Structural bioinformatics studies of glutamate transporters and their AlphaFold2 predicted water-soluble QTY variants and uncovering the natural mutations of L->Q, I->T, F->Y and Q->L, T->I and Y->F.

Glutamate transporters play key roles in nervous physiology by modulating excitatory neurotransmitter levels, when malfunctioning, involving in a wide range of neurological and physiological disorders. However, integral transmembrane proteins including the glutamate transporters remain notoriously difficult to study, due to their localization within the cell membrane. Here we present the structural bioinformatics studies of glutamate transporters and their water-soluble variants generated through QTY-code, a protein design strategy based on systematic amino acid substitutions. These include 2 structures determined by X-ray crystallography, cryo-EM, and 6 predicted by AlphaFold2, and their predicted water-soluble QTY variants. In the native structures of glutamate transporters, transmembrane helices contain hydrophobic amino acids such as leucine (L), isoleucine (I), and phenylalanine (F). To design water-soluble variants, these hydrophobic amino acids are systematically replaced by hydrophilic amino acids, namely glutamine (Q), threonine (T) and tyrosine (Y). The QTY variants exhibited water-solubility, with four having identical isoelectric focusing points (pI) and the other four having very similar pI. We present the superposed structures of the native glutamate transporters and their water-soluble QTY variants. The superposed structures displayed remarkable similarity with RMSD 0.528Å-2.456Å, despite significant protein transmembrane sequence differences (41.1%->53.8%). Additionally, we examined the differences of hydrophobicity patches between the native glutamate transporters and their QTY variants. Upon closer inspection, we discovered multiple natural variations of L->Q, I->T, F->Y and Q->L, T->I, Y->F in these transporters. Some of these natural variations were benign and the remaining were reported in specific neurological disorders. We further investigated the characteristics of hydrophobic to hydrophilic substitutions in glutamate transporters, utilizing variant analysis and evolutionary profiling. Our structural bioinformatics studies not only provided insight into the differences between the hydrophobic helices and hydrophilic helices in the glutamate transporters, but they are also expected to stimulate further study of other water-soluble transmembrane proteins.

Structural bioinformatics studies of six human ABC transporters and their AlphaFold2-predicted water-soluble QTY variants.

Human ATP-binding cassette (ABC) transporters are one of the largest families of membrane proteins and perform diverse functions. Many of them are associated with multidrug resistance that often results in cancer treatment with poor outcomes. Here, we present the structural bioinformatics study of six human ABC membrane transporters with experimentally determined cryo-electron microscopy (CryoEM) structures including ABCB7, ABCC8, ABCD1, ABCD4, ABCG1, ABCG5, and their AlphaFold2-predicted water-soluble QTY variants. In the native structures, there are hydrophobic amino acids such as leucine (L), isoleucine (I), valine (V), and phenylalanine (F) in the transmembrane alpha helices. These hydrophobic amino acids are systematically replaced by hydrophilic amino acids glutamine (Q), threonine (T), and tyrosine (Y). Therefore, these QTY variants become water soluble. We also present the superposed structures of native ABC transporters and their water-soluble QTY variants. The superposed structures show remarkable similarity with root mean square deviations between 1.064 and 3.413 Å despite significant (41.90-54.33%) changes to the protein sequence of the transmembrane domains. We also show the differences in hydrophobicity patches between the native ABC transporters and their QTY variants. We explain the rationale behind why the QTY membrane protein variants become water soluble. Our structural bioinformatics studies provide insight into the differences between the hydrophobic helices and hydrophilic helices and will likely further stimulate designs of water-soluble multispan transmembrane proteins and other aggregated proteins. The water-soluble ABC transporters may be useful as soluble antigens to generate therapeutic monoclonal antibodies for combating multidrug resistance in clinics.

Corrigendum: Experimental validation of immunogenic SARS-CoV-2 T cell epitopes identified by artificial intelligence.

[This corrects the article DOI: 10.3389/fimmu.2023.1265044.].

Experimental validation of immunogenic SARS-CoV-2 T cell epitopes identified by artificial intelligence.

