Automating combinatorial chemistry: A primer on benchtop robotic systems

Summary Benchtop robotic systems are inexpensive, flexible automation tools with potential applications in a wide array of disciplines such as combinatorial chemistry, high-throughput screening, and genomics. We explain the basic components of a benchtop system and explore factors to consider when purchasing or customizing a robot, such as automation benefits, vendor selection, and current system limitations. Issues involving system specification, software design, and hardware customization are then discussed. Additionally, system optimization, validation, and support are detailed. Given a properly designed and implemented system, the combinatorial laboratory can markedly increase compound synthesis and purification.     

Finite-field method calculations. IV. Higher-order moments,dipole moment gradients,polarisability gradients and field-induced shifts in molecular properties: Application to N2, CO,CN−, HCN and HNC

In this paper, theoretical methods developed in III are applied in calculating polarisabilities, polarisability gradients and field-induced shifts, by the finite-field method. Values of dipole moment gradients and higher-order moments, calculated from the unperturbed wavefunctions, are also reported. Results for N₂, CO, CN^?, HCN and HNC have been obtained at the SCF level; some CI results for the N₂ polarisability components and moments and for the dipole moment gradients of HCN are also given. The calculated polarisability gradients and dipole moment gradients have been used to estimate the Raman scattering intensities and depolarisation ratios and the IR absorption intensities. Model calculations of field-induced shifts in bond length, vibrational levels, spectroscopic constants, force constants and dipole moment gradient are reported for N₂ and CO.The discrepancy between the SCF and experimental bond dipole moment gradients for HCN, previously noted in the literature, has been re-examined and resolved by our CI results.     

Micellar hydrolysis of hydroxamic acids. Michaelis-menten kinetics

Rates of reaction for the alkaline hydrolysis of various hydroxamic acids in the presence of cetyltrimethylammonium bromide have been determined. Empirical reaction orders of zero, one-half, and one were found for the hydroxamic acids depending upon reaction conditions and substrate structure. N -methylhydroxamic acids exhibited only first-order kinetics. The results are consistent with the Michaelis-Menten rate equation.     

A correlation of gas solubilities and kinetics of hydrolysis in binary aqueous mixtures

A treatment which predicts the solubilities of gases in solvent mixtures is examined in the context of the analysis of kinetic data for reactions in aqueous mixtures. The treatment is qualitatively successful to some extent in resolving the effects of changes in the initial state of the reacting substrate in the activation parameters.     

Boundary Value Problems for Second‐Order Elliptic Operators Satisfying a Carleson Condition

Let Ω be a Lipschitz domain in , and be a second‐order elliptic operator in divergence form. We establish the solvability of the Dirichlet regularity problem with boundary data in and of the Neumann problem with data for the operator L on Lipschitz domains with small Lipschitz constant. We allow the coefficients of the operator L to be rough, obeying a certain Carleson condition with small norm. These results complete the results of Dindo?, Petermichl, and Pipher (2007), where the Dirichlet problem was considered under the same assumptions, and Dindo? and Rule (2010), where the regularity and Neumann problems were considered on two‐dimensional domains.© 2016 Wiley Periodicals, Inc.     

A chemical approach to the pharmaceutical optimization of an anti-HIV protein

Chemical protein synthesis is important for dissecting the molecular basis of protein function. Here we advance its scope by demonstrating the significant improvement of the multifaceted pharmaceutical profile of small proteins exclusively via a chemical-based approach. The focus of this work centered on CCL-5 (RANTES) derivatives with potent anti-HIV activity. The overall chemical strategy involved a combination of coded and noncoded amino acid mutagenesis, peptide backbone engineering, and site-specific polymer attachment. The ability to alter specific protein residues, as well as precise control of the position and type of polymer attachment, allows for the exploration of specific molecular designs and resulted in novel CCL-5 analogues with significant differences in their respective biochemical and pharmaceutical properties. Using this approach, the complex-interplay of variables contributing to the noncovalent self-association (aggregation) state, CCR-5 specificity, in vivo elimination half-life, and anti-HIV activity of CCL-5-based protein analogues could be empirically evaluated via total chemical synthesis. This work has led to the identification of potent (sub-nanomolar) anti-HIV proteins with significantly improved pharmaceutical profiles, and illustrates the increasing value of protein chemical synthesis in contemporary therapeutic discovery. These antiviral molecules provide a novel mechanism of action for the development of a new generation of anti-HIV therapeutics which are still desperately needed.     

Integrating subcellular location for improving machine learning models of remote homology detection in eukaryotic organisms

A significant challenge in homology detection is to identify sequences that share a common evolutionary ancestor, despite significant primary sequence divergence. Remote homologs will often have less than 30% sequence identity, yet still retain common structural and functional properties. We demonstrate a novel method for identifying remote homologs using a support vector machine (SVM) classifier trained by fusing sequence similarity scores and subcellular location prediction. SVMs have been shown to perform well in a variety of applications where binary classification of data is the goal. At the same time, data fusion methods have been shown to be highly effective in enhancing discriminative power of data. Combining these two approaches in the application SVM-SimLoc resulted in identification of significantly more remote homologs (p-value<0.006) than using either sequence similarity or subcellular location independently.     

Cell adhesion and growth to Peptide-patterned supported lipid membranes

Lipid vesicles displaying RGD peptide amphiphiles were fused with glass coverslips to control the ability of these surfaces to support cell adhesion and growth. Cell adhesion was prevented on phosphatidylcholine bilayers in the absence of RGD, whereas cells adhered and grew in the presence of accessible RGD amphiphiles. This specific interaction between cells and RGD peptides was further explored in a concentration-dependent fashion by creating surface composition arrays using microfluidics. For the range of concentrations studied adhesion and growth were favored by increased peptide concentration, but this concentration dependence was found to diminish in the higher concentration regions of the array. Developing peptide composition gradients in a membrane environment is demonstrated as an effective method to screen biological probes for cell adhesion and growth.