Lipid Bilayer Strengthens the Cooperative Network of a Membrane-Integral Enzyme.

Lipid bilayer provides a two-dimensional hydrophobic solvent milieu for membrane proteins in cells. Although the native bilayer is widely recognized as an optimal environment for folding and function of membrane proteins, the underlying physical basis remains elusive. Here, employing the intramembrane protease GlpG of Escherichia coli as a model, we elucidate how the bilayer stabilizes a membrane protein and engages the protein's residue interaction network compared to the nonnative hydrophobic medium, micelles. We find that the bilayer enhances GlpG stability by promoting residue burial in the protein interior compared to micelles. Strikingly, while the cooperative residue interactions cluster into multiple distinct regions in micelles, the whole packed regions of the protein act as a single cooperative unit in the bilayer. Molecular dynamics (MD) simulation indicates that lipids less efficiently solvate GlpG than detergents. Thus, the bilayerinduced enhancement of stability and cooperativity likely stems from the dominant intraprotein interactions outcompeting the weak lipid solvation. Our findings reveal a foundational mechanism in the folding, function, and quality control of membrane proteins. The enhanced cooperativity benefits function facilitating propagation of local structural perturbation across the membrane. However, the same phenomenon can render the proteins' conformational integrity vulnerable to missense mutations causing conformational diseases1,2.

Unsupervised and supervised AI on molecular dynamics simulations reveals complex characteristics of HLA-A2-peptide immunogenicity.

Immunologic recognition of peptide antigens bound to class I major histocompatibility complex (MHC) molecules is essential to both novel immunotherapeutic development and human health at large. Current methods for predicting antigen peptide immunogenicity rely primarily on simple sequence representations, which allow for some understanding of immunogenic features but provide inadequate consideration of the full scale of molecular mechanisms tied to peptide recognition. We here characterize contributions that unsupervised and supervised artificial intelligence (AI) methods can make toward understanding and predicting MHC(HLA-A2)-peptide complex immunogenicity when applied to large ensembles of molecular dynamics simulations. We first show that an unsupervised AI method allows us to identify subtle features that drive immunogenicity differences between a cancer neoantigen and its wild-type peptide counterpart. Next, we demonstrate that a supervised AI method for class I MHC(HLA-A2)-peptide complex classification significantly outperforms a sequence model on small datasets corrected for trivial sequence correlations. Furthermore, we show that both unsupervised and supervised approaches reveal determinants of immunogenicity based on time-dependent molecular fluctuations and anchor position dynamics outside the MHC binding groove. We discuss implications of these structural and dynamic immunogenicity correlates for the induction of T cell responses and therapeutic T cell receptor design.

Development of InDel markers for interspecific hybridization between hill pigeons and feral pigeons based on whole-genome re-sequencing.

Interspecific hybridization occurs among birds, and closely related sister taxa tend to hybridize at a high rate. Genomic hybridization markers are useful for understanding the patterns and processes of hybridization and for conserving endangered species in captivity and the wild. In this study, we developed genomic hybridization markers for the F1 progeny of the sister taxa feral pigeons (Columba livia var. domestica) and endangered hill pigeons (Columba rupestris) (family Columbidae). Using whole-genome re-sequencing data, we performed genome-wide analysis for insertion/deletion (InDel) polymorphisms and validated using primers. We conducted polymerase chain reaction (PCR) and agarose gel electrophoresis to identify species-specific InDels. We produced eight F1 hybrids of hill and feral pigeons, and their samples were tested by re-performing analyses and sequencing using 11 species-specific InDel polymorphisms. Eight InDel markers simultaneously amplified two DNA fragments from all F1 hybrids, and there was no abnormality in the sequencing results. The application of genomic tools to detect hybrids can play a crucial role in the assessment of hybridization frequency in the wild. Moreover, systematic captive propagation efforts with hybrids can help control the population decline of hill pigeons.

Deep generative molecular design reshapes drug discovery.

