Screening Of Combinatorial Libraries Research Articles

Mapping protein selectivity landscapes using multi-target selective screening and next-generation sequencing of combinatorial libraries

Characterizing the binding selectivity landscape of interacting proteins is crucial both for elucidating the underlying mechanisms of their interaction and for developing selective inhibitors. However, current mapping methods are laborious and cannot provide a sufficiently comprehensive description of the landscape. Here, we introduce a novel and efficient strategy for comprehensively mapping the binding landscape of proteins using a combination of experimental multi-target selective library screening and in silico next-generation sequencing analysis. We map the binding landscape of a non-selective trypsin inhibitor, the amyloid protein precursor inhibitor (APPI), to each of the four human serine proteases (kallikrein-6, mesotrypsin, and anionic and cationic trypsins). We then use this map to dissect and improve the affinity and selectivity of APPI variants toward each of the four proteases. Our strategy can be used as a platform for the development of a new generation of target-selective probes and therapeutic agents based on selective protein–protein interactions.

Scaffold Ranking and Positional Scanning Identify Novel Neurite Outgrowth Promoters with Nanomolar Potency.

Central nervous system (CNS) neurons typically fail to regrow their axons after injury. Injuries or neuropathies that damage CNS axons and disrupt neuronal circuitry often result in permanent functional deficits. Axon regeneration is therefore an intensely pursued therapeutic strategy for numerous CNS disorders. Phenotypic screens utilizing primary neurons have proven successful at identifying agents that promote axon regeneration in vivo. Here, we report the screening of mixture-based combinatorial small molecule libraries in a phenotypic assay utilizing primary CNS neurons and the discovery of neurite outgrowth promoters with low nanomolar potency.

DNA-encoded chemical libraries - achievements and remaining challenges.

DNA-encoded chemical libraries (DECLs) are collections of compounds, individually coupled to DNA tags serving as amplifiable identification barcodes. Since individual compounds can be identified by the associated DNA tag, they can be stored as a mixture, allowing the synthesis and screening of combinatorial libraries of unprecedented size, facilitated by the implementation of split-and-pool synthetic procedures or other experimental methodologies. In this review, we briefly present relevant concepts and technologies, which are required for the implementation and interpretation of screening procedures with DNA-encoded chemical libraries. Moreover, we illustrate some success stories, detailing how novel ligands were discovered from encoded libraries. Finally, we critically review what can realistically be achieved with the technology at the present time, highlighting challenges and opportunities for the future.

Machine-Learning Energy Gaps of Porphyrins with Molecular Graph Representations.

Molecular functionalization of porphyrins opens countless new opportunities in tailoring their physicochemical properties for light-harvesting applications. However, the immense materials space spanned by a vast number of substituent ligands and chelating metal ions prohibits high-throughput screening of combinatorial libraries. In this work, machine-learning algorithms equipped with the domain knowledge of chemical graph theory were employed for predicting the energy gaps of >12 000 porphyrins from the Computational Materials Repository. Among a variety of graph-based molecular descriptors, the electrotopological-state index, which encodes electronic and topological structure information, captures the energy gaps of porphyrins with a prediction RMSE < 0.06 eV. Importantly, feature sensitivity analysis suggests that the carbon structural motif in methine bridges connected to the anchor group predominantly influences the energy gaps of porphyrins, consistent with the spatial distribution of their frontier molecular orbitals from quantum-chemical calculations.

Development of N-acetylneuraminic acid responsive biosensors based on the transcriptional regulator NanR.

Transcriptional biosensors have various applications in metabolic engineering, including dynamic pathway control and high-throughput screening of combinatorial strain libraries. Previously, various biosensors have been created from naturally occurring transcription factors (TFs), largely relying on native sequences without the possibility to modularly optimize their response curve. The lack of design and engineering techniques thus greatly hinders the development of custom biosensors. In view of the intended application this is detrimental. In contrast, a bottom-up approach to design tailor-made biosensors was pursued here. Novel biosensors were created that respond to N-acetylneuraminic acid (Neu5Ac), an important sugar moiety with various biological functions, by employing native and engineered promoters that interact with the TF NanR. This bottom-up approach, whereby various tuned modules, e.g., the ribosome binding site (RBS) controlling NanR translation can be combined, enabled the reliable engineering of various response curve characteristics. The latter was validated by testing these biosensors in combination with various Neu5Ac-producing pathways, which allowed to produce up to 1.4 ± 0.4 g/L extracellular Neu5Ac. In this way, the repertoire of biosensors was expanded with seven novel functional Neu5Ac-responsive biosensors.

