BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

“Bioinformatics” 특집을 내면서

There are 20(200) possible amino-acid sequences for a 200-residue protein, of which the natural evolutionary process has sampled only an infinitesimal subset. De novo protein design explores the full sequence space, guided by the physical principles that underlie protein folding. Computational methodology has advanced to the point that a wide range of structures can be designed from scratch with atomic-level accuracy. Almost all protein engineering so far has involved the modification of naturally occurring proteins; it should now be possible to design new functional proteins from the ground up to tackle current challenges in biomedicine and nanotechnology.

The coming of age of de novo protein design

Over the past decade, the Rosetta biomolecular modeling suite has informed diverse biological questions and engineering challenges ranging from interpretation of low-resolution structural data to design of nanomaterials, protein therapeutics, and vaccines. Central to Rosetta’s success is the energy function: a model parametrized from small-molecule and X-ray crystal structure data used to approximate the energy associated with each biomolecule conformation. This paper describes the mathematical models and physical concepts that underlie the latest Rosetta energy function, called the Rosetta Energy Function 2015 (REF15). Applying these concepts, we explain how to use Rosetta energies to identify and analyze the features of biomolecular models. Finally, we discuss the latest advances in the energy function that extend its capabilities from soluble proteins to also include membrane proteins, peptides containing noncanonical amino acids, small molecules, carbohydrates, nucleic acids, and other macromolecules.

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The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design.

Lung Wa Chung,† W. M. C. Sameera,‡ Romain Ramozzi,‡ Alister J. Page, Miho Hatanaka,‡ Galina P. Petrova, Travis V. Harris,‡,⊥ Xin Li, Zhuofeng Ke, Fengyi Liu, Hai-Bei Li, Lina Ding, and Keiji Morokuma*,‡ †Department of Chemistry, South University of Science and Technology of China, Shenzhen 518055, China ‡Fukui Institute for Fundamental Chemistry, Kyoto University, 34-4 Takano Nishihiraki-cho, Sakyo, Kyoto 606-8103, Japan Newcastle Institute for Energy and Resources, The University of Newcastle, Callaghan 2308, Australia Faculty of Chemistry and Pharmacy, University of Sofia, Bulgaria Boulevard James Bourchier 1, 1164 Sofia, Bulgaria Department of Chemistry, State University of New York at Oswego, Oswego, New York 13126, United States State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China School of Chemistry and Chemical Engineering, Sun Yat-sen University, Guangzhou 510275, China Key Laboratory of Macromolecular Science of Shaanxi Province, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi’an, Shaanxi 710119, China School of Ocean, Shandong University, Weihai 264209, China School of Pharmaceutical Sciences, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, Henan 450001, China

The ONIOM Method and Its Applications

It's challenging to measure non-repetitive events in real time in the field of instrumentation and measurement. Dispersive Fourier transformation is an emerging method that permits capture of rare events, such as optical rogue waves and rare cancer cells in blood. This Review article covers the principle of dispersive Fourier transformation and its implementation in diverse applications.

Dispersive Fourier transformation for fast continuous single-shot measurements

Interaction specificity is a required feature of biological networks and a necessary characteristic of protein or small-molecule reagents and therapeutics. The ability to alter or inhibit protein interactions selectively would advance basic and applied molecular science. Assessing or modelling interaction specificity requires treating multiple competing complexes, which presents computational and experimental challenges. Here we present a computational framework for designing protein-interaction specificity and use it to identify specific peptide partners for human basic-region leucine zipper (bZIP) transcription factors. Protein microarrays were used to characterize designed, synthetic ligands for all but one of 20 bZIP families. The bZIP proteins share strong sequence and structural similarities and thus are challenging targets to bind specifically. Nevertheless, many of the designs, including examples that bind the oncoproteins c-Jun, c-Fos and c-Maf (also called JUN, FOS and MAF, respectively), were selective for their targets over all 19 other families. Collectively, the designs exhibit a wide range of interaction profiles and demonstrate that human bZIPs have only sparsely sampled the possible interaction space accessible to them. Our computational method provides a way to systematically analyse trade-offs between stability and specificity and is suitable for use with many types of structure-scoring functions; thus, it may prove broadly useful as a tool for protein design.

/pdf/design-of-protein-interaction-specificity-gives-selective-1t0kj60430.pdf

Design of protein-interaction specificity gives selective bZIP-binding peptides.

Structural specificity in coiled-coil interactions

The design of functional membrane proteins from first principles represents a grand challenge in chemistry and structural biology. Here, we report the design of a membrane-spanning, four-helical bundle that transports first-row transition metal ions Zn(2+) and Co(2+), but not Ca(2+), across membranes. The conduction path was designed to contain two di-metal binding sites that bind with negative cooperativity. X-ray crystallography and solid-state and solution nuclear magnetic resonance indicate that the overall helical bundle is formed from two tightly interacting pairs of helices, which form individual domains that interact weakly along a more dynamic interface. Vesicle flux experiments show that as Zn(2+) ions diffuse down their concentration gradients, protons are antiported. These experiments illustrate the feasibility of designing membrane proteins with predefined structural and dynamic properties.

/pdf/de-novo-design-of-a-transmembrane-zn2-transporting-four-u4vfmkibth.pdf

De novo design of a transmembrane Zn2+-transporting four-helix bundle.

Probing Designability via a Generalized Model of Helical Bundle Geometry

There is a general need for the engineering of protein-like molecules that organize into geometrically specific superstructures on molecular surfaces, directing further functionalization to create richly textured, multilayered assemblies. Here we describe a computational approach whereby the surface properties and symmetry of a targeted surface define the sequence and superstructure of surface-organizing peptides. Computational design proceeds in a series of steps that encode both surface recognition and favorable intersubunit packing interactions. This procedure is exemplified in the design of peptides that assemble into a tubular structure surrounding single-walled carbon nanotubes (SWNTs). The geometrically defined, virus-like coating created by these peptides converts the smooth surfaces of SWNTs into highly textured assemblies with long-scale order, capable of directing the assembly of gold nanoparticles into helical arrays along the SWNT axis.

/pdf/computational-design-of-virus-like-protein-assemblies-on-ygab9mmxbi.pdf

Gevorg Grigoryan

Papers

Design of protein-interaction specificity gives selective bZIP-binding peptides.

Structural specificity in coiled-coil interactions

De novo design of a transmembrane Zn2+-transporting four-helix bundle.

Probing Designability via a Generalized Model of Helical Bundle Geometry

Computational Design of Virus-Like Protein Assemblies on Carbon Nanotube Surfaces