Tumor-Targeting Ability of Novel Anti-Prostate-Specific Membrane Antigen Antibodies.

Patients with prostate-specific membrane antigen (PSMA)-positive tumors can benefit from PSMA-targeted therapy; thus, we have constructed a phage-displayed synthetic antibody library for the production of novel PSMA antibodies with superior PSMA-targeting ability, favoring clinical management. The binding affinities of anti-PSMA antibodies were verified by an enzyme-linked immunosorbent assay (ELISA). Several in vitro and in vivo experiments, including cellular uptake, internalization, and cytotoxicity studies, micro single photon emission computed tomography (microSPECT)/CT, and biodistribution studies, were performed to select the most promising antibody among six different antibodies. The results showed the target affinities of our antibodies in the ELISA assays (7A, 8C, 8E, and 11A) were comparable to the existing antibodies (J591). The half-maximal effective concentrations of 7A, 8C, 8E, 11A, and J591 were 2.95, 6.64, 5.50, 2.08, and 4.79, respectively. The radiochemical yield of 111In-labeled antibodies ranged from 30% to 50% with high radiochemical purity (>90%). In the cellular uptake studies, the accumulated radioactivity of 111In-J591, 111In-7A, and 111In-11A increased over time. The internalized percentage of 111In-11A was the highest (32.14% ± 2.06%) at 48 h after incubation, whereas that of 111In-J591 peaked at 22.43% ± 4.38% at 24 h and dropped to 13.52% ± 3.03% at 48 h postincubation. Twenty-four hours after injection, radioactivity accumulation appeared in the LNCaP xenografts of the mice injected with 111In-11A, 111In-8E, 111In-7A, and 111In-J591 but not in the xenografts of the 111In-8C-injected group. Marked liver uptake was noticed in all groups except the 111In-11A-injected group. Moreover, the killing effect of 177Lu-11A was superior to that of 177Lu-J591 at low concentrations. In conclusion, we successfully demonstrated that 11A IgG owned the most optimal biological characteristics among several new anti-PSMA antibodies and it can be an excellent PSMA-targeting component for the clinical use.

Antibody CDR amino acids underlying the functionality of antibody repertoires in recognizing diverse protein antigens.

Antibodies recognize protein antigens with exquisite specificity in a complex aqueous environment, where interfacial waters are an integral part of the antibody-protein complex interfaces. In this work, we elucidate, with computational analyses, the principles governing the antibodies' specificity and affinity towards their cognate protein antigens in the presence of explicit interfacial waters. Experimentally, in four model antibody-protein complexes, we compared the contributions of the interaction types in antibody-protein antigen complex interfaces with the antibody variants selected from phage-displayed synthetic antibody libraries. Evidently, the specific interactions involving a subset of aromatic CDR (complementarity determining region) residues largely form the predominant determinant underlying the specificity of the antibody-protein complexes in nature. The interfacial direct/water-mediated hydrogen bonds accompanying the CDR aromatic interactions are optimized locally but contribute little in determining the epitope location. The results provide insights into the phenomenon that natural antibodies with limited sequence and structural variations in an antibody repertoire can recognize seemingly unlimited protein antigens. Our work suggests guidelines in designing functional artificial antibody repertoires with practical applications in developing novel antibody-based therapeutics and diagnostics for treating and preventing human diseases.

Functionalized Terpolymer-Brush-Based Biointerface with Improved Antifouling Properties for Ultra-Sensitive Direct Detection of Virus in Crude Clinical Samples.

