Computational Structural Analysis Research Articles

Structural Features of Cytochrome b5-Cytochrome b5 Reductase Complex Formation and Implications for the Intramolecular Dynamics of Cytochrome b5 Reductase.

Membrane cytochrome b5 reductase is a pleiotropic oxidoreductase that uses primarily soluble reduced nicotinamide adenine dinucleotide (NADH) as an electron donor to reduce multiple biological acceptors localized in cellular membranes. Some of the biological acceptors of the reductase and coupled redox proteins might eventually transfer electrons to oxygen to form reactive oxygen species. Additionally, an inefficient electron transfer to redox acceptors can lead to electron uncoupling and superoxide anion formation by the reductase. Many efforts have been made to characterize the involved catalytic domains in the electron transfer from the reduced flavoprotein to its electron acceptors, such as cytochrome b5, through a detailed description of the flavin and NADH-binding sites. This information might help to understand better the processes and modifications involved in reactive oxygen formation by the cytochrome b5 reductase. Nevertheless, more than half a century since this enzyme was first purified, the one-electron transfer process toward potential electron acceptors of the reductase is still only partially understood. New advances in computational analysis of protein structures allow predicting the intramolecular protein dynamics, identifying potential functional sites, or evaluating the effects of microenvironment changes in protein structure and dynamics. We applied this approach to characterize further the roles of amino acid domains within cytochrome b5 reductase structure, part of the catalytic domain, and several sensors and structural domains involved in the interactions with cytochrome b5 and other electron acceptors. The computational analysis results allowed us to rationalize some of the available spectroscopic data regarding ligand-induced conformational changes leading to an increase in the flavin adenine dinucleotide (FAD) solvent-exposed surface, which has been previously correlated with the formation of complexes with electron acceptors.

Calibrated uncertainty for molecular property prediction using ensembles of message passing neural networks

Data-driven methods based on machine learning have the potential to accelerate computational analysis of atomic structures. In this context, reliable uncertainty estimates are important for assessing confidence in predictions and enabling decision making. However, machine learning models can produce badly calibrated uncertainty estimates and it is therefore crucial to detect and handle uncertainty carefully. In this work we extend a message passing neural network designed specifically for predicting properties of molecules and materials with a calibrated probabilistic predictive distribution. The method presented in this paper differs from previous work by considering both aleatoric and epistemic uncertainty in a unified framework, and by recalibrating the predictive distribution on unseen data. Through computer experiments, we show that our approach results in accurate models for predicting molecular formation energies with well calibrated uncertainty in and out of the training data distribution on two public molecular benchmark datasets, QM9 and PC9. The proposed method provides a general framework for training and evaluating neural network ensemble models that are able to produce accurate predictions of properties of molecules with well calibrated uncertainty estimates.

A Conservative Replacement in the Transmembrane Domain of SARS-CoV-2 ORF7a as a Putative Risk Factor in COVID-19.

Simple SummaryThe pathogenicity and transmissibility of the COVID-19 pandemic causative agent, the SARS-CoV-2 virus, is related to the functions of the proteins synthesized intracellularly, as guided by viral RNA. It is vitally important to accurately pinpoint novel variants of concern of the SARS-CoV-2 virus, in order to understand the molecular features of novel mutations and manage the on-going battle against the COVID-19 pandemic. We focused on A105V mutation in the ORF7a accessory protein. Sequencing and clinical data showed that this mutation is associated with increased severity and lethality in a group of Romanian patients, despite a lower viral copy number and a lower number of associated comorbidities. This effect is primarily due to increased protein stability through allosteric effects as shown by molecular dynamics analyses. This behavior manifests especially among residues 39–56, and the ones adjacent to 26–30 loop, placed in direct contact with potential interaction partners. Together, the results provide novel insights into the role of ORF7a in the pathogenicity of SARS-CoV-2.The ongoing COVID-19 pandemic follows an unpredictable evolution, driven by both host-related factors such as mobility, vaccination status, and comorbidities and by pathogen-related ones. The pathogenicity of its causative agent, SARS-CoV-2 virus, relates to the functions of the proteins synthesized intracellularly, as guided by viral RNA. These functions are constantly altered through mutations resulting in increased virulence, infectivity, and antibody-evasion abilities. Well-characterized mutations in the spike protein, such as D614G, N439K, Δ69–70, E484K, or N501Y, are currently defining specific variants; however, some less studied mutations outside the spike region, such as p. 3691 in NSP6, p. 9659 in ORF-10, 8782C > T in ORF-1ab, or 28144T > C in ORF-8, have been proposed for altering SARS-CoV-2 virulence and pathogenicity. Therefore, in this study, we focused on A105V mutation of SARS-CoV-2 ORF7a accessory protein, which has been associated with severe COVID-19 clinical manifestation. Molecular dynamics and computational structural analyses revealed that this mutation differentially alters ORF7a dynamics, suggesting a gain-of-function role that may explain its role in the severe form of COVID-19 disease.

