COMPUTATIONAL MODELING OF BACTERIAL OUTER MEMBRANES AND DEVELOPMENT OF HIGH-THROUGHPUT SCREENING PLATFORM FOR ANTIBIOTICS

Antibiotic resistance is a major health challenge because it limits the treatment options for common infectious diseases and will cause 10 million deaths each year after 2050. There is an urgent need to reduce the misuse of antibiotics and seek new classes of antibiotics that induce less or no resistance. Despite the push for new therapeutics, there has been a precipitous decline in the number of newly approved antibacterial drugs due to a limited understanding of how bacteria adapt to the chemical stress stimuli. The development of antimicrobial resistance is especially true for Gram-negative bacteria that develop resistance to antibiotics readily due to their unique highly charged outer membrane. Structurally, the Gram-negative bacteria is highly asymmetric bilayer that comprises of an inner leaflet of phospholipids and an outer leaflet of lipopolysaccharides. Embedded in the bilayer are outer membrane proteins (OMPs) that form pores to allow passage of nutrients and other small molecules through the cell wall. In addition to the outer membrane, the Gram-negative bacteria have a thin peptidoglycan layer and an inner phospholipid membrane that surrounds the cytosol. All potential small molecule antibiotic molecule have to navigate through all three layers of the Gram-negative bacterial cell wall before targeting the cellular functions. There is, however, limited understanding of the chemical specificity, structure, and functional aspects of each layer in the cell wall. To enhance our understanding of the bacterial cell wall, we first developed molecular models of ten commensal or human pathogenic bacterial species: Pseudomonas aeruginosa, Escherichia coli, Helicobacter pylori, Porphyromonas gingivalis, Bacteroides fragilis, Bordetella pertussis, Chlamydia trachomatis, Campylobacter jejuni, Neisseria meningitidis, and Salmonella minnesota. Second, we studied the self-assembly of OMPs that in some cases form trimers in the outer membranes to perform their function. In the third step, we combined the outer membrane models and the OMPs to build a computational screening platform to quantify the transport properties of molecules across a bacterial outer membrane. The goal of the computational platform is to provide high-throughput screening of vast libraries of small molecules that have the potential of being active antibacterial agents against Gram-negative bacteria. A computational platform has merit to producing reliable first-round screening of molecules at a fraction of the cost in the otherwise expensive drug-discovery pipeline

Metallo \u3b2 lactamase: reactivity and site directed evolution pathways addressed by computational approaches

The indiscriminate prescription of antibiotics by physicians, along with their incorrect use [1] 1 has increased the exposition of bacteria to antibiotics, and thus has created a favorable environment for the Darwinian evolution of resistant strains [2]. Further increase of drug resistance is caused by the unnecessary massive use of antibiotics (70% of the total market is in the US!) to animals crammed into the unhygienic crowded quarters of factories [3, 4]. Diseases like tubercolosis, gonorrhea, malaria, and childhood ear infections, are increasingly becoming hard to treat with antibiotic drugs, posing serious concern in the human public health [5, 6]. The problem is even more serious if one considers that already in 70\u2019s and 80\u2019s that modification of the chemical structure of the already known antibiotics turned out to be exhausted and, at the same time, pharmacological companies decided not design of totally new antibiotics [2]

Enhanced sampling methods and their application in the study of molecular permeation in gram-negative bacteria