New analytical techniques that overcome major drawbacks of current routinely used viral infection diagnosis methods, i.e., the long analysis time and laboriousness of real-time reverse-transcription polymerase chain reaction (qRT-PCR) and the insufficient sensitivity of "antigen tests", are urgently needed in the context of SARS-CoV-2 and other highly contagious viruses. Here, we report on an antifouling terpolymer-brush biointerface that enables the rapid and sensitive detection of SARS-CoV-2 in untreated clinical samples. The developed biointerface carries a tailored composition of zwitterionic and non-ionic moieties and allows for the significant improvement of antifouling capabilities when postmodified with biorecognition elements and exposed to complex media. When deployed on a surface of piezoelectric sensor and postmodified with human-cell-expressed antibodies specific to the nucleocapsid (N) protein of SARS-CoV-2, it made possible the quantitative analysis of untreated samples by a direct detection assay format without the need of additional amplification steps. Natively occurring N-protein-vRNA complexes, usually disrupted during the sample pre-treatment steps, were detected in the untreated clinical samples. This biosensor design improved the bioassay sensitivity to a clinically relevant limit of detection of 1.3 × 104 PFU/mL within a detection time of only 20 min. The high specificity toward N-protein-vRNA complexes was validated both by mass spectrometry and qRT-PCR. The performance characteristics were confirmed by qRT-PCR through a comparative study using a set of clinical nasopharyngeal swab samples. We further demonstrate the extraordinary fouling resistance of this biointerface through exposure to other commonly used crude biological samples (including blood plasma, oropharyngeal, stool, and nasopharyngeal swabs), measured via both the surface plasmon resonance and piezoelectric measurements, which highlights the potential to serve as a generic platform for a wide range of biosensing applications.

Eradicating mesothelin-positive human gastric and pancreatic tumors in xenograft models with optimized anti-mesothelin antibody-drug conjugates from synthetic antibody libraries.

Mesothelin (MSLN) is an attractive candidate of targeted therapy for several cancers, and hence there are increasing needs to develop MSLN-targeting strategies for cancer therapeutics. Antibody-drug conjugates (ADCs) targeting MSLN have been demonstrated to be a viable strategy in treating MSLN-positive cancers. However, developing antibodies as targeting modules in ADCs for toxic payload delivery to the tumor site but not to normal tissues is not a straightforward task with many potential hurdles. In this work, we established a high throughput engineering platform to develop and optimize anti-MSLN ADCs by characterizing more than 300 scFv CDR-variants and more than 50 IgG CDR-variants of a parent anti-MSLN antibody as candidates for ADCs. The results indicate that only a small portion of the complementarity determining region (CDR) residues are indispensable in the MSLN-specific targeting. Also, the enhancement of the hydrophilicity of the rest of the CDR residues could drastically increase the overall solubility of the optimized anti-MSLN antibodies, and thus substantially improve the efficacies of the ADCs in treating human gastric and pancreatic tumor xenograft models in mice. We demonstrated that the in vivo treatments with the optimized ADCs resulted in almost complete eradication of the xenograft tumors at the treatment endpoints, without detectable off-target toxicity because of the ADCs' high specificity targeting the cell surface tumor-associated MSLN. The technological platform can be applied to optimize the antibody sequences for more effective targeting modules of ADCs, even when the candidate antibodies are not necessarily feasible for the ADC development due to the antibodies' inferior solubility or affinity/specificity to the target antigen.

Development of theranostic active-targeting boron-containing gold nanoparticles for boron neutron capture therapy (BNCT).

