Arup K. Ghose

Prediction of Solvation Free Energies of Small Organic Molecules: Additive-Constitutive Models Based on Molecular Fingerprints and Atomic Constants

Solvation free energy is an important molecular characteristic useful in drug discovery because it represents the desolvation cost of a ligand binding to a receptor. Most of the recent developments in the estimation of solvation free energy require the use of molecular mechanics and dynamics calculations. Group contribution methods have been rarely used in the past for calculating solvation free energy because automated prediction methods have not been developed in this regard. As an aid to combinatorial library design, we explored rapid and accurate means of computing solvation free energies from the covalent structures of organic molecules and compared the results on a test set with the GB/SA solvation model. Two independent additive-constitutive QSPR methods have been developed for the computation of solvation free energy. The first is a QSPR model (HLOGS) derived using a technique that uses the counts of distinct/similar fragments and substructures for each molecule as variables in a PLS regression. T...

2,7-disubstituted-pyrrolo[2,1-f][1,2,4]triazines: new variant of an old template and application to the discovery of anaplastic lymphoma kinase (ALK) inhibitors with in vivo antitumor activity.

A novel 2,7-disubstituted-pyrrolo[2,1-f][1,2,4]triazine scaffold has been designed as a new kinase inhibitor platform mimicking the bioactive conformation of the well-known diaminopyrimidine motif. The design, synthesis, and validation of this new pyrrolo[2,1-f][1,2,4]triazine scaffold will be described for inhibitors of anaplastic lymphoma kinase (ALK). Importantly, incorporation of appropriate potency and selectivity determinants has led to the discovery of several advanced leads that were orally efficacious in animal models of anaplastic large cell lymphoma (ALCL). A lead inhibitor (30) displaying superior efficacy was identified and in depth in vitro/in vivo characterization will be presented.

ALK mutants in the kinase domain exhibit altered kinase activity and differential sensitivity to small molecule ALK inhibitors.

Abnormal expression of constitutively active anaplastic lymphoma kinase (ALK) chimeric proteins in the pathogenesis of anaplastic large-cell lymphoma (ALCL) is well established. Recent studies with small molecule kinase inhibitors have provided solid proof-of-concept validation that inhibition of ALK is sufficient to attenuate the growth and proliferation of ALK (+) ALCL cells. In this study, several missense mutants of ALK in the phosphate anchor and gatekeeper regions were generated and their kinase activity was measured. NPM-ALK L182M, L182V, and L256M mutants displayed kinase activity in cells comparable to or higher than that of NPM-ALK wild type (WT) and rendered BaF3 cells into IL-3-independent growth, while NPM-ALK L182R, L256R, L256V, L256P, and L256Q displayed much weaker or little kinase activity in cells. Similar kinase activities were obtained with corresponding GST-ALK mutants with in vitro kinase assays. With regard to inhibitor response, NPM-ALK L182M and L182V exhibited sensitivity to a fused pyrrolocarbazole (FP)-derived ALK inhibitor comparable to that of NPM-ALK WT but were dramatically less sensitive to a diaminopyrimidine (DAP)-derived ALK inhibitor. On the other hand, NPM-ALK L256M exhibited >30-fold lower sensitivity to both FP-derived and DAP-derived ALK inhibitors. The growth inhibition and cytotoxicity of BaF3/NPM-ALK mutant cells induced by ALK inhibitors were consistent with inhibition of cellular NPM-ALK autophosphorylation. In a mouse survival model, treatment with the orally bioavailable DAP-ALK inhibitor substantially extended the survival of the mice inoculated with BaF3/NPM-ALK WT cells but not those inoculated with BaF3/NPM-ALK L256M cells. Binding of ALK inhibitors to ALK WT and mutants was analyzed using ALK homology models. In summary, several potential active ALK mutants were identified, and our data indicate that some of these mutants are resistant to select small molecule ALK inhibitors. Further characterization of these mutants may help to identify and develop potent ALK inhibitors active against both WT and resistant mutants of ALK.

Discovery of an Orally Efficacious Inhibitor of Anaplastic Lymphoma Kinase

Anaplastic lymphoma kinase (ALK) is a promising therapeutic target for the treatment of cancer, supported by considerable favorable preclinical and clinical activities over the past several years and culminating in the recent FDA approval of the ALK inhibitor crizotinib. Through a series of targeted modifications on an ALK inhibitor diaminopyrimidine scaffold, our research group has driven improvements in ALK potency, kinase selectivity, and overall pharmaceutical properties. Optimization of this scaffold has led to the identification of a potent and efficacious inhibitor of ALK, 25b. A striking feature of 25b over previously described ALK inhibitors is its >600-fold selectivity over insulin receptor (IR), a closely related kinase family member. Most importantly, 25b exhibited dose proportional escalation in rat compared to compound 3 which suffered dose limiting absorption preventing further advancement. Compound 25b exhibited significant in vivo antitumor efficacy when dosed orally in an ALK-positive ALCL tumor xenograft model in SCID mice, warranting further assessment in advanced preclinical models.