Antimicrobial resistance is inhibiting our ability to fight against pathogens. By selectively changing the composition and expression of influx water-filled proteins filling their outer membrane, gram- negative bacteria are able to reduce the rates at which specific polar compounds are able to permeate. A clear comprehension of the mechanism determining substrates diffusion through these pores is still missing. In this thesis, we show how biased computer simulations may offer a unique perspective in the study of molecular permeation through porins, overcoming the intrinsic limitations of both experimental techniques and standard molecular dynamics. The first test-case is Acinetobacter baumannii’s CarO. The use of substrates with varying charge and molecular weight, as well as the creation of a loop-less mutant missing the extracellular domain of the protein, allowed to determine the charge selectivity and the transition rates of polar molecules. We obtained good agreement with the results of liposome swelling assays experiments. Further, we compared the passage of two carbapenem antibiotics in a series of mutated proteins extracted from a patient undergoing long term hospital infection. We connected the mutation of few key residues to a drastic change in the internal electric field of the proteins, showing that the antibiotics follow the choreography of water molecules inside the channels. In the last section, we present a kinetic model that allows to determine for a molecule the relative probability of different conformations and the time required for the translocation through a pore. This approach allowed to connect the results of enhanced sampling MD methods with current blockages in single channel experiments.All these results together show that multiscale MD techniques can offer an exhaustive view on the mechanism of molecular diffusion through pores, helping to understand the most important charac- teristics that determine the rates of translocation of different com- pounds in gram-negative bacteria. We can use these data to com- plement experimental results and to design the next generation of antibiotics

Diffusion of tin from TEC-8 conductive glass into mesoporous titanium dioxide in dye sensitized solar cells

The photoanode of a dye sensitized solar cell is typically a mesoporous titanium dioxide thin film adhered to a conductive glass plate. In the case of TEC-8 glass, an approximately 500 nm film of tin oxide provides the conductivity of this substrate. During the calcining step of photoanode fabrication, tin diffuses into the titanium dioxide layer. Scanning Electron Microscopy and Electron Dispersion Microscopy are used to analyze quantitatively the diffusion of tin through the photoanode. At temperatures (400 to 600 °C) and times (30 to 90 min) typically employed in the calcinations of titanium dioxide layers for dye sensitized solar cells, tin is observed to diffuse through several micrometers of the photoanode. The transport of tin is reasonably described using Fick\u27s Law of Diffusion through a semi-infinite medium with a fixed tin concentration at the interface. Numerical modeling allows for extraction of mass transport parameters that will be important in assessing the degree to which tin diffusion influences the performance of dye sensitized solar cells

Development of Computational Antibiotic Screening Platform Across Bacterial Outer Membrane Proteins

Antibiotics are medicines used to treat bacterial infections by either killing bacteria or stopping them from reproducing. Throughout the use of antibiotics, bacteria has developed a variety of defense mechanisms against antibiotics and thus diminishing their effectiveness. Antibiotic resistance is a growing threat and becomes a global crisis as it is able to constantly evolve and rapidly spread. In the face of increasing bacterial resistance to all known antibiotics, there is an urgent need to accelerate the antibiotic discovery pipeline and discover new classes of antibiotics. A major bottleneck in the discovery of novel antibiotics is the limited permeability of potent drug molecules across the bacterial envelope to reach their target, and thus hindering their activities in vivo. With the aid of state-of-the-art computational methods and tools, we developed a computational platform to automate and study the translocation of small molecule drugs across bacterial outer membrane proteins, with a goal of accelerating the antibiotic discovery process. We applied all-atom and coarse-grained molecular modeling, enhanced sampling techniques, and a parallel computing environment to maximize the performance. We further demonstrate the efficacy of this platform with a comprehensive study of a benchmark case. Key findings include free energy profile, translocation kinetics and thermodynamics, and molecular interactions between drug molecules and protein residues. Ultimately, this approach is designed to screen small molecule libraries with a fast turnaround time to yield structure-property relationships to discover antibiotics with high permeability. Furthermore, this work is expected to provide insights in inverse engineering and mutation design during drug development

Modular Approaches to Skeletally Diverse and Stereochemically-rich 7- to 11-membered Ring Sultams

