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 CO2 from feed streams. Here we report the investigation of four zeolites that have been predicted to be effective at separating CO2 from methane, but which have not to date been synthesized experimentally as membranes. Using an in silico de novo design procedure, we identify organic structure-directing agents (OSDAs) that are predicted to aid the synthesis of these zeolites. Using a genetic algorithm approach, we designed OSDAs for zeolites for which no purely siliceous form is known, and we also designed OSDAs for predicted zeolites. Stabilization energies of the best OSDAs designed for the zeolites GIS, ABW, and predicted zeolite 8198030 lie within -8 to -12 kJ/(mol Si), in the range of values for other known OSDAs. Stabilization energies of the OSDAs designed for predicted zeolite 8186909 are -16 kJ/(mol Si), comparable to the best known OSDAs for any zeolite. The OSDAs reported here may lead to zeolites that could enable a practical separation of CO2 from methane.

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. We find a significant number of real materials are in this predicted database of zeolite-like structures. These results suggest that many other predicted structures in this database may be suitable targets for designer materials synthesis.

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. We here design organic structure directing agents (OSDAs) for four of the zeolites with the best predicted separation performance, two that are ethylene selective and two that are ethane selective. The designed OSDAs may enable the synthesis of these zeolites for more energy efficient separation of ethylene and ethane.

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. We find that the stabilization energies predicted by the neural network are highly correlated with the molecular dynamics computations. We further find that the evolutionary design algorithm samples the space of chemically feasible OSDAs thoroughly. In total, we find 469 OSDAs with verified stabilization energies below -17 kJ/(mol Si), comparable to or better than known OSDAs for zeolite beta, and greatly expanding our previous list of 152 such predicted OSDAs. We expect that these OSDAs will lead to syntheses of zeolite beta.

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

We have de novo 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 CO2 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.

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. Enantiopure organic structure directing agents are designed with the assistance of computational methods and used to synthesize enantioenriched, polycrystalline molecular sieve samples of either enantiomer. Computational results correctly predicted which enantiomer is obtained, and enantiomeric enrichment is proven by high-resolution transmission electron microscopy. The enantioenriched and racemic samples of the molecular sieves are tested as adsorbents and heterogeneous catalysts. The enantioenriched molecular sieves show enantioselectivity for the ring opening reaction of epoxides and enantioselective adsorption of 2-butanol (the R enantiomer of the molecular sieve shows opposite and approximately equal enantioselectivity compared with the S enantiomer of the molecular sieve, whereas the racemic sample of the molecular sieve shows no enantioselectivity).

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. This in turn allows us to suggest approaches to address the problem of false positive hits in de novo structure based drug design by introducing structural and physicochemical constraints in the designed molecules, and by forcing essential interactions between these molecules and their target receptor.

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

SUMMAY: 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. To assess the efficacy of alofanib on FGF-mediated cell proliferation, SKOV3 cells were incubated and were treated with serially diluted alofanib. Basic FGF was added at a concentration of 25 ng/ml. Control wells were left untreated. Cell growth inhibition was determined using Promega's Cell Titer-Glo® assay. Immunocompromised mice were used for xenotransplantation of SKOV3 cancer cells. Seventy animals with measurable tumors were selected on day 10 and randomized into control groups (no treatment or chemotherapy alone (paclitaxel + carboplatin) and treatment groups (alofanib orally or intravenously (different dose levels) in combination with chemotherapy). Measurements of tumor volume (mm3) were performed by digital calipers every 3 days during 31 days after tumor inoculation. Number of tumor vessels and Ki-67 index were calculated. Results SKOV3 cells express FGFR1 and FGFR2 but not FGFR3. Basic FGF increased proliferation of the ovarian cancer cells in untreated control group (P = 0.001). Alofanib inhibited growth of FGFR2-expressing SKOV3 cells with GI50 value of 0.37 µmol/L. Treatment with alofanib in combination with paclitaxel/carboplatin resulted in tumor growth delay phenotype in all treatment groups compared to control non-treatment groups. Compound exhibited a dose-dependent effect on tumor growth. Daily intravenous regimen of alofanib (total maximum dose per week was 350 mg/kg) demonstrated significant effect (inhibiting growth by 80 % and by 53 % in comparison with vehicle and chemotherapy group alone, respectively (P < 0.001). Alofanib decreased number of vessels in tumor (-49 %; P < 0.0001) and number of Ki-67-positive SKOV3 cells (-42 %, P < 0.05). There were tumor necrosis and cell degeneration in alofanib group. Conclusions We suggest that FGFR2 inhibition has potent effects on ovarian cancer growth in preclinical studies.