Recent advances and accomplishments of artificial intelligence (AI) and deep generative models have established their usefulness in medicinal applications, especially in drug discovery and development. To correctly apply AI, the developer and user face questions such as which protocols to consider, which factors to scrutinize, and how the deep generative models can integrate the relevant disciplines. This review summarizes classical and newly developed AI approaches, providing an updated and accessible guide to the broad computational drug discovery and development community. We introduce deep generative models from different standpoints and describe the theoretical frameworks for representing chemical and biological structures and their applications. We discuss the data and technical challenges and highlight future directions of multimodal deep generative models for accelerating drug discovery.

Whole-genome sequencing revealed different demographic histories among the Korean endemic hill pigeon (Columba rupestris), rock pigeon (Columba livia var. domestica) and oriental turtle dove (Streptopelia orientalis).

BACKGROUND: The family Columbidae is known as the pigeon family and contains approximately 351 species and 50 genera. Compared to the wealth of biological and genomic information on these Columba livia var. domesteca, information on Columba rupestris and Streptopelia orientalis has been rather limited. The C. rupestris population size is decreasing in Korea. OBJECTIVES: Whole-genome sequencing and identification of population characterization of each species based genome variation on 9 Korean pigeon and dove samples, namely, six hill pigeon (C. rupestris), one rock pigeon (C. livia var. domestica) and two oriental turtle dove (S. orientalis) samples. RESULTS: The whole genome of 9 genotypes were sequenced and mapped to the C. livia reference genome. Sequence alignment showed over 96% identity in C. rupestris and 94% identity in S. orientalis to the reference genome (GenBank assembly accession: GCA_001887795.1). Sequence variations, including single nucleotide polymorphisms (SNPs), insertions and deletions (InDels), and structural variations, revealed that intergenus (Columba vs. Streptopelia) variations were approximately four times higher than intragenus variations (C. livia vs. C. rupestris). Of the two Columba species, C. livia var. domestica is closer to S. orientalis than C. rupestris. Pairwise sequentially Markovian coalescent (PSMC) demographic history analysis revealed that the three species underwent a common population bottleneck between 105 and 120 Kya; since then, the effective population sizes of the rock pigeon and oriental turtle dove have increased. CONCLUSION: The effective population size of the hill pigeon, an Endangered Species of Grade II in Korea, has increased slowly from the second severe bottleneck that occurred approximately 0.5-1.4 × 104 years ago. Our results showed no relationship between copy number variation in the Norrie disease protein (NDP) regulatory regions and plumage color patterns. We report the first comparative analysis of three pigeon genomes.

Analysis of Training and Seed Bias in Small Molecules Generated with a Conditional Graph-Based Variational Autoencoder─Insights for Practical AI-Driven Molecule Generation.

The application of deep learning to generative molecule design has shown early promise for accelerating lead series development. However, questions remain concerning how factors like training, data set, and seed bias impact the technology's utility to medicinal and computational chemists. In this work, we analyze the impact of seed and training bias on the output of an activity-conditioned graph-based variational autoencoder (VAE). Leveraging a massive, labeled data set corresponding to the dopamine D2 receptor, our graph-based generative model is shown to excel in producing desired conditioned activities and favorable unconditioned physical properties in generated molecules. We implement an activity-swapping method that allows for the activation, deactivation, or retention of activity of molecular seeds, and we apply independent deep learning classifiers to verify the generative results. Overall, we uncover relationships between noise, molecular seeds, and training set selection across a range of latent-space sampling procedures, providing important insights for practical AI-driven molecule generation.

Population genetic structure and conservation management of hill pigeons (Columba rupestris) recently endangered in South Korea.

