Chemical transformation webserver for ADMET Optimization
OptADMET is a high-quality and comprehensive public chemical transformation webserver for rationalizing lead optimization. By comprehensively applying OptADMET webserver, chemists would achieve desirable ADMET optimization.
Introducing OptADMET
Chemical transformation webserver for ADMET Optimization
One of the great challenges in drug discovery is rationalizing lead optimization. In this phase, compounds that have been identified as the potential drug candidates need to be modified carefully with appropriate ADMET properties. The key questions faced by medicinal chemists are which compound(s) should be made next and how to balance multiple properties. To avoid the poor or ill-advised decisions, it is crucial to draw credible transformation rules from multiple experimental assays and apply them for efficient optimization. Therefore, OptADMET, the first integrated chemical transformation rule platform covering 32 important ADMET properties, is able to provide multiple-property rules and apply invaluable experience for lead optimization.
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01 High-quality and large optimization guidance database
Based on 177,191 experimental data, 41,779 credible transformation rules are provided for rendering desirable molecules. Besides, 239,194 accurate predicted molecular data are integrated for expansion, which have converted 146,450 rules as the supplement.
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02 Multi-property chemical rules with detailed information
All chemical transformation rules provide transformation environment, variety and credibility information, and more than 7,000 transformation rules own two and more property change. Such informative rules can benefit different research need.
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03 Effective multi-property optimization and comprehensive evaluation
Based on the large and credible rule database, user can achieve the efficient multi-parameter optimization for the queried molecule. Moreover, the ADMET profile of all optimized molecules provided by OptADMET is able to for comprehensively evaluate molecular potential.
Experimental Data
Experimental Transformation Rules
predicted Molecular Data
Rule Supplement