Hung-Ju Hsu

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.

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 β-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.

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.

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/

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.

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.

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 β 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.

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.

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.

Impacts of NH 3 Plasma Treatment on Double-Gated Poly-Si Nanowire Thin-Film Transistors

NH3 plasma treatment has been employed to improve the performance of a novel double-gated poly-Si nanowire thin-film transistor in terms of increased on-state current, reduced off-state current, and steeper sub-threshold slope. An interesting finding is that the radiation damage, accompanying by a negative shift in threshold voltage, appears to occur in the early stage of plasma treatment for devices with top poly-gate. Such effect disappears when an Al top-gate is used instead.