Scyllatoxin-based peptide design for E. coli expression and HIV gp120 binding.

Targeting the hydrophobic Phe43 pocket of HIV's envelope glycoprotein gp120 is a critical strategy for antiviral interventions due to its role in interacting with the host cell's CD4. Previous inhibitors, including small molecules and CD4 mimetic peptides based on scyllatoxin, have demonstrated significant binding and neutralization capabilities but were often chemically synthesized or contained non-canonical amino acids. Microbial expression using natural amino acids offers advantages such as cost-effectiveness, scalability, and efficient production of fusion proteins. In this study, we enhanced the previous scyllatoxin-based synthetic peptide by substituting natural amino acids and successfully expressed it in E. coli. The peptide was optimized by mutating the C-terminal amidated valine to valine and glutamine, and by reducing the disulfide bonds from three to two. Circular dichroism confirmed proper secondary structure formation, and fluorescence polarization analysis revealed specific, concentration-dependent binding to HIV gp120, supported by molecular dynamics simulations. These findings indicate the potential for scalable microbial production of effective antiviral peptides, with significant applications in pharmaceutical development for HIV treatment.

A novel syphilis Treponema pallidum lipoprotein peptide antigen diagnostic assay using red cell kodecytes in routine blood centre column agglutination testing platforms.

BACKGROUND AND OBJECTIVES: The detection of treponemal antibodies, which are used to make a diagnosis of syphilis, is important both for diagnostic purposes and as a mandatory blood donor test in most countries. We evaluated the feasibility of using Kode Technology to make syphilis peptide red cell kodecytes for use in column agglutination serologic platforms. MATERIALS AND METHODS: Candidate Kode Technology function-spacer-lipid (FSL) constructs were made for the Treponema pallidum lipoprotein (TmpA) of T. pallidum, using the peptide and FSL selection algorithms, and then used to make kodecytes. Developmental kodecytes were evaluated against a large range of syphilis antibody reactive and non-reactive samples in column agglutination platforms and compared against established methodologies. Overall, 150 reactive and 2072 non-reactive Syphicheck assay (a modified T. pallidum particle agglutination) blood donor samples were used to evaluate the agreement rate of the developed kodecyte assay. RESULTS: From three FSL-peptide candidate constructs, one was found to be the most suitable for diagnostics. Of 150 Syphicheck assay reactive samples, 146 were TmpA-kodecyte reactive (97.3% agreement), compared with 58.0% with the rapid plasmin reagin (RPR) assay for the same samples. Against the 2072 expected syphilis non-reactive samples the agreement rate for TmpA-kodecytes was 98.8%. CONCLUSION: TmpA-kodecytes are viable for use as cost-effective serologic reagent red cells for the detection of treponemal antibodies to diagnose syphilis with a high level of specificity in blood centres. This kodecyte methodology also potentially allows for introduction of the reverse-algorithm testing into low-volume laboratories, by utilizing existing transfusion laboratory infrastructure.

Repurposing Navitoclax to block SARS-CoV-2 fusion and entry by targeting heptapeptide repeat sequence 1 in S2 protein.

Along with the long pandemic of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has come the dilemma of emerging viral variants of concern (VOC), particularly Omicron and its subvariants, able to deftly escape immune surveillance and the otherwise protective effect of current vaccines and antibody drugs. We previously identified a peptide-based pan-CoV fusion inhibitor, termed as EK1, able to bind the HR1 region in viral spike (S) protein S2 subunit. This effectively blocked formation of the six-helix bundle (6-HB) fusion core and, thus, showed efficacy against all human coronaviruses (HCoVs). EK1 is now in phase 3 clinical trials. However, the peptide drug generally lacks oral availability. Therefore, we herein performed a structure-based virtual screening of the libraries of biologically active molecules and identified nine candidate compounds. One is Navitoclax, an orally active anticancer drug by inhibition of Bcl-2. Like EK1 peptide, it could bind HR1 and block 6-HB formation, efficiently inhibiting fusion and infection of all SARS-CoV-2 variants tested, as well as SARS-CoV and MERS-CoV, with IC50 values ranging from 0.5 to 3.7 µM. These findings suggest that Navitoclax is a promising repurposed drug candidate for development as a safe and orally available broad-spectrum antiviral drug to combat the current SARS-CoV-2 and its variants, as well as other HCoVs.

Antibodies against hyaluronan oligosaccharides in xenotransplantation.