During the COVID-19 pandemic we utilized an AI-driven T cell epitope prediction tool, the NEC Immune Profiler (NIP) to scrutinize and predict regions of T cell immunogenicity (hotspots) from the entire SARS-CoV-2 viral proteome. These immunogenic regions offer potential for the development of universally protective T cell vaccine candidates. Here, we validated and characterized T cell responses to a set of minimal epitopes from these AI-identified universal hotspots. Utilizing a flow cytometry-based T cell activation-induced marker (AIM) assay, we identified 59 validated screening hits, of which 56% (33 peptides) have not been previously reported. Notably, we found that most of these novel epitopes were derived from the non-spike regions of SARS-CoV-2 (Orf1ab, Orf3a, and E). In addition, ex vivo stimulation with NIP-predicted peptides from the spike protein elicited CD8+ T cell response in PBMC isolated from most vaccinated donors. Our data confirm the predictive accuracy of AI platforms modelling bona fide immunogenicity and provide a novel framework for the evaluation of vaccine-induced T cell responses.

Effects of ion type and concentration on the structure and aggregation of the amyloid peptide A ß 16 - 22 $$ {\boldsymbol{\beta}}_{16-22} $$.

Among the various factors controlling the amyloid aggregation process, the influences of ions on the aggregation rate and the resulting structures are important aspects to consider, which can be studied by molecular simulations. There is a wide variety of protein force fields and ion models, raising the question of which model to use in such studies. To address this question, we perform molecular dynamics simulations of Aß16-22 , a fragment of the Alzheimer's amyloid ß peptide, using different protein force fields, AMBER99SB-disp (A99-d) and CHARMM36m (C36m), and different ion parameters. The influences of NaCl and CaCl2 at various concentrations are studied and compared with the systems without the addition of ions. Our results indicate a sensitivity of the peptide-ion interactions to the different ion models. In particular, we observe a strong binding of Ca2+ to residue E22 with C36m and also with the Åqvist ion model used together with A99-d, which slightly affects the monomeric Aß16-22 structures and the aggregation rate, but significantly affects the oligomer structures formed in the aggregation simulations. For example, at high Ca2+ concentrations, there was a switch from an antiparallel to a parallel ß-sheet. Such ionic influences are of biological relevance because local ion concentrations can change in vivo and could help explain the polymorphism of amyloid fibrils.

Structural bioinformatics studies of bacterial outer membrane beta-barrel transporters and their AlphaFold2 predicted water-soluble QTY variants.

Beta-barrel outer membrane proteins (OMP) are integral components of Gram-negative bacteria, eukaryotic mitochondria, and chloroplasts. They play essential roles in various cellular processes including nutrient transport, membrane stability, host-pathogen interactions, antibiotic resistance and more. The advent of AlphaFold2 for accurate protein structure predictions transformed structural bioinformatic studies. We previously used a QTY code to convert hydrophobic alpha-helices to hydrophilic alpha-helices in over 50 membrane proteins with all alpha-helices. The QTY code systematically replaces hydrophobic leucine (L), isoleucine (I), valine (V), and phenylalanine (F) with hydrophilic glutamine (Q), threonine (T), and tyrosine (Y). We here present a structural bioinformatic analysis of five outer membrane beta-barrel proteins with known molecular structures, including a) BamA, b) Omp85 (also called Sam50), c) FecA, d) Tsx, and e) OmpC. We superposed the structures of five native beta-barrel outer membrane proteins and their AlphaFold2-predicted corresponding QTY variant structures. The superposed structures of OMPs and their QTY variants exhibit remarkable structural similarity, as evidenced by residue mean square distance (RMSD) values between 0.206Å to 0.414Å despite the replacement of at least 22% (Transmembrane variation) of the amino acids in the transmembrane regions. We also show that native outer membrane proteins and QTY variants have different hydrophobicity patches. Our study provides important insights into the differences between hydrophobic and hydrophilic beta-barrels and validates the QTY code for studying beta-barrel membrane proteins and perhaps other hydrophobic aggregated proteins. Our findings demonstrate that the QTY code can be used as a simple tool for designing hydrophobic proteins in various biological contexts.