Computational Study of Glycosaminoglycan Specificity for Growth Factor and Chemokine Family Members

Glycosaminoglycans (GAGs), linear polysaccharides with repeating disaccharide units, bind to proteins through primarily electrostatic interactions, which tend to induce considerable non‐specificity of recognition. Yet, GAG–protein interactions are known to regulate various physiological and pathological functions. To date, only one sequence the heparin pentasaccharide sequence that binds to antithrombin has been identified as a specific sequence with therapeutic promise. Are specific GAG sequences so rare despite the millions of natural occurring GAG sequences? Our hypothesis has been that GAG sequences that bind to proteins are not rare but it has been difficult to identify them due to the phenomenal heterogeneity of GAGs and the near impossibility of synthesizing all possible natural (and unnatural) sequences. For example, a natural hexasaccharide sequence belonging to the heparan sulfate family can be of 46,656 types. To overcome this, our lab has developed a computational strategy called as Combinatorial Virtual Library Screening (CVLS), which is exhibit impressive application in identifying sequences displaying a high level of specificity against chosen targets. Here, we extend the applicability of CVLS by adding molecular dynamics (MD) simulations as a powerful approach to identify specific and non‐specific GAG sequences for a particular target. Application of CVLS‐MD approach to well‐known GAG target, fibroblast growth factor 2 (FGF2) and chemokine CXCL13 led to unique understanding on the nature of GAG recognition and origin of specificity for therapeutic targeting. Libraries of 2592 tetrasaccharides (HS04) and 46,656 hexasaccharides (HS06) were screened against both protein targets. CVLS identified 14 HS04 sequences as highly promising sequences for CXCL13, whereas FGF2 was found to be better recognized by 9 HS06 sequences. The co‐complexes of these sequences were studied using MD in the presence of explicit water and analyzed to understand specificity of interaction through analysis of direct and indirect hydrogen bonding, single residue energy decomposition and binding free energy. There was a strong correlation of CVLS‐MD predictions with experimental data. Interesting, FGF2–HS06 co‐complex exhibited differences in hydrogen bonding pattern and binding free energy due to IdoA2S ring puckering (both 1C4 to 2SO), whereas CXCL13 showed preferential recognition of one HS04 binding site of the two possible on protein surface. Most importantly, the CVLS–MD approach identified HS sequences showing specific as well as plastic (non‐specific) hydrogen bonding interactions in solution. The in silico predictions corresponded very well with solution NMR chemical shift perturbation (CSP) data resulting in identification of a specific HS04 sequence that stabilizes the chemokine dimer. Overall, this combined CVLS–MD approach is likely to serve as a promising strategy for the identification of specific and non‐specific GAG sequences against various target proteins.Support or Funding InformationThis work was supported in part by grants from the NIH including HL107152, HL090586 and HL128639. We thank Lortat‐Jacob H, University of Grenoble Alpes, CNRS, CEA, IBS, 38000 Grenoble, France hugues.lortat-jacob@ibs.fr. for experimental dataThis abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Identification of Biofilm Inhibitors by Screening Combinatorial Libraries of Metal Oxide Thin Films.

With the rise in nosocomial infections worldwide, research on materials with an intrinsic ability to inhibit biofilm formation has been generating a great deal of interest. In the present work, we describe how thin film material libraries generated by pulsed laser deposition can be used for simultaneously screening several novel metal oxide mixtures that inhibit biofilm formation in a common human pathogen, Salmonella enterica serovar Typhimurium. We discovered that in a material library constructed using two metal oxides, the net effect on biofilm formation can be modeled as an addition of the activities of the individual oxides weighted to their relative composition at that particular point on the library. In contrast, for similar material libraries constructed using three metal oxides, there was a nonlinear relation between the amount of dominant metal oxide and the formation of Salmonella biofilms. This nonlinearity resulted in several useful metal oxide combinations that were not expected from the weighted average predictions. Our novel application will lead to the discovery of additional alternatives for creating antimicrobial surfaces.