Creation of a recombinant Komagataella phaffii strain, a producer of proteinase K from Tritirachium album.

The objects of the study were recombinant clones of Komagataella phaffii K51 carrying the heterologous proteinase K (PK-w) gene from Tritirachium album integrated into their genome as well as samples of recombinant proteinase K isolated from these clones. The aims of this work were i) to determine whether it is possible to create recombinant K. phaffii K51 clones overexpressing functionally active proteinase K from T. album and ii) to analyze the enzymatic activity of the resulting recombinant enzyme. The following methods were used: computational analysis of primary structure of the proteinase K gene, molecular biological methods (PCR, electrophoresis of DNA in an agarose gel, electrophoresis of proteins in an SDS polyacrylamide gel under denaturing conditions, spectrophotometry, and quantitative assays of protease activity), and genetic engineering techniques (cloning and selection of genes in bacterial cells Escherichia coli TOP10 and in the methylotrophic yeast K. phaffii K51). The gene encoding natural proteinase K (PK-w) was designed and optimized for expression in K. phaffii K51. The proteinase K gene was synthesized and cloned within the plasmid pPICZα-A vector in E. coli TOP10 cells. The proteinase K gene was inserted into pPICZα-A in such a way that – at a subsequent stage of transfection into yeast cells – it was efficiently expressed under the control of the promoter and terminator of the AOX1 gene, and the product of the exogenous gene contained the signal peptide of the Saccharomyces cerevisiae a-factor to ensure the protein’s secretion into the culture medium. The resultant recombinant plasmid (pPICZα-A/PK-w) was transfected into K. phaffii K51 cells. A recombinant K. phaffii K51 clone was obtained that carried the synthetic proteinase K gene and ensured its effective expression and secretion into the culture medium. An approximate productivity of the yeast recombinant clones for recombinant proteinase K was 25 μg/ mL after 4 days of cultivation. The resulting recombinant protease has a high specific proteolytic activity: ~5000 U/mg.

Experimental investigation of failure mechanism of grid structure with bolted spherical joints

Under strong earthquakes, the grid structure members may frequently bear plastic strain so that the grid failure, which is characterized by ultra-low cyclic fatigue. In the present study, the ultra-low cycle fatigue test of three full-scale grid structures, which are under vertical cyclic large plastic strain load, is carried out. The hysteretic and skeleton curves, energy consumption capacity, ductility performance, bearing capacity degradation, and stiffness change are obtained. Also, the macroscopic morphology of rod fracture is analyzed. In addition, the corresponding recommendations are made based on the failure mechanism of the rod and the deformation characteristics of the joint. It was found that the ultra-low cycle fatigue damage of the lower chord is the main cause of grid failure. Also, the failure behavior of the rod in the structure is very similar to that in the member test. The coupling effect of ultra-low circumferential fatigue and local buckling causes the strain to concentrate in the middle of the rod. The computational analysis of such structures under strong earthquakes should consider the degradation of joint stiffness.

Fe-N-C Catalysts for Oxygen Reduction Reaction: A Computational Analysis of Electronic Structure and Spectroscopic Properties

In proton exchange fuel cells (PEFCs), the electrochemical reduction of oxygen (ORR) plays a key role as the complementary half-cell reaction to the oxidation of hydrogen. It requires the transport of four electrons per oxygen molecule associated with high activation barriers and slow kinetics and thus requires high amounts of catalyst. [1] State-of-the art catalysts for both reactions are based on platinum, an expensive metal.Iron and nitrogen doped carbon (Fe-N-C) catalysts show high ORR activity and are thus a very promising alternative to Pt catalysts. It is believed that in Fe-N-C catalysts, iron is atomically dispersed as pseudo-molecular active centres with four- or fivefold nitrogen coordination spheres which are embedded in a graphene matrix. However, the exact nature of the active site in terms of Fe spin and oxidation states, precise coordination environment and spatial extent of the graphene sheets are still debated, as is the influence of these factors on the ORR mechanism in Fe-N-C catalysts. [2-4]Unlike other spectroscopies, Mössbauer spectroscopy, which provides direct insights on iron spin and oxidation states, is used successfully to characterise the amorphous FeNC catalysts. Until recently, the interpretation of Mössbauer spectra was limited to comparisons with small reference complexes [2] which lack the extended π-systems of Fe-N-C catalysts. Recently, with increasing use of in situ and operando experiments on these catalysts, the interest in computational models for the interpretation of experimental Mössbauer spectra has grown. [4-6]. Using density functional theory, we show for different FeN4 environments how the electronic structure is influenced by the size and symmetry of the π-system. The influence is quantified in terms of structural parameters, relative spin state energies, spin distributions and spectroscopic properties.

