Design of organic structure directing agents to guide the synthesis of zeolites for the separation of ethylene-ethane mixtures.

Industrial production of ethylene entails a costly separation from the ethane by-product, and this separation is the dominant consumer of energy in the process. Zeolites have been proposed as a next generation material for this separation process, and a molecular screen of all known zeolites has revealed several promising candidate materials. None of the identified materials has yet been synthesized in the all-silica form evaluated in the screen.

Nanoporous materials with predicted zeolite topologies.

An increasing number of newly synthesized materials have been found to be previously present in databases of predicted porous materials. This has been observed not only for zeolites, but also for other inorganic materials and for MOFs. We here quantify the number of synthesized zeolites that are present in a large database of predicted zeolite structures as well as the number of other inorganic crystals and MOFs present in this same database.

Design of Organic Structure-Directing Agents for the Controlled Synthesis of Zeolites for Use in Carbon Dioxide/Methane Membrane Separations.

One strategy to mitigate global warming is carbon capture and sequestration. Membrane separation is one promising approach to separation of CO from feed streams. Here we report the investigation of four zeolites that have been predicted to be effective at separating CO from methane, but which have not to date been synthesized experimentally as membranes.

Design of organic structure directing agents to control the synthesis of zeolites for carbon capture and storage.

We have designed organic structure directing agents (OSDAs) for zeolites that have been predicted to be effective materials for carbon capture and storage. The zeolites were selected for their reduced parasitic energy when used as CO adsorbants in a pressure-temperature swing process in coal- or natural gas-fired power plants. Synthetically accessible OSDAs were designed for five known and two theoretical frameworks.

Machine-learning approach to the design of OSDAs for zeolite beta.

We report a machine-learning strategy for design of organic structure directing agents (OSDAs) for zeolite beta. We use machine learning to replace a computationally expensive molecular dynamics evaluation of the stabilization energy of the OSDA inside zeolite beta with a neural network prediction. We train the neural network on 4,781 candidate OSDAs, spanning a range of stabilization energies.

Enantiomerically enriched, polycrystalline molecular sieves.

Zeolite and zeolite-like molecular sieves are being used in a large number of applications such as adsorption and catalysis. Achievement of the long-standing goal of creating a chiral, polycrystalline molecular sieve with bulk enantioenrichment would enable these materials to perform enantioselective functions. Here, we report the synthesis of enantiomerically enriched samples of a molecular sieve.

A Pareto Algorithm for Efficient De Novo Design of Multi-functional Molecules.

We have introduced a Pareto sorting algorithm into Synopsis, a de novo design program that generates synthesizable molecules with desirable properties. We give a detailed description of the algorithm and illustrate its working in 2 different de novo design settings: the design of putative dual and selective FGFR and VEGFR inhibitors, and the successful design of organic structure determining agents (OSDAs) for the synthesis of zeolites. We show that the introduction of Pareto sorting not only enables the simultaneous optimization of multiple properties but also greatly improves the performance of the algorithm to generate molecules with hard-to-meet constraints.

Alofanib, an allosteric FGFR2 inhibitor, has potent effects on ovarian cancer growth in preclinical studies.

Purpose Early data suggest that combining FGFR2 inhibitors with platinum-containing cytotoxic agents for the treatment of epithelial ovarian cancer may yield increased antitumor activity. We investigated antitumor activity of alofanib (RPT835), a novel allosteric FGFR2 inhibitor, in ovarian cancer in vitro and in vivo. Methods Equal amounts of ovarian cancer cell (SKOV3) lysates were analyzed for FGFR1-3 protein expression using Wes.

Targeting FGFR2 with alofanib (RPT835) shows potent activity in tumour models.