Successful boron neutron capture therapy (BNCT) requires sufficient and specific delivery of boron atoms to malignant cells. Gold nanoparticles (AuNPs) have been used as a useful delivery system for selectively releasing cytotoxic payloads in the tumor. However, studies demonstrating the in vivo distribution or pharmacokinetics of boron-containing AuNPs via noninvasive imaging are lacking. This study aims to develop theranostic AuNP-boron cage assemblies (B-AuNPs) and evaluate its feasibility for BNCT. The commercial citrate-coated AuNPs were subjected to PEGylation, azide addition, and carborane modification on the surface. To further arm the AuNPs, we conjugated anti-HER2 antibody (61 IgG) with boron-containing PEGylated AuNPs to form 61-B-AuNPs. The diameter and radiolabeling efficiency of boron-containing AuNPs were determined by dynamic light scattering (DLS) and radio thin-layer chromatography (radio TLC), respectively. Noninvasive single-photon emission computed tomography (SPECT)/computed tomography (CT) imaging was performed to determine the pharmacokinetics of radioiodinated AuNPs in N87 gastric cancer xenografts, and the content of boron in tumor and muscle was assessed by inductively coupled plasma mass spectrometry (ICP-MS). After the 3-step modification, the diameter of B-AuNPs increased by ˜25 nm, and antibody conjugation did not affect the diameter of AuNPs. Radioactive iodine (I-123) was introduced in AuNPs by Click chemistry under copper catalysis. The radiolabeling efficiency of 123I-B-AuNPs and 123I-61-B-AuNPs was approximately 60 ± 5%. After purification, the radiochemical purity (RCP) of these NPs was greater than 90%. MicroSPECT/CT imaging showed that the tumor-to-muscle (T/M) ratio of 123I-B-AuNP-injected mice reached 1.91 ± 0.17 at 12 h post-injection, while that of 123I-61-B-AuNP-injected mice was 12.02 ± 0.94. However, the increased uptake of AuNPs by the thyroid was observed at 36 h after the administration of 123I-61-B-AuNPs, indicating antibody-mediated phagocytosis. The T/M ratio, assessed by ICP-MS, of B-AuNP- and 61-B-AuNP-injected mice was 4.91 ± 2.75 and 41.05 ± 11.15, respectively. We successfully developed detectable HER2-targeting boron-containing AuNPs with high RCP and an acceptable yield. Noninvasive imaging could be a valuable tool for the noninvasive determination of the pharmacokinetics of AuNPs and measurement of boron concentration in the tumor.

Effective binding to protein antigens by antibodies from antibody libraries designed with enhanced protein recognition propensities.

Antibodies provide immune protection by recognizing antigens of diverse chemical properties, but elucidating the amino acid sequence-function relationships underlying the specificity and affinity of antibody-antigen interactions remains challenging. We designed and constructed phage-displayed synthetic antibody libraries with enriched protein antigen-recognition propensities calculated with machine learning predictors, which indicated that the designed single-chain variable fragment variants were encoded with enhanced distributions of complementarity-determining region (CDR) hot spot residues with high protein antigen recognition propensities in comparison with those in the human antibody germline sequences. Antibodies derived directly from the synthetic antibody libraries, without affinity maturation cycles comparable to those in in vivo immune systems, bound to the corresponding protein antigen through diverse conformational or linear epitopes with specificity and affinity comparable to those of the affinity-matured antibodies from in vivo immune systems. The results indicated that more densely populated CDR hot spot residues were sustainable by the antibody structural frameworks and could be accompanied by enhanced functionalities in recognizing protein antigens. Our study results suggest that synthetic antibody libraries, which are not limited by the sequences found in antibodies in nature, could be designed with the guidance of the computational machine learning algorithms that are programmed to predict interaction propensities to molecules of diverse chemical properties, leading to antibodies with optimal characteristics pertinent to their medical applications.

Antibody-drug conjugates with HER2-targeting antibodies from synthetic antibody libraries are highly potent against HER2-positive human gastric tumor in xenograft models.

HER2-ECD (human epidermal growth factor receptor 2 - extracellular domain) is a prominent therapeutic target validated for treating HER2-positive breast and gastric cancer, but HER2-specific therapeutic options for treating advanced gastric cancer remain limited. We have developed antibody-drug conjugates (ADCs), comprising IgG1 linked via valine-citrulline to monomethyl auristatin E, with potential to treat HER2-positive gastric cancer in humans. The antibodies optimally selected from the ADC discovery platform, which was developed to discover antibody candidates suitable for immunoconjugates from synthetic antibody libraries designed using antibody-antigen interaction principles, were demonstrated to be superior immunoconjugate targeting modules in terms of efficacy and off-target toxicity. In comparison with the two control humanized antibodies (trastuzumab and H32) derived from murine antibody repertoires, the antibodies derived from the synthetic antibody libraries had enhanced receptor-mediated internalization rate, which could result in ADCs with optimal efficacies. Along with the ADCs, two other forms of immunoconjugates (scFv-PE38KDEL and IgG1-AL1-PE38KDEL) were used to test the antibodies for delivering cytotoxic payloads to xenograft tumor models in vivo and to cultured cells in vitro. The in vivo experiments with the three forms of immunoconjugates revealed minimal off-target toxicities of the selected antibodies from the synthetic antibody libraries; the off-target toxicities of the control antibodies could have resulted from the antibodies' propensity to target the liver in the animal models. Our ADC discovery platform and the knowledge gained from our in vivo tests on xenograft models with the three forms of immunoconjugates could be useful to anyone developing optimal ADC cancer therapeutics.