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. In a panel of four cell lines representing several tumour types (triple-negative breast cancer, melanoma, and ovarian cancer), alofanib inhibited FGF-mediated proliferation with 50% growth inhibition (GI50) values of 16-370 nmol/l. Alofanib dose dependently inhibited the proliferation and migration of human and mouse endothelial cells (GI50 11-58 nmol/l) compared with brivanib and bevacizumab. Treatment with alofanib ablated experimental FGF-induced angiogenesis in vivo. In a FGFR-driven human tumour xenograft model, oral administration of alofanib was well tolerated and resulted in potent antitumour activity. Importantly, alofanib was effective in FGFR2-expressing models. These results show that alofanib is a potent FGFR2 inhibitor and provide strong rationale for its evaluation in patients with FGFR2-driven cancers.

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. This protocol, or scoring function, was used in combination with the de novo synthesis program 'SYNOPSIS' to generate high scoring and synthetically accessible compounds. RESULTS: Eight compounds belonging to 3 separate chemical classes were synthesized. One of these compounds, alofanib (RPT835), was found to be an effective inhibitor of the FGF/FGFR2 pathway. The preclinical in vitro data support an allosteric inhibition mechanism of RPT835. RPT835 potently inhibited growth of KATO III gastric cancer cells expressing FGFR2, with GI50 value of 10 nmol/L. CONCLUSION: These results provide strong rationale for the evaluation of compound in advanced cancers.

An ant algorithm for the conformational analysis of flexible molecules.

Originally, the ant system was developed for optimization in discrete search spaces such as the traveling salesman problem. We detail our adaptation of the algorithm to optimization in the continuous search space of conformational analysis. The parameters of the algorithm were tuned using a simple test molecule, undecane, and a drug molecule, imatinib. The algorithm is further tested on four more drug or drug-like molecules, on vitamin A and on alanine tetrapeptide.

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.

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.

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. The presence of a single carbonyl-hydroxy-aromatic nitrogen motif was shown to be essential for the enzymatic activity and this was confirmed by molecular docking studies. The enzymatically most active compound from this series is 7-(3,4-dichlorobenzyl)-5,9-dihydroxypyrrolo[3,4-g]quinoxaline-6,8-dione (15l) with an IC(50) value of 112 nM on the HIV-1 integrase enzyme, while ((7-(4-chlorobenzyl)-5,9-dihydroxy-pyrrolo[3,4-g]quinoxaline-6,8-dione (15k)) showed an EC(50) of 270 nM against HIV-1 in a cell-based assay.

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).

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. We apply the method to the prediction of pIC(50) of HIV-1 reverse transcriptase inhibitors. The model predicts the activity of an arbitrary compound with a q(2) of 0.681 and an average absolute error of 0.66 log value, and it is fast enough to be used in high-throughput computational applications.

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. Physicochemical parameters comprised lipophilicity (octanol/water partition coefficient [cLogP]), ionisation constant (pKa), solubility and aggregate radius. Cell-based assays included human colonic adenocarcinoma cell (Caco-2) permeability (transepithelial transport), drug metabolism and antiviral activity (negative logarithm of the molar effective concentration inhibiting viral replication by 50% [pEC50]). Exposure was tested in rats, dogs and human volunteers. RESULTS: Of the 15 parameters, eight correlated consistently among one another. Exposure (area under the plasma concentration-time curve [AUC]) in humans correlated positively with that in rats (r = 1.00), with transepithelial transport (r = 0.83), lipophilicity (r = 0.60), ionisability (r = 0.89), hydrodynamic radius of aggregates (r = 0.66) and with antiviral activity (r = 0.61). Exposure in humans was also seen to correlate negatively with SASA (r = -0.89). No consistent correlation was found between exposure in dogs and the eight parameters. Of the 14 DATA/DAPY molecules, 11 form aggregates with radii between 34 and 100 nm. CONCLUSIONS: We observed correlations between exposure in humans with exposure in rats, transepithelial transport (Caco-2 cells), ionisability, lipophilicity, aggregate radius and SASA in the class of DATA/DAPY NNRTI compounds. The lipophilic DATA/DAPY compounds form aggregates. It can be assumed that absorption in the intestinal tract and endocytosis in infected cells of these lipophilic compounds are governed by the common phenomenon of aggregate formation. As the lymphatic system offers a pathway for intestinal uptake of aggregates, this may offer a therapeutic advantage in the treatment of HIV-1 infection. Although it was not the objective of the study, we found that the rat was a better in vivo model than the dog for the prediction of systemic exposure in this particular set of compounds.

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. The docking algorithms studied are an energy-based simulated annealing algorithm and a novel pharmacophore docking algorithm. It turns out that the energy-based docking of the ligands into non-native pockets is far less successful than the docking into their native pockets. The results can be improved by using explicit pharmacophore information, and by docking a ligand into a panel of protein structures and selecting the ligand-protein combination with the lowest interaction energy as the final result.

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. In the case of the design of anti-HIV compounds we observed that the more active compounds that are also resilient against mutation of the non-nucleoside binding site of HIV1-reverse transcriptase make use of more binding modes than the less active and resilient compounds.