Carbohydrate-specific antibodies are significant mediators of xenograft rejection. This study analyzed the carbohydrate specificity of antibodies in baboons before and after xenotransplantation of organs or injection of porcine red blood cells from hDAF transgenic pigs, using a glycan array with structurally defined glycans. Antibodies against hyaluronic acid disaccharide (HA2) showed the highest reactivity at baseline and rose after xenogeneic exposure. We also investigated in the serum of baboons that underwent xenotransplantation with either hDAF or hDAF/hMCP transgenic pig organs and Lewis rats after hamster-skin xenotransplantation the specificity of anti-HA antibodies on a glycan microarray representing HA oligosaccharides containing from two to 40 saccharides. Notably, the HA oligosaccharides ranging from 32 to 40 saccharides exhibited the highest antibody binding intensities at baseline in baboon and rat sera. After xenotransplantation, antibodies against HA38 and HA40 in baboons, and HA32, HA34, and HA36 in rats showed the highest titer increases. The changes of anti-HA IgM and IgG antibodies in rats after skin xenotransplantation was also confirmed by an ELISA specific for HA2, HA24, and HA85 antibodies. Thus, xenotransplantation is associated with increased antibodies against HA-oligosaccharides, which may represent a new target for intervention.

AI-Driven De Novo Design and Molecular Modeling for Discovery of Small-Molecule Compounds as Potential Drug Candidates Targeting SARS-CoV-2 Main Protease.

Over the past three years, significant progress has been made in the development of novel promising drug candidates against COVID-19. However, SARS-CoV-2 mutations resulting in the emergence of new viral strains that can be resistant to the drugs used currently in the clinic necessitate the development of novel potent and broad therapeutic agents targeting different vulnerable spots of the viral proteins. In this study, two deep learning generative models were developed and used in combination with molecular modeling tools for de novo design of small molecule compounds that can inhibit the catalytic activity of SARS-CoV-2 main protease (Mpro), an enzyme critically important for mediating viral replication and transcription. As a result, the seven best scoring compounds that exhibited low values of binding free energy comparable with those calculated for two potent inhibitors of Mpro, via the same computational protocol, were selected as the most probable inhibitors of the enzyme catalytic site. In light of the data obtained, the identified compounds are assumed to present promising scaffolds for the development of new potent and broad-spectrum drugs inhibiting SARS-CoV-2 Mpro, an attractive therapeutic target for anti-COVID-19 agents.

SARS-CoV-2 Peptide Bioconjugates Designed for Antibody Diagnostics.

In the near future, the increase in the number of required tests for COVID-19 antibodies is expected to be many hundreds of millions. Obviously, this will be done using a variety of analytical methods and using different antigens, including peptides. In this work, we compare three method variations for detecting specific immunoglobulins directed against peptides of approximately 15-aa of the SARS-CoV-2 spike protein. These linear peptide epitopes were selected using antigenicity algorithms, and were synthesized with an additional terminal cysteine residue for their bioconjugation. In two of the methods, constructs were prepared where the peptide (F, function) is attached to a negatively charged hydrophilic spacer (S) linked to a dioleoylphosphatidyl ethanolamine residue (L, lipid) to create a function-spacer-lipid construct (FSL). These FSLs were easily and controllably incorporated into erythrocytes for serologic testing or in a lipid bilayer deposited on a polystyrene microplate for use in an enzyme immunoassays (EIA). The third method, also an EIA, used polyacrylamide conjugated peptides (peptide-PAA) prepared by controlled condensation of the cysteine residue of the peptide with the maleimide-derived PAA polymer which were immobilized on polystyrene microplates by physisorption of the polymer. In this work, we describe the synthesis of the PAA and FSL peptide bioconjugates, design of test systems, and comparison of the bioassays results, and discuss potential reasons for higher performance of the FSL conjugates, particularly in the erythrocyte-based serologic assay.

40 years of glyco-polyacrylamide in glycobiology.

Polyacrylamide conjugates of glycans have long been widely used in many research areas of glycobiology, mainly for immobilizing glycans in solid-phase assays and as multivalent inhibitors. Pending biotin tag allows immobilizing Glyc-PAA quantitatively on any surface, and acts as a tracer for detection of carbohydrate-binding proteins. However, the scope of already realized capabilities of these probes is immeasurably richer than those listed above. This review is not so much about routine as about less common, but not less significant applications. Also, the data on the glycopolymers themselves, their molecular weight, size and polymer chain flexibility are presented, as well as the methods of synthesis, clusterisation and entropy factor in their interaction with proteins.