Combinatorial Library Design and Evaluation: Principles, Software Tools, and Applications in Drug Discovery

Introduction - library design concepts and implementation strategies. Part 1 Design principles: fundamentals of pharmacophore modelling for combinatorial chemistry quantitative structure-activity relationships (QSAR) - versatile tool in drug design quantitative structure-activity relationships (QSAR) - a review of 3D QSAR binding energy landscapes of ligand-protein complexes and molecular docking - principles, methods and validation experiments fast continuum electrostatics methods for structure-based ligand design quo vadis, scoring functions? toward an integrated pharmacokinetic and binding affinity prediction framework. Part 2 Current methods and software tools: knowledge-based approaches for the design of small molecule libraries for drug discovery drug-likeness profiles of chemical libraries tools for designing diverse, drug-like, cost-effective combinatorial libraries relative and asbolute diversity analysis of combinatorial libraries rational combinatorial library design and database mining using inverse QSAR approach dissimilarity-based compound selection for library design pharmacore-based approaches to combinatorial library design high throughput conformational sampling and fuzzy similarity metrics - a novel approach to similarity searching and focused combinatorial library design and its role in the drug discovery laboratory. Part 3 Applications: applications of cell-based diversity methods to combinatorial library design structure based combinatorial library design and screening - applications of the multiple copy simultaneous search method genetic algorithm-directed lead generation enhancement of the drug discovery process by integration of structure-based drug design and combinatorial synthesis design of structrural combinatorial libraries that mimic biological motifs.

Discovery of Clinical Candidate CEP-37440, a Selective Inhibitor of Focal Adhesion Kinase (FAK) and Anaplastic Lymphoma Kinase (ALK)

Analogues structurally related to anaplastic lymphoma kinase (ALK) inhibitor 1 were optimized for metabolic stability. The results from this endeavor not only led to improved metabolic stability, pharmacokinetic parameters, and in vitro activity against clinically derived resistance mutations but also led to the incorporation of activity for focal adhesion kinase (FAK). FAK activation, via amplification and/or overexpression, is characteristic of multiple invasive solid tumors and metastasis. The discovery of the clinical stage, dual FAK/ALK inhibitor 27b, including details surrounding SAR, in vitro/in vivo pharmacology, and pharmacokinetics, is reported herein.

An estimation of the atomic contribution to octanol-water partition coefficient and molar refractivity from fundamental atomic and structural properties: Its uses in computer aided drug design

It has been shown earlier that atomic physicochemical properties can be extremely valuable in determining the molecular similarities and in modeling the hypothetical ligand-receptor interaction [Ghose etal. (1989) J. Med. Chem. 32 746 and references cited therein]. In all previous studies a discretized atom classification was used to assign the atomic octanol-water partition coefficient and molar refractivity. We have presented here a more continuous empirical method for evaluating these two physicochemical properties using the topological information, and van der Waals radii and electronegativities of the atoms. The method is good for evaluating both the atomic and molecular properties. The basic hypothesis of the method is that these molecular properties are the overall effect of contribution of the individual atoms, although the contributions of the atoms are altered by its environment. We have suggested some functions that can estimate the property of any atom from its environment. Being an atom based approach it is capable of evaluating the property at any local region of a molecule. The contributions for carbon, hydrogen, oxygen, nitrogen, sulfur, phosphorus, selenium and halogens at their various hybridized states have been assigned in terms of 21 atom types. In the case of hydrophobicity (octanol-water partition coefficient) the correction for the neighboring atoms has been modeled in terms of Van der Waals radius, electronegativity and the bonding pattern using 36 adjustable parameters. The observed and the calculated values for a training set of 893 compounds showed a correlation coefficient of 0.909 and an rms deviation of 0.542. The corresponding values for the test set of 127 compounds were 0.817 and 0.620. For molar refractivity the neighboring effect was modeled in terms of van der Waals radius and bonding pattern using 21 adjustable parameters. The training set containing 547 compounds showed a correlation coefficient of 0.997 and an rms deviation of 1.014 between the observed and calculated values. The test set of 62 compounds on the other hand showed the corresponding statistics of 0.995 and 1.605.

Technically Extended MultiParameter Optimization (TEMPO): An Advanced Robust Scoring Scheme To Calculate Central Nervous System Druggability and Monitor Lead Optimization

At the discovery stage, it is important to understand the drug design concepts for a CNS drug compared to those for a non-CNS drug. Previously, we published on ideal CNS drug property space and defined in detail the physicochemical property distribution of CNS versus non-CNS oral drugs, the application of radar charting (a graphical representation of multiple physicochemical properties used during CNS lead optimization), and a recursive partition classification tree to differentiate between CNS- and non-CNS drugs. The objective of the present study was to further understand the differentiation of physicochemical properties between CNS and non-CNS oral drugs by the development and application of a new CNS scoring scheme: Technically Extended MultiParameter Optimization (TEMPO). In this multiparameter method, we identified eight key physicochemical properties critical for accurately assessing CNS druggability: (1) number of basic amines, (2) carbon-heteroatom (non-carbon, non-hydrogen) ratio, (3) number of aromatic rings, (4) number of chains, (5) number of rotatable bonds, (6) number of H-acceptors, (7) computed octanol/water partition coefficient (AlogP), and (8) number of nonconjugated C atoms in nonaromatic rings. Significant features of the CNS-TEMPO penalty score are the extension of the multiparameter approach to generate an accurate weight factor for each physicochemical property, the use of limits on both sides of the computed property space range during the penalty calculation, and the classification of CNS and non-CNS drug scores. CNS-TEMPO significantly outperformed CNS-MPO and the Schrödinger QikProp CNS parameter (QP_CNS) in evaluating CNS drugs and has been extensively applied in support of CNS lead optimization programs.