Coarse Graining to Invesitigate Peptide-Lipid Interactions

Experimental characterization of molecular details is challenging, and although single molecule experiments have gained prominence, oligomer characterization remains largely unexplored. The ability to monitor the time evolution of individual molecules while they self assemble is essential in providing mechanistic insights about biological events. Molecular dynamics (MD) simulations can fill the gap in knowledge between single molecule experiments and ensemble studies like NMR, and are increasingly used to gain a better understanding of microscopic properties. Coarse-grained (CG) models aid in both exploring longer length and time scale molecular phenomena, and narrowing down the key interactions responsible for significant system characteristics. Over the past decade, CG techniques have made a significant impact in understanding physicochemical processes. However, the realm of peptide-lipid interfacial interactions, primarily binding, partitioning and folding of amphipathic peptides, remains largely unexplored compared to peptide folding in solution. The main drawback of existing CG models is the inability to capture environmentally sensitive changes in dipolar interactions, which are indigenous to protein folding, and lipid dynamics. We have used the Drude oscillator approach to incorporate structural polarization and dipolar interactions in CG beads to develop a minimalistic peptide model, WEPPROM (Water Explicit Polarizable PROtein Model), and a lipid model WEPMEM (Water Explicit Polarizable MEmbrane Model). The addition of backbone dipolar interactions in a CG model for peptides enabled us to achieve alpha-beta secondary structure content de novo, without any added bias. As a prelude to studying amphipathic peptide-lipid membrane interactions, the balance between hydrophobicity and backbone dipolar interactions in driving ordered peptide aggregation in water and at a hydrophobic-hydrophilic interface, was explored. We found that backbone dipole interactions play a crucial role in driving ordered peptide aggregation, both in water and at hydrophobic-hydrophilic interfaces; while hydrophobicity is more relevant for aggregation in water. A zwitterionic (POPC: 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine) and an anionic lipid (POPS: 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-L-serine) are used as model lipids for WEPMEM. The addition of head group dipolar interactions in lipids significantly improved structural, dynamic and dielectric properties of the model bilayer. Using WEPMEM and WEPPROM, we studied membrane-induced peptide folding of a cationic antimicrobial peptide with anticancer activity, SVS-1. We found that membrane-induced peptide folding is driven by both (a) cooperativity in peptide self interaction and (b) cooperativity in membrane-peptide interactions. The dipolar interactions between the peptide and the lipid head-groups contribute to stabilizing folded conformations. The role of monovalent ion size and peptide concentration in driving lipid domain formation in anionic/zwitterionic lipid mixtures was also investigated. Our study suggest monovalent ion size to be a crucial determinant of interaction with lipid head groups, and hence domain formation in lipid mixtures. This study reinforces the role of dipole interactions in protein folding, lipid membrane properties, membrane induced peptide folding and lipid domain formation. Therefore, the models developed in this thesis can be used to explore a multitude of biomolecular processes, both at longer time-scales and larger system sizes.

Microfabricated elastomer tactile sensors for robotic fingertip systems

Tactile sensing is an important aspect of robotic systems, and enables safe, dexterous robot-environment interaction. The design and implementation of tactile sensors on robots has been a topic of research over the past 30 years, and current challenges include mechanically flexible “sensing skins”, high dynamic range (DR) sensing (i.e.: high force range and fine force resolution), multi-axis sensing, and integration between the sensors and robot. This dissertation focuses on addressing some of these challenges through a novel manufacturing process that incorporates conductive and dielectric elastomers in a reusable, multilength-scale mold, and new sensor designs for multi-axis sensing that improve force range without sacrificing resolution. A single taxel was integrated into a 1 degree of freedom robotic gripper for closed-loop slip detection. Manufacturing involved casting a composite silicone rubber, polydimethylsiloxane (PDMS) filled with conductive particles such as carbon nanotubes, into a mold to produce microscale flexible features on the order of 10s of microns. Molds were produced via microfabrication of silicon wafers, but were limited in sensing area and were costly. An improved technique was developed that produced molds of acrylic using a computer numerical controlled (CNC) milling machine. This maintained the ability to produce microscale features, and increased the sensing area while reducing costs. New sensing skins had features as small as 20 microns over an area as large as a human hand. Sensor architectures capable of sensing both shear and normal force sensing with high dynamic range were produced. Using this architecture, two sensing modalities were developed: a capacitive approach and a contact resistive approach. The capacitive approach demonstrated better dynamic range, while the contact resistive approach used simpler circuitry. Using the contact resistive approach, normal force range and resolution were 8,000 mN and 1,000 mN, respectively, and shear force range and resolution were 450 mN and 100 mN, respectively. Using the capacitive approach, normal force range and resolution were 10,000 mN and 100 mN, respectively, and shear force range and resolution were 1,500 mN and 50 mN, respectively.

Dielectric studies of Liquid Crystal Nanocomposites and Nanomaterial systems.

Liquid crystals (LCs) have revolutionized the display and communication technologies. Doping of LCs with inorganic nanoparticles such as carbon nanotubes, gold nanoparticles and ferroelectric nanoparticles have garnered the interest of research community as they aid in improving the electro-optic performance. In this thesis, we examine a hybrid nanocomposite comprising of 5CB liquid crystal and block copolymer functionalized barium titanate ferroelectric nanoparticles. This hybrid system exhibits a giant soft-memory effect. Here, spontaneous polarization of ferroelectric nanoparticles couples synergistically with the radially aligned BCP chains to create nanoscopic domains that can be rotated electromechanically and locked in space even after the removal of the applied electric field. The resulting non-volatile memory is several times larger than the non-functionalized sample and provides an insight into the role of non-covalent polymer functionalization. We also present the latest results from the dielectric and spectroscopic study of field assisted alignment of gold nanorods.