Computational Fluid Dynamic Technique for Assessment of How Changing Character of Blood Flow and Different Value of Hct Influence Blood Hemodynamic in Dissected Aorta.

Using computer tomography angiography (CTA) and computational structural analysis, we present a non-invasive method of mass flow rate/velocity and wall stress analysis in type B aortic dissection. Three-dimensional (3D) computer models of the aorta were calculated using pre-operative (baseline) and post-operative CT data from 12 male patients (aged from 51 to 64 years) who were treated for acute type B dissection. A computational fluid dynamics (CFD) technique was used to quantify the displacement forces acting on the aortic wall in the areas of endografts placement. The mass flow rate and wall stress were measured and quantified using the CFD technique. The CFD model indicated the places with a lower value of blood velocity and shear rate, which corelated with higher blood viscosity and a probability of thrombus appearance. Moreover, with the increase in Hct, blood viscosity also increased, while the intensity of blood flow provoked changing viscosity values in these areas. Furthermore, the velocity gradient near the tear surface caused high wall WSS; this could lead to a decreased resistance in the aorta’s wall with further implications to a patient.

Computational design, synthesis, structural analysis and biological evaluation some novel N-methylated indole incorporating pyrazole moieties

A new method for N -methylation of indoles using methylating reagent dimethyl sulphate has been developed. Structures of the newly synthesized compounds have been established by elemental analysis and spectral data and evaluated as biological activity. The synthesized indoyl pyrazole compounds have been evaluated for their antioxidant and anticancer activities. The obtained results reveal clearly that compounds IVb and e display the highest antioxidant activity and compounds c and f exhibit better radical scavenging ability; whereas the same compound IVb exhibits excellent activity (IC 50 24µM) against HeLa (human cervical carcinoma) cancer cell lines. Theoretical calculation of the title compounds have been carried out using density functional theory method. The geometrical optimization of the prepared target compounds has been theoretically analyzed. Based on the geometries, the HOMO and LUMO, Mulliken population analysis and reactivity indices have been calculated.

β-Caryophyllene Induces Apoptosis and Inhibits Angiogenesis in Colorectal Cancer Models.

Beta-Caryophyllene (BCP), a naturally occurring sesquiterpene abundantly found in cloves, hops, and cannabis, is the active candidate of a relatively new group of vascular-inhibiting compounds that aim to block existing tumor blood vessels. Previously, we have reported the anti-cancer properties of BCP by utilizing a series of in-vitro anti-tumor-related assays using human colorectal carcinoma cells. The present study aimed to investigate the effects of BCP on in-vitro, ex-vivo, and in-vivo models of anti-angiogenic assays and evaluate its anti-cancer activity in xenograft tumor (both ectopic and orthotopic) mice models of human colorectal cancer. Computational structural analysis and an apoptosis antibody array were also performed to understand the molecular players underlying this effect. BCP exhibited strong anti-angiogenic activity by blocking the migration of endothelial cells, tube-like network formation, suppression of vascular endothelial growth factor (VEGF) secretion from human umbilical vein endothelial cells and sprouting of rat aorta microvessels. BCP has a probable binding at Site#0 on the surface of VEGFR2. Moreover, BCP significantly deformed the vascularization architecture compared to the negative control in a chick embryo chorioallantoic membrane assay. BCP showed a remarkable reduction in tumor size and fluorescence molecular tomography signal intensity in all the mice treated with BCP, in a dose-dependent relationship, in ectopic and orthotopic tumor xenograft models, respectively. The histological analysis of the tumor from BCP-treated mice revealed a clear reduction of the density of vascularization. In addition, BCP induced apoptosis through downregulation of HSP60, HTRA, survivin, and XIAP, along with the upregulation of p21 expressions. These results suggest that BCP acts at multiple stages of angiogenesis and could be used as a promising therapeutic candidate to halt the growth of colorectal tumor cells.