Alofanib (RPT835) is a novel selective allosteric inhibitor of fibroblast growth factor receptor 2 (FGFR2). We showed previously that alofanib could bind to the extracellular domain of FGFR2 and has an inhibitory effect on FGF2-induced phoshphorylation of FRS2α. In the present study, we further showed that alofanib inhibited phosphorylation of FRS2α with the half maximal inhibitory concentration (IC50) values of 7 and 9 nmol/l in cancer cells expressing different FGFR2 isoforms.

Molecular Modeling, de novo Design and Synthesis of a Novel, Extracellular Binding Fibroblast Growth Factor Receptor 2 Inhibitor Alofanib (RPT835).

Background: Fibroblast growth factor (FGF) receptors (FGFRs) play a key role in tumor growth and angiogenesis. The present report describes our search for an extracellularly binding FGFR inhibitor using a combined molecular modeling and de novo design strategy.

Methods: Based upon crystal structures of the receptor with its native ligand and knowledge of inhibiting peptides, we have developed a computational protocol that predicts the putative binding of a molecule to the extracellular domains of the receptor.

Improving QSAR models for the biological activity of HIV Reverse Transcriptase inhibitors: Aspects of outlier detection and uninformative variable elimination.

The goal of this study is to derive a methodology for modeling the biological activity of non-nucleoside HIV Reverse Transcriptase (RT) inhibitors. The difficulties that were encountered during the modeling attempts are discussed, together with their origin and solutions. With the selected multivariate techniques: robust principal component analysis, partial least squares, robust partial least squares and uninformative variable elimination partial least squares, it is possible to explore and to model the contaminated data satisfactory.

Structure based activity prediction of HIV-1 reverse transcriptase inhibitors.

We have developed a fast and robust computational method for prediction of antiviral activity in automated de novo design of HIV-1 reverse transcriptase inhibitors. This is a structure-based approach that uses a linear relation between activity and interaction energy with discrete orientation sampling and with localized interaction energy terms. The localization allows for the analysis of mutations of the protein target and for the separation of inhibition and a specific binding to the enzyme.

Synthesis of novel diarylpyrimidine analogues and their antiviral activity against human immunodeficiency virus type 1.

This paper reports the synthesis and the antiviral properties of new diarylpyrimidine (DAPY) compounds as nonnucleoside reverse transcriptase inhibitors (NNRTIs). The synthesis program around this new DAPY series was further optimized to produce compounds displaying improved activity against a panel of eight clinically relevant single and double mutant strains of human immunodeficiency virus type 1 (HIV-1).

Design and optimization of tricyclic phtalimide analogues as novel inhibitors of HIV-1 integrase.

Human immunodeficiency virus type-1 integrase is an essential enzyme for effective viral replication and hence a valid target for the design of inhibitors. We report here on the design and synthesis of a novel series of phthalimide analogues as integrase inhibitors. The short synthetic pathway enabled us to synthesize a series of analogues with a defined structure diversity.

Design, synthesis, and SAR of a novel pyrazinone series with non-nucleoside HIV-1 reverse transcriptase inhibitory activity.

A series of novel pyrazinones designed as non-nucleoside reverse transcriptase inhibitors (NNRTIs) was synthesized and their anti-HIV structure-activity relationship (SAR) was studied.

In search of a novel anti-HIV drug: multidisciplinary coordination in the discovery of 4-[[4-[[4-[(1E)-2-cyanoethenyl]-2,6-dimethylphenyl]amino]-2- pyrimidinyl]amino]benzonitrile (R278474, rilpivirine).

Ideally, an anti-HIV drug should (1) be highly active against wild-type and mutant HIV without allowing breakthrough; (2) have high oral bioavailability and long elimination half-life, allowing once-daily oral treatment at low doses; (3) have minimal adverse effects; and (4) be easy to synthesize and formulate. R278474, a new diarylpyrimidine (DAPY) non-nucleoside reverse transcriptase inhibitor (NNRTI), appears to meet these criteria and to be suitable for high compliance oral treatment of HIV-1 infection. The discovery of R278474 was the result of a coordinated multidisciplinary effort involving medicinal chemists, virologists, crystallographers, molecular modelers, toxicologists, analytical chemists, pharmacists, and many others.