Combinatorial peptide library screening for discovery of diverse α-glucosidase inhibitors using molecular dynamics simulations and binary QSAR models

Human α-glucosidase is an enzyme involved in the catalytic cleavage of the glucoside bond and involved in numerous functionalities of the organism, as well as in the insurgence of diabetes mellitus 2 and obesity. Thus, developing chemicals that inhibit this enzyme is a promising approach for the treatment of several pathologies. Small peptides such as di- and tri-peptides may be in natural organism as well as in the GI tract in high concentration, coming from the digestive process of meat, wheat and milk proteins. In this work, we reported the first tentative hierarchical structure-based virtual screening of peptides for human α-glucosidase. The goal of this work is to discover novel and diverse lead compounds that my act as inhibitors of α-glucosidase such as small peptides by performing a computer aided virtual screening and to find novel scaffolds for further development. Thus, in order to select novel candidates with original structure we performed molecular dynamics (MD) simulations among the 12 top-ranked peptides taking as comparison the MD simulations performed on crystallographic inhibitor acarbose. The compounds with the lower RMSD variability during the MD, were reserved for in vitro biological assay. The selected 4 promising structures were prepared on solid phase peptide synthesis and used for the inhibitory assay, among them compound 2 showed good inhibitory activity, which validated our method as an original strategy to discover novel peptide inhibitors. Moreover, pharmacokinetic profile predictions of these 4 peptides were also carried out with binary QSAR models using MetaCore/MetaDrug applications.

Development of Novel Antimicrobial Peptides with Improved Hemocompatibility via Combinatorial Library Screening and Rational Engineering

Development of Novel Antimicrobial Peptides with Improved Hemocompatibility via Combinatorial Library Screening and Rational Engineering

DNA-Encoded Chemical Libraries: A Selection System Based on Endowing Organic Compounds with Amplifiable Information.

The discovery of organic ligands that bind specifically to proteins is a central problem in chemistry, biology, and the biomedical sciences. The encoding of individual organic molecules with distinctive DNA tags, serving as amplifiable identification bar codes, allows the construction and screening of combinatorial libraries of unprecedented size, thus facilitating the discovery of ligands to many different protein targets. Fundamentally, one links powers of genetics and chemical synthesis. After the initial description of DNA-encoded chemical libraries in 1992, several experimental embodiments of the technology have been reduced to practice. This review provides a historical account of important milestones in the development of DNA-encoded chemical libraries, a survey of relevant ongoing research activities, and a glimpse into the future.

Fusion with the cold-active esterase facilitates autotransporter-based surface display of the 10th human fibronectin domain in Escherichia coli.

Cell surface display is a popular approach for the construction of whole-cell biocatalysts, live vaccines, and screening of combinatorial libraries. To develop a novel surface display system for the popular scaffold protein 10th human fibronectin type III domain (10Fn3) in Escherichia coli cells, we have used an α-helical linker and a C-terminal translocator domain from previously characterized autotransporter from Psychrobacter cryohalolentis K5T. The level of 10Fn3 passenger exposure at the cell surface provided by the hybrid autotransporter Fn877 and its C-terminal variants was low. To improve it, the fusion proteins containing 10Fn3 and the native autotransporter passenger Est877 or the cold-active esterase EstPc in different orientations were constructed and expressed as passenger domains. Using the whole-cell ELISA and activity assays, we have demonstrated that N-terminal position of EstPc in the passenger significantly improves the efficiency of the surface display of 10Fn3 in E. coli cells.

