Structural arrangement of the VH and VL domains in the COBRA™ T-cell engaging single chain diabody

Background COBRA™ (COnditional Bispecific Redirected Activation) T-cell engagers are designed to target solid tumors as a single polypeptide chain prodrug that becomes activated by proteolysis in the tumor microenvironment. One COBRA molecule comprises seven Ig domains: three single-domain antibodies (sdAbs) recognizing a tumor target or human serum albumin (HSA), and CD3ε-binding VH and VL and their inactivated counterparts, VHi and VLi. Pairing of VH and VL, and VLi and VHi, into scFvs is prevented by shortened inter-domain linkers. Instead, VH and VL are expected to interact with VLi and VHi, respectively, thus making a diabody whose binding to CD3ε on the T-cells is impaired. Methods We analyzed the structure of an EGFR COBRA in solution using negative stain electron microscopy (EM) and small-angle X-ray scattering (SAXS). Results We found that this EGFR COBRA forms stable monomers with a very dynamic interdomain arrangement. At most, only five domains at a time appeared ordered, and only one VH-VL pair was found in the Fv orientation. Non-enzymatic post-translational modifications suggest that the CDR3 loops in the VL-VHi pair are exposed but are buried in the VH-VLi pair. The MMP9 cleavage rate of the prodrug when bound to recombinant EGFR or HSA is not affected, indicating positioning of the MMP9-cleavable linker away from the EGFR and HSA binding sites. Conclusion Here we propose a model for EGFR COBRA where VH and VLi form an Fv, and VL and VHi do not, possibly interacting with other Ig domains. SAXS and MMP9 cleavage analyses suggest that all COBRA molecules tested have a similar structural architecture.

De novo design of a nanopore for single-molecule detection that incorporates a β-hairpin peptide

The amino-acid sequence of a protein encodes information on its three-dimensional structure and specific functionality. De novo design has emerged as a method to manipulate the primary structure for the development of artificial proteins and peptides with desired functionality. This paper describes the de novo design of a pore-forming peptide, named SV28, that has a β-hairpin structure and assembles to form a stable nanopore in a bilayer lipid membrane. This large synthetic nanopore is an entirely artificial device for practical applications. The peptide forms multidispersely sized nanopore structures ranging from 1.7 to 6.3 nm in diameter and can detect DNAs. To form a monodispersely sized nanopore, we redesigned the SV28 by introducing a glycine-kink mutation. The resulting redesigned peptide forms a monodisperse pore with a diameter of 1.7 nm leading to detection of a single polypeptide chain. Such de novo design of a β-hairpin peptide has the potential to create artificial nanopores, which can be size adjusted to a target molecule.

Low Serum Albumin is A Significant Prognostic Factor in Burn Mortality; A Retrospective Study from January 2016 – November 2020 in Buth Jos Nigeria

Introduction: Albumin is a single polypeptide chain of 585 amino acids synthesized by the liver which accounts for 75-80% Osmotic pressure. Hypo albuminemia in burns occurs due to loss from damage tissues, reduction in hepatic blood and due to inhibitory tissue factor such as Necrotic tissue factor, interleukin 1 and 6 released at burn sites. Method: The information about the 73 patients in our study was from our unit records and the hospital records. We Used the Cobas C III system, colorimetric assay method to carry out the serum albumin and total protein investigations. Result: We had 11 burn mortality out of the 73 patients, and based on the serum albumin at the time of death, those with serum albumin of < 25g/L have burn mortality sensitivity of 90.9% and specificity of 83.3%. Discussion: Amongst all the prognostic factors we evaluated such as type, size of burns, age of patients, inhalational injury, co-morbid factors, we found that serum albumin of < 25g/L to be a more useful prognostic factor in burn mortality. Conclusion: We used serum albumin of < 25g/L in our patients to prognosticate burn mortality and to use this knowledge to optimize their serum albumin to avert death.

