Automatic design of protein binder structures using AI!
In recent years, functional protein binders have become important in drug discovery for controlling and exploring protein functions. However, their design is very complex and not easy, even with the use of generative AI. However, with Discovery Studio, it is possible to automatically design the structure and sequence of binders in an all-in-one approach. The execution steps are quite simple. - Molecular structure of the target protein - Residues at the interaction site (when a specific target is chosen) - Size of the binder to be designed You only need to set the three points above. Data regarding the structure and sequence of the binder is generated from scratch, and candidates that meet the minimum design requirements are explored. Furthermore, the discovered candidates are evaluated using a scoring function, improved iteratively to enhance the scores, and ultimately, the "desired parameter set" and "the complex structure of the binder and target" are listed along with their scores. For a detailed technical explanation, please visit our introduction page below! https://www.wavefront.co.jp/tech-blog/posts/ai-assisted-design.html
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basic information
★Product Name BIOVIA DiscoveryStudio 【Features】 ■Support for a wide range of drug discovery modalities - In addition to the currently mainstream small molecule drugs (small molecule ligands), it includes numerous specialized tools for biopharmaceuticals that are actively researched and developed (mAbs, ADCs, bispecific antibodies, multispecific antibodies, fusion proteins, mRNA vaccines). ■Support for a wide range of drug design methods - Capable of 3D designing lead compounds for various scenarios with different target structures and numbers of known active substances (supports combinations of structure-based design, ligand-based design, fragment-based design, and de novo design methods). ■Support for a wide range of drug discovery phases - Provides a useful set of tools and workflows simultaneously for various situations such as target validation, large-scale virtual screening, lead identification, mechanism of action elucidation, ADME-Tox prediction, stability prediction, and lead optimization. *For more details, please refer to the related links or contact us.
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【Applications (Partial)】 - Homology modeling of three-dimensional structures - Reconstruction of loops and side chains, structural optimization - "Conformation search" - Fragment-based molecular construction, etc. *For more details, please refer to the related links or feel free to contact us.
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Our company develops and sells a "Maintenance Management System" for managing and operating various plants, factories, and other facilities and assets. Currently, this system is undergoing significant evolution into one that incorporates IoT technologies, such as sensor information and input from tablet devices, as well as AI technologies like machine learning, featuring functions for failure prediction and automatic scheduling. Additionally, as part of the recent trend towards digital transformation (DX), there is a growing movement to digitize and automate manufacturing processes and research and development sites in factories to enhance operational efficiency. In line with this trend, our company provides a solution aimed at improving efficiency in research and development environments, known as the Laboratory Information Management System (LIMS), which includes features such as workflow management, data tracking, data management, data analysis, and integration of electronic lab notebooks.