De novo design of covalently constrained mesosize protein scaffolds with unique tertiary structures

The folding of natural proteins typically relies on hydrophobic packing, metal binding, or disulfide bond formation in the protein core. Alternatively, a 3D structure can be defined by incorporating a multivalent cross-linking agent, and this approach has been successfully developed for the selection of bicyclic peptides from large random-sequence libraries. By contrast, there is no general method for the de novo computational design of multicross-linked proteins with predictable and well-defined folds, including ones not found in nature. Here we use Rosetta and Tertiary Motifs (TERMs) to design small proteins that fold around multivalent cross-linkers. The hydrophobic cross-linkers stabilize the fold by macrocyclic restraints, and they also form an integral part of a small apolar core. The designed CovCore proteins were prepared by chemical synthesis, and their structures were determined by solution NMR or X-ray crystallography. These mesosized proteins, lying between conventional proteins and small peptides, are easily accessible either through biosynthetic precursors or chemical synthesis. The unique tertiary structures and ease of synthesis of CovCore proteins indicate that they should provide versatile templates for developing inhibitors of protein-protein interactions.

Development of Selective Peptide Catalysts with Secondary Structural Frameworks.

Enzymes are biogenic catalysts that enable the vital activity of organisms. Enzymes promote reactions in a selective manner with a high level of substrate recognition ability. The development of such a sophisticated catalyst has been one of the goals for chemists. A synthetic peptide is the prime candidate to realize an enzyme-like catalyst. Considering that the catalytic function of enzymes derives from their molecular structures, the key for the creation of a peptide catalyst might be the introduction of a specific three-dimensional structure. Our motivation was to find a peptide catalyst with a versatile secondary structural framework and apply the peptide to a variety of selective reactions. Although helical-peptide-catalyzed asymmetric epoxidation of enones is popular, no other highly enantioselective reaction with a helical peptide has been reported. It was found that resin-supported α-helical polyleucine promoted asymmetric conjugate addition of a carbon nucleophile to enones via the formation of an iminium intermediate at the N-terminal amino group. By changing the helical chain to a repetitive Leu-Leu-Aib (Aib = α-aminoisobutyric acid) sequence and introducing a few amino acids to the N-terminus, a highly enantioselective peptide catalyst was obtained. The helical peptide catalyst was applicable for a tandem enamine/iminium-mediated reaction and asymmetric epoxidation of enones. Although the extension of the helical peptide to conjugate addition of a nucleophile to an enal was not successful simply by attaching proline to the N-terminus of the helix, the incorporation of a β-turn motif was effective to improve the catalytic performance. In the sequence of such a turn-helix-type peptide, the helical part was seemingly distant from the N-terminal amino group; however, the hydrophobicity, structure, and chirality of the helix largely affected the reaction. The turn-helix-type peptide promoted a wide range of asymmetric reactions: conjugated additions of hydride and carbon nucleophiles to enals via the iminium activation and α-oxyamination of aldehydes via the enamine activation. The peptides with turn-helix and helix frameworks were also employed for several reactions that were difficult to achieve with low-molecular-weight catalysts: enzyme-cocatalyzed asymmetric oxidation in water, diastereo- and enantioselective cyclopropanation, regioselective reduction of dienals, kinetic resolution of planar-chiral compounds, and desymmetrization to induce planar chirality. To explore other types of peptide catalysts, a combinatorial library screening was performed. On the way, it was revealed that a histidyl residue assisted to accelerate a reaction via reversible addition to an iminium intermediate. Through the screening of random peptide libraries, novel peptide sequences for efficient and enantioselective conjugate addition were discovered. Although we have no information about the molecular structure of the newly found peptides, they can be an entry point for establishing a versatile framework of peptide catalysts.

Combinatorial Library Screening with Liposomes for Discovery of Membrane Active Peptides.

Membrane active peptides (MAPs) represent a class of short biomolecules that have shown great promise in facilitating intracellular delivery without disrupting cellular plasma membranes. Yet their clinical application has been stalled by numerous factors: off-target delivery, a requirement for high local concentration near cells of interest, degradation en route to the target site, and in the case of cell-penetrating peptides, eventual entrapment in endolysosomal compartments. The current method of deriving MAPs from naturally occurring proteins has restricted the discovery of new peptides that may overcome these limitations. Here, we describe a new branch of assays featuring high-throughput functional screening capable of discovering new peptides with tailored cell uptake and endosomal escape capabilities. The one-bead-one-compound (OBOC) combinatorial method is used to screen libraries containing millions of potential MAPs for binding to synthetic liposomes, which can be adapted to mimic various aspects of limiting membranes. By incorporating unnatural and d-amino acids in the library, in addition to varying buffer conditions and liposome compositions, we have identified several new highly potent MAPs that improve on current standards and introduce motifs that were previously unknown or considered unsuitable. Since small variations in pH and lipid composition can be controlled during screening, peptides discovered using this methodology could aid researchers building drug delivery platforms with unique requirements, such as targeted intracellular localization.