Influence of copper pillar bump structure on flip chip packaging during reflow soldering: a numerical approach

Purpose The purpose of this paper is to present the experimental and simulation studies on the influence of copper pillar bump structure on flip chip packaging during reflow soldering. Design/methodology/approach In this work, solidification/melting modelling and volume of fluid modelling were used. Reflow soldering process of Cu pillar type FC was modelled using computational fluid dynamic software (FLUENT). The experimental results have been validated with the simulation results to prove the accuracy of the numerical method. Findings The findings of this study reveal that solder volume is the most important element influencing reflow soldering. The solder cap volume reduces as the Cu pillar bump diameter lowers, making the reflow process more difficult to establish a good solder union, as less solder is allowed to flow. Last but not least, the solder cap height for the reflow process must be optimized to enable proper solder joint formation. Practical implications This study provides a basis and insights into the impact of copper pillar bump structure on flip chip packaging during reflow soldering that will be advancing the future design of 3D stack package. This study also provides a superior visualization and knowledge of the melting and solidification phenomenon during the reflow soldering process. Originality/value The computational fluid dynamics analysis of copper pillar bump structure on flip chip packaging during reflow soldering is scant. To the authors’ best knowledge, no research has been concentrated on copper pillar bump size configurations in a thorough manner. Without the in-depth study, copper pillar bump size might have the impact of copper pillar bump structure on flip chip packaging during reflow soldering. Five design of parameter of flip chip IC package model was proposed for the investigation of copper pillar bump structure on flip chip packaging during reflow soldering.

The never-ending quest to understand the shapes and motions of molecules

Why is it so important to know the shape of molecules? How can virtual reality and advances in scientific visualization help? These are recurrent questions about the importance of understanding molecular shapes and molecular motions. In this brief feature article some background is provided to better understand the central role played by visual and computational analysis of molecular structures. The role of hardware devices and software tools to assist scientists in this quest is pointed out, along with challenges to share visual experiences more broadly. These topics touch upon many current questions in research. Examples related to biological membranes, molecular medicine, -omics data and SARS-Cov-2 structural data are provided to illustrate convincing use cases.

Epistasis shapes the fitness landscape of an allosteric specificity switch

Epistasis is a major determinant in the emergence of novel protein function. In allosteric proteins, direct interactions between inducer-binding mutations propagate through the allosteric network, manifesting as epistasis at the level of biological function. Elucidating this relationship between local interactions and their global effects is essential to understanding evolution of allosteric proteins. We integrate computational design, structural and biophysical analysis to characterize the emergence of novel inducer specificity in an allosteric transcription factor. Adaptive landscapes of different inducers of the designed mutant show that a few strong epistatic interactions constrain the number of viable sequence pathways, revealing ridges in the fitness landscape leading to new specificity. The structure of the designed mutant shows that a striking change in inducer orientation still retains allosteric function. Comparing biophysical and functional properties suggests a nonlinear relationship between inducer binding affinity and allostery. Our results highlight the functional and evolutionary complexity of allosteric proteins.

Structural and energetic profiling of SARS-CoV-2 receptor binding domain antibody recognition and the impact of circulating variants.

The SARS-CoV-2 pandemic highlights the need for a detailed molecular understanding of protective antibody responses. This is underscored by the emergence and spread of SARS-CoV-2 variants, including Alpha (B.1.1.7) and Delta (B.1.617.2), some of which appear to be less effectively targeted by current monoclonal antibodies and vaccines. Here we report a high resolution and comprehensive map of antibody recognition of the SARS-CoV-2 spike receptor binding domain (RBD), which is the target of most neutralizing antibodies, using computational structural analysis. With a dataset of nonredundant experimentally determined antibody-RBD structures, we classified antibodies by RBD residue binding determinants using unsupervised clustering. We also identified the energetic and conservation features of epitope residues and assessed the capacity of viral variant mutations to disrupt antibody recognition, revealing sets of antibodies predicted to effectively target recently described viral variants. This detailed structure-based reference of antibody RBD recognition signatures can inform therapeutic and vaccine design strategies.

Computational investigation, comparative approaches, molecular structural, vibrational spectral, non-covalent interaction (NCI), and electron excitations analysis of benzodiazepine derivatives.