Scalable biomimetic sensing system with membrane receptor dual-monolayer probe and graphene transistor arrays.

Affinity-based biosensing can enable point-of-care diagnostics and continuous health monitoring, which commonly follows bottom-up approaches and is inherently constrained by bioprobes' intrinsic properties, batch-to-batch consistency, and stability in biofluids. We present a biomimetic top-down platform to circumvent such difficulties by combining a "dual-monolayer" biorecognition construct with graphene-based field-effect-transistor arrays. The construct adopts redesigned water-soluble membrane receptors as specific sensing units, positioned by two-dimensional crystalline S-layer proteins as dense antifouling linkers guiding their orientations. Hundreds of transistors provide statistical significance from transduced signals. System feasibility was demonstrated with rSbpA-ZZ/CXCR4QTY-Fc combination. Nature-like specific interactions were achieved toward CXCL12 ligand and HIV coat glycoprotein in physiologically relevant concentrations, without notable sensitivity loss in 100% human serum. The construct is regeneratable by acidic buffer, allowing device reuse and functional tuning. The modular and generalizable architecture behaves similarly to natural systems but gives electrical outputs, which enables fabrication of multiplex sensors with tailored receptor panels for designated diagnostic purposes.

Toward real-world automated antibody design with combinatorial Bayesian optimization.

Antibodies are multimeric proteins capable of highly specific molecular recognition. The complementarity determining region 3 of the antibody variable heavy chain (CDRH3) often dominates antigen-binding specificity. Hence, it is a priority to design optimal antigen-specific CDRH3 to develop therapeutic antibodies. The combinatorial structure of CDRH3 sequences makes it impossible to query binding-affinity oracles exhaustively. Moreover, antibodies are expected to have high target specificity and developability. Here, we present AntBO, a combinatorial Bayesian optimization framework utilizing a CDRH3 trust region for an in silico design of antibodies with favorable developability scores. The in silico experiments on 159 antigens demonstrate that AntBO is a step toward practically viable in vitro antibody design. In under 200 calls to the oracle, AntBO suggests antibodies outperforming the best binding sequence from 6.9 million experimentally obtained CDRH3s. Additionally, AntBO finds very-high-affinity CDRH3 in only 38 protein designs while requiring no domain knowledge.

Structural informatic study of determined and AlphaFold2 predicted molecular structures of 13 human solute carrier transporters and their water-soluble QTY variants.

Solute carrier transporters are integral membrane proteins, and are important for diverse cellular nutrient transports, metabolism, energy demand, and other vital biological activities. They have recently been implicated in pancreatic cancer and other cancer metastasis, angiogenesis, programmed cell death and proliferation, cell metabolism and chemo-sensitivity. Here we report the study of 13 human solute carrier membrane transporters using the highly accurate AlphaFold2 predictions of 3D protein structures. In the native structures, there are hydrophobic amino acids leucine (L), isoleucine (I), valine (V) and phenylalanine (F) in the transmembrane alpha-helices. These hydrophobic amino acids L, I, V, F are systematically replaced by hydrophilic amino acids glutamine (Q), threonine (T) and tyrosine (Y), thus the QTY code. Therefore, these QTY variant transporters become water-soluble without requiring detergents. We present the superposed structures of these native solute carrier transporters and their water-soluble QTY variants. The superposed structures show remarkable similarity with RMSD ~ 1 Å-< 3 Å despite > 46% protein sequence substitutions in transmembrane alpha-helices. We also show the differences of surface hydrophobicity between the native solute carrier transporters and their QTY variants. Our study may further stimulate designs of water-soluble transmembrane proteins and other aggregated proteins for drug discovery and biotechnological applications.

Development of a High-Affinity Antibody against the Tumor-Specific and Hyperactive 611-p95HER2 Isoform.

