Fabio Parmeggiani

Bio: Fabio Parmeggiani is an academic researcher from Polytechnic University of Milan. The author has contributed to research in topics: Biocatalysis & Protein structure. The author has an hindex of 29, co-authored 110 publications receiving 2679 citations. Previous affiliations of Fabio Parmeggiani include University of Washington & Fred Hutchinson Cancer Research Center.

Exploring the repeat protein universe through computational protein design.

Abstract: A central question in protein evolution is the extent to which naturally occurring proteins sample the space of folded structures accessible to the polypeptide chain. Repeat proteins composed of multiple tandem copies of a modular structure unit are widespread in nature and have critical roles in molecular recognition, signalling, and other essential biological processes. Naturally occurring repeat proteins have been re-engineered for molecular recognition and modular scaffolding applications. Here we use computational protein design to investigate the space of folded structures that can be generated by tandem repeating a simple helix-loop-helix-loop structural motif. Eighty-three designs with sequences unrelated to known repeat proteins were experimentally characterized. Of these, 53 are monomeric and stable at 95 °C, and 43 have solution X-ray scattering spectra consistent with the design models. Crystal structures of 15 designs spanning a broad range of curvatures are in close agreement with the design models with root mean square deviations ranging from 0.7 to 2.5 A. Our results show that existing repeat proteins occupy only a small fraction of the possible repeat protein sequence and structure space and that it is possible to design novel repeat proteins with precisely specified geometries, opening up a wide array of new possibilities for biomolecular engineering.

De novo design of a four-fold symmetric TIM-barrel protein with atomic-level accuracy

Abstract: Despite efforts for over 25 years, de novo protein design has not succeeded in achieving the TIM-barrel fold. Here we describe the computational design of four-fold symmetrical (β/α)8 barrels guided by geometrical and chemical principles. Experimental characterization of 33 designs revealed the importance of side chain-backbone hydrogen bonds for defining the strand register between repeat units. The X-ray crystal structure of a designed thermostable 184-residue protein is nearly identical to that of the designed TIM-barrel model. PSI-BLAST searches do not identify sequence similarities to known TIM-barrel proteins, and sensitive profile-profile searches indicate that the design sequence is distant from other naturally occurring TIM-barrel superfamilies, suggesting that Nature has sampled only a subset of the sequence space available to the TIM-barrel fold. The ability to design TIM barrels de novo opens new possibilities for custom-made enzymes.

Computational design of self-assembling cyclic protein homo-oligomers.

Abstract: Self-assembling cyclic protein homo-oligomers play important roles in biology, and the ability to generate custom homo-oligomeric structures could enable new approaches to probe biological function. Here we report a general approach to design cyclic homo-oligomers that employs a new residue-pair-transform method to assess the designability of a protein-protein interface. This method is sufficiently rapid to enable the systematic enumeration of cyclically docked arrangements of a monomer followed by sequence design of the newly formed interfaces. We use this method to design interfaces onto idealized repeat proteins that direct their assembly into complexes that possess cyclic symmetry. Of 96 designs that were characterized experimentally, 21 were found to form stable monodisperse homo-oligomers in solution, and 15 (four homodimers, six homotrimers, six homotetramers and one homopentamer) had solution small-angle X-ray scattering data consistent with the design models. X-ray crystal structures were obtained for five of the designs and each is very close to their corresponding computational model.

Synthetic and Therapeutic Applications of Ammonia-lyases and Aminomutases

Abstract: Ammonia-lyases and aminomutases are mechanistically and structurally diverse enzymes which catalyze the deamination and/or isomerization of amino acids in nature by cleaving or shifting a C–N bond. Of the many protein families in which these enzyme activities are found, only a subset have been employed in the synthesis of optically pure fine chemicals or in medical applications. This review covers the natural diversity of these enzymes, highlighting particular enzyme classes that are used within industrial and medical biotechnology. These highlights detail the discovery and mechanistic investigations of these commercially relevant enzymes, along with comparisons of their various applications as stand-alone catalysts, components of artificial biosynthetic pathways and biocatalytic or chemoenzymatic cascades, and therapeutic tools for the potential treatment of various pathologies.