Differential ligand-selective control of opposing enzymatic activities within a bifunctional c-di-GMP enzyme

Cyclic dimeric guanosine monophosphate (c-di-GMP) serves as a second messenger that modulates bacterial cellular processes, including biofilm formation. While proteins containing both c-di-GMP synthesizing (GGDEF) and c-di-GMP hydrolyzing (EAL) domains are widely predicted in bacterial genomes, it is poorly understood how domains with opposing enzymatic activity are regulated within a single polypeptide. Herein, we report the characterization of a globin-coupled sensor protein (GCS) from Paenibacillus dendritiformis (DcpG) with bifunctional c-di-GMP enzymatic activity. DcpG contains a regulatory sensor globin domain linked to diguanylate cyclase (GGDEF) and phosphodiesterase (EAL) domains that are differentially regulated by gas binding to the heme; GGDEF domain activity is activated by the Fe(II)-NO state of the globin domain, while EAL domain activity is activated by the Fe(II)-O2 state. The in vitro activity of DcpG is mimicked in vivo by the biofilm formation of P. dendritiformis in response to gaseous environment, with nitric oxide conditions leading to the greatest amount of biofilm formation. The ability of DcpG to differentially control GGDEF and EAL domain activity in response to ligand binding is likely due to the unusual properties of the globin domain, including rapid ligand dissociation rates and high midpoint potentials. Using structural information from small-angle X-ray scattering and negative stain electron microscopy studies, we developed a structural model of DcpG, providing information about the regulatory mechanism. These studies provide information about full-length GCS protein architecture and insight into the mechanism by which a single regulatory domain can selectively control output domains with opposing enzymatic activities.

INDI - Integrated Nanobody Database for Immunoinformatics

Nanobodies, a subclass of antibodies found in camelids, are a versatile molecular binding scaffold composed of a single polypeptide chain. The small size of nanobodies bestows multiple therapeutic advantages (stability, tumor penetration) with the first therapeutic approval in 2018 cementing the clinical viability of this format. Structured data and sequence information of nanobodies will enable the accelerated clinical development of nanobody-based therapeutics. Though the nanobody sequence and structure data are deposited in the public domain at an accelerating pace, the heterogeneity of sources and lack of standardization hampers reliable harvesting of nanobody information. We address this issue by creating the Integrated Database of Nanobodies for Immunoinformatics (INDI, http://research.naturalantibody.com/nanobodies). INDI collates nanobodies from all the major public outlets of biological sequences: patents, GenBank, next-generation sequencing repositories, structures and scientific publications. We equip INDI with powerful nanobody-specific sequence and text search facilitating access to more than 11 million nanobody sequences. INDI should facilitate development of novel nanobody-specific computational protocols helping to deliver on the therapeutic promise of this drug format.

Structure and analysis of nanobody binding to the human ASIC1a ion channel

ASIC1a is a proton-gated sodium channel involved in modulation of pain, fear, addiction, and ischemia-induced neuronal injury. We report isolation and characterization of alpaca-derived nanobodies (Nbs) that specifically target human ASIC1a. Cryo-electron microscopy of the human ASIC1a channel at pH 7.4 in complex with one of these, Nb.C1, yielded a structure at 2.9 Å resolution. It is revealed that Nb.C1 binds to a site overlapping with that of the Texas coral snake toxin (MitTx1) and the black mamba venom Mambalgin-1; however, the Nb.C1-binding site does not overlap with that of the inhibitory tarantula toxin psalmotoxin-1 (PcTx1). Fusion of Nb.C1 with PcTx1 in a single polypeptide markedly enhances the potency of PcTx1, whereas competition of Nb.C1 and MitTx1 for binding reduces channel activation by the toxin. Thus, Nb.C1 is a molecular tool for biochemical and structural studies of hASIC1a; a potential antidote to the pain-inducing component of coral snake bite; and a candidate to potentiate PcTx1-mediated inhibition of hASIC1a in vivo for therapeutic applications.