The expression of human epidermal growth factor receptor 2 (HER2) is a key classification factor in breast cancer. Many breast cancers express isoforms of HER2 with truncated carboxy-terminal fragments (CTF), collectively known as p95HER2. A common p95HER2 isoform, 611-CTF, is a biomarker for aggressive disease and confers resistance to therapy. Contrary to full-length HER2, 611-p95HER2 has negligible normal tissue expression. There is currently no approved diagnostic assay to identify this subgroup and no therapy targeting this mechanism of tumor escape. The purpose of this study was to develop a monoclonal antibody (mAb) against 611-CTF-p95HER2. Hybridomas were generated from rats immunized with cells expressing 611-CTF. A hybridoma producing a highly specific Ab was identified and cloned further as a mAb. This mAb, called Oslo-2, gave strong staining for 611-CTF and no binding to full-length HER2, as assessed in cell lines and tissues by flow cytometry, immunohistochemistry and immunofluorescence. No cross-reactivity against HER2 negative controls was detected. Surface plasmon resonance analysis demonstrated a high binding affinity (equilibrium dissociation constant 2 nM). The target epitope was identified at the N-terminal end, using experimental alanine scanning. Further, the mAb paratope was identified and characterized with hydrogen-deuterium-exchange, and a molecular model for the (Oslo-2 mAb:611-CTF-p95HER2) complex was generated by an experimental-information-driven docking approach. We conclude that the Oslo-2 mAb has a high affinity and is highly specific for 611-CTF-p95HER2. The Ab may be used to develop potent and safe therapies, overcoming p95HER2-mediated tumor escape, as well as for developing diagnostic assays.

Protein Design: From the Aspect of Water Solubility and Stability.

Water solubility and structural stability are key merits for proteins defined by the primary sequence and 3D-conformation. Their manipulation represents important aspects of the protein design field that relies on the accurate placement of amino acids and molecular interactions, guided by underlying physiochemical principles. Emulated designer proteins with well-defined properties both fuel the knowledge-base for more precise computational design models and are used in various biomedical and nanotechnological applications. The continuous developments in protein science, increasing computing power, new algorithms, and characterization techniques provide sophisticated toolkits for solubility design beyond guess work. In this review, we summarize recent advances in the protein design field with respect to water solubility and structural stability. After introducing fundamental design rules, we discuss the transmembrane protein solubilization and de novo transmembrane protein design. Traditional strategies to enhance protein solubility and structural stability are introduced. The designs of stable protein complexes and high-order assemblies are covered. Computational methodologies behind these endeavors, including structure prediction programs, machine learning algorithms, and specialty software dedicated to the evaluation of protein solubility and aggregation, are discussed. The findings and opportunities for Cryo-EM are presented. This review provides an overview of significant progress and prospects in accurate protein design for solubility and stability.

Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies.

Although the therapeutic efficacy and commercial success of monoclonal antibodies (mAbs) are tremendous, the design and discovery of new candidates remain a time and cost-intensive endeavor. In this regard, progress in the generation of data describing antigen binding and developability, computational methodology, and artificial intelligence may pave the way for a new era of in silico on-demand immunotherapeutics design and discovery. Here, we argue that the main necessary machine learning (ML) components for an in silico mAb sequence generator are: understanding of the rules of mAb-antigen binding, capacity to modularly combine mAb design parameters, and algorithms for unconstrained parameter-driven in silico mAb sequence synthesis. We review the current progress toward the realization of these necessary components and discuss the challenges that must be overcome to allow the on-demand ML-based discovery and design of fit-for-purpose mAb therapeutic candidates.

Comparing 2 crystal structures and 12 AlphaFold2-predicted human membrane glucose transporters and their water-soluble glutamine, threonine and tyrosine variants.

