cheminformatics

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Translated

Cheminformatics pipeline for small-molecule property calculation, filtering, and similarity analysis using RDKit. Use when the user asks to compute molecular descriptors, filter compounds by Lipinski or Veber rules, detect PAINS, calculate fingerprint similarity, run matched molecular pair analysis, generate ADMET descriptors, or process SMILES. Triggers include "RDKit", "molecular descriptors", "Lipinski", "rule of five", "Veber", "PAINS", "pan-assay interference", "Morgan fingerprint", "Tanimoto", "fingerprint similarity", "matched molecular pair", "MMP", "mmpdb", "ADMET", "druglikeness", "SMILES", "cheminformatics", "compound filtering", "chemical similarity".

50installs

Sourceawslabs/hcls-agent-skills

Added on2026-10-08

NPX Install

npx skill4agent add awslabs/hcls-agent-skills cheminformatics

SKILL.md Content

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Cheminformatics (RDKit) — Pipeline Skill (Thin Scaffold)

Overview

Adds fingerprint selection logic, filter cascade ordering, and version-specific gotchas for RDKit workflows. The agent already knows RDKit syntax — this skill prevents parameter mismatches and deprecated API usage.

Usage

Activate when filtering compound libraries (Lipinski/Veber/PAINS)
Activate for fingerprint similarity search or clustering
Activate for matched molecular pair (MMP) analysis with mmpdb

Core Concepts

Filter cascade order: Lipinski → Veber → PAINS → similarity (cheapest first, most expensive last).

Fingerprint API: Use

rdFingerprintGenerator

module exclusively (since RDKit 2024.03). The

AllChem.GetMorganFingerprintAsBitVect()

path is deprecated and will be removed.

SMILES validation: Always parse with

sanitize=False

then explicit

SanitizeMol()

in try/except. Default

MolFromSmiles

silently returns None on partial failures.

Decision Logic

Fingerprint Selection

Goal	Fingerprint	Parameters	Tanimoto threshold
General similarity	Morgan (ECFP4)	radius=2, fpSize=2048	≥ 0.7
High-specificity matching	Morgan (ECFP6)	radius=3, fpSize=4096	≥ 0.6
Substructure screening	MACCS 166 keys	—	≥ 0.8
Pharmacophore similarity	FCFP	radius=2, `GetMorganFeatureAtomInvGen()`	≥ 0.6
Large-scale clustering	Morgan	radius=2, fpSize=1024	Speed over precision

Filter Thresholds

Filter	Rule	Threshold	Notes
Lipinski MW	≤ 500 Da	Allow ≤1 violation total	Not binary pass/fail
Lipinski LogP	≤ 5	—	—
Lipinski HBD	≤ 5	—	—
Lipinski HBA	≤ 10	—	—
Veber TPSA	≤ 140 Å²	Hard cutoff	—
Veber RotBonds	≤ 10	Hard cutoff	—
PAINS	A+B+C catalogs	HTS triage only	Don't apply to advanced compounds

MMP Analysis Decision

Scenario	Tool	Key parameter
SAR from compound pairs	mmpdb fragment → index → transform	`--min-pairs 3`
Property prediction	mmpdb predict	Requires indexed DB with property data
Core identification	`rdFMCS.FindMCS()`	`ringMatchesRingOnly=True, completeRingsOnly=True`
Large libraries (>10K)	mmpdb CLI	`--max-variable-size 10` to limit fragmentation

Critical Parameters

Parameter	Value	When to change
Morgan radius	2 (ECFP4)	3 for higher specificity
fpSize	2048	1024 for speed; 4096 for precision
includeChirality	False	True for stereo-sensitive applications
Lipinski max_violations	1	0 for strict; exempt biologics entirely
mmpdb --min-pairs	3	Lower for sparse datasets
mmpdb --max-variable-size	10	Increase for macrocycle transformations
PAINS catalogs	A+B+C (all three)	Never use partial sets

Common Mistakes

Wrong:

AllChem.GetMorganFingerprintAsBitVect()

→ Right:

rdFingerprintGenerator.GetMorganGenerator(radius=2, fpSize=2048).GetFingerprint(mol)

→ Why: AllChem FP functions deprecated since RDKit 2024.03, will be removed

Wrong: Default
```
MolFromSmiles(smi)
```
without error handling → Right:
```
MolFromSmiles(smi, sanitize=False)
```
+
```
SanitizeMol()
```
in try/except → Why: Default silently returns None; explicit sanitize catches partial failures
Wrong: Lipinski as hard binary filter → Right: Allow ≤1 violation → Why: Many approved drugs violate one rule; binary filtering rejects valid candidates
Wrong: PAINS on clinical candidates → Right: PAINS only for HTS library triage → Why: Designed for screening artifacts; flags valid advanced compounds
Wrong: Morgan radius=1 → Right: radius=2 minimum (ECFP4) → Why: Radius 1 loses structural information; too many false-positive similarities
Wrong: Comparing FPs with different radius or nBits → Right: Identical parameters for both FPs → Why: Tanimoto only meaningful in same parameter space
Wrong: Ignoring stereochemistry for chiral compounds → Right:
```
includeChirality=True
```
in generator → Why: Default treats enantiomers as identical
Wrong: Fixed 0.7 threshold for all FP types → Right: Validate threshold per fingerprint type and chemical series → Why: 0.7 convention is ECFP4-specific; other types need different cutoffs
Wrong: Raw SMILES into mmpdb → Right: Pre-canonicalize with
```
MolToSmiles(MolFromSmiles(smi))
```
→ Why: mmpdb expects canonical SMILES; non-canonical causes fragmentation errors
Wrong: Confusing LogP with LogD → Right: Use LogD at pH 7.4 for ionizable compounds; RDKit computes LogP only → Why: LogP overestimates lipophilicity for ionizable molecules at physiological pH

Response Format

Lead with the command or code the user needs — explain after
Structure as: confirm inputs → working code → key parameters explained → gotchas
One complete working example per task; do not show every alternative
Keep code comments minimal and functional
Target: 50-100 lines of code with brief surrounding explanation