Project Grant R44GM131484

This Project Grant award from the National Institute of General Medical Sciences (NIGMS) Biomedical Research and Research Training program (CFDA 93.859) totaling $202,274 provides funding to Acpharis to develop an algorithm and software tool for predicting the structure and degradation efficiency of proteolysis targeting chimera (PROTAC) compounds. The key goals are to: Implement a computational protocol to accurately model PROTAC ternary complexes, including the optimal linker design to...

This $350,000 Project Grant award from the National Institute of General Medical Sciences (NIGMS) under the Biomedical Research and Research Training program (CFDA 93.859) supports the development of a high-resolution native capillary zone electrophoresis system with inline UV and native mass spectrometry capabilities for characterizing charge variants in biologics. The funded project aims to address critical challenges in the characterization and quality control of protein therapeutics by...

This Project Grant award of $408,007 from the National Science Foundation (NSF) Engineering program (CFDA 47.041) aims to develop a technology called "glycosequencing" that uses next-generation sequencing (NGS) to sequence and quantify glycan structures. The project will first identify an optimal set of lectins, biochemically characterize them, and prepare lectin barcoding for NGS. It will also build a training dataset using recombinant proteins produced in glycoengineered Chinese...

This Project Grant award from the National Institute of Environmental Health Sciences (NIEHS), under the Medical Library Assistance program (CFDA 93.879), provides $343,124 to The University of Kentucky Research Foundation to develop and validate structure-function-aware large protein language models (SF-PLM) for enhanced biomedical applications. The key objectives are to: (1) create large protein language models that incorporate 2D and 3D structural information using multi-view contrastive...

This Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering program (CFDA 47.070) provides $101,368 to North Carolina Agricultural and Technical State University (NC A&T) to develop new computational methods for de novo protein sequencing and filling gaps in protein scaffolds. The key products and services to be delivered include: Through a two-phase approach, the researchers will first analyze top-down and bottom-up mass...

The National Science Foundation Division of Information and Intelligent Systems awarded Indiana University a $113,029 Project Grant under the Computer and Information Science and Engineering program (CFDA 47.070). The grant supports research that will integrate deep learning and high-throughput experimentation to engineer proteins for non-native enzyme catalysis. Researchers will develop artificial intelligence models to interpret experimental data and guide iterative protein design. Two...

This Project Grant award from the National Institute of General Medical Sciences (NIGMS) Biomedical Research and Research Training program (CFDA 93.859) provides $591,842 to 3D Molecular Designs LLC to develop two applications leveraging machine learning and object detection technology. The first application will provide augmented reality-based feedback to students on their modeling of protein structures using 3D Molecular Designs' Mini-Toobers modeling tools. The second application will...

This Project Grant award from the National Science Foundation (CFDA 47.084 - NSF Technology, Innovation, and Partnerships) provides $274,640 to Protein Design Solutions LLC to develop a computational platform that can predict and mitigate protein aggregation issues in the development of protein therapeutics. The project aims to validate and enhance the platform's ability to identify aggregation-prone sites and suggest mutational strategies to stabilize proteins without disrupting their...

This three-year, $338,355 Project Grant from the National Science Foundation's Division of Chemistry and Mathematical and Physical Sciences program will support the development of new machine learning methods to design DNA and RNA aptamers for molecular targets. Principal Investigator Petr Sulc of Arizona State University will use restricted Boltzmann machine architectures to analyze sequences from selection experiments and naturally occurring non-coding RNAs to extract structural and...

This $350,000 Project Grant award from the National Center for Advancing Translational Sciences (NCATS), under the 93.350 CFDA program, supports the development of the Codomax EPI-MAX platform. This integrated omics and computational technology leverages cellular stress responses to enhance the production of difficult-to-express therapeutic proteins, with a focus on improving secretion and preventing aggregation in the Pichia pastoris expression system. The key products or services to be...