The overarching goal of this dissertation is the development of efficient methods for the generation of medium- and large-sized heterocycles, specifically 7- to 11-membered sultams, for facilitating probe and drug discovery. Chapter One summarizes the structural components that are prevalent in current marketed pharmaceutical agents, highlighting underrepresented rings, rings systems and frameworks, which have the potential to introduce chemical novelty into the existing limited list of chemical ring systems that describe the majority of the drugs. Chapter Two introduces the concept of pairing of a reaction triad, namely sulfonylation, SNAr addition and Mitsunobu alkylation, in varying order via the use of central o-fluorobenzene sulfonyl chloride building blocks that afford rapid access to both bridged- and fused-tricyclic, 7- to 10-membered benzofused sultams. This simple approach obviates the need for the construction of elaborate multi-functional scaffolds and merely requires use of o-fluorobenzene sulfonyl chlorides, amines and alcohols as building blocks. Simple changes in the reaction pair sequence (e.g., sulfonylation–SNAr vs sulfonylation–SNAr–Mitsunobu vs sulfonylation–Mitsunobu– SNAr), or changes in the building blocks (1,2-amino alcohol vs 1,3-amino alcohol), allows access to skeletal and stereochemical diversity. Chapter Three presents the concept of complementary pairing of activated sulfonyl aziridines (simple 6-atom bis-electrophilic synthon) via "chemo- and regioselective" aziridine ring-opening with an amino component of an amino alcohol (bis-nucleophiles). Subsequent intramolecular SNAr cyclization with the alcohol component of the amino alcohol affords unprecedented, functionally rich mediumsized benzofused sultams in overall, chemoselective “6+4” and “6+5” heterocyclization pathways. Moreover, the use of primary amines for the sulfonyl aziridine ring-opening step, whereby the resulting secondary amines cyclize via a subsequent intramolecular SNAr reaction, enables the generation of 7-membered benzofused sultams via an overall “6+1” atom cyclization sequence Chapter Four describes efforts aimed at the use of one-pot, sequential 3- or 4- component sulfonylation–aza-Michael–amide cyclization protocols to generate a library of skeletally and stereochemically diverse 7/4, 7/5 and 7/6-fused bicyclic acyl sultams. In this library effort, sulfonylation of different amines with 2-chloroethane sulfonyl chloride, followed by Michael reaction with a variety of amino acids, and subsequent amide cyclization provides access to the titled bicyclic sultams, which are currently being screened for biological activity as well as unique chemical properties

Development of an Accurate and Efficient Method for Normal Mode Analysis in Extended Molecular Systems: the Mobile Block Hessian Method