Peptide-binding motifs of two common equine class I MHC molecules in Thoroughbred horses.

Quantitative peptide-binding motifs of MHC class I alleles provide a valuable tool to efficiently identify putative T cell epitopes. Detailed information on equine MHC class I alleles is still very limited, and to date, only a single equine MHC class I allele, Eqca-1*00101 (ELA-A3 haplotype), has been characterized. The present study extends the number of characterized ELA class I specificities in two additional haplotypes found commonly in the Thoroughbred breed. Accordingly, we here report quantitative binding motifs for the ELA-A2 allele Eqca-16*00101 and the ELA-A9 allele Eqca-1*00201. Utilizing analyses of endogenously bound and eluted ligands and the screening of positional scanning combinatorial libraries, detailed and quantitative peptide-binding motifs were derived for both alleles. Eqca-16*00101 preferentially binds peptides with aliphatic/hydrophobic residues in position 2 and at the C-terminus, and Eqca-1*00201 has a preference for peptides with arginine in position 2 and hydrophobic/aliphatic residues at the C-terminus. Interestingly, the Eqca-16*00101 motif resembles that of the human HLA A02-supertype, while the Eqca-1*00201 motif resembles that of the HLA B27-supertype and two macaque class I alleles. It is expected that the identified motifs will facilitate the selection of candidate epitopes for the study of immune responses in horses.

Discovering Novel Antimicrobial Peptides using High-Throughput Screening in the Presence of Human Erythrocytes

Antimicrobial peptides (AMPs) have long been considered excellent candidates for development as antibiotic agents to combat the threat of drug resistant bacterial pathogens. Yet, the promise AMPs have displayed in the laboratory has not yielded correlative clinical success. We hypothesized that a major reason for the disparity between outcomes at the bench and in the clinic is AMP interaction with and toxicity towards host cells. Here, we validate this theory using human red blood cells as model eukaryotic cells. Indeed, the potency of several well-studied antimicrobial peptides decreases from minimum sterilizing concentrations (MSC) of 1-5 μM to >30 μM in the presence of RBCs at 1x109 cells/ml; equivalent to 20% of the human physiological concentration. To address this issue, we have developed a high-throughput method to screen a combinatorial peptide library for antimicrobial activity in the presence of concentrated human cells. The screen consists of assays that assess the effect of RBCs on antimicrobial activity as well as toxicity toward eukaryotic cells. We present data on peptides identified and characterized from the high-throughput library screen and show that these new peptides were not as effective as they initially appeared during the screen. We demonstrate that the difference between observed and expected results is due to unforeseen proteolytic activity sequestered within the cytosol of the red blood cells. Finally, we show that a library consensus sequence synthesized using all d-amino acids outperforms all library isolates as well as the template sequence in terms of microbicidal activity in the presence of RBCs. Ultimately, our results suggest that combining the power of combinatorial library screening with the nuance of rational sequence engineering is an effective approach to engineering novel antimicrobial peptides that retain activity under physiological conditions.

Copper-nickel combinatorial library screening for electrocatalytic formaldehyde oxidation

The electrocatalytic behaviour of a thermally evaporated Cu–Ni thin film combinatorial library was investigated by screening the entire compositional spread in alkaline solution using flow-type scanning droplet cell microscopy. Crystallographic properties and surface microstructure were investigated using XRD and SEM. The obtained Cu–Ni thin film alloys (1–13 at.% Ni) showed suitability for being used in formaldehyde detection. The electrochemical performance of the thin film electrodes was investigated by cyclic voltammetric and chronoamperometric measurements. The highest electrocatalytic effect was found for Cu-6.9 at.% Ni. The concept of a formaldehyde sensor using Cu-6.9 at.% Ni was tested. The identified alloy showed good performance for formaldehyde detection in a wide linear range (3–200 mM), high reproducibility (relative standard deviation ∼6%), long-term stability and sensitivity to formaldehyde oxidation.

