RGD-avidin–biotin pretargeting to αvβ3 integrin enhances the proapoptotic activity of TNFα related apoptosis inducing ligand (TRAIL)

Recombinant TNF-related apoptosis-inducing ligand (TRAIL) is considered a powerful and selective inducer of tumor cell death. We hypothesize that TRAIL’s potential as anticancer agent can be enhanced further by promoting its accumulation in tumor tissue. For this purpose, we developed TRAIL complexes that bind to angiogenic endothelial cells. We employed an avidin–biotin pretargeting approach, in which biotinylated TRAIL interacted with RGD-equipped avidin. The assembled complexes killed tumor cells (Jurkat T cells) via apoptosis induction. Furthermore, we demonstrated that the association of the RGD-avidin-TRAIL complex onto endothelial cells enhanced the tumor cell killing activity. Endothelial cells were not killed by TRAIL nor its derived complexes. Our approach can facilitate the enrichment of TRAIL onto angiogenic blood vessels, which may enhance intratumoral accumulation. Furthermore, it offers a versatile technology for the complexation of targeting ligands with therapeutic recombinant proteins and by this a novel way to enhance their specificity and activity

Building blocks for protein interaction devices

Here, we propose a framework for the design of synthetic protein networks from modular protein–protein or protein–peptide interactions and provide a starter toolkit of protein building blocks. Our proof of concept experiments outline a general work flow for part–based protein systems engineering. We streamlined the iterative BioBrick cloning protocol and assembled 25 synthetic multidomain proteins each from seven standardized DNA fragments. A systematic screen revealed two main factors controlling protein expression in Escherichia coli: obstruction of translation initiation by mRNA secondary structure or toxicity of individual domains. Eventually, 13 proteins were purified for further characterization. Starting from well-established biotechnological tools, two general–purpose interaction input and two readout devices were built and characterized in vitro. Constitutive interaction input was achieved with a pair of synthetic leucine zippers. The second interaction was drug-controlled utilizing the rapamycin-induced binding of FRB(T2098L) to FKBP12. The interaction kinetics of both devices were analyzed by surface plasmon resonance. Readout was based on Förster resonance energy transfer between fluorescent proteins and was quantified for various combinations of input and output devices. Our results demonstrate the feasibility of parts-based protein synthetic biology. Additionally, we identify future challenges and limitations of modular design along with approaches to address them

Generative Active Learning for the Search of Small-molecule Protein Binders

Despite substantial progress in machine learning for scientific discovery in recent years, truly de novo design of small molecules which exhibit a property of interest remains a significant challenge. We introduce LambdaZero, a generative active learning approach to search for synthesizable molecules. Powered by deep reinforcement learning, LambdaZero learns to search over the vast space of molecules to discover candidates with a desired property. We apply LambdaZero with molecular docking to design novel small molecules that inhibit the enzyme soluble Epoxide Hydrolase 2 (sEH), while enforcing constraints on synthesizability and drug-likeliness. LambdaZero provides an exponential speedup in terms of the number of calls to the expensive molecular docking oracle, and LambdaZero de novo designed molecules reach docking scores that would otherwise require the virtual screening of a hundred billion molecules. Importantly, LambdaZero discovers novel scaffolds of synthesizable, drug-like inhibitors for sEH. In in vitro experimental validation, a series of ligands from a generated quinazoline-based scaffold were synthesized, and the lead inhibitor N-(4,6-di(pyrrolidin-1-yl)quinazolin-2-yl)-N-methylbenzamide (UM0152893) displayed sub-micromolar enzyme inhibition of sEH

Computational Design of TNF Ligand-Based Protein Therapeutics

Members of the TNF ligand and TNF receptor family are controlling a variety of cellular processes including host defence, development, autoimmunity, inflammation, and tumor surveillance. Not surprisingly, both families are considered to be an attractive collection of therapeutic targets. Most therapeutics acting on these targets are protein-based drugs. In this review we will discuss current progress in computational design of protein-based therapeutics acting on TNF ligands or TNF receptors. In addition, we describe how this technology can also be used to design tools to study signaling in the TNF ligand/receptor family

Protein design in biological networks: from manipulating the input to modifying the output

Protein engineering has been an invaluable tool for the deciphering of protein folding and function and in the understanding of biological signaling networks. From an applied point of view it has been of paramount importance in biotechnological and biopharmaceutical products and applications. Traditionally, the protein engineering tools of choice were 'classical' rational design, or directed evolution-based methods. In recent years, a third tool has matured: computational protein design (CPD). In this review, we summarize the underlying principles of CPD and discuss its application for understanding and modifying biological systems. Three main applications of the use of protein design will be highlighted and reviewed: artificially rewiring of signal transduction networks, prediction and generation of large-scale in silico interaction networks and using protein design to manipulate gene expression

Computational Design of TNF Ligand-Based Protein Therapeutics

Members of the TNF ligand and TNF receptor family are controlling a variety of cellular processes including host defence, development, autoimmunity, inflammation, and tumor surveillance. Not surprisingly, both families are considered to be an attractive collection of therapeutic targets. Most therapeutics acting on these targets are protein-based drugs. In this review we will discuss current progress in computational design of protein-based therapeutics acting on TNF ligands or TNF receptors. In addition, we describe how this technology can also be used to design tools to study signaling in the TNF ligand/receptor family

Generation of rationally-designed nerve growth factor (NGF) variants with receptor specificity

Nerve growth factor (NGF) is the prototypic member of the neurotrophin family and binds two receptors, TrkA and the 75 kDa neurotrophin receptor (p75NTR), through which diverse and sometimes opposing effects are mediated. Using the FoldX protein design algorithm, we generated eight NGF variants with different point mutations predicted to have altered binding to TrkA or p75NTR. Of these, the I31R NGF variant exhibited specific binding to p75NTR. The generation of this NGF variant with selective affinity for p75NTR can be used to enhance understanding of neurotrophin receptor imbalance in diseases and identifies a key targetable residue for the development of small molecules to disrupt binding of NGF to TrkA with potential uses in chronic pain.This material is based upon works supported by the Science Foundation Ireland under Grant No. 09/RFP/BMT2153, Enterprise Ireland (IP 2016 0480), the Higher Education Authority [PRTLI 5] and the Beckman Fund, School of Natural Sciences, NUI Galway, Ireland.peer-reviewed2018-11-0

Generation of rationally-designed nerve growth factor (NGF) variants with receptor specificity

Nerve growth factor (NGF) is the prototypic member of the neurotrophin family and binds two receptors, TrkA and the 75 kDa neurotrophin receptor (p75NTR), through which diverse and sometimes opposing effects are mediated. Using the FoldX protein design algorithm, we generated eight NGF variants with different point mutations predicted to have altered binding to TrkA or p75NTR. Of these, the I31R NGF variant exhibited specific binding to p75NTR. The generation of this NGF variant with selective affinity for p75NTR can be used to enhance understanding of neurotrophin receptor imbalance in diseases and identifies a key targetable residue for the development of small molecules to disrupt binding of NGF to TrkA with potential uses in chronic pain.This material is based upon works supported by the Science Foundation Ireland under Grant No. 09/RFP/BMT2153, Enterprise Ireland (IP 2016 0480), the Higher Education Authority [PRTLI 5] and the Beckman Fund, School of Natural Sciences, NUI Galway, Ireland.2018-11-0