Vibrational spectroscopy is an important technique for the structural characterization of (bio)molecules and (nano)materials. For example, it is particularly suited for studying proteins in their natural environment (i.e., in aqueous solution), and can be used in many cases where other techniques such as Xray crystallography and nuclear magnetic resonance spectroscopy cannot be employed. In particular infrared (IR) and Raman spectroscopy have been used extensively for gaining information on the secondary structure of polypeptides and proteins. Also in other fields, these techniques help to identify the functional groups in the material, or provide a unique “fingerprint” of the material, the so-called skeleton vibrations. A frequently encountered problem in spectroscopy is the precise interpretation of the obtained experimental spectra. Many of these nanostructured systems are characterized by very complex vibrational spectra and the assignment of specific bands to particular vibrations is difficult if based solely on experimental techniques. In this field theoretical predictions form an undeniable complement to the measured spectra. Each observed band in the spectrum consists of a number of close-lying normal modes, which result from normal mode analysis (NMA). This is the diagonalization of the full mass-weighted molecular Hessian matrix, which contains the second derivatives of the total potential energy with respect to Cartesian nuclear coordinates, evaluated in an equilibrium point on the potential energy surface (PES). By performing NMA, the system is approximated as a set of decoupled harmonic oscillators. The frequencies and modes contain information on the curvatures of the PES and the mass distribution in the system. NMA is a static approach that samples the PES exactly, if higher order derivatives, i.e. anharmonic corrections, are neglected, and is therefore an approximate analysis method complementary to molecular dynamics and Monte Carlo simulations. In extended molecular systems (like polypeptides, polymer chains, supramolecular assemblies, systems embedded in a solvent or molecules adsorbed within porous materials etc.), this procedure poses two major problems. First, the size of the relevant systems can easily reach a few hundreds or several ten thousands of atoms, and full calculations of such large systems are computationally demanding if not impossible with accurate methods. Second, even if possible, such calculations provide a large amount of data that will be increasingly difficult to interpret. Here lies the scope of this PhD work: The aim of this PhD is the calculation of accurate frequencies and modes in extended molecular systems in an efficient manner. Mainly two categories of approximate normal mode calculations can be identified: (1) the PES description is simplified; (2) the description of the PES is unchanged, but only a subset of the modes is calculated in an approximate way. This PhD work focuses on the latter category and presents the new Mobile Block Hessian (MBH) method and its variants. The key concept is the partitioning of the system into several blocks of atoms, which move as rigid bodies during the vibrational analysis with only rotational and translational degrees of freedom. The MBH has several variants according to the block choice and the way blocks are adjoined together. The MBH is currently implemented in the last upgrade of CHARMM and Q-Chem and the method will be available too in the next release of ADF. Outline PhD thesis In the introductory Chapter 1, normal mode analysis is presented as a technique to scan the potential energy surface within the harmonic oscillator approximation. The standard NMA equations with the full Hessian are revised. The problems brought up by nonstationary points motivate the necessity of a profound theoretical study of the NMA of partially optimized geometries as is the case for MBH. Chapter 2 elaborates the MBH theory in two sets of coordinates: internal coordinates and block parameters. For the extension of the MBH to all kind of blocks (including linear, single-atom blocks) and adjoined blocks (linked by a common “adjoining” atom), the general formulation in block parameters is also linked to Cartesian quantities (Cartesian Hessian, gradient). Five practical implementation schemes for MBH conclude this chapter. In Chapter 3, the MBH is assessed in its performance to reproduce accurate frequencies and normal modes. During my PhD, a large test set has three examples are outlined. The thanol molecule shows how MBH yields physical frequencies for a partially optimized structure, and that MBH is an improvement with respect to the Partial Hessian Vibrational Analysis (PHVA) because of the correct mass description of the block. The MBH is capable of reproducing accurate reaction rate constants given an acceptable block choice, as is illustrated with an aminophosphonate reaction in solvent. The usefulness of adjoined blocks is demonstrated with the calculation of the lowest normal modes of crambin, a small protein. Finally Chapter 4 gives some concluding remarks on the MBH’s performance. Perspectives for the further improvements of MBH include the optimization of the implementation in frequently used program packages, as well as several combined models for advanced NMA. Besides MBH there are other models in literature for the calculation of frequencies in extended systems. In particular, the vibrational subsystem analysis (VSA) method by B. R. Brooks is a competitive scheme. A comparative study of NMA methods based on Hessians of reduced dimension (partial Hessians) has been accomplished very recently in collaboration with prof. B. R. Brooks of the Laboratory of Computational Biology (National Institutes of Health) in Bethesda (Maryland). PHVA is found to be capable of reproducing localized modes. In addition to localized modes, the MBH can reproduce more global modes. VSA is most suited for the reproduction of the modes and frequencies in the lower spectrum. In partially optimized structures, PHVA and MBH can still yield physical frequencies. Moreover, by varying the size of the blocks, MBH can be used as an analysis tool of the spectrum. The comparative study is added in the Appendix. This PhD work has resulted in eight papers, six related to MBH – published, in press, or submitted – and two papers not directly related to MBH. All publications are included in the Appendix

The influence of structure on reactivity in alkene metathesis

Abstract Alkene metathesis has grown from a niche technique to a common component of the synthetic organic chemistry toolbox, driven in part by the development of more active catalyst systems, or those optimized for particular purposes. While the range of synthetic chemistry achieved has been exciting, the effects of structure on reactivity have not always been particularly clear, and rarely quantified. Understanding these relationships is important when designing new catalysts, reactions, and syntheses. Here, we examine what is known about the effect of structure on reactivity from two perspectives: the catalyst, and the substrate. The initiation of the precatalyst determines the rate at which active catalyst enters the catalytic cycle; the rate and selectivity of the alkene metathesis reaction is dependent on how the substrate and active catalyst interact. The tools deployed in modern studies of mechanism and structure/activity relationships in alkene metathesis are discussed