Noninvasive assessment of characteristics of novel anti-HER2 antibodies by molecular imaging in a human gastric cancer xenograft-bearing mouse model.

Human epidermal growth factor receptor 2 (HER2) overexpression occurs in various types of cancers. Regarding the anti-HER2 targeted therapies showed superior treatment outcomes in several (pre)clinical studies, we used multimodality image to rapidly select novel HER2-targeting antibodies for further therapeutics development. The four anti-HER2 antibodies (H32 IgG, 75 IgG, 61 IgG, and trastuzumab) labeled with either In-111 or a DyLight680 fluorescent dye were applied to perform cellular uptake, endocytosis, optical/microSPECT/CT imaging and biodistribution studies. In vitro and in vivo relative effectiveness of these antibodies were also compared in an N87 gastric cancer xenograft model. The internalized radioactivity of [111In]61 IgG in N87 cells increased from 33% at 12 hr to 56% at 48 hr after incubation, while the majority of other antibodies stayed on the cell membranes. Among these antibodies, 61 IgG showed the highest accumulation in tumors with the tumor-to-muscle ratio (T/M) of 131 ± 61.4 and 19.13 ± 3.42 conducted by IVIS and microSPECT/CT, respectively. We demonstrated that multimodality imaging is a reliable approach for selecting potential antibodies and found that 61 IgG manifested significant tumor accumulation with elevated internalization rate thus could be a suitable candidate for further development of new HER2-targeted therapies.

Discovery of Potent Cysteine-Containing Dipeptide Inhibitors against Tyrosinase: A Comprehensive Investigation of 20 × 20 Dipeptides in Inhibiting Dopachrome Formation.

Tyrosinase is an essential copper-containing enzyme required for melanin synthesis. The overproduction and abnormal accumulation of melanin cause hyperpigmentation and neurodegenerative diseases. Thus, tyrosinase is promising for use in medicine and cosmetics. Our previous study identified a natural product, A5, resembling the structure of the dipeptide WY and apparently inhibiting tyrosinase. Here, we comprehensively estimated the inhibitory capability of 20 × 20 dipeptides against mushroom tyrosinase. We found that cysteine-containing dipeptides, directly blocking the active site of tyrosinase, are highly potent in inhibition; in particular, N-terminal cysteine-containing dipeptides markedly outperform the C-terminal-containing ones. The cysteine-containing dipeptides, CE, CS, CY, and CW, show comparative bioactivities, and tyrosine-containing dipeptides are substrate-like inhibitors. The dipeptide PD attenuates 16.5% melanin content without any significant cytotoxicity. This study reveals the functional role of cysteine residue positional preference and the selectivity of specific amino acids in cysteine-containing dipeptides against tyrosinase, aiding in developing skin-whitening products.

Serendipitous discovery of short peptides from natural products as tyrosinase inhibitors.