Synthesis of bodipy-labeled bacterial polysaccharides and their interaction with human dendritic cells.

In this report, we describe the fluorescent labeling of bacterial polysaccharides (Escherichia coli O86:B7, Escherichia coli O19ab, Pseudomonas aeruginosa O10a10b, and Shigella flexneri 2b) at the "natural" amino group of their phosphoethanolamine moiety. Two protocols for labeling are compared: 1) on a scale of a few mg of the polysaccharide, with a dialysis procedure for purification from excessive reagents; and 2) on a scale of 0.1 mg of the polysaccharide, with a simple precipitation procedure instead of dialysis. The microscale version is sufficient for comfortable cytofluorometric analysis. The resulting probes were found to specifically bind to human dendritic cells in a dose-dependent manner. The used limited set of polysaccharides did not allow us even to get close to understanding which dendritic cell-associated lectins and which cognate polysaccharide epitopes are involved in recognition, but the proposed microscale protocol allows to generate a library of fluorescent probes for further mapping of the polysaccharide specificity of the dendritic cells.

COVID-19 antibody screening with SARS-CoV-2 red cell kodecytes using routine serologic diagnostic platforms.

BACKGROUND: The Coronavirus disease 2019 (COVID-19) pandemic is having a major global impact, and the resultant response in the development of new diagnostics is unprecedented. The detection of antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a role in managing the pandemic. We evaluated the feasibility of using SARS-CoV-2 peptide Kode Technology-modified red cells (C19-kodecytes) to develop an assay compatible with existing routine serologic platforms. STUDY DESIGN AND METHODS: A panel of eight unique red cells modified using Kode Technology function-spacer-lipid constructs and bearing short SARS-CoV-2 peptides was developed (C19-kodecyte assay). Kodecytes were tested against undiluted expected antibody-negative and -positive plasma samples in manual tube and three column agglutination technology (CAT) platforms. Parallel analysis with the same peptides in solid phase by enzyme immunoassays was performed. Evaluation samples included >120 expected negative blood donor samples and >140 COVID-19 convalescent plasma samples, with independent serologic analysis from two centers. RESULTS: Specificity (negative reaction rate against expected negative samples) in three different CAT platforms against novel C19-kodecytes was >91%, which correlated with published literature. Sensitivity (positive reaction rate against expected positive convalescent, PCR-confirmed samples) ranged from 82% to 97% compared to 77% with the Abbott Architect SARS-CoV-2 IgG assay. Manual tube serology was less sensitive than CAT. Enzyme immunoassay results with some Kode Technology constructs also had high sensitivity. CONCLUSIONS: C19-kodecytes are viable for use as serologic reagent red cells for the detection of SARS-CoV-2 antibody with routine blood antibody screening equipment.

Gene ontology improves template selection in comparative protein docking.

Structural characterization of protein-protein interactions is essential for our ability to study life processes at the molecular level. Computational modeling of protein complexes (protein docking) is important as the source of their structure and as a way to understand the principles of protein interaction. Rapidly evolving comparative docking approaches utilize target/template similarity metrics, which are often based on the protein structure. Although the structural similarity, generally, yields good performance, other characteristics of the interacting proteins (eg, function, biological process, and localization) may improve the prediction quality, especially in the case of weak target/template structural similarity. For the ranking of a pool of models for each target, we tested scoring functions that quantify similarity of Gene Ontology (GO) terms assigned to target and template proteins in three ontology domains-biological process, molecular function, and cellular component (GO-score). The scoring functions were tested in docking of bound, unbound, and modeled proteins. The results indicate that the combined structural and GO-terms functions improve the scoring, especially in the twilight zone of structural similarity, typical for protein models of limited accuracy.

Blood Group O→A Transformation by Chemical Ligation of Erythrocytes.

Agglutination of red blood cells (RBCs) remains the only practical method for routine use for ABH typing in clinical practice. However, exact mechanistic details of agglutination are not yet thoroughly studied. In this research, RBCs of blood group O were converted to blood group A through two approaches: by chemical ligation of the cells' glycocalyx with synthetic blood group A tetrasaccharide, and by insertion of synthetic glycolipid carrying the same A antigen into the cells' membranes. The O→A ligated RBCs and natural A RBCs showed comparable agglutination characteristics with antibodies. As expected, RBCs with inserted glycolipid showed lower agglutination scores. This approach could help cell biologists in site-specific and cell-friendly modification of glycocalyx by other ligands.