Pathogen Moonlighting Proteins: From Ancestral Key Metabolic Enzymes to Virulence Factors

Moonlighting and multitasking proteins refer to proteins with two or more functions performed by a single polypeptide chain. An amazing example of the Gain of Function (GoF) phenomenon of these proteins is that 25% of the moonlighting functions of our Multitasking Proteins Database (MultitaskProtDB-II) are related to pathogen virulence activity. Moreover, they usually have a canonical function belonging to highly conserved ancestral key functions, and their moonlighting functions are often involved in inducing extracellular matrix (ECM) protein remodeling. There are three main questions in the context of moonlighting proteins in pathogen virulence: (A) Why are a high percentage of pathogen moonlighting proteins involved in virulence? (B) Why do most of the canonical functions of these moonlighting proteins belong to primary metabolism? Moreover, why are they common in many pathogen species? (C) How are these different protein sequences and structures able to bind the same set of host ECM protein targets, mainly plasminogen (PLG), and colonize host tissues? By means of an extensive bioinformatics analysis, we suggest answers and approaches to these questions. There are three main ideas derived from the work: first, moonlighting proteins are not good candidates for vaccines. Second, several motifs that might be important in the adhesion to the ECM were identified. Third, an overrepresentation of GO codes related with virulence in moonlighting proteins were seen.

Moonlighting protein prediction using physico-chemical and evolutional properties via machine learning methods

Background Moonlighting proteins (MPs) are a subclass of multifunctional proteins in which more than one independent or usually distinct function occurs in a single polypeptide chain. Identification of unknown cellular processes, understanding novel protein mechanisms, improving the prediction of protein functions, and gaining information about protein evolution are the main reasons to study MPs. They also play an important role in disease pathways and drug-target discovery. Since detecting MPs experimentally is quite a challenge, most of them are detected randomly. Therefore, introducing an appropriate computational approach to predict MPs seems reasonable. Results In this study, we introduced a competent model for detecting moonlighting and non-MPs through extracted features from protein sequences. We attempted to set up a well-judged scheme for detecting outlier proteins. Consequently, 37 distinct feature vectors were utilized to study each protein’s impact on detecting MPs. Furthermore, 8 different classification methods were assessed to find the best performance. To detect outliers, each one of the classifications was executed 100 times by tenfold cross-validation on feature vectors; proteins which misclassified 90 times or more were grouped. This process was applied to every single feature vector and eventually the intersection of these groups was determined as the outlier proteins. The results of tenfold cross-validation on a dataset of 351 samples (containing 215 moonlighting and 136 non-moonlighting proteins) reveal that the SVM method on all feature vectors has the highest performance among all methods in this study and other available methods. Besides, the study of outliers showed that 57 of 351 proteins in the dataset could be an appropriate candidate for the outlier. Among the outlier proteins, there were non-MPs (such as P69797) that have been misclassified in 8 different classification methods with 16 different feature vectors. Because these proteins have been obtained by computational methods, the results of this study could reduce the likelihood of hypothesizing whether these proteins are non-moonlighting at all. Conclusions MPs are difficult to be identified through experimentation. Using distinct feature vectors, our method enabled identification of novel moonlighting proteins. The study also pinpointed that a number of non-MPs are likely to be moonlighting.

Designed folding pathway of modular coiled-coil-based proteins

Natural proteins are characterised by a complex folding pathway defined uniquely for each fold. Designed coiled-coil protein origami (CCPO) cages are distinct from natural compact proteins, since their fold is prescribed by discrete long-range interactions between orthogonal pairwise-interacting coiled-coil (CC) modules within a single polypeptide chain. Here, we demonstrate that CCPO proteins fold in a stepwise sequential pathway. Molecular dynamics simulations and stopped-flow Förster resonance energy transfer (FRET) measurements reveal that CCPO folding is dominated by the effective intra-chain distance between CC modules in the primary sequence and subsequent folding intermediates, allowing identical CC modules to be employed for multiple cage edges and thus relaxing CCPO cage design requirements. The number of orthogonal modules required for constructing a CCPO tetrahedron can be reduced from six to as little as three different CC modules. The stepwise modular nature of the folding pathway offers insights into the folding of tandem repeat proteins and can be exploited for the design of modular protein structures based on a given set of orthogonal modules.