Call for Papers: GRC, CADD, and statistics, and all that

Area of Science:

• Computational chemistry
• cheminformatics
• pharmacology

Background:

• Computer-aided drug discovery (CADD) and molecular modeling often lack robust statistical integration.
• This limitation hinders the reliable calculation of crucial molecular properties.

Purpose of the Study:

• To investigate the barriers preventing wider statistical application in routine CADD.
• To increase awareness of the potential benefits and possibilities of statistical methods in drug discovery.

Main Methods:

• Discussion of practical statistical methods applicable to CADD.
• Addressing challenges in implementing standard statistical approaches.
• Presentation of interdisciplinary research on statistical successes and failures.

Main Results:

• Identified key obstacles to statistical adoption in CADD.
• Highlighted potential improvements in modeling reliability through statistical integration.
• Showcased examples of effective and ineffective statistical applications from other fields.

Conclusions:

• Enhanced statistical utilization can significantly improve CADD reliability.
• Further research and interdisciplinary collaboration are needed to overcome current limitations.
• Raising awareness is crucial for advancing the field.