Application scenario-oriented molecule generation platform developed for drug discovery.

Design of molecules for candidate compound selection is one of the central challenges in drug discovery due to the complexity of chemical space and requirement of multi-parameter optimization. Here we present an application scenario-oriented platform (ID4Idea) for molecule generation in different scenarios of drug discovery. This platform utilizes both library or rule based and generative based algorithms (VAE, RNN, GAN, etc.), in combination with various AI learning types (pre-training, transfer learning, reinforcement learning, active learning, etc.) and input representations (1D SMILES, 2D graph, 3D shape, binding site, pharmacophore, etc.), to enable customized solutions for a given molecular design scenario. Besides the usual generation followed screening protocol, goal-directed molecule generation can also be conducted towards predefined goals, enhancing the efficiency of hit identification, lead finding, and lead optimization. We demonstrate the effectiveness of ID4Idea platform through case studies, showcasing customized solutions for different design tasks using various input information, such as binding pockets, pharmacophores, and compound representations. In addition, remaining challenges are discussed to unlock the full potential of AI models in drug discovery and pave the way for the development of novel therapeutics.

Genome-wide association analyses identify new loci influencing intraocular pressure.

Elevated intraocular pressure (IOP) is a significant risk factor for glaucoma, the leading cause of irreversible blindness worldwide. While previous studies have identified numerous genetic variants associated with IOP, these loci only explain a fraction of IOP heritability. Recently established of biobank repositories have resulted in large amounts of data, enabling the identification of the remaining heritability for complex traits. Here, we describe the largest genome-wide association study of IOP to date using participants of European ancestry from the UK Biobank. We identified 671 directly genotyped variants that are significantly associated with IOP (P < 5 × 10-8). In addition to 103 novel loci, the top ranked novel IOP genes are LMX1B, NR1H3, MADD and SEPT9. We replicated these findings in an external population and examined the pleiotropic nature of these loci. These discoveries not only further our understanding of the genetic architecture of IOP, but also shed new light on the biological processes underlying glaucoma.

Genetic Risk Score Is Associated with Vertical Cup-to-Disc Ratio and Improves Prediction of Primary Open-Angle Glaucoma in Latinos.

PURPOSE: Genome-wide association studies have identified multiple genetic variants associated with vertical cup-to-disc ratio (VCDR). Genetic risk scores (GRS) examine the aggregate genetic effect of individual variants on a trait by combining these separate genetic variants into a single measure. The purpose of this study was to construct GRS for VCDR and to determine whether the GRS are associated with VCDR and whether the GRS increase the discriminatory ability for primary open-angle glaucoma (POAG) in a Latino population. DESIGN: Population-based genetic association study. PARTICIPANTS: A total of 4018 Latino participants recruited from Los Angeles. METHODS: Weighted and unweighted GRS were constructed using 68 previously reported VCDR single nucleotide polymorphisms (SNPs), as well as SNPs from our own genome-wide association data. Linear and logistic regression analyses examined the associations of GRS with VCDR and POAG, respectively. To evaluate the discriminatory ability of the GRS for POAG, we conducted receiver operating characteristic (ROC) analyses. MAIN OUTCOME MEASURES: The relationship between GRS and VCDR in Latinos. RESULTS: The GRS were associated significantly with VCDR (P < 0.0001), after adjusting for age, gender, central corneal thickness, intraocular pressure, and education. The weighted GRS explained an additional 2.74% of the variation in VCDR. Adding the weighted GRS derived from previously reported SNPs resulted in a moderate improvement in the discriminatory ability for POAG during ROC analyses, yielding an area under the ROC curve (AUC) of 0.735 (95% CI, 0.701-0.768). When our own SNPs were used, the AUC increased significantly to 0.809 (95% CI, 0.781-0.837; P < 0.0001). We obtained similar results for the unweighted GRS. CONCLUSIONS: To our knowledge, we identified a novel association between GRS and VCDR and its improvement in the discriminatory ability of POAG in a Latino population.