BACKGROUND: Hill pigeons (Columba rupestris) are close to local extinction (ca. less than 100 individuals) in South Korea where a variety of conservation management procedures are urgently required. OBJECTIVE: This study was aimed at determining the conservation direction of captive propagation and reintroduction of hill pigeons using genetic information based on mitochondrial DNA. We also evaluated the extent of hybridization between hill pigeons and cohabiting domestic pigeons. METHODS: We used 51 blood samples of hill pigeons from Goheung (GH), Gurye (GR), and Uiryeong (UR), and domestic pigeons cohabiting with hill pigeon populations. Genetic diversity, pairwise Fst, analysis of molecular variance, and haplotype network analysis were used to examine the genetic structure of hill pigeons. RESULTS: Hill pigeons that inhabited South Korea were not genetically distinct from Mongolian and Russian populations and showed relatively low genetic diversity compared with other endangered species in Columbidae. The GR population that exhibited the largest population size showed lower genetic diversity, compared to the other populations, although the pairwise Fst values of the three populations indicated low genetic differentiation. The GH and GR populations were confirmed to lack hybridization, relatively, whereas the UR population was found to exhibit some degrees of hybridization. CONCLUSION: To conserve hill pigeons with low genetic diversity and differentiation in South Korea, the conservation process of captive propagation and reintroduction may require artificial gene flows among genetically verified populations in captivity and wildness. The introduction of foreign individuals from surrounding countries is also considered an alternative strategy for maintaining genetic diversity.

Simplified, interpretable graph convolutional neural networks for small molecule activity prediction.

We here present a streamlined, explainable graph convolutional neural network (gCNN) architecture for small molecule activity prediction. We first conduct a hyperparameter optimization across nearly 800 protein targets that produces a simplified gCNN QSAR architecture, and we observe that such a model can yield performance improvements over both standard gCNN and RF methods on difficult-to-classify test sets. Additionally, we discuss how reductions in convolutional layer dimensions potentially speak to the "anatomical" needs of gCNNs with respect to radial coarse graining of molecular substructure. We augment this simplified architecture with saliency map technology that highlights molecular substructures relevant to activity, and we perform saliency analysis on nearly 100 data-rich protein targets. We show that resultant substructural clusters are useful visualization tools for understanding substructure-activity relationships. We go on to highlight connections between our models' saliency predictions and observations made in the medicinal chemistry literature, focusing on four case studies of past lead finding and lead optimization campaigns.

CASTELO: clustered atom subtypes aided lead optimization-a combined machine learning and molecular modeling method.

BACKGROUND: Drug discovery is a multi-stage process that comprises two costly major steps: pre-clinical research and clinical trials. Among its stages, lead optimization easily consumes more than half of the pre-clinical budget. We propose a combined machine learning and molecular modeling approach that partially automates lead optimization workflow in silico, providing suggestions for modification hot spots. RESULTS: The initial data collection is achieved with physics-based molecular dynamics simulation. Contact matrices are calculated as the preliminary features extracted from the simulations. To take advantage of the temporal information from the simulations, we enhanced contact matrices data with temporal dynamism representation, which are then modeled with unsupervised convolutional variational autoencoder (CVAE). Finally, conventional and CVAE-based clustering methods are compared with metrics to rank the submolecular structures and propose potential candidates for lead optimization. CONCLUSION: With no need for extensive structure-activity data, our method provides new hints for drug modification hotspots which can be used to improve drug potency and reduce the lead optimization time. It can potentially become a valuable tool for medicinal chemists.

Nano-Crystallization Behavior and Optical Properties of Diopside: Eu2O3-Based Glass-Ceramic System.

In this study, glass-ceramic was prepared by adding TiO2 as a nucleating agent to induce the internal crystallization behavior of diopside (CaO-MgO-2SiO2)-based glass. The optimum composition for producing a transparent glass-ceramic was a composition of 15 wt% of TiO2 mixed with 85% diopside. The light transmittance of the specimen decreased as the heat treatment temperature increased. When 394 nm excitation light was incident on the glass-ceramic containing 0.05% Eu2O3, red light of 614 nm wavelength emitted. We examined the relationship between the light emission mechanism and the crystal structure of the diopside-based glass-ceramic. We also discussed the applicability of the specimens prepared in this study as light emitting materials in various fields.

Structural cavities are critical to balancing stability and activity of a membrane-integral enzyme.

