Neglected tropical diseases, such as Chagas disease caused by Trypanosoma cruzi, remain a critical global health problem, particularly in underprivileged communities. Our research aims to develop potential therapeutic agents by synthesizing and characterizing analogues of aureothin, a polyketide with known antiparasitic activity.
A novel statistical correlation method, MM-DP4+, was developed to enhance NMR-based molecular structure elucidation by significantly reducing computational costs through the use of MM-optimized geometries. A comprehensive evaluation of 36 theory levels identified SMD/ωB97XD/6-31+G**//MMFF as the most accurate and cost-effective approach, achieving 91% accuracy in stereochemical assignments. A Python-based software, DP4+App, was created to streamline the implementation of DP4+, MM-DP4+, and customizable DP4+ calculations via a user-friendly interface.
ViridisChem has built one of the largest and most comprehensive chemical databases and an in-silico data generator with a focus on toxicity of chemicals. The Chemical Analyzer tool offers critical information to help define safer-greener and sustainable product development.
Here are some powerful features we have added to our product Chemical Analyzer:
AI's potential in meeting sustainability challenges include improving resource management; mitigating wastes generated through industrial processes; and minimizing disruptions while still preserving excellent safety standards. AI tools have already been shown to improve processes for chemical engineering but AI as a part of a digital revolution in the chemical industries is still unfolding.
Digital automatization of chemistry to make chemical synthesis easy and instant. Chemify uses a programming language to employ the world’s largest database of validated chemical reactions. By implementing the full digital chemistry stack into their automated robotic synthesis cluster facility, Chemify can transform chemical code into real molecules on demand and at scale. Artificial intelligence is also used to discover and design novel molecules rapidly. Digitizing and automating chemistry helps prevent exposure to toxic chemicals in the workplace and waste generation.
Purpose:
The Data Science and Modeling for Green Chemistry award aims to recognize the research and development of computational tools that guide the design of sustainable chemical processes and the execution of green chemistry that demonstrates compelling environmental, safety, and efficiency improvements over current technologies in the pharmaceutical industry and its allied industrial partners.
Description:
