Molecular intelligence
Molecular intelligence is an interdisciplinary field of science that combines molecular biology principles with artificial intelligence and computational biology.
It focuses on the understanding and manipulation of molecular structures and interactions for applications, especially in biotechnology and pharmaceutical research. In this area, computational tools, AI algorithms and big data analysis are used to predict the behavior of molecules, develop drugs and simulate biological processes. Key technologies include bioinformatics and molecular modeling.
The main goal of molecular intelligence is to accelerate scientific discoveries and improve the efficacy and precision of therapeutic interventions and biotechnological processes. In this field, computer-aided tools, AI algorithms and extensive data analysis are used to predict the behavior of molecules, develop drugs and simulate biological processes.
Key applications are drug discovery[1], enzyme-driven systems[2] and protein-based nano-machines. The integration of these technologies enables researchers to analyze large amounts of data of complete genomes and make predictions about the behavior of molecules and biological systems.
In drug research, molecular intelligence plays a crucial role in the identification and development of new drugs, for off-target analysis, the in-silico prediction of adverse side-effects and repurposing. By using AI algorithms and computer models, researchers can identify potential drug candidates and predict their efficacy and safety. Molecular intelligence also plays an important role in the analysis of enzyme activities, which are important for the development of new biotechnological processes.
Companies active in this area include BenevolentAI, which uses AI to improve drug discovery and development, Innophore, which specializes in AI-powered molecular analysis with a point-cloud based Catalophore technology, Atomwise, which focuses on AI for drug discovery, particularly on predicting drug-target interactions, Recursion Pharmaceuticals, which combines experimental biology with AI to unravel biological complexity and accelerate drug discovery, and Schrodinger, which provides software solutions and services for computational chemistry, including drug discovery.
Recent applications of molecular intelligence-based methods include predicting the binding affinity of SARS-CoV-2 variants to human cells[3], repurposing existing drugs for novel applications[4], genome-wide analysis of potential drug targets for emerging pathogens[5] or predicting massive protein-ligand interactions involving 36 billion chemical compounds.
References
- ↑ "AI's potential to accelerate drug discovery needs a reality check". Nature. 622 (7982): 217. 2023-10-10. Bibcode:2023Natur.622..217.. doi:10.1038/d41586-023-03172-6. PMID 37817040 Check
|pmid=value (help). - ↑ Markus, Braun; C, Gruber Christian; Andreas, Krassnigg; Arkadij, Kummer; Stefan, Lutz; Gustav, Oberdorfer; Elina, Siirola; Radka, Snajdrova (2023-11-03). "Accelerating Biocatalysis Discovery with Machine Learning: A Paradigm Shift in Enzyme Engineering, Discovery, and Design". ACS Catalysis. 13 (21): 14454–14469. doi:10.1021/acscatal.3c03417. ISSN 2155-5435. PMC 10629211 Check
|pmc=value (help). PMID 37942268 Check|pmid=value (help). - ↑ Köchl, Katharina; Schopper, Tobias; Durmaz, Vedat; Parigger, Lena; Singh, Amit; Krassnigg, Andreas; Cespugli, Marco; Wu, Wei; Yang, Xiaoli; Zhang, Yanchong; Wang, Welson Wen-Shang; Selluski, Crystal; Zhao, Tiehan; Zhang, Xin; Bai, Caihong (2023-01-14). "Optimizing variant-specific therapeutic SARS-CoV-2 decoys using deep-learning-guided molecular dynamics simulations". Scientific Reports. 13 (1): 774. Bibcode:2023NatSR..13..774K. doi:10.1038/s41598-023-27636-x. ISSN 2045-2322. PMC 9840421 Check
|pmc=value (help). PMID 36641503 Check|pmid=value (help). - ↑ Hetmann, M.; Langner, C.; Durmaz, V.; Cespugli, M.; Köchl, K.; Krassnigg, A.; Blaschitz, K.; Groiss, S.; Loibner, M.; Ruau, D.; Zatloukal, K.; Gruber, K.; Steinkellner, G.; Gruber, C. C. (2023-07-21). "Identification and validation of fusidic acid and flufenamic acid as inhibitors of SARS-CoV-2 replication using DrugSolver CavitomiX". Scientific Reports. 13 (1): 11783. Bibcode:2023NatSR..1311783H. doi:10.1038/s41598-023-39071-z. ISSN 2045-2322. PMC 10362000 Check
|pmc=value (help). PMID 37479788 Check|pmid=value (help). - ↑ Parigger, Lena; Krassnigg, Andreas; Grabuschnig, Stefan; Gruber, Karl; Steinkellner, Georg; Gruber, Christian C. (2023-12-12). Chang, Wen, ed. "AI-assisted structural consensus-proteome prediction of human monkeypox viruses isolated within a year after the 2022 multi-country outbreak". Microbiology Spectrum. 11 (6): e0231523. doi:10.1128/spectrum.02315-23. ISSN 2165-0497. PMC 10714838 Check
|pmc=value (help). PMID 37874150 Check|pmid=value (help).
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