The present work explores the structural parameters and vibrational frequencies as well as molecular interactions of benzodiazepine derivatives, such as clothiapine (CT), clozapine (CZ), and loxapine (LX). Employing fitting experimental data to theoretical results is used to assess the structural parameters of heading composites. The main assignment is passed out according to the overall distribution of energy of the vibrational modes. From the hyper-conjugative interaction, the permanency of the structure had been predicted through natural bond orbital analysis; it is also used to identify the bonding and antibonding regions of the molecules. Moreover, electrostatic potential (ESP), density of states (DOS), and charge transfer occurring of the molecule among HOMO as well as LUMO energy were calculated and presented; utilizing electron localized field (ELF), localized orbital locator (LOL), and reduced density gradient (RDG), the chemical interactive regions are found. Additionally, mean polarizability (αtot), the first-order hyperpolarizability (βtot), and softness and hardness of the entitled compounds were also performed. The interaction between protein-ligand was also predicted by docking studies.

Structural and biochemical characterization of the novel serpin Iripin-5 from Ixodes ricinus.

Iripin-5 is the main Ixodes ricinus salivary serpin, which acts as a modulator of host defence mechanisms by impairing neutrophil migration, suppressing nitric oxide production by macrophages and altering complement functions. Iripin-5 influences host immunity and shows high expression in the salivary glands. Here, the crystal structure of Iripin-5 in the most thermodynamically stable state of serpins is described. In the reactive-centre loop, the main substrate-recognition site of Iripin-5 is likely to be represented by Arg342, which implies the targeting of trypsin-like proteases. Furthermore, a computational structural analysis of selected Iripin-5-protease complexes together with interface analysis revealed the most probable residues of Iripin-5 involved in complex formation.

Solvophobicity-directed assembly of microporous molecular crystals

Dense packing is a universal tendency of organic molecules in the solid state. Typical porous crystals utilize reticular strong intermolecular bonding networks to overcome this principle. Here, we report a solvophobicity-based methodology for assembling discrete molecules into a porous form and succeed in synthesizing isostructural porous polymorphs of an amphiphilic aromatic molecule Py6Mes. A computational analysis of the crystal structure reveals the major contribution of dispersion interaction as the driving force for assembling Py6Mes into a columnar stacking while the columns are sterically salient and form nanopores between them. The porous packing is facilitated particularly in solvents with weak dispersion interaction due to the solvophobic effect. Conversely, solvents with strong dispersion interaction intercalate between Py6Mes due to the solvophilic effect and provide non-porous inclusion crystals. The solvophobicity-directed polymorphism is further corroborated by the polymorphs of Py6Mes-analogues, m-Py6Mes and Ph6Mes.

One-way fluid-material interaction study on a plunging UAV wing

This research is the one-way interaction study of fluid loading on a plunging NACA-2412 modeled UAV wing. Fluid and Structures are two separate domains combined to study both, and their effects on the Aeroelastic structure. This study consists of experimental and computational analysis of the wing structure and the results were compared for effectiveness. The modeled wing was mounted on a cantilever structural setup by restricted to a single degree of freedom. The experimentation was comprised of the static aeroelastic responses of the wings under the aerodynamic loading produced in the wind tunnel for various Reynolds numbers and different angles of attack (α). After the deflection calculations, the model analysis was done using the ANSYS Workbench solid structural analysis and the results were compared with experimental values. The results of the Fluid-Structure Interaction (FSI) study of the wing were concluded for all angles of attack for different Reynolds numbers and aerodynamic loading. The rate of change of deflection due to the fluid loading at every α = 100 angles of attack was found to be 30% at the lowest Reynold’s numbers and a hike up to 60% for higher values.

Strengthening Semaglutide-GLP-1R Binding Affinity via a Val27-Arg28 Exchange in the Peptide Backbone of Semaglutide: A Computational Structural Approach

Semaglutide is a glucagon-like peptide 1 analog used for the treatment of patients with type 2 diabetes mellitus. With 94% sequence similarity to human GLP-1, semaglutide is a glucagon-like peptide-1 receptor (GLP-1R) agonist, which binds directly to GLP-1R, causing various beneficial downstream effects that reduce blood glucose. Incorporating currently (June 21, 2021) available experimental structural data in PDB of semaglutide and GLP-1R, and with a set of computational structural and biophysical analysis, this short paper for the first time puts forward an experimentally testable hypothesis: semaglutide is able to bind tighter to GLP-1R via a simple Val27-Arg28 exchange in its peptide backbone.

