Computer-Aided Chemical Drug Synthesis

Currently, the cost of bringing a single drug to the market exceeds $200 to $3 billion. A large part of this cost is attributed to two factors: the high rate of attrition of candidate molecules through clinical trials and the complexity of the drug discovery phase. Both of them require a large investment of time and resources. A stronger pipeline of preclinical drug candidates will have a beneficial impact on the downstream. Advances in computer hardware and computer methods are aimed at speeding up and improving all aspects of the typical drug discovery cycle (design-manufacture-test-analysis (DMTA)).

Application of Our Computer-Aided Chemical Drug Synthesis

With the deepening of quantum chemistry research and the improvement of computing software, they play an important role in the process of scientific research and chemistry teaching. We apply multiple quantum chemistry computing software to provide computer-aided chemical drug synthesis services in a competitive fashion. We have prepared the most convenient services for you.

• Computational planning of synthesis of natural products

Chemists study how nature builds the molecules and identify the key biosynthetic step in planning the syntheses procedure of natural products. Protheragen-ING uses both Quantum mechanics (QM) and molecular dynamics (MD) simulation to investigate the interactions of fundamental chemical forces in the field of complex small molecule synthesis using our professional knowledge of organic chemistry and data-based artificial intelligence (AI).

• Condition recommendation and pathway evaluation

In order to provide our clients with the optimal chemical condition and pathway, Protheragen-ING has established various methodologies to carry out reliable condition recommendation and pathway evaluation with high reliability and reproducibility by creating multiple machine-learning algorithms such as network searching, rule-based synthetic design and over-representation analysis method.

• Retrosynthetic route planning based on molecular similarity

As a purely data-driven reverse synthesis methodology, retrosynthetic route planning based on molecular similarity is used to design a synthetic route from a given ideal molecule. Our teams select and use reaction templates to generate ideal precursor molecules in the similarity-based method, in which various known reactions are applied to build the model.

• Synthetic products prediction and path formation

Nowadays, artificial intelligence (AI) technology has shown great potential in the field of drug design and synthesis. AI hase brought various opportunities for the development of the prediction of synthetic products and reaction path prediction. Protheragen-ING has introduced advanced AI approaches to provide high quality services of synthetic products prediction and path formation studies.

• Template-based computer-aided retrosynthetic route planning

The template-based computer-aided retrosynthetic route planning method is designed to generate one or more candidate precursors through the matching reaction rules in which the templates can be sorted by experts or automatically extracted from the reaction database. Our computer-aided chemical drug synthesis platform supports a diversity of machine learning (ML) methods such as deep neural network (DNN) model, Monte Carlo tree search and similarity-based approach.

• Template-free automatic retrosynthetic route planning

Compared to the template-based computer-aided retrosynthetic route planning method, template-free automatic retrosynthetic route planning has various advantages including small mount of calculation, without requirement of a manual coding, etc. Protheragen-ING has created a new template-free strategy for automatic reverse synthesis route planning to support your computer-aided chemical drug synthesis.