Packing interaction is a critical driving force in the folding of helical membrane proteins. Despite the importance, packing defects (i.e., cavities including voids, pockets, and pores) are prevalent in membrane-integral enzymes, channels, transporters, and receptors, playing essential roles in function. Then, a question arises regarding how the two competing requirements, packing for stability vs. cavities for function, are reconciled in membrane protein structures. Here, using the intramembrane protease GlpG of Escherichiacoli as a model and cavity-filling mutation as a probe, we tested the impacts of native cavities on the thermodynamic stability and function of a membrane protein. We find several stabilizing mutations which induce substantial activity reduction without distorting the active site. Notably, these mutations are all mapped onto the regions of conformational flexibility and functional importance, indicating that the cavities facilitate functional movement of GlpG while compromising the stability. Experiment and molecular dynamics simulation suggest that the stabilization is induced by the coupling between enhanced protein packing and weakly unfavorable lipid desolvation, or solely by favorable lipid solvation on the cavities. Our result suggests that, stabilized by the relatively weak interactions with lipids, cavities are accommodated in membrane proteins without severe energetic cost, which, in turn, serve as a platform to fine-tune the balance between stability and flexibility for optimal activity.

Modeling and Structural Characterization of the Sweet Taste Receptor Heterodimer.

Sweet taste receptor, a heterodimer belonging to the class C G-protein coupled receptor (GPCR) family and composed of the T1R2 and T1R3 subunits, is responsible for the perception of natural sugars, sweet proteins, various d-amino acids, as well as artificial sweeteners. Despite the critical importance of the sweet receptor not only in mediating gustation but also in its role in the food industry, the architecture of the T1R2-T1R3 complex and the mechanism by which extracellular stimuli induce conformational changes that are propagated to the intracellular milieu, i.e., the signal transduction pathway, remain largely unknown. Here, we constructed and characterized a full-length structural model of the T1R2-T1R3 receptor, including both the transmembrane (TM) and extracellular (EC) domains of the heterodimer, using comparative modeling and extensive all-atom molecular dynamics simulations. Several heterodimer interfaces were first examined for the TM domain, and conformational changes occurring at the intracellular side and associated with the receptor's activation were characterized. From the analysis on the simulated data, putative allosteric binding sites for ligands, ions, and cholesterol were proposed. Also, insights into the protein interface of the TM domain upon activation are provided. The EC domain of the heterodimer, including both the Venus flytrap and cysteine-rich domains, was also investigated. Several important intersubunit interactions located at regions responsible for the receptor's proper function were observed, which resemble those recently identified in other class C GPCR members. Integration of the results from the TM and EC domains facilitates the generation of a full-length T1R2-T1R3 receptor. These findings along with the full-length structural model of the T1R2-T1R3 receptor provide a structural framework that may assist in understanding the mechanistic details associated with the receptor activation process for the sweet T1R2-T1R3 receptor as well as other members of the same family.

Raptor genomes reveal evolutionary signatures of predatory and nocturnal lifestyles.

BACKGROUND: Birds of prey (raptors) are dominant apex predators in terrestrial communities, with hawks (Accipitriformes) and falcons (Falconiformes) hunting by day and owls (Strigiformes) hunting by night. RESULTS: Here, we report new genomes and transcriptomes for 20 species of birds, including 16 species of birds of prey, and high-quality reference genomes for the Eurasian eagle-owl (Bubo bubo), oriental scops owl (Otus sunia), eastern buzzard (Buteo japonicus), and common kestrel (Falco tinnunculus). Our extensive genomic analysis and comparisons with non-raptor genomes identify common molecular signatures that underpin anatomical structure and sensory, muscle, circulatory, and respiratory systems related to a predatory lifestyle. Compared with diurnal birds, owls exhibit striking adaptations to the nocturnal environment, including functional trade-offs in the sensory systems, such as loss of color vision genes and selection for enhancement of nocturnal vision and other sensory systems that are convergent with other nocturnal avian orders. Additionally, we find that a suite of genes associated with vision and circadian rhythm are differentially expressed in blood tissue between nocturnal and diurnal raptors, possibly indicating adaptive expression change during the transition to nocturnality. CONCLUSIONS: Overall, raptor genomes show genomic signatures associated with the origin and maintenance of several specialized physiological and morphological features essential to be apex predators.

Rotating Arm Internally Can Change the Arthroscopic Diagnosis of a Partial-thickness Tear of the Subscapularis.

