach to the design, docking, and virtual screening of multiple combinatorial libraries against a family of proteins. The method consists of three main stages: docking the scaffold, selecting the best substituents at each site of diversity, and comparing the resultant molecules within and between the libraries. The core "divide-and-conquer" algorithm for side-chain selection, developed from an earlier version (Sun et al., J Comp Aided Mol Design 1998;12:597-604), provides a way to explore large lists of substituents with linear rather than combinatorial time dependence. We have applied our method to three combinatorial libraries and three serine proteases: trypsin, chymotrypsin, and elastase. We show that the scaffold docking procedure, in conjunction with a novel vector-based orientation filter, reproduces crystallographic binding modes. In addition, the free-energy-based scoring procedure (Zou et al., J Am Chem Soc 1999;121:8033-8043) is able to reproduce experimental binding data for P1 mutants of macromolecular protease inhibitors. Finally, we show that our method discriminates between a peptide library and virtual libraries built on benzodiazepine and tetrahydroisoquinolinone scaffolds. Implications of the docking results for library design are explored.

Development and screening of a polyketide virtual library for drug leads against a motilide pharmacophore

A virtual library of macrocyclic polyketide molecules was generated and screened to identify novel, conformationally constrained potential motilin receptor agonists ("motilides"). A motilide pharmacophore model was generated from the potent 6,9-enol ether erythromycin and known derivatives from the literature. The pharmacophore for each molecular conformation was a point in a distance-volume space based on presentation of the putative binding moieties. Two methods, one fragment based method and the other reaction based, were explored for constructing the polyketide virtual library. First, a virtual library was assembled from monomeric fragments using the CHORTLES language. Second, the virtual library was assembled by the in silico application of all possible polyketide synthase enzyme reactions to generate the product library. Each library was converted to low-energy 3D conformations by distance geometry and standard minimization methods. The distance-volume metric was calculated for low-energy conformations of the members of the virtual polyketide library and screened against the enol ether pharmacophore. The goal was to identify novel macrocycles that satisfy the pharmacophore. We identified three conformationally constrained, novel polyketide series that have low-energy conformations satisfying the distance-volume constraints of the motilide pharmacophore.

Novel cathepsin D inhibitors block the formation of hyperphosphorylated tau fragments in hippocampus

Lysosomal disturbances may be a contributing factor to Alzheimer's disease. We used novel compounds to test if suppression of the lysosomal protease cathepsin D blocks production of known precursors to neurofibrillary tangles. Partial lysosomal dysfunction was induced in cultured hippocampal slices with a selective inhibitor of cathepsins B and L. This led within 48 h to hyperphosphorylated tau protein fragments recognized by antibodies against human tangles. Potent nonpeptidic cathepsin D inhibitors developed using combinatorial chemistry and structure-based design blocked production of the fragments in a dose-dependent fashion. Threshold was in the submicromolar range, with higher concentrations producing complete suppression. The effects were selective and not accompanied by pathophysiology. Comparable results were obtained with three structurally distinct inhibitors. These results support the hypothesis that cathepsin D links lysosomal dysfunction to the etiology of Alzheimer's disease and suggest a new approach to treating the disease.

Potent, low-molecular-weight non-peptide inhibitors of malarial aspartyl protease plasmepsin II

A number of single-digit nanomolar, low-molecular-weight plasmepsin II aspartyl protease inhibitors have been identified using combinatorial chemistry and structure-based design. By identifying multiple, small-molecule inhibitors using the parallel synthesis of several focused libraries, it was possible to select for compounds with desirable characteristics including enzyme specificity and minimal binding to serum proteins. The best inhibitors identified have Ki's of 2-10 nM, molecular weights between 594 and 650 Da, between 3- and 15-fold selectivity toward plasmepsin II over cathepsin D, the most closely related human protease, good calculated log P values (2.86-4.56), and no apparent binding to human serum albumin at 1 mg/mL in an in vitro assay. These compounds represent the most potent non-peptide plasmepsin II inhibitors reported to date.

A rapid method for exploring the protein structure universe

We have developed an automatic protein fingerprinting method for the evaluation of protein structural similarities based on secondary structure element compositions, spatial arrangements, lengths, and topologies. This method can rapidly identify proteins sharing structural homologies as we demonstrate with five test cases: the globins, the mammalian trypsinlike serine proteases, the immunoglobulins, the cupredoxins, and the actinlike ATPase domain-containing proteins. Principal components analysis of the similarity distance matrix calculated from an all-by-all comparison of 1,031 unique chains in the Protein Data Bank has produced a distribution of structures within a high-dimensional structural space. Fifty percent of the variance observed for this distribution is bounded by six axes, two of which encode structural variability within two large families, the immunoglobulins and the trypsinlike serine proteases. Many aspects of the spatial distribution remain stable upon reduction of the database to 140 proteins with minimal family overlap. The axes correlated with specific structural families are no longer observed. A clear hierarchy of organization is seen in the arrangement of protein structures in the universe. At the highest level, protein structures populate regions corresponding to the all-alpha, all-beta, and alpha/beta superfamilies. Large protein families are arranged along family-specific axes, forming local densely populated regions within the space. The lowest level of organization is intrafamilial; homologous structures are ordered by variations in peripheral secondary structure elements or by conformational shifts in the tertiary structure.

CombiDOCK: structure-based combinatorial docking and library design

We have developed a strategy for efficiently docking a large combinatorial library into a target receptor. For each scaffold orientation, all potential fragments are attached to the scaffold, their interactions with the receptor are individually scored and factorial combinations of fragments are constructed. To test its effectiveness, this approach is compared to two simple control algorithms. Our method is more efficient than the controls at selecting best scoring molecules and at selecting fragments for the construction of an exhaustive combinatorial library. We also carried out a retrospective analysis of the experimental results of a 10 x 10 x 10 exhaustive combinatorial library. An enrichment factor of approximately 4 was found for identifying the compounds in the library that are active at 330 nM.

Rational design of novel antimicrobials: blocking purine salvage in a parasitic protozoan

All parasitic protozoa obtain purine nucleotides solely by salvaging purine bases and/or nucleosides from their host. This observation suggests that inhibiting purine salvage may be a good way of killing these organisms. To explore this idea, we attempted to block the purine salvage pathway of the parasitic protozoan Tritrichomonas foetus. T. foetus is a good organism to study because its purine salvage depends primarily on a single enzyme, hypoxanthine-guanine-xanthine phosphoribosyltransferase (HGXPRTase), and could provide a good model for rational drug design through specific enzyme inhibition. Guided by the crystal structure of T. foetus HGXPRTase, we used structure-based drug design to identify several non-purine compounds that inhibited this enzyme without any detectable effect on human HGPRTase. One of these compounds, 4-[N-(3, 4-dichlorophenyl)carbamoyl]phthalic anhydride (referred to as TF1), was selected for further characterization. TF1 was shown to be a competitive inhibitor of T. foetus HGXPRTase with respect to both guanine (in the forward reaction; Ki = 13 microM) and GMP (in the reverse reaction; Ki = 10 microM), but showed no effect on the homologous human enzyme at concentrations of up to 1 mM. TF1 inhibited the in vitro growth of T. foetus with an EC50 of approximately 40 microM. This inhibitory effect was associated with a decrease in the incorporation of exogenous guanine into nucleic acids, and could be reversed by supplementing the growth medium with excess exogenous hypoxanthine or guanine. Thus, rationally targeting an essential enzyme in a parasitic organism has yielded specific enzyme inhibitors capable of suppressing that parasite's growth.

Structure-based design and combinatorial chemistry yield low nanomolar inhibitors of cathepsin D

BACKGROUND

The identification of potent small molecule ligands to receptors and enzymes is one of the major goals of chemical and biological research. Two powerful new tools that can be used in these efforts are combinatorial chemistry and structure-based design. Here we address how to join these methods in a design protocol that produces libraries of compounds that are directed against specific macromolecular targets. The aspartyl class of proteases, which is involved in numerous biological processes, was chosen to demonstrate this effective procedure.

RESULTS

Using cathepsin D, a prototypical aspartyl protease, a number of low nanomolar inhibitors were rapidly identified. Although cathepsin D is implicated in a number of therapeutically relevant processes, potent nonpeptide inhibitors have not been reported previously. The libraries, synthesized on solid support, displayed nonpeptide functionality about the (hydroxyethyl)amine isostere. The (hydroxyethyl)amine isostere, which targets the aspartyl protease class, is a stable mimetic of the tetrahedral intermediate of amide hydrolysis. Structure-based design, using the crystal structure of cathepsin D complexed with the peptide-based natural product pepstatin, was used to select the building blocks for the library synthesis. The library yielded a 'hit rate' of 6-7% at 1 microM inhibitor concentrations, with the most potent compound having a Ki value of 73 nM. More potent, nonpeptide inhibitors (Ki = 9-15 nM) of cathepsin D were rapidly identified by synthesizing and screening a small second generation library.

CONCLUSIONS

The success of these studies clearly demonstrates the power of coupling the complementary methods of combinatorial chemistry and structure-based design. We anticipate that the general approaches described here will be successful for other members of the aspartyl protease class and for many other enzyme classes.