AbFlex: designing antibody complementarity determining regions with flexible CDR definition.

MOTIVATION: Antibodies are proteins that the immune system produces in response to foreign pathogens. Designing antibodies that specifically bind to antigens is a key step in developing antibody therapeutics. The complementarity determining regions (CDRs) of the antibody are mainly responsible for binding to the target antigen, and therefore must be designed to recognize the antigen. RESULTS: We develop an antibody design model, AbFlex, that exhibits state-of-the-art performance in terms of structure prediction accuracy and amino acid recovery rate. Furthermore, >38% of newly designed antibody models are estimated to have better binding energies for their antigens than wild types. The effectiveness of the model is attributed to two different strategies that are developed to overcome the difficulty associated with the scarcity of antibody-antigen complex structure data. One strategy is to use an equivariant graph neural network model that is more data-efficient. More importantly, a new data augmentation strategy based on the flexible definition of CDRs significantly increases the performance of the CDR prediction model. AVAILABILITY AND IMPLEMENTATION: The source code and implementation are available at https://github.com/wsjeon92/AbFlex.

Rising of LOXHD1 as a signature causative gene of down-sloping hearing loss in people in their teens and 20s.

BACKGROUND: Down-sloping sensorineural hearing loss (SNHL) in people in their teens and 20s hampers efficient learning and communication and in-depth social interactions. Nonetheless, its aetiology remains largely unclear, with the exception of some potential causative genes, none of which stands out especially in people in their teens and 20s. Here, we examined the role and genotype-phenotype correlation of lipoxygenase homology domain 1 (LOXHD1) in down-sloping SNHL through a cohort study. METHODS: Based on the Seoul National University Bundang Hospital (SNUBH) genetic deafness cohort, in which the patients show varying degrees of deafness and different onset ages (n=1055), we have established the 'SNUBH Teenager-Young Adult Down-sloping SNHL' cohort (10-35 years old) (n=47), all of whom underwent exome sequencing. Three-dimensional molecular modelling, minigene splicing assay and short tandem repeat marker genotyping were performed, and medical records were reviewed. RESULTS: LOXHD1 accounted for 33.3% of all genetically diagnosed cases of down-sloping SNHL (n=18) and 12.8% of cases in the whole down-sloping SNHL cohort (n=47) of young adults. We identified a potential common founder allele, as well as an interesting genotype-phenotype correlation. We also showed that transcript 6 is necessary and probably sufficient for normal hearing. CONCLUSIONS: LOXHD1 exceeds other genes in its contribution to down-sloping SNHL in young adults, rising as a signature causative gene, and shows a potential but interesting genotype-phenotype correlation.

Hypomorphic Mutations in TONSL Cause SPONASTRIME Dysplasia.

SPONASTRIME dysplasia is a rare, recessive skeletal dysplasia characterized by short stature, facial dysmorphism, and aberrant radiographic findings of the spine and long bone metaphysis. No causative genetic alterations for SPONASTRIME dysplasia have yet been determined. Using whole-exome sequencing (WES), we identified bi-allelic TONSL mutations in 10 of 13 individuals with SPONASTRIME dysplasia. TONSL is a multi-domain scaffold protein that interacts with DNA replication and repair factors and which plays critical roles in resistance to replication stress and the maintenance of genome integrity. We show here that cellular defects in dermal fibroblasts from affected individuals are complemented by the expression of wild-type TONSL. In addition, in vitro cell-based assays and in silico analyses of TONSL structure support the pathogenicity of those TONSL variants. Intriguingly, a knock-in (KI) Tonsl mouse model leads to embryonic lethality, implying the physiological importance of TONSL. Overall, these findings indicate that genetic variants resulting in reduced function of TONSL cause SPONASTRIME dysplasia and highlight the importance of TONSL in embryonic development and postnatal growth.

FP2VEC: a new molecular featurizer for learning molecular properties.

MOTIVATION: One of the most successful methods for predicting the properties of chemical compounds is the quantitative structure-activity relationship (QSAR) methods. The prediction accuracy of QSAR models has recently been greatly improved by employing deep learning technology. Especially, newly developed molecular featurizers based on graph convolution operations on molecular graphs significantly outperform the conventional extended connectivity fingerprints (ECFP) feature in both classification and regression tasks, indicating that it is critical to develop more effective new featurizers to fully realize the power of deep learning techniques. Motivated by the fact that there is a clear analogy between chemical compounds and natural languages, this work develops a new molecular featurizer, FP2VEC, which represents a chemical compound as a set of trainable embedding vectors. RESULTS: To implement and test our new featurizer, we build a QSAR model using a simple convolutional neural network (CNN) architecture that has been successfully used for natural language processing tasks such as sentence classification task. By testing our new method on several benchmark datasets, we demonstrate that the combination of FP2VEC and CNN model can achieve competitive results in many QSAR tasks, especially in classification tasks. We also demonstrate that the FP2VEC model is especially effective for multitask learning. AVAILABILITY AND IMPLEMENTATION: FP2VEC is available from https://github.com/wsjeon92/FP2VEC. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Effect of Electric Current on Oxidation of Zn Films to ZnO Films Using Electrochemical System.

In this study, we fabricated ZnO films from Zn films using an electrochemical system under different oxidation currents of 0.2, 0.5, 1, and 2 mA. Most of the samples showed fluctuating potential values near 0 V, and the pH value also showed the same tendency. The morphology of the ZnO films showed a polycrystalline film form and short hexagonal pillars at the underside and upside, respectively, due to the preferred growth of (101) orientation. In the photoluminescence spectra, the highest value of the near band-edge and deep-level emission ratio indicated that a high-quality ZnO film was obtained. To investigate the photoresponse properties, we measured the dark current and photocurrent using a current-voltage measurement system. The ZnO films with the highest quality showed a large number of photocurrent generations and high responsivity value. We expect that this method can offer a novel method of studying the growth of high-quality ZnO films for application to optoelectronic devices.

An enhanced variant effect predictor based on a deep generative model and the Born-Again Networks.

The development of an accurate and reliable variant effect prediction tool is important for research in human genetic diseases. A large number of predictors have been developed towards this goal, yet many of these predictors suffer from the problem of data circularity. Here we present MTBAN (Mutation effect predictor using the Temporal convolutional network and the Born-Again Networks), a method for predicting the deleteriousness of variants. We apply a form of knowledge distillation technique known as the Born-Again Networks (BAN) to a previously developed deep autoregressive generative model, mutationTCN, to achieve an improved performance in variant effect prediction. As the model is fully unsupervised and trained only on the evolutionarily related sequences of a protein, it does not suffer from the problem of data circularity which is common across supervised predictors. When evaluated on a test dataset consisting of deleterious and benign human protein variants, MTBAN shows an outstanding predictive ability compared to other well-known variant effect predictors. We also offer a user-friendly web server to predict variant effects using MTBAN, freely accessible at http://mtban.kaist.ac.kr . To our knowledge, MTBAN is the first variant effect prediction tool based on a deep generative model that provides a user-friendly web server for the prediction of deleteriousness of variants.

Autonomous molecule generation using reinforcement learning and docking to develop potential novel inhibitors.

We developed a computational method named Molecule Optimization by Reinforcement Learning and Docking (MORLD) that automatically generates and optimizes lead compounds by combining reinforcement learning and docking to develop predicted novel inhibitors. This model requires only a target protein structure and directly modifies ligand structures to obtain higher predicted binding affinity for the target protein without any other training data. Using MORLD, we were able to generate potential novel inhibitors against discoidin domain receptor 1 kinase (DDR1) in less than 2 days on a moderate computer. We also demonstrated MORLD's ability to generate predicted novel agonists for the D4 dopamine receptor (D4DR) from scratch without virtual screening on an ultra large compound library. The free web server is available at http://morld.kaist.ac.kr .

Metformin restores the penile expression of nitric oxide synthase in high-fat-fed obese rats.

Obesity is a well-known risk factor for erectile dysfunction, which is associated with reduced penile nitric oxide synthase (NOS) expression. Recently it was reported that metformin activates AMP-activated protein kinase (AMPK), which increases the expression of neuronal (n) NOS and endothelial (e) NOS. Thus, to evaluate whether metformin restores NOS expression in penile tissue, we measured penile expression of nNOS and eNOS after 4 weeks of metformin treatment (300 mg/kg/d) in 5-month-old high-fat-fed obese (HFO) rats. HFO rats have increased fat accumulation in visceral areas and marked suppression of nNOS and eNOS expression in penile tissue. However, metformin treatment decreased visceral fat deposition and restored nNOS and eNOS expression in penile tissue. The levels of AMPK and phosphorylated AMPK were also decreased in HFO rats but were subsequently elevated by metformin treatment. These results suggest that expression of NOS was suppressed by the high-fat diet but restored by metformin treatment. The effect of metformin on the expression of NOS may be associated with its activation of AMPK.

Identification and Clinical Implications of Novel MYO15A Mutations in a Non-consanguineous Korean Family by Targeted Exome Sequencing.

Mutations of MYO15A are generally known to cause severe to profound hearing loss throughout all frequencies. Here, we found two novel MYO15A mutations, c.3871C>T (p.L1291F) and c.5835T>G (p.Y1945X) in an affected individual carrying congenital profound sensorineural hearing loss (SNHL) through targeted resequencing of 134 known deafness genes. The variant, p.L1291F and p.Y1945X, resided in the myosin motor and IQ2 domains, respectively. The p.L1291F variant was predicted to affect the structure of the actin-binding site from three-dimensional protein modeling, thereby interfering with the correct interaction between actin and myosin. From the literature analysis, mutations in the N-terminal domain were more frequently associated with residual hearing at low frequencies than mutations in the other regions of this gene. Therefore we suggest a hypothetical genotype-phenotype correlation whereby MYO15A mutations that affect domains other than the N-terminal domain, lead to profound SNHL throughout all frequencies and mutations that affect the N-terminal domain, result in residual hearing at low frequencies. This genotype-phenotype correlation suggests that preservation of residual hearing during auditory rehabilitation like cochlear implantation should be intended for those who carry mutations in the N-terminal domain and that individuals with mutations elsewhere in MYO15A require early cochlear implantation to timely initiate speech development.