Iterative model-building, structure refinement, and density modification with the PHENIX AutoBuild Wizard

Abstract: Iterative model-building, structure refinement, and density modification with the PHENIX AutoBuild Wizard Thomas C. Terwilliger a* , Ralf W. Grosse-Kunstleve b , Pavel V. Afonine b , Nigel W. Moriarty b , Peter Zwart b , Li-Wei Hung a , Randy J. Read c , Paul D. Adams b* a b Los Alamos National Laboratory, Mailstop M888, Los Alamos, NM 87545, USA Lawrence Berkeley National Laboratory, One Cyclotron Road, Bldg 64R0121, Berkeley, CA 94720, USA. c Department of Haematology, University of Cambridge, Cambridge CB2 0XY, UK. * Email: terwill@lanl.gov or PDAdams@lbl.gov Running title: The PHENIX AutoBuild Wizard Abstract The PHENIX AutoBuild Wizard is a highly automated tool for iterative model- building, structure refinement and density modification using RESOLVE or TEXTAL model- building, RESOLVE statistical density modification, and phenix.refine structure refinement. Recent advances in the AutoBuild Wizard and phenix.refine include automated detection and application of NCS from models as they are built, extensive model completion algorithms, and automated solvent molecule picking. Model completion algorithms in the AutoBuild Wizard include loop-building, crossovers between chains in different models of a structure, and side-chain optimization. The AutoBuild Wizard has been applied to a set of 48 structures at resolutions ranging from 1.1 A to 3.2 A, resulting in a mean R-factor of 0.24 and a mean free R factor of 0.29. The R-factor of the final model is dependent on the quality of the starting electron density, and relatively independent of resolution. Keywords: Model building; model completion; macromolecular models; Protein Data Bank; structure refinement; PHENIX Introduction Iterative model-building and refinement is a powerful approach to obtaining a complete and accurate macromolecular model. The approach consists of cycles of building an atomic model based on an electron density map for a macromolecular structure, refining the structure, using the refined structure as a basis for improving the map, and building a new model. This type of approach has been carried out in a semi-automated fashion for many years, with manual model-building iterating with automated refinement (Jensen, 1997). More recently, with the development first of ARP/wARP (Perrakis et al., 1999), and later other procedures including RESOLVE iterative model-building and refinement (Terwilliger,

The coming of age of de novo protein design

Abstract: 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.

Biocatalysis: Enzymatic Synthesis for Industrial Applications

Abstract: Biocatalysis has found numerous applications in various fields as an alternative to chemical catalysis. The use of enzymes in organic synthesis, especially to make chiral compounds for pharmaceuticals as well for the flavors and fragrance industry, are the most prominent examples. In addition, biocatalysts are used on a large scale to make specialty and even bulk chemicals. This review intends to give illustrative examples in this field with a special focus on scalable chemical production using enzymes. It also discusses the opportunities and limitations of enzymatic syntheses using distinct examples and provides an outlook on emerging enzyme classes.

Interactions and the initiation of the inflammatory response

Abstract: The orderly migration of various white blood cell types to inflammatory sites is a highly regulated process that involves a diversity of adhesion and signaling molecules. This cellular influx is initiated by relatively low affinity interactions that allow for leukocytes to roll along the vascular surfa ce. This rolling phe­ nomenon is mediated by adhesive interactions between lectin containing ad­ hesion molecules, termed selectins, on both the vascular endothelium and leukocytes, and car bohydrate ligands immobilized on mucin-like scaffolds. This adhesion allows for a rapid recognition of various cell types under the conditions of vascular flow, with the result that inflammatory cells are spe­