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Modeling a crowdsourced definition of molecular complexity.

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  • 1Structural Chemistry, Merck Research Laboratories, Merck & Co., Inc., P.O. Box 2000, Rahway, New Jersey 07065, United States.

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Crowdsourcing molecular complexity assessments using 386 chemists proved effective. A quantitative structure-activity relationship (QSAR) model accurately predicted mean molecular complexity, demonstrating crowdsourcing

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Area of Science:

  • Medicinal Chemistry
  • Computational Chemistry
  • Drug Discovery

Background:

  • Assessing molecular complexity is crucial in drug discovery.
  • Traditional methods for complexity evaluation can be subjective and time-consuming.
  • Crowdsourcing offers a novel approach to aggregate expert opinions.

Purpose of the Study:

  • To investigate the utility of crowdsourcing for evaluating molecular complexity.
  • To develop a predictive model for molecular complexity using quantitative structure-activity relationship (QSAR) methods.
  • To correlate crowdsourced complexity metrics with synthetic and process mass intensity (PMI) data.

Main Methods:

  • 386 chemists rated the complexity of 2681 molecules on a scale of 1-5.
  • Mean complexity was calculated as the average of all votes per molecule.
  • QSAR models were built using physical descriptors to predict mean complexity.
  • Cross-validation (R² ≈ 0.88) was used to assess model performance.

Main Results:

  • Mean molecular complexity was reliably predicted by QSAR models with high self-consistency.
  • Crowdsourced complexity showed correlation with literature-derived synthetic complexity metrics.
  • Mean complexity correlated with process mass intensity (PMI) from both literature and in-house data.
  • Crowdsourcing demonstrated significant power in aggregating subjective assessments.

Conclusions:

  • Crowdsourcing provides a robust method for assessing molecular complexity.
  • QSAR modeling of crowdsourced complexity is feasible and accurate.
  • Molecular complexity, assessed via crowdsourcing, can serve as a valuable metric for process optimization and program evaluation.