Publications by authors named "Per Greisen"

Endocytosis and lysosomal trafficking of cell surface receptors can be triggered by endogenous ligands. Therapeutic approaches such as lysosome-targeting chimaeras (LYTACs) and cytokine receptor-targeting chimeras (KineTACs) have used this to target specific proteins for degradation by fusing modified native ligands to target binding proteins. Although powerful, these approaches can be limited by competition with native ligands and requirements for chemical modification that limit genetic encodability and can complicate manufacturing, and, more generally, there may be no native ligands that stimulate endocytosis through a given receptor.

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To address the challenges of short half-life, immunogenicity, and nonspecific distribution, chemical modifications of peptide and protein-based drugs have emerged as a versatile strategy for improving their therapeutic efficacy. One such modification involves the derivatization of peptides and proteins with fatty acids, which can protract their half-life, modify their biodistribution, and potentially enable targeted delivery to specific tissues or disease sites of interest. However, the present strategies for the synthesis of such synthetically modified biologics require numerous rounds of experimental testing and often yield unstable, inactive, or heterogeneous products.

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Endocytosis and lysosomal trafficking of cell surface receptors can be triggered by interaction with endogenous ligands. Therapeutic approaches such as LYTAC and KineTAC, have taken advantage of this to target specific proteins for degradation by fusing modified native ligands to target binding proteins. While powerful, these approaches can be limited by possible competition with the endogenous ligand(s), the requirement in some cases for chemical modification that limits genetic encodability and can complicate manufacturing, and more generally, there may not be natural ligands which stimulate endocytosis through a given receptor.

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Efficient identification of epitopes is crucial for drug discovery and design as it enables the selection of optimal epitopes, expansion of lead antibody diversity, and verification of binding interface. Although high-resolution low throughput methods like x-ray crystallography can determine epitopes or protein-protein interactions accurately, they are time-consuming and can only be applied to a limited number of complexes. To overcome these limitations, we have developed a rapid computational method that incorporates N-linked glycans to mask epitopes or protein interaction surfaces, thereby providing a mapping of these regions.

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Article Synopsis
  • Proteases are important proteins that help with various essential processes in the body, like blood clotting.
  • Trypsin-like serine proteases (TLPs) have a special structure that allows them to work in different ways depending on their specific needs.
  • By studying and changing parts of TLPs systematically, scientists discovered new insights about how these proteins work, leading to better knowledge of their functions and potential uses in research and medicine.
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Substrate inhibition of enzymes can be a major obstacle to the production of valuable chemicals in engineered microorganisms. Here, we show substrate inhibition of lycopene cyclase as the main limitation in carotenoid biosynthesis in Yarrowia lipolytica. To overcome this bottleneck, we exploit two independent approaches.

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In phenylketonuria (PKU) patients, a genetic defect in the enzyme phenylalanine hydroxylase (PAH) leads to elevated systemic phenylalanine (Phe), which can result in severe neurological impairment. As a treatment for PKU, Escherichia coli Nissle (EcN) strain SYNB1618 was developed under Synlogic's Synthetic Biotic™ platform to degrade Phe from within the gastrointestinal (GI) tract. This clinical-stage engineered strain expresses the Phe-metabolizing enzyme phenylalanine ammonia lyase (PAL), catalyzing the deamination of Phe to the non-toxic product trans-cinnamate (TCA).

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Article Synopsis
  • Cytochrome P450s (P450s) are crucial for plants to synthesize a variety of metabolites, but their functional characterization is challenging due to gene redundancy.
  • Using advanced protein engineering and modeling techniques, researchers redesigned the active site of a specific P450 (CYP87D20) to convert it into a monooxygenase, improving its efficiency.
  • The study highlights the importance of optimizing both the active site and surface residues in P450 engineering, offering new methods to develop enzymes for producing valuable compounds like mogrol.
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Despite recent success in computational design of structured cyclic peptides, de novo design of cyclic peptides that bind to any protein functional site remains difficult. To address this challenge, we develop a computational "anchor extension" methodology for targeting protein interfaces by extending a peptide chain around a non-canonical amino acid residue anchor. To test our approach using a well characterized model system, we design cyclic peptides that inhibit histone deacetylases 2 and 6 (HDAC2 and HDAC6) with enhanced potency compared to the original anchor (IC values of 9.

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Hemophilia A is a bleeding disorder resulting from deficient factor VIII (FVIII), which normally functions as a cofactor to activated factor IX (FIXa) that facilitates activation of factor X (FX). To mimic this property in a bispecific antibody format, a screening was conducted to identify functional pairs of anti-FIXa and anti-FX antibodies, followed by optimization of functional and biophysical properties. The resulting bispecific antibody (Mim8) assembled efficiently with FIXa and FX on membranes, and supported activation with an apparent equilibrium dissociation constant of 16 nM.

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Functional manipulation of biosynthetic enzymes such as cytochrome P450s (or P450s) has attracted great interest in metabolic engineering of plant natural products. Cucurbitacins and mogrosides are plant triterpenoids that share the same backbone but display contrasting bioactivities. This structural and functional diversity of the two metabolites can be manipulated by engineering P450s.

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Aggregation can be a major challenge in the development of antibody-based pharmaceuticals as it can compromise the quality of the product during bioprocessing, formulation, and drug administration. To avoid aggregation, developability assessment is often run in parallel with functional optimization in the early screening phases to flag and deselect problematic molecules. As developability assessment can be demanding with regard to time and resources, there is a high focus on the development of molecule design strategies for engineering molecules with a high developability potential.