The TB Portals: an Open-Access, Web-Based Platform for Global Drug-Resistant-Tuberculosis Data Sharing and Analysis.

The TB Portals program is an international consortium of physicians, radiologists, and microbiologists from countries with a heavy burden of drug-resistant tuberculosis working with data scientists and information technology professionals. Together, we have built the TB Portals, a repository of socioeconomic/geographic, clinical, laboratory, radiological, and genomic data from patient cases of drug-resistant tuberculosis backed by shareable, physical samples. Currently, there are 1,299 total cases from five country sites (Azerbaijan, Belarus, Moldova, Georgia, and Romania), 976 (75.1%) of which are multidrug or extensively drug resistant and 38.2%, 51.9%, and 36.3% of which contain X-ray, computed tomography (CT) scan, and genomic data, respectively. The top Mycobacterium tuberculosis lineages represented among collected samples are Beijing, T1, and H3, and single nucleotide polymorphisms (SNPs) that confer resistance to isoniazid, rifampin, ofloxacin, and moxifloxacin occur the most frequently. These data and samples have promoted drug discovery efforts and research into genomics and quantitative image analysis to improve diagnostics while also serving as a valuable resource for researchers and clinical providers. The TB Portals database and associated projects are continually growing, and we invite new partners and collaborations to our initiative. The TB Portals data and their associated analytical and statistical tools are freely available at https://tbportals.niaid.nih.gov/.

Alterations in hemagglutinin receptor-binding specificity accompany the emergence of highly pathogenic avian influenza viruses.

UNLABELLED: Highly pathogenic avian influenza viruses (HPAIVs) of hemagglutinin H5 and H7 subtypes emerge after introduction of low-pathogenic avian influenza viruses (LPAIVs) from wild birds into poultry flocks, followed by subsequent circulation and evolution. The acquisition of multiple basic amino acids at the endoproteolytical cleavage site of the hemagglutinin (HA) is a molecular indicator for high pathogenicity, at least for infections of gallinaceous poultry. Apart from the well-studied significance of the multibasic HA cleavage site, there is only limited knowledge on other alterations in the HA and neuraminidase (NA) molecules associated with changes in tropism during the emergence of HPAIVs from LPAIVs. We hypothesized that changes in tropism may require alterations of the sialyloligosaccharide specificities of HA and NA. To test this hypothesis, we compared a number of LPAIVs and HPAIVs for their HA-mediated binding and NA-mediated desialylation of a set of synthetic receptor analogs, namely, α2-3-sialylated oligosaccharides. NA substrate specificity correlated with structural groups of NAs and did not correlate with pathogenic potential of the virus. In contrast, all HPAIVs differed from LPAIVs by a higher HA receptor-binding affinity toward the trisaccharides Neu5Acα2-3Galß1-4GlcNAcß (3'SLN) and Neu5Acα2-3Galß1-3GlcNAcß (SiaLe(c)) and by the ability to discriminate between the nonfucosylated and fucosylated sialyloligosaccharides 3'SLN and Neu5Acα2-3Galß1-4(Fucα1-3)GlcNAcß (SiaLe(x)), respectively. These results suggest that alteration of the receptor-binding specificity accompanies emergence of the HPAIVs from their low-pathogenic precursors. IMPORTANCE: Here, we have found for the first time correlations of receptor-binding properties of the HA with a highly pathogenic phenotype of poultry viruses. Our study suggests that enhanced receptor-binding affinity of HPAIVs for a typical "poultry-like" receptor, 3'SLN, is provided by substitutions in the receptor-binding site of HA which appeared in HA of LPAIVs in the course of transmission of LPAIVs from wild waterfowl into poultry flocks, with subsequent adaptation in poultry. The identification of LPAIVs with receptor characteristics of HPAIVs argues that the sialic acid-binding specificity of the HA may be used as a novel phenotypic marker of HPAIVs.

Ultra-Fast Glyco-Coating of Non-Biological Surfaces.