Virtual screening of combinatorial library of novel benzenesulfonamides on mycobacterial carbonic anhydrase II

Abstract Combinatorial library of novel benzenesulfonamides was docked (Schrodinger Glide) into mycobacterial carbonic anhydrase (mtCA II) and human (hCA II) isoforms with an aim to find drug candidates with selective activity on mtCA II. The predicted selectivity was calculated based on optimized MM-GBSA free energies for ligand enzyme interactions. Selectivity, LogP (o/w) and interaction energy were used to calculate the selection index which determined the subset of best scoring molecules selected for further evaluation. Structure-activity relationship was found for fragment subsets, showing us the possible way regarding how to influence lipophilicity without affecting ligand-enzyme binding properties.

PS2 - 178 Brevican-Specific Peptides for the Development of Next-Generation Targeted Theranostics for High Grade Gliomas

High-grade gliomas are deadly cancers, and current standard-of-care has demonstrated limited success. The ability to specifically target glioma cells can allow for the development of improved theranostic agents leading to better detection methods, as well as safer anti-cancer therapies. Brevican (Bcan), a CNS-specific protein is upregulated in glioma cells and correlates with tumor progression. Particularly, a Bcan isoform lacking normal glycosylation, called B/bDg is a unique glioma marker and is not expressed in non-cancerous tissues. Therefore, B/bDg represents a valuable target for anti-cancer strategies. We describe here the discovery of novel high-affinity B/bDg-targeted peptides using rapid combinatorial library screening approaches and a microfluidic sorting device of our own design. Briefly, a one-bead-one-compound (OBOC) peptide library was screened against small magnetic particles decorated with B/bDg. Positive “hit” beads labeled with magnetic particles were isolated using an inexpensive but yet, accurate and high-throughput in-house microfluidic magnetic-activated sorter. These hits were exposed to cells expressing B/bDg, and beads with the highest cell association were isolated and sequenced. Seven novel peptides were identified. Cell uptake analyses and blocking studies revealed that 5 of these peptides displayed specific uptake in B/bDg-overexpressing cells. These candidates displayed nano-/micromolar binding affinity for recombinant B/bDg protein. Further analyses of these candidates using confocal microscopy revealed increased peptide binding/uptake in patient-derived glioma stem cells (GSCs) compared with primary human astrocytes. We plan to incorporate these onto multi-functional BBB-penetrating nanoparticles loaded with imaging agents or a drug payload to translate them into highly selective and efficacious brain cancer theranostic agents.

A Novel Peptide Thrombopoietin Mimetic Designing and Optimization Using Computational Approach.

Thrombopoietin receptor (TPOR) is a cytokine receptor protein present on the cell surface. The activation of TPOR by thrombopoietin (TPO) (a glycoprotein hormone) triggers an intracellular cascade of megakaryocytopoiesis for the formation of platelets. Recent studies on ex vivo megakaryocytopoiesis have evolved the possibilities of therapeutics uses. These findings have paved the way for the development of various TPO alternatives (recombinant TPO, peptide, and non-peptide TPO mimetics), which are useful in regenerative medicine. However, these alternatives possess various limitations such as induction of autoimmune effects, high production cost, low specificity, and hence activity. In the present study, a novel peptidic TPO mimetic was designed through computational studies by studying the binding sites of TPO and TMP to TPOR and analogs of known mimetics. Screening of combinatorial library was done through molecular docking using ClusPro. These studies indicated mimetic-9 as a significant molecule since it was found to have better binding score of −938.8 kcal/mol with seven hydrogen bonds and a high number of hydrophobic interactions, than known mimetic TMP with docking score of −798.4 kcal/mol and TMP dimer with docking score of −811.9 kcal/mol for TPOR. Mimetic9-TPOR complex was further assessed by the molecular dynamics simulation, and their complex was found to be stable with an RMSD value of 0.091 Å. While studying the parameters, mimetic-9 was found to have overall good physiochemical properties with positive grand average hydropathy (GRAVY) score and high instability index score and was found to be localized in the extracellular region. The designed mimetic-9 might prove to be a useful lead molecule for mimicking the role of TPO for in vitro platelet production with higher efficiency.