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Single-chain variable fragments (scFv) are widely used in several fields. However, they can be challenging to purify unless using expensive Protein L-based affinity adsorbents or affinity tags. In this work, a purification process for a scFv using mixed-mode (MM) chromatography was developed by design of experiments (DoE) and proteomics for host cell protein (HCP) quantification.

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Attempts to create novel ligand-binding proteins often focus on formation of a binding pocket with shape complementarity against the desired ligand (particularly for compounds that lack distinct polar moieties). Although designed proteins often exhibit binding of the desired ligand, in some cases they display unintended recognition behavior. One such designed protein, that was originally intended to bind tetrahydrocannabinol (THC), was found instead to display binding of 25-hydroxy-cholecalciferol (25-D3) and was subjected to biochemical characterization, further selections for enhanced 25-D3 binding affinity and crystallographic analyses.

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We describe the computational design of proteins that bind the potent analgesic fentanyl. Our approach employs a fast docking algorithm to find shape complementary ligand placement in protein scaffolds, followed by design of the surrounding residues to optimize binding affinity. Co-crystal structures of the highest affinity binder reveal a highly preorganized binding site, and an overall architecture and ligand placement in close agreement with the design model.

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Improving an enzyme's initially low catalytic efficiency with a new target substrate by an order of magnitude or two may require only a few rounds of mutagenesis and screening or selection. However, subsequent rounds of optimization tend to yield decreasing degrees of improvement (diminishing returns) eventually leading to an optimization plateau. We aimed to optimize the catalytic efficiency of bacterial phosphotriesterase (PTE) toward V-type nerve agents.

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Most biomolecular modeling energy functions for structure prediction, sequence design, and molecular docking have been parametrized using existing macromolecular structural data; this contrasts molecular mechanics force fields which are largely optimized using small-molecule data. In this study, we describe an integrated method that enables optimization of a biomolecular modeling energy function simultaneously against small-molecule thermodynamic data and high-resolution macromolecular structural data. We use this approach to develop a next-generation Rosetta energy function that utilizes a new anisotropic implicit solvation model, and an improved electrostatics and Lennard-Jones model, illustrating how energy functions can be considerably improved in their ability to describe large-scale energy landscapes by incorporating both small-molecule and macromolecule data.

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Naturally occurring, pharmacologically active peptides constrained with covalent crosslinks generally have shapes that have evolved to fit precisely into binding pockets on their targets. Such peptides can have excellent pharmaceutical properties, combining the stability and tissue penetration of small-molecule drugs with the specificity of much larger protein therapeutics. The ability to design constrained peptides with precisely specified tertiary structures would enable the design of shape-complementary inhibitors of arbitrary targets.

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The nearly 200,000 fatalities following exposure to organophosphorus (OP) pesticides each year and the omnipresent danger of a terroristic attack with OP nerve agents emphasize the demand for the development of effective OP antidotes. Standard treatments for intoxicated patients with a combination of atropine and an oxime are limited in their efficacy. Thus, research focuses on developing catalytic bioscavengers as an alternative approach using OP-hydrolyzing enzymes such as Brevundimonas diminuta phosphotriesterase (PTE).

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The ability to design novel activities in existing metalloenzyme active sites is a stringent test of our understanding of enzyme mechanisms, sheds light on enzyme evolution, and would have many practical applications. Here, we describe a computational method in the context of the macromolecular modeling suite Rosetta to repurpose active sites containing metal ions for reactions of choice. The required inputs for the method are a model of the transition state(s) for the reaction and a set of crystallographic structures of proteins containing metal ions.

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Phosphorus is a ubiquitous element of the cell, which is found throughout numerous key molecules related to cell structure, energy and information storage and transfer, and a diverse array of other cellular functions. In this work, we adopt an approach often used for characterizing metal binding and selectivity of metalloproteins in terms of interactions in a first shell (direct residue interactions with the metal) and a second shell (residue interactions with first shell residues) and use it to characterize binding of phosphorus compounds. Similar analyses of binding have previously been limited to individual structures that bind to phosphate groups; here, we investigate a total of 8307 structures obtained from the RCSB Protein Data Bank (PDB).

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VX and its Russian (RVX) and Chinese (CVX) analogues rapidly inactivate acetylcholinesterase and are the most toxic stockpile nerve agents. These organophosphates have a thiol leaving group with a choline-like moiety and are hydrolyzed very slowly by natural enzymes. We used an integrated computational and experimental approach to increase Brevundimonas diminuta phosphotriesterase's (PTE) detoxification rate of V-agents by 5000-fold.

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The ability to redesign enzymes to catalyze noncognate chemical transformations would have wide-ranging applications. We developed a computational method for repurposing the reactivity of metalloenzyme active site functional groups to catalyze new reactions. Using this method, we engineered a zinc-containing mouse adenosine deaminase to catalyze the hydrolysis of a model organophosphate with a catalytic efficiency (k(cat)/K(m)) of ~10(4) M(-1) s(-1) after directed evolution.

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Detailed electronic structures of Zn(II) and Cu(II) clusters from metallothioneins (MT) have been obtained using density functional theory (DFT), in order to investigate how oxidative stress-caused Cu(II) intermediates affect Zn-binding to MT and cooperatively lead to Cu(I)MT. The inferred accuracy is ∼0.02-0.

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Linear rate-equilibrium (RE) relations, also known as linear free energy relations, are widely observed in chemical reactions, including protein folding, enzymatic catalysis, and channel gating. Despite the widespread occurrence of linear RE relations, the principles underlying the linear relation between changes in activation and equilibrium energy in macromolecular reactions remain enigmatic. When examining amphiphile regulation of gramicidin channel gating in lipid bilayers, we noted that the gating process could be described by a linear RE relation with a simple geometric interpretation.

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