The ability to glycosylate surfaces has medical and diagnostic applications, but there is no technology currently recognized as being able to coat any surface without the need for prior chemical modification of the surface. Recently, a family of constructs called function-spacer-lipids (FSL) has been used to glycosylate cells. Because it is known that lipid-based material can adsorb onto surfaces, we explored the potential and performance of cell-labelling FSL constructs to "glycosylate" non-biological surfaces. Using blood group A antigen as an indicator, the performance of a several variations of FSL constructs to modify a large variety of non-biological surfaces was evaluated. It was found the FSL constructs when optimised could in a few seconds glycosylate almost any non-biological surface including metals, glass, plastics, rubbers and other polymers. Although the FSL glycan coating was non-covalent, and therefore temporary, it was sufficiently robust with appropriate selection of spacer and surface that it could capture anti-glycan antibodies, immobilize cells (via antibody), and withstand incubation in serum and extensive buffer washing, making it suitable for diagnostic and research applications.

Simulated unbound structures for benchmarking of protein docking in the DOCKGROUND resource.

BACKGROUND: Proteins play an important role in biological processes in living organisms. Many protein functions are based on interaction with other proteins. The structural information is important for adequate description of these interactions. Sets of protein structures determined in both bound and unbound states are essential for benchmarking of the docking procedures. However, the number of such proteins in PDB is relatively small. A radical expansion of such sets is possible if the unbound structures are computationally simulated. RESULTS: The DOCKGROUND public resource provides data to improve our understanding of protein-protein interactions and to assist in the development of better tools for structural modeling of protein complexes, such as docking algorithms and scoring functions. A large set of simulated unbound protein structures was generated from the bound structures. The modeling protocol was based on 1 ns Langevin dynamics simulation. The simulated structures were validated on the ensemble of experimentally determined unbound and bound structures. The set is intended for large scale benchmarking of docking algorithms and scoring functions. CONCLUSIONS: A radical expansion of the unbound protein docking benchmark set was achieved by simulating the unbound structures. The simulated unbound structures were selected according to criteria from systematic comparison of experimentally determined bound and unbound structures. The set is publicly available at http://dockground.compbio.ku.edu.

Structural templates for comparative protein docking.

Structural characterization of protein-protein interactions is important for understanding life processes. Because of the inherent limitations of experimental techniques, such characterization requires computational approaches. Along with the traditional protein-protein docking (free search for a match between two proteins), comparative (template-based) modeling of protein-protein complexes has been gaining popularity. Its development puts an emphasis on full and partial structural similarity between the target protein monomers and the protein-protein complexes previously determined by experimental techniques (templates). The template-based docking relies on the quality and diversity of the template set. We present a carefully curated, nonredundant library of templates containing 4950 full structures of binary complexes and 5936 protein-protein interfaces extracted from the full structures at 12 Å distance cut-off. Redundancy in the libraries was removed by clustering the PDB structures based on structural similarity. The value of the clustering threshold was determined from the analysis of the clusters and the docking performance on a benchmark set. High structural quality of the interfaces in the template and validation sets was achieved by automated procedures and manual curation. The library is included in the Dockground resource for molecular recognition studies at http://dockground.bioinformatics.ku.edu.

Protein models docking benchmark 2.

Structural characterization of protein-protein interactions is essential for our ability to understand life processes. However, only a fraction of known proteins have experimentally determined structures. Such structures provide templates for modeling of a large part of the proteome, where individual proteins can be docked by template-free or template-based techniques. Still, the sensitivity of the docking methods to the inherent inaccuracies of protein models, as opposed to the experimentally determined high-resolution structures, remains largely untested, primarily due to the absence of appropriate benchmark set(s). Structures in such a set should have predefined inaccuracy levels and, at the same time, resemble actual protein models in terms of structural motifs/packing. The set should also be large enough to ensure statistical reliability of the benchmarking results. We present a major update of the previously developed benchmark set of protein models. For each interactor, six models were generated with the model-to-native C(α) RMSD in the 1 to 6 Å range. The models in the set were generated by a new approach, which corresponds to the actual modeling of new protein structures in the "real case scenario," as opposed to the previous set, where a significant number of structures were model-like only. In addition, the larger number of complexes (165 vs. 63 in the previous set) increases the statistical reliability of the benchmarking. We estimated the highest accuracy of the predicted complexes (according to CAPRI criteria), which can be attained using the benchmark structures. The set is available at http://dockground.bioinformatics.ku.edu.

Protein models: the Grand Challenge of protein docking.