Adaptation-Driven Evolution of Sirtuin 1 (SIRT1), a Key Regulator of Metabolism and Aging, in Marmot Species

The sirtuin protein family plays a role in the lifespan of various species and is involved in numerous key metabolic processes. To understand the evolutionary role of sirtuins in marmots, a long-living rodent species group with remarkable metabolic shutdown during hibernation, we conducted a phylogeny-based substitution rate analysis of coding genes based on genetic information of seven marmot species. We show that sirtuin 1 (SIRT1) has evolved under positive selection in the marmot lineage. We pinpoint three amino acid changes in four different marmot species that underlie the signal of positive selection and that may favor increased longevity in marmots. Based on a computational structural analysis we can show that all three substitutions affect the secondary structure of the same region in human SIRT1. We propose that the identified region is close to the catalytic domain and that the potential structural changes may impact the catalytic activity of the enzyme and therefore might be playing a functional role in marmot's extended lifespan and metabolic shutdown.

HMBD004, a Novel Anti-CD47xCD33 Bispecific Antibody Displays Potent Anti-Tumor Effects in Pre-Clinical Models of AML

CD47 is the “don't-eat-me” signal and is ubiquitously expressed on normal cells where binding to SIRPalpha on macrophages inhibits phagocytosis. CD47 is commonly over-expressed in tumors where it correlates with immune evasion and poor prognosis. Blocking CD47-SIRPalpha interaction restores macrophage phagocytosis of tumor cells and anti-CD47 mAbs have shown anti-tumor efficacy in mouse models of solid tumors and hematological malignancies. Nevertheless, the widespread expression of CD47 decreases the bioavailability of anti-CD47 mAbs at the tumor due to antigen sink effects, and also risks off-target toxicities, most significantly from cross-linking of erythrocytes that show high expression of CD47. Therefore, increasing the specificity for binding CD47, and inhibiting the interaction with SIRPalpha, to tumor cells alone should increase the efficacy and safety of anti-CD47 therapy.CD33 is expressed on myeloid cells, but is highly over-expressed in 90% of AML patients, where it marks leukemic blast cells. The safety of CD33 as an antibody target for directing effector molecules to tumor cells has been convincingly demonstrated by the efficacy of gemtuzumab ozogamicin (Mylotarg), an antibody-drug conjugate (ADC) that binds CD33 with high affinity, in the treatment of relapsed AML. However, ADCs are notable for their significant risk of toxicities, and gemtuzumab ozogmicin was withdrawn for this reason in 2010. Still, other companies continue development on next generation anti-CD33 ADCs, e.g. vadastuximab talirine.Hummingbird Bioscience has used its proprietary Rational Antibody Development Platform for the design and development of novel therapeutic antibodies against CD47. Computational sequence and structural analyses predicted a highly specific surface epitope, with strong antigenicity and good safety profile, where antibody binding would inhibit binding to SIRPalpha. Subsequently, an in-house mouse immunization and screening strategy efficiently yielded a monoclonal antibody (mAb, 11a1) that bound with low nM (KD 5 nM) affinity and high specificity to the desired epitope on human CD47. In vitro, 11a1 demonstrated 100% inhibition of SIRPalpha binding at 1 nM, and potently induced phagocytosis of Raji cells by isolated macrophages.11a1 was subsequently humanized by CDR grafting and back-mutation, and the resulting humanized mAb maintained high affinity binding to CD47. Hummingbird Bioscience then constructed a bispecific anti-CD47xCD33 antibody (bsAb), based on a standard 1+1 IgG format, with a humanized anti-CD47 variable domain as an effector arm and the gemtuzumab variable domain as an anti-CD33 specificity arm. This bsAb (HMBD004) maintained the potent inhibition of SIRPalpha binding and induction of phagocytosis but, unlike many CD47 mAbs, caused negligible hemagglutination (i.e. cross-linking) of erythrocytes in vitro . Furthermore, HMBD004 showed preferential sorting of CD47+ CD33+ cells during FACS of mixed populations of CD47+ cells. Finally, in vivo CDX mouse models of AML were established by engrafting NCr nude mice with the CD47+ CD33+ AML cell line, HL-60, via subcutaneous implantation. Treatment of these mice with HMBD004 showed a significant decrease in tumor burden and increased PFS.Together, these data highlight the benefit of using CD33 binding to enhance the specificity, efficacy and safety of anti-CD47 antibody therapy in AML. Hummingbird Bioscience is currently advancing HMBD004 towards the clinic in 2018. DisclosuresNo relevant conflicts of interest to declare.