Small MoleculeLibrary

Assay.Works' library of 150,000 small molecule compounds originates from the screening deck of a renowned bio-pharmaceutical enterprise enriched with compounds from a leading commercial supplier. It has been exclusively designed by experienced computational chemists and meticulously curated for optimal lead-likeness and diversity. To ensure the quality of compound samples in the library, molecular mass and purity have been verified by LC/UV/MS analysis during admission.

Assay.Works sets itself apart with its state-of-the-art compound management facility. A cutting-edge acoustic dispensing platform allows to precisely dispense quantities ranging from nanoliters to microliters, resulting in significant resource savings. Sample management operations, including compound registration, screening plate production, and inventory management are backed by Mosaic Sample Management, a leading LIMS solution.

Modular Screening Library

Assay.Works offers unique and non-redundant small molecule sets which can be combined to modular high-throughput screening decks:

  • 150,000 commercially available compounds with freedom to operate. Full disclosure [1].
  • Carefully selected by experienced chemists. Lead-likeness and chemotype filtered.
  • Molecular mass and purity verified [2].

 

Lipinski Rule-of-5

Property Prediction

Physico-chemical property profile according to Lipinski’s Rule of 5 (left); Prediction of compound properties and drug-like features: Colloidal Aggregation[i], Permeability[ii], Bioavailability[iii], Solubility[iv], PAINS[v] (right)

AW1: 70k, maximized diversity

  • Assembled from the screening deck of a major bio-pharmaceutical company.
  • Compounds from 70+ vendors
Molecular Weight358.16
H-bond Donors (Lipinski)0.96
H-bond Acceptors (Lipinski)5.87
SlogP2.97
TPSA71.10
Rotatable Bonds4.34
Fsp30.31

Physico-chemical properties of AW1 set (average)

Vendor distribution of AW1

DvS: 80k, diversity set

  • Custom selection from ChemBridge’s DIVERSet-EXP and DIVERSet-CL.
  • Excellent lead/drug-like property profile, Fsp3 enriched
  • Analogs available from ChemBridge’s catalog of 1,200k compounds
Molecular Weight327.92
H-bond Donors (Lipinski)1.07
H-bond Acceptors (Lipinski)5.37
SlogP2.48
TPSA62.96
Rotatable Bonds4.65
Fsp30.42

Physico-chemical properties of DvS set (average)

Modular Screening Decks for Various Applications and Budgets

Compound sets and diversity metrics based on Bemis-Murcko clusters (1)[i]

BioactivesCollection

Assay.Works offers a modular toolbox of eleven non-redundant sets of 5000 bioactive small molecules, including endogenous metabolites, enzyme inhibitors, receptor ligands, and FDA-approved drugs.

  • Broad coverage of drug target classes, therapeutic indications, and research areas
  • Structurally diverse, pharmacologically active, and cell permeable
  • Screen-ready DMSO stocks, quality-controlled by HPLC and NMR
  • Rich set of chemical and biological annotations

 

Applications

  • Target validation
  • pathway deconvolution
  • combination studies
  • Assay validation
  • exploratory screening

 

Pathway

Immunology (IMN) Immunology/Inflammation-related compounds. Targets include CCR, COX, Interleukin Related, IRAK, MyD88, PDE, PD-1/PD-L1, TLR, and more. Includes some compounds related to tumor-immunology.

292

Epigenetics (EPG) Epigenetics-related compounds targeting HDAC, Histone Demethylase, Histone Acetyltransferase (HAT), DNA Methyltransferase (DNMT), Epigenetic Reader Domain, MicroRNA, etc.

302

Neuronal Signaling (NRS) Compounds related to Neuronal Signaling. Targets include 5-HT Receptor, AChE, Adrenergic Receptor, AMPAR, Beta- and Gamma-secretase, Dopamine Receptor, FAAH, Melatonin Receptor, AChR, Opioid Receptor, etc.

497

Autophagy (APH) Compounds with biological activity used for autophagy research and associated assays. Targets include Autophagy, LRRK2, ULK, etc.

427

Cell Death (CLD) Compounds related to cell cycle, cell survival, DNA damage, and apoptosis. Targets includes CDK, ROCK, Aurora Kinase, ATM/ATR, DNA-PK, DNA/RNA Synthesis, Bcl-2 Family, Caspase, DAPK, IAP, MDM2/p53, PKD, Survivin, etc.

405

Metabolism (MET) Metabolism/Protease-related small molecules. Targets include PDE, Cytochrome P450, HMG-CoA Reductase, DPP4, Proteasome, HCV Protease, IDO, Cathepsin, MMP, etc.

608

Target Class

Transporter & Ion Channels (TIC) Modulators of ion channels and membrane transporters related to targets and pathways not contained in the above sets.

237

GPCR & G-Protein (GPR) Modulators of GPCR and G-proteins related to targets and pathways not contained in the above sets.

317

Kinase Inhibitors (KIN) Protein kinase inhibitors related to pathways not contained in the above sets.

429

Other

Anti-Infection (AIN) Anti-infective compounds targeting Bacteria, Fungi, Parasite, CMV, HIV, SARS-CoV, Influenza Virus, etc.

442

Other Bioactives (OBA) Other bioactive compounds related to targets and pathways not contained in the above sets.

1,095

Sample Management

Our comprehensive services related to small molecule libraries include:

  • Cost-effective compound identification and selection
  • High-throughput compound analysis 
  • Multi-format plating and reformatting, accommodating volumes from nanoliters to microliters
  • Preparation of assay.ready compound plates for for screening
  • Expedited order fulfillment and worldwide delivery
  • Low and ultra-low temperature storage and hosting options for external libraries
  • Full traceability of compound- and sample-level information in real-time

[1] Structures and annotations disclosed under confidentiality agreement upon request.
[2] At the time added to the original source collections. To validate sample integrity, random samples are re-analyzed during the lifetime of stored liquid aliquots.

[i] Small Colloidal Aggregating Molecule (SCAM) prediction based on a consensus model. Fail criteria: 95% consensus that a molecule is a SCAM. Molina C, Ait-Ouarab L, Minoux H. J Chem Inf Model. 2022.

[ii] Caco-2 permeability prediction based on a conditional consensus model. Pass criteria: High to medium permeability, > 2x10-6 cm/s. Falcón-Cano G, Molina C, Cabrera-Pérez MÁ. ADME Prediction with KNIME: An automated prediction platform for in silico assessment of Caco-2 permeability. 2022, Submitted.

[iii] Human oral bioavailability prediction. Pass criteria: F > 50%. Falcón-Cano G, Molina C, Cabrera-Pérez MÁ. J Chem Inf Model. 2020

[iv] Aqueous solubility prediction based on consensus model. Pass criteria: logS >= -5 (S in mol/l). Falcón-Cano G, Molina C, Cabrera-Pérez MÁ. ADMET DMPK. 2020

[v] Pan Assay Interference Compound (PAINS) filter using a published KNIME workflow. Saubern S, Guha R, Baell JB. Mol Inform. 2011

[vi] BemisGW, Murcko MA. J Med Chem. 1996