Characterization of life processes at the molecular level requires structural details of protein-protein interactions (PPIs). The number of experimentally determined protein structures accounts only for a fraction of known proteins. This gap has to be bridged by modeling, typically using experimentally determined structures as templates to model related proteins. The fraction of experimentally determined PPI structures is even smaller than that for the individual proteins, due to a larger number of interactions than the number of individual proteins, and a greater difficulty of crystallizing protein-protein complexes. The approaches to structural modeling of PPI (docking) often have to rely on modeled structures of the interactors, especially in the case of large PPI networks. Structures of modeled proteins are typically less accurate than the ones determined by X-ray crystallography or nuclear magnetic resonance. Thus the utility of approaches to dock these structures should be assessed by thorough benchmarking, specifically designed for protein models. To be credible, such benchmarking has to be based on carefully curated sets of structures with levels of distortion typical for modeled proteins. This article presents such a suite of models built for the benchmark set of the X-ray structures from the Dockground resource (http://dockground.bioinformatics.ku.edu) by a combination of homology modeling and Nudged Elastic Band method. For each monomer, six models were generated with predefined C(α) root mean square deviation from the native structure (1, 2, …, 6 Å). The sets and the accompanying data provide a comprehensive resource for the development of docking methodology for modeled proteins.

Biantennary oligoglycines and glyco-oligoglycines self-associating in aqueous medium.

Oligoglycines designed in a star-like fashion, so-called tri- and tetraantennary molecules, were found to form highly ordered supramers in aqueous medium. The formation of these supramers occurred either spontaneously or due to the assistance of a mica surface. The driving force of the supramer formation is hydrogen bonding, the polypeptide chain conformation is related to the folding of helical polyglycine II (PG II). Tri- and tetraantennary molecules are capable of association if the antenna length reach 7 glycine (Gly) residues. Properties of similar biantennary molecules have not been investigated yet, and we compared their self-aggregating potency with similar tri- and tetraantennary analogs. Here, we synthesized oligoglycines of the general formula R-Gly n -Х-Gly n -R (X = -HN-(СН2) m -NH-, m = 2, 4, 10; n = 1-7) without pendant ligands (R = H) and with two pendant sialoligands (R = sialic acid or sialooligosaccharide). Biantennary oligoglycines formed PG II aggregates, their properties, however, differ from those of the corresponding tri- and tetraantennary oligoglycines. In particular, the tendency to aggregate starts from Gly4 motifs instead of Gly7. The antiviral activity of end-glycosylated peptides was studied, and all capable of assembling glycopeptides demonstrated an antiviral potency which was up to 50 times higher than the activity of peptide-free glycans.

Effect of ligand and shell densities on the surface structure of core-shell nanoparticles self-assembled from function-spacer-lipid constructs.

Biomolecular corona is the major obstacle to the clinical translation of nanomedicines. Since corona formation is governed by molecular interactions at the nano-bio interface, nanoparticle surface properties such as topography, charge and surface chemistry can be tuned to manipulate biomolecular corona formation. To this end, as the first step towards a deep understanding of the processes of corona formation, it is necessary to develop nanoparticles employing various biocompatible materials and characterize their surface structure and dynamics at the molecular level. In this work, we applied molecular dynamics simulation to study the surface structure of organic core-shell nanoparticles formed by the self-assembly of synthetic molecules composed of a DOPE lipid, a carboxymethylglycine spacer and biotin. Lipid moieties form the hydrophobic core, spacer motifs serve as a hydrophilic shell and biotin residues function as a targeting ligand. By mixing such function-spacer-lipid, spacer-lipid and lipid-only constructs at various molar ratios, densities of the ligand and spacer on the nanoparticle surface were modified. For convenient analysis of the structure and dynamics of all regions of the nanoparticle surface, we compiled topography maps based on atomic coordinates. It was shown that an increase in the density of the shell does not reduce exposure of the core, but increases shell average thickness. Biotin, due to its alkyl valeric acid chain and spacer flexibility, is localized primarily near the hydrophobic core and its partial presentation on the surface occurs only in nanoparticles with higher ligand densities. However, an increase in biotin density leads to its clustering. In turn, ligand clustering diminishes the stealth properties of the shell and targeting efficiency. Based on nanoparticle surface structures, we determined the optimal density of biotin. Experimental studies reported in the literature confirm these conclusions. We also suggest design tips to achieve the preferred biotin presentation. Simulation results are consistent with the synchrotron SAXS profile. We believe that such studies will contribute to a better understanding of nano-bio interactions towards the rational design of efficient drug delivery systems.