Focused Small Molecule Library Design

Home ServicesCompound & Biological Library DesignFocused Small Molecule Library Design

Overview

A focused library is a bet about where actives are likely to be found, and the quality of that bet determines the hit rate. We design target-class libraries — kinase, GPCR, protease, epigenetic, ion channel — by combining privileged scaffold knowledge, pharmacophore requirements from known actives, structure-based filtering against your target and property-based developability filters. Selections are clustered for diversity and sourced against real catalogues so the library can be bought rather than admired.

Schematic: screening runs as a cascade. Cheap filters remove the bulk, expensive scoring is applied only to survivors, and the attrition at every stage is reported.

Key Advantages

Target-Class Knowledge Applied

Scaffold and pharmacophore preferences established for the target class shape the selection, which is what separates a focused library from a diverse one.

Structure-Based Filtering Where Possible

When a structure exists, docking and shape filtering are used to bias the selection toward compounds complementary to your specific pocket, not merely to the class.

Diversity Measured And Enforced

Selections are clustered so that chemotype coverage is maximised for the number of compounds purchased, avoiding libraries dominated by a handful of series.

Purchasable By Construction

Compounds are sourced against current catalogues with availability, price band and purity information, so the design converts directly into a purchase order.

Where This Service Is Used

Assembling a screening library for a newly started target programme

Building a target-class library to support several programmes at once

Expanding an internal collection where chemotype coverage is weak

Designing a follow-up set around confirmed hits for SAR exploration

Selecting a fragment library shaped to a specific target family

Methods and Techniques Applied

Definition of the target class profile and the pharmacophore requirements from known actives

Catalogue assembly and standardisation with removal of problematic chemistry and reactive groups

Property, drug-likeness and ADMET pre-filtering to the agreed developability window

Similarity, shape and pharmacophore screening against known actives for the class

Structure-based docking filters where a target structure is available

Diversity clustering, coverage analysis and final selection with supplier sourcing

What We Need From You

The target or target class and, where available, the structure

Known actives for the target or class, which strongly shape the selection

Library size, budget and any preferred suppliers or existing purchasing arrangements

Assay format and constraints, including solubility and interference requirements

What You Receive

Final compound list with structures, supplier identifiers, catalogue numbers and price bands

Property and diversity analysis of the selected set with coverage statistics

Docking results and predicted interactions where structure-based selection was used

Selection rationale documenting every filter and threshold applied

Plate layout suggestions and any solubility or handling flags

What We Compute and Report

Property and drug-likeness distributions across the selected set

Diversity and chemotype coverage statistics quantifying what the library samples

Docking scores and predicted interactions where structure-based selection was applied

Per-compound supplier availability, catalogue identity and price band

Attrition at each filter stage, so the selection is fully traceable

Interpretation and Limitations

Computational predictions prioritise hypotheses; they do not independently establish binding, biological activity, therapeutic efficacy, safety or clinical validity. Performance depends on input quality, target class, the structural evidence available and the applicability domain of the selected methods. Scores used for ranking are comparative devices and should not be read as measured quantities. All deliverables are for research use only and are not intended for diagnostic or therapeutic use.

Specifications

Item	Specification	Notes
Library size	500–100,000 compounds	Set by budget and assay throughput
Typical turnaround	2–5 weeks	Including sourcing and availability checking
Target classes	Kinase, GPCR, protease, epigenetic and others	Custom classes supported
Output	Compound list + analysis	Ready for direct ordering

Service Workflow

Step 01

Scientific Consultation

We discuss the objective, the decision it supports and the data you hold. Nothing is quoted before we understand what the result has to answer.

Step 02

Feasibility Review

We check that the data, target class and available structural evidence can support the proposed approach, and say plainly where they cannot.

Step 03

Technical Proposal

Scope, methods, deliverables, timeline and price are confirmed in writing, together with the limitations we expect to report.

Step 04

Computation and QC

The analysis runs on pinned tool versