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22.4 Chemical Structure Analysis SAR and Library Design		Next

1. Getting Started: Opening Chemical Files and Calculating Properties

  • Open Chemical Data: Go to File > Open and select the drug_like.sdf file (see workshop files). The data will automatically display as a chemical spreadsheet within the ICM interface.
  • Calculate Molecular Properties: Navigate to Chemistry > Calculate Properties.
  • Select Desired Columns: Choose the properties you wish to calculate, such as MolLogP, MolLogD, MolLogS, PSA, and Molecular Volume.
  • Finalize Calculation: Click OK to populate the spreadsheet with the new property columns.

2. Working with Chemical Spreadsheets

  • Sort Data: Single left-click on any column header to sort the spreadsheet by that specific property.
  • Access Formatting Tools: Right-click on a column header to access options for formatting, color-coding, and other display settings.

3. Data Plotting and Visualization

  • Create a Plot: Click the Plot button in the table tools panel to open the Plot Options dialog.
  • Define Axes: In the Plot Options window, assign variables to the axes (e.g., molWeight for the x-axis and molLogP for the y-axis).
  • Customize Appearance: Adjust the point size and color-coding based on other properties like molLogS or molVolume.
  • Interactive Selection: Click and drag to select points on the plot; these will be highlighted in red on the graph and blue in the corresponding spreadsheet rows.
  • Structure Visualization (Balloons): In the Misc tab of Plot Options, enter "mol" into the Balloon field to display chemical structures when hovering over data points.

4. Advanced Filtering

  • Open Filter Panel: Click the Filter tab in the table tools panel.
  • Set Criteria: Drag the sliders or enter specific values for numerical properties like molLogP.
  • Chemical/Substructure Filtering: Use the Contains criteria to filter by a sketched substructure or use In List to match a specific set of IDs.
  • Apply Filters: Click the green tick button to update the spreadsheet view. An icon will appear on the column header to indicate an active filter.

5. Chemical Search and Substructure Analysis

  • Initiate Search: Open the ICM Chemical Search window.
  • Input Query: You can search by drawing a structure, entering a SMILES string, or using an InChIKey.
  • Define Search Conditions: Add conditions such as "molLogP < 4" or "molVolume < 450" to narrow your search across spreadsheets or external SDF files.
  • Annotate by Substructure: Go to Chemistry > Annotate by Substructure to group chemicals into series. Use the Draw Fragments tab to sketch and label specific scaffolds (e.g., "Sulfonyl Series").

6. Data Aggregation

  • Group Data: Right-click on a column (e.g., a "pKd" or ID column) and select Group by Column.
  • Select Aggregation Method: Choose how to aggregate data for each group, such as calculating the mean, median, or RMSD of values.
  • View Results: A new table will be created containing the unique values and their aggregated properties.

Multi Parameter Optimization

This tutorial introduces Multi-Parameter Optimization (MPO) in ICM, a framework for evaluating and optimizing compounds based on multiple molecular properties simultaneously. MPO combines key physicochemical descriptors such as lipophilicity, molecular weight, hydrogen bonding, and polar surface area into a single composite desirability score using customizable weighting and scoring functions. You will learn how MPO scores are constructed, how desirability functions are defined, and how built-in models such as Lipinski, CNS, and QED can be applied or customized. The tutorial also demonstrates how MPO can be used for compound prioritization, property balancing, and binary classification tasks in drug discovery workflows.

How to Enumerate a Library by Markush

This tutorial demonstrates how to create and use a Markush structure in ICM for representing and analyzing combinatorial chemical libraries. A Markush structure defines a common molecular scaffold with variable substituent positions (R-groups), enabling compact representation of large compound families. You will learn how to define attachment points on a scaffold, assign and manage R-group libraries, and generate a flexible chemical template that can be used for enumeration or downstream analysis. The workflow also illustrates how Markush structures support library design, virtual screening, and systematic exploration of chemical space by linking scaffold variability directly to real compound sets.

Library Decomposition

This tutorial demonstrates how to decompose a chemical library into scaffold and substituent components using ICM cheminformatics tools. Library decomposition is a key step in structure–activity relationship (SAR) analysis, allowing compounds to be broken down into a common core (scaffold) and associated R-groups for systematic comparison. In this exercise, you will learn how to define a Markush structure, map library members onto a shared scaffold, and extract corresponding R-group variations into a structured table. The resulting decomposition enables clear visualization of substitution patterns, facilitates SAR interpretation, and supports downstream applications such as lead optimization and library design.

Detecting Activity Cliffs

This tutorial introduces the concept of activity cliffs in medicinal chemistry and demonstrates how to identify them using ICM cheminformatics tools. Activity cliffs occur when structurally similar compounds exhibit large differences in biological activity, making them especially valuable for understanding structure–activity relationships (SAR). In this exercise, you will learn how to compare molecular pairs, quantify structural similarity, and map changes in potency to specific chemical modifications. The workflow highlights how activity cliff analysis can reveal key drivers of binding affinity and guide lead optimization by pinpointing small structural changes with large functional impact.

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