Artificial intelligence and cheminformatics tools: a contribution to the drug development and chemical science

Abstract

In the ever-evolving field of drug discovery, the integration of Artificial Intelligence (AI) and Machine Learning (ML) with cheminformatics has proven to be a powerful combination. Cheminformatics, which combines the principles of computer science and chemistry, is used to extract chemical information and search compound databases, while the application of AI and ML allows for the identification of potential hit compounds, optimization of synthesis routes, and prediction of drug efficacy and toxicity. This collaborative approach has led to the discovery, preclinical evaluations and approval of over 70 drugs in recent years. To aid researchers in the pursuit of new drugs, this article presents a comprehensive list of databases, datasets, predictive and generative models, scoring functions and web platforms that have been launched between 2021 and 2022. These resources provide a wealth of information and tools for computer-assisted drug development, and are a valuable asset for those working in the field of cheminformatics. Overall, the integration of AI, ML and cheminformatics has greatly advanced the drug discovery process and continues to hold great potential for the future. As new resources and technologies become available, we can expect to see even more groundbreaking discoveries and advancements in these fields.

Communicated by Ramaswamy H. Sarma

Keywords:

• Drug discovery
• artificial intelligence
• cheminformatics
• pharmacokinetics
• molecular modeling and machine learning

Acknowledgement

Authors would like to thank Dr. Pankaj Mishra for his feedback during the preparation of the manuscript.

Author contribution

IS and BAB conceived the idea. IS, BAB and CA collected the literature and participated in writing. IF, BAB, CA, SSH, MAM, SG and THD proofread and edited the final version. All authors have read and approved the final version of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Availability of data and materials

The authors declared that the data supporting the findings of this study are available within the article.

Additional information

Funding

The authors extend their appreciation to the Deanship of Scientific Research, King Khalid University, Abha, Saudi Arabia, for funding this work under Grant No. RGP.1/304/44