Membrane transporters including glucose transporters (GLUTs) are involved in cellular energy supplies, cell metabolism and other vital biological activities. They have also been implicated in cancer proliferation and metastasis, thus they represent an important target in combatting cancer. However, membrane transporters are very difficult to study due to their multispan transmembrane properties. The new computational tool, AlphaFold2, offers highly accurate predictions of three-dimensional protein structures. The glutamine, threonine and tyrosine (QTY) code provides a systematic method of rendering hydrophobic sequences into hydrophilic ones. Here, we present computational studies of native integral membrane GLUTs with 12 transmembrane helical segments determined by X-ray crystallography and CryoEM, comparing the AlphaFold2-predicted native structure to their water-soluble QTY variants predicted by AlphaFold2. In the native structures of the transmembrane helices, there are hydrophobic amino acids leucine (L), isoleucine (I), valine (V) and phenylalanine (F). Applying the QTY code, these hydrophobic amino acids are systematically replaced by hydrophilic amino acids, glutamine (Q), threonine (T) and tyrosine (Y) rendering them water-soluble. We present the superposed structures of native GLUTs and their water-soluble QTY variants. The superposed structures show remarkable similar residue mean square distance values between 0.47 and 3.6 Å (most about 1-2 Å) despite >44% transmembrane amino acid differences. We also show the differences of hydrophobicity patches between the native membrane transporters and their QTY variants. We explain the rationale why the membrane protein QTY variants become water-soluble. Our study provides insight into the differences between the hydrophobic helices and hydrophilic helices, and offers confirmation of the QTY method for studying multispan transmembrane proteins and other aggregated proteins through their water-soluble variants.

Erratum: Comparing 2 crystal structures and 12 AlphaFold2-predicted human membrane glucose transporters and their water-soluble glutamine, threonine and tyrosine variants - CORRIGENDUM.

[This corrects the article DOI: 10.1017/qrd.2022.6.].

Unconstrained generation of synthetic antibody-antigen structures to guide machine learning methodology for antibody specificity prediction.

Machine learning (ML) is a key technology for accurate prediction of antibody-antigen binding. Two orthogonal problems hinder the application of ML to antibody-specificity prediction and the benchmarking thereof: the lack of a unified ML formalization of immunological antibody-specificity prediction problems and the unavailability of large-scale synthetic datasets to benchmark real-world relevant ML methods and dataset design. Here we developed the Absolut! software suite that enables parameter-based unconstrained generation of synthetic lattice-based three-dimensional antibody-antigen-binding structures with ground-truth access to conformational paratope, epitope and affinity. We formalized common immunological antibody-specificity prediction problems as ML tasks and confirmed that for both sequence- and structure-based tasks, accuracy-based rankings of ML methods trained on experimental data hold for ML methods trained on Absolut!-generated data. The Absolut! framework has the potential to enable real-world relevant development and benchmarking of ML strategies for biotherapeutics design.

Comparing Native Crystal Structures and AlphaFold2 Predicted Water-Soluble G Protein-Coupled Receptor QTY Variants.

Accurate predictions of 3-dimensional protein structures by AlphaFold2 is a game-changer for biology, especially for structural biology. Here we present the studies of several native chemokine receptors including CCR5, CCR9, CXCR2 and CXCR4 determined by X-ray crystallography, and their water-soluble QTY counter parts predicted by AlphaFold2. In the native structures, there are hydrophobic amino acids leucine (L), isoleucine (I), valine (V) and phenylalanine (F) in the transmembrane helices. These hydrophobic amino acids are systematically replaced by hydrophilic amino acids glutamine (Q), threonine (T), and tyrosine (Y). Thus, the QTY variants become water-soluble. We also present the superimposed structures of native CCR10, CXCR5, CXCR7 and an olfactory receptor OR1D2 and their water-soluble QTY variants. Since the CryoEM structural determinations for the QTY variants of CCR10QTY and OR1D2QTY are in progress, it will be of interest to compare them when the structures become available. The superimposed structures show remarkable similarity within RMSD 1Å-2Å despite significant sequence differences (~26%-~33%). We also show the differences of hydrophobicity patches between the native GPCR and their QTY variants. Our study provides insight into the subtle differences between the hydrophobic helices and hydrophilic helices, and may further stimulate designs of water-soluble membrane proteins and other aggregated proteins.