BACKGROUND: The aims of this study were (1) to examine the footprint of the subscapularis tendon using the traditional posterior portal and 30° arthroscope by simple internal rotation of the arm during surgery, and (2) to classify the pattern of a subscapularis partial-thickness tear. METHODS: This study analyzed a total of 231 patients with a partial-thickness subscapularis tear from 550 consecutive patients undergoing an arthroscopic operation who had a visualization of the subscapularis tendon footprint by internal rotation of the arm. First, the patients were classified into four categories according to the tear pattern: (1) stable lamination, (2) unstable lamination, (3) avulsion, and (4) laminated avulsion. Randomized arthroscopic videos were reviewed blindly by two independent orthopedic surgeons. The pattern of the tear of the subscapularis at the neutral position and after internal rotating the arm were assessed and compared with the treatment decision (level IV case series). RESULTS: Stable lamination, unstable lamination, avulsion, and laminated avulsion were observed in 9.1% (n=21), 20.8% (n=48), 41.1% (n=95), and 29.0% (n=67) of cases, respectively. In 145 out of 231 cases (62.8%), the decision was changed after inspecting the footprint after internal rotation of the arm, and the treatment method was changed in 116 (50.2%) cases. CONCLUSIONS: In a subscapularis tendon partial-thickness tear, inspecting the footprint of the subscapularis tendon is essential to diagnosing and deciding on the appropriate treatment. In addition, simply internal rotating the arm during surgery when using the traditional posterior portal and 30° arthroscope can be a valuable method.

Arthroscopic Capsular Repair without Relaying Sutures: 'Simple Sewing Technique'.

We report a simple technique for repairing capsular tear, using only a hook-like, cannulated instrument and braided sutures without relaying steps. A No. 2 braided suture is passed through the lumen of the instrument. Under direct arthroscopic view, the tip of the instrument is passed through the side of the capsule that has previously been separated with the probe. One end of the suture is retrieved with a grasper through a separate portal. The tip is moved back without withdrawing through the skin, and reinserted into the other side of the capsule. Holding the end retrieved earlier, the other end of the suture is retrieved with a suture retriever. After complete removal of the instrument, the suture is tied through a cannula using the standard knot tying techniques. The same procedures are repeated for other required knots.

Complete mitochondrial genome of Aethia cristatella (Charadriiformes: Alcidae).

The complete mitochondrial genome sequence of the crested auklet, Aethia cristatella, was obtained using high-throughput whole genome sequencing. This is the first report indicating that the complete mitochondrial genome of Aethia has been sequenced. The circular genome is 16,848 bp in length. It contains thirteen protein-coding genes, twenty-two transfer RNAs, two ribosomal RNAs, and a control region. The ND3 gene possessed an insertion mutation. Maximum likelihood phylogenetic analysis demonstrated that A. cristatella is the sister clade of P. aleuticus clustered with the Alcinae species, belonging to Alcidae.

Molecular mechanism of phosphoinositides' specificity for the inwardly rectifying potassium channel Kir2.2.

Phosphoinositides are essential signaling lipids that play a critical role in regulating ion channels, and their dysregulation often results in fatal diseases including cardiac arrhythmia and paralysis. Despite decades of intensive research, the underlying molecular mechanism of lipid agonism and specificity remains largely unknown. Here, we present a systematic study of the binding mechanism and specificity of a native agonist, phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2) and two of its variants, PI(3,4)P2 and PI(3,4,5)P3, on inwardly rectifying potassium channel Kir2.2, using molecular dynamics simulations and free energy perturbations (FEPs). Our results demonstrate that the major driving force for the PI(4,5)P2 specificity on Kir2.2 comes from the highly organized salt-bridge network formed between the charged inositol head and phosphodiester linker of PI(4,5)P2. The unsaturated arachidonic chain is also shown to contribute to the stable binding through hydrophobic interactions with nearby Kir2.2 hydrophobic residues. Consistent with previous experimental findings, our FEP results confirmed that non-native ligands, PI(3,4)P2 and PI(3,4,5)P3, show significant loss in binding affinity as a result of the substantial shift from the native binding mode and unfavorable local solvation environment. However, surprisingly, the underlying molecular pictures for the unfavorable binding of both ligands are quite distinctive: for PI(3,4)P2, it is due to a direct destabilization in the bound state, whereas for PI(3,4,5)P3, it is due to a relative stabilization in its free state. Our findings not only provide a theoretical basis for the ligand specificity, but also generate new insights into the allosteric modulation of ligand-gated ion channels.

Rare Dissipative Transitions Punctuate the Initiation of Chemical Denaturation in Proteins.

Protein unfolding dynamics are bound by their degree of entropy production, a quantity that relates the amount of heat dissipated by a nonequilibrium process to a system's forward and time-reversed trajectories. We here explore the statistics of heat dissipation that emerge in protein molecules subjected to a chemical denaturant. Coupling large molecular dynamics datasets and Markov state models with the theory of entropy production, we demonstrate that dissipative processes can be rigorously characterized over the course of the urea-induced unfolding of the protein chymotrypsin inhibitor 2. By enumerating full entropy production probability distributions as a function of time, we first illustrate that distinct passive and dissipative regimes are present in the denaturation dynamics. Within the dissipative dynamical region, we next find that chymotrypsin inhibitor 2 is strongly driven into unfolded states in which the protein's hydrophobic core has been penetrated by urea molecules and disintegrated. Detailed analyses reveal that urea's interruption of key hydrophobic contacts between core residues causes many of the protein's native structural features to dissolve.

Charging nanoparticles: increased binding of Gd@C82(OH)22 derivatives to human MMP-9.

Unlike most matrix metalloproteinase (MMP) inhibitors, which target the conserved catalytic zinc site, Gd@C82(OH)22 indirectly inhibits MMP-9 activity by binding at the ligand specificity S1' loop. The allosteric binding makes Gd@C82(OH)22 a promising inhibitor selective for MMP-9. However, the hydrophobic nature of the aromatic carbon cage may cause Gd@C82(OH)22 to self-aggregate in aqueous solutions, hence weakening the binding. In this study, we designed Gd@C82(OH)22 derivatives aiming at improving the binding affinity for MMP-9. Upon a mutation that substitutes a new functional group (-PO42-, -CH2CO2-, -CO2-, -NH3+, or -CONH2) for a hydroxyl group on the fullerenol surface, we calculated the changes in the binding free energy to the catalytic domain of human MMP-9 using the free energy perturbation (FEP) method. We found that the higher the net charge of the functional group, the stronger the binding. Compared with Gd@C82(OH)22, Gd@C82(OH)21(PO4)2- binds at least 1.5 to 2.5 kcal mol-1 more strongly to MMP-9. The binding is specifically controlled by electrostatic interactions between the phosphate group and the charged residues at the binding site. In addition to the net charge, the binding free energy can be delicately adjusted by other factors, such as the functionalization site on Gd@C82(OH)22, the local environment of the putative binding site of MMP-9, and the presence of ions near the charged functional group. The results of our study shed light on the potential of developing Gd@C82(OH)22 derivatives as nanodrugs for treating the pathological diseases associated with unregulated MMP-9 activity.

T cell receptors for the HIV KK10 epitope from patients with differential immunologic control are functionally indistinguishable.

HIV controllers (HCs) are individuals who can naturally control HIV infection, partially due to potent HIV-specific CD8+ T cell responses. Here, we examined the hypothesis that superior function of CD8+ T cells from HCs is encoded by their T cell receptors (TCRs). We compared the functional properties of immunodominant HIV-specific TCRs obtained from HLA-B*2705 HCs and chronic progressors (CPs) following expression in primary T cells. T cells transduced with TCRs from HCs and CPs showed equivalent induction of epitope-specific cytotoxicity, cytokine secretion, and antigen-binding properties. Transduced T cells comparably, albeit modestly, also suppressed HIV infection in vitro and in humanized mice. We also performed extensive molecular dynamics simulations that provided a structural basis for similarities in cytotoxicity and epitope cross-reactivity. These results demonstrate that the differential abilities of HIV-specific CD8+ T cells from HCs and CPs are not genetically encoded in the TCRs alone and must depend on additional factors.