Tyrosinase, which is the crucial copper-containing enzyme involved in melanin synthesis, is strongly associated with hyperpigmentation disorders, cancer, and neurodegenerative disease; thus, it has attracted considerable interest in the fields of medicine and cosmetics. The known tyrosinase inhibitors show numerous adverse side effects, and there is a lack of safety regulations governing their use. As a result, there is a need to develop novel inhibitors with no toxicity and long-term stability. In this study, we use molecular docking and pharmacophore modeling to construct a reasonable and reliable pharmacophore model, called Hypo 1, that could be used for identifying potent natural products with crucial complementary functional groups for mushroom tyrosinase inhibition. It was observed that, out of 47,263 natural compounds, A5 structurally resembles a dipeptide (WY) and natural compound B16 is the equivalent of a tripeptide (KFY), revealing that the C-terminus tyrosine residues play a key role in tyrosinase inhibition. Tripeptides RCY and CRY, which show high tyrosinase inhibitory potency, revealed a positional and functional preference for the cysteine residue at the N-terminus of the tripeptides, essentially determining the capacity of tyrosinase inhibition. CRY and RCY used the thiol group of cysteine residues to coordinate with the Cu ions in the active site of tyrosinase and showed reduced tyrosinase activity. We discovered the novel tripeptide CRY that shows the most striking inhibitory potency against mushroom tyrosinase (IC50 = 6.16 µM); this tripeptide is more potent than the known oligopeptides and comparable with kojic acid-tripeptides. Our study provides an insight into the structural and functional roles of key amino acids of tripeptides derived from the natural compound B16, and the results are expected to be useful for the development of tyrosinase inhibitors.

Substrate phage display for protease substrate sequence characterization: bovine factor Xa as a model system.

Regulatory proteases modulate proteomic dynamics with a spectrum of specificities against substrate proteins. Substrate phage display is one of the key methodologies in producing substrate sequence information in vitro. Factor Xa, a key regulatory protease in the blood coagulation system, is used as a model system to demonstrate a high-throughput procedure to quantitatively characterize substrate sequences and their susceptibilities for enzymatic cleavage. This methodology can be generalized to proteases for which the active forms (not necessarily purified forms) are available for the in vitro experiments.

Antibody variable domain interface and framework sequence requirements for stability and function by high-throughput experiments.

Protein structural stability and biological functionality are dictated by the formation of intradomain cores and interdomain interfaces, but the intricate sequence-structure-function interrelationships in the packing of protein cores and interfaces remain difficult to elucidate due to the intractability of enumerating all packing possibilities and assessing the consequences of all the variations. In this work, groups of ß strand residues of model antibody variable domains were randomized with saturated mutagenesis and the functional variants were selected for high-throughput sequencing and high-throughput thermal stability measurements. The results show that the sequence preferences of the intradomain hydrophobic core residues are strikingly flexible among hydrophobic residues, implying that these residues are coupled indirectly with antigen binding through energetic stabilization of the protein structures. By contrast, the interdomain interface residues are directly coupled with antigen binding. The interdomain interface should be treated as an integral part of the antigen-binding site.

Loop-sequence features and stability determinants in antibody variable domains by high-throughput experiments.

Protein loops are frequently considered as critical determinants in protein structure and function. Recent advances in high-throughput methods for DNA sequencing and thermal stability measurement have enabled effective exploration of sequence-structure-function relationships in local protein regions. Using these data-intensive technologies, we investigated the sequence-structure-function relationships of six complementarity-determining regions (CDRs) and ten non-CDR loops in the variable domains of a model vascular endothelial growth factor (VEGF)-binding single-chain antibody variable fragment (scFv) whose sequence had been optimized via a consensus-sequence approach. The results show that only a handful of residues involving long-range tertiary interactions distant from the antigen-binding site are strongly coupled with antigen binding. This implies that the loops are passive regions in protein folding; the essential sequences of these regions are dictated by conserved tertiary interactions and the consensus local loop-sequence features contribute little to protein stability and function.

Rationalization and design of the complementarity determining region sequences in an antibody-antigen recognition interface.