Correlations between factors determining the pharmacokinetics and antiviral activity of HIV-1 non-nucleoside reverse transcriptase inhibitors of the diaryltriazine and diarylpyrimidine classes of compounds.

Objective: To investigate the important factors that determine the bioavailability and the antiviral activity of the diaryltriazine (DATA) and diarylpyrimidine (DAPY) non-nucleoside reverse transcriptase inhibitors (NNRTIs) of HIV-1 in animal species and humans using cell-based assays, physicochemical and computed parameters.

Methods: This naturalistic study included 15 parameters ranging from molecular mechanics calculations to phase I clinical trials. The calculated parameters were solvent-accessible surface area (SASA), polar surface area and Gibbs free energy of solvation.

Roles of conformational and positional adaptability in structure-based design of TMC125-R165335 (etravirine) and related non-nucleoside reverse transcriptase inhibitors that are highly potent and effective against wild-type and drug-resistant HIV-1 variants.

Anti-AIDS drug candidate and non-nucleoside reverse transcriptase inhibitor (NNRTI) TMC125-R165335 (etravirine) caused an initial drop in viral load similar to that observed with a five-drug combination in naïve patients and retains potency in patients infected with NNRTI-resistant HIV-1 variants. TMC125-R165335 and related anti-AIDS drug candidates can bind the enzyme RT in multiple conformations and thereby escape the effects of drug-resistance mutations. Structural studies showed that this inhibitor and other diarylpyrimidine (DAPY) analogues can adapt to changes in the NNRTI-binding pocket in several ways: (1).

Classification and regression trees--studies of HIV reverse transcriptase inhibitors.

In this paper, the application of Classification And Regression Trees (CART) is presented for the analysis of biological activity of Non-Nucleoside Reverse Transcriptase Inhibitors (NNRTIs). The data consist of the biological activities, expressed as pIC50, of 208 NNRTIs against wild-type HIV virus (HIV-1) and four mutant strains (181C, 103N, 100I, 188L) and the computed interaction energies with the Reverse Transcriptase (RT) binding pocket. CART explains the observed biological activity of NNRTIs in terms of interactions with individual amino acids in the RT binding pocket, i.

A pharmacophore docking algorithm and its application to the cross-docking of 18 HIV-NNRTI's in their binding pockets.

The docking of small molecules into the binding site of a target protein is an important but difficult step in structure-based drug design. The performance of a docking algorithm is usually evaluated by re-docking ligands into their native binding sites. We have explored the cross-docking of 18 HIV-NNRTIs (non-nucleoside inhibitors of HIV reverse transcriptase) of which the ligand-protein structure has been determined: each of the 18 ligands was docked into each of the 18 binding sites.

On the detection of multiple-binding modes of ligands to proteins, from biological, structural, and modeling data.

There are several indications that a given compound or a set of related compounds can bind in different modes to a specific binding site of a protein. This is especially evident from X-ray crystallographic structures of ligand-protein complexes. The availability of multiple binding modes of a ligand in a binding site may present an advantage in drug design when simultaneously optimizing several criteria.

SYNOPSIS: SYNthesize and OPtimize System in Silico.

We present a de novo design program called SYNOPSIS, that includes a synthesis route for each generated molecule. SYNOPSIS designs novel molecules by starting from a database of available molecules and simulating organic synthesis steps. This way of generating molecules imposes synthetic accessibility on the molecules.

Evolution of anti-HIV drug candidates. Part 3: Diarylpyrimidine (DAPY) analogues.

The synthesis and anti-HIV-1 activity of a series of diarylpyrimidines (DAPYs) are described. Several members of this novel class of non-nucleoside reverse transcriptase inhibitors (NNRTIs) are extremely potent against both wild-type and a panel of clinically significant single- and double-mutant strains of HIV-1.