The specific binding between antibodies (Ab) and antigens (Ag) is crucial for developing drugs and vaccines to treat major diseases. Therefore, accurate identification of antibody-antigen interactions (AAI) is crucial for a comprehensive understanding of antibody therapeutic mechanisms. While wet-lab methods accurately characterize AAI, they require significant human, financial, and time costs. Traditional computational methods help to reduce the resource consumption of AAI identification, but suffer from several problems, such as (1) they rely solely on sequence data, ignoring critical 3D structural determinants; (2) the scarcity of data on antibody-antigen interactions severely limits existing methods' ability to represent unseen antibodies; (3) they focus narrowly on paratope-epitope residues, overlooking the contextual information provided by distal non-binding regions that can influence interaction patterns. To address these issues, we present an innovative model that learns sequence and structural representations to predict antibody-antigen interactions (SSRAAI). We extracted structural features by constructing contact maps from predicted PDB 3D structures. Additionally, the integration of sequence features based on adaptive relational graphs led to enhanced prediction outcomes. Our approach offers a unique integration of 3D structural information from PDB with sequence data, applied directly to Ab and Ag. Comparative results on two datasets, HIV and SARS-CoV-2, demonstrate the validity of our approach in identifying AAIs.

Creating synthetic lines is the standard mating mode for commercial pig production. Traditional mating performance was evaluated through a strictly designed cross-combination test at the 'breed level' to maximize the benefits of production. The Duroc-Landrace-Yorkshire (DLY) three-way crossbred production system became the most widely used breeding scheme for pigs. Here, we proposed an 'individual level' genomic mating procedure that can be applied to commercial pig production with efficient algorithms for estimating marker effects and for allocating the appropriate boar-sow pairs, which can be freely accessed to public in our developed HIBLUP software at https://www.hiblup.com/tutorials#genomic-mating. A total of 875 Duroc boars, 350 Landrace-Yorkshire sows and 3573 DLY pigs were used to carry out the genomic mating to assess the production benefits theoretically. The results showed that genomic mating significantly improved the performances of progeny across different traits compared with random mating, such as the feed conversion rate, days from 30 to 120 kg and eye muscle area could be improved by -0.12, -4.64 d and 2.65 cm2, respectively, which were consistent with the real experimental validations. Overall, our findings indicated that genomic mating is an effective strategy to improve the performances of progeny by maximizing their total genetic merit with consideration of both additive and dominant effects. Also, a herd of boars from a richer genetic source will increase the effectiveness of genomic mating further.

MOTIVATION: Small non-coding RNAs (ncRNAs), especially microRNAs (miRNAs) and piwi-interacting RNAs (piRNAs), play key roles in many biological processes. However, only a few tools can be used to develop the optimal primer or probe design for the expression profile of small ncRNAs. Here, we developed sRNAPrimerDB, the first automated primer designing and query web service for small ncRNAs. RESULTS: The primer online designing module of sRNAPrimerDB is composed of primer design algorithms and quality evaluation of the polymerase chain reaction (PCR) primer. Five types of primers, namely, generic or specific reverse transcription primers, specific PCR primers pairs, TaqMan probe, double-hairpin probe and hybridization probe for different small ncRNA detection methods, can be designed and searched using this service. The quality of PCR primers is further evaluated using melting temperature, primer dimer, hairpin structure and specificity. Moreover, the sequence and size of each amplicon are also provided for the subsequent experiment verification. At present, 531 306 and 2 941 669 primer pairs exist across 223 species for miRNAs and piRNAs, respectively, according to sRNAPrimerDB. Several primers designed by sRNAPrimerDB are further successfully validated by subsequent experiments. AVAILABILITY AND IMPLEMENTATION: sRNAPrimerDB is a valuable platform that can be used to detect small ncRNAs. This module can be publicly accessible at http://www.srnaprimerdb.com or http://123.57.239.141. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.