Protein-protein interactions are critical determinants in biological systems. Engineered proteins binding to specific areas on protein surfaces could lead to therapeutics or diagnostics for treating diseases in humans. But designing epitope-specific protein-protein interactions with computational atomistic interaction free energy remains a difficult challenge. Here we show that, with the antibody-VEGF (vascular endothelial growth factor) interaction as a model system, the experimentally observed amino acid preferences in the antibody-antigen interface can be rationalized with 3-dimensional distributions of interacting atoms derived from the database of protein structures. Machine learning models established on the rationalization can be generalized to design amino acid preferences in antibody-antigen interfaces, for which the experimental validations are tractable with current high throughput synthetic antibody display technologies. Leave-one-out cross validation on the benchmark system yielded the accuracy, precision, recall (sensitivity) and specificity of the overall binary predictions to be 0.69, 0.45, 0.63, and 0.71 respectively, and the overall Matthews correlation coefficient of the 20 amino acid types in the 24 interface CDR positions was 0.312. The structure-based computational antibody design methodology was further tested with other antibodies binding to VEGF. The results indicate that the methodology could provide alternatives to the current antibody technologies based on animal immune systems in engineering therapeutic and diagnostic antibodies against predetermined antigen epitopes.

Effects of signal sequence on phage-displayed disulfide-stabilized single chain antibody variable fragment (sc-dsFv) libraries.

Phage-displayed single chain variable fragment (scFv) libraries are powerful tools in antibody engineering. Disulfide-stabilized scFv (sc-dsFv) with an interface disulfide bond is structure-wise more stable than the corresponding scFv. A set of recently discovered signal sequences replacing the wild type (pelB) signal peptidase cleavage site in the c-region has been shown to be effective in rescuing the expression of sc-dsFv libraries on the phage surface. However, the effects of the other regions of the signal sequence on the expression of the sc-dsFv libraries and on the formation of the interface disulfide bond in the phage-displayed sc-dsFv have not been clear. In this work, selected novel signal sequence variants in the h-region were shown to be equally effective in promoting sc-dsFv library expression on the phage surface; the expression level and complexity of the sc-dsFv libraries were comparable to the corresponding scFv libraries produced with the wild-type (pelB) signal sequence. The interface disulfide bond in the phage-displayed sc-dsFv was proven to form to a large extent in the library variant ensemble generated with signal sequence variants in both the h-region and the c-region. The sc-dsFv engineering platform established in this work can be applied to many of the known scFv molecules which are in need of a more stable version for the applications under harsh conditions or for longer shelf-life.

Signal sequence as a determinant in expressing disulfide-stabilized single chain antibody variable fragments (sc-dsFv) against human VEGF.

Phage-displayed single chain variable fragment (scFv) libraries have been powerful tools in antibody engineering. But the scFv structures are frequently unstable due to the dissociation of the dimeric interface between the two variable domains. One solution is the sc-dsFv construct, where the single chain variable domain fragment is stabilized with an additional interface disulfide bond, leading to stable and homogeneous dimeric interface for the sc-dsFv structure. However, the phagemid system that is capable of effective expression for both sc-dsFv-pIII fusion proteins on phage surface and secreted non-fusion sc-dsFv in bacterial culture medium has not been demonstrated. In this work, a biological combinatorial approach was applied to optimize the signal sequence N-terminal to the sc-dsFv-pIII fusion protein encoded in a phagemid. The optimized sc-dsFv phage display systems were compatible with both the phage-based directed evolution procedure and the high throughput screening of the soluble sc-dsFv. The utility of the phagemid systems was demonstrated in generating anti-VEGF sc-dsFv with VEGF-binding affinity one order of magnitude higher than the corresponding scFv, due only to the interface disulfide bond in the sc-dsFv. Moreover, the protein stability of the sc-dsFv construct was unmatched by the corresponding scFv. These advantages of the sc-dsFv were gained through the interface disulfide bond of the sc-dsFv and the novel signal sequence in the phagemid.

Engineering anti-vascular endothelial growth factor single chain disulfide-stabilized antibody variable fragments (sc-dsFv) with phage-displayed sc-dsFv libraries.

Phage display of antibody fragments from natural or synthetic antibody libraries with the single chain constructs combining the variable fragments (scFv) has been one of the most prominent technologies in antibody engineering. However, the nature of the artificial single chain constructs results in unstable proteins expressed on the phage surface or as soluble proteins secreted in the bacterial culture medium. The stability of the variable domain structures can be enhanced with interdomain disulfide bond, but the single chain disulfide-stabilized constructs (sc-dsFv) have yet to be established as a feasible format for bacterial phage display due to diminishing expression levels on the phage surface in known phage display systems. In this work, biological combinatorial searches were used to establish that the c-region of the signal sequence is critically responsible for effective expression and functional folding of the sc-dsFv on the phage surface. The optimum signal sequences increase the expression of functional sc-dsFv by 2 orders of magnitude compared with wild-type signal sequences, enabling the construction of phage-displayed synthetic antivascular endothelial growth factor sc-dsFv libraries. Comparison of the scFv and sc-dsFv variants selected from the phage-displayed libraries for vascular endothelial growth factor binding revealed the sequence preference differences resulting from the interdomain disulfide bond. These results underlie a new phage display format for antibody fragments with all the benefits from the scFv format but without the downside due to the instability of the dimeric interface in scFv.

Molecular evolution of cystine-stabilized miniproteins as stable proteinaceous binders.

Small cystine-stabilized proteins are desirable scaffolds for therapeutics and diagnostics. Specific folding and binding properties of the proteinaceous binders can be engineered with combinatorial protein libraries in connection with artificial molecular evolution. The combinatorial protein libraries are composed of scaffold variants with random sequence variation, which inevitably produces a portion of the library sequences incompatible with the parent structure. Here, we used artificial molecular evolution to elucidate structure-determining residues in a smallest cystine-stabilized scaffold. The structural determinant information was then applied to designing cystine-stabilized miniproteins binding to human vascular endothelial growth factor. This work demonstrated a general methodology on engineering artificial cystine-stabilized proteins as antibody mimetics with simultaneously enhanced folding and binding properties.

Protease substrate site predictors derived from machine learning on multilevel substrate phage display data.

MOTIVATION: Regulatory proteases modulate proteomic dynamics with a spectrum of specificities against substrate proteins. Predictions of the substrate sites in a proteome for the proteases would facilitate understanding the biological functions of the proteases. High-throughput experiments could generate suitable datasets for machine learning to grasp complex relationships between the substrate sequences and the enzymatic specificities. But the capability in predicting protease substrate sites by integrating the machine learning algorithms with the experimental methodology has yet to be demonstrated. RESULTS: Factor Xa, a key regulatory protease in the blood coagulation system, was used as model system, for which effective substrate site predictors were developed and benchmarked. The predictors were derived from bootstrap aggregation (machine learning) algorithms trained with data obtained from multilevel substrate phage display experiments. The experimental sampling and computational learning on substrate specificities can be generalized to proteases for which the active forms are available for the in vitro experiments. AVAILABILITY: http://asqa.iis.sinica.edu.tw/fXaWeb/

Factor Xa active site substrate specificity with substrate phage display and computational molecular modeling.

Structural origin of substrate-enzyme recognition remains incompletely understood. In the model enzyme system of serine protease, canonical anti-parallel beta-structure substrate-enzyme complex is the predominant hypothesis for the substrate-enzyme interaction at the atomic level. We used factor Xa (fXa), a key serine protease of the coagulation system, as a model enzyme to test the canonical conformation hypothesis. More than 160 fXa-cleavable substrate phage variants were experimentally selected from three designed substrate phage display libraries. These substrate phage variants were sequenced and their specificities to the model enzyme were quantified with quantitative enzyme-linked immunosorbent assay for substrate phage-enzyme reaction kinetics. At least three substrate-enzyme recognition modes emerged from the experimental data as necessary to account for the sequence-dependent specificity of the model enzyme. Computational molecular models were constructed, with both energetics and pharmacophore criteria, for the substrate-enzyme complexes of several of the representative substrate peptide sequences. In contrast to the canonical conformation hypothesis, the binding modes of the substrates to the model enzyme varied according to the substrate peptide sequence, indicating that an ensemble of binding modes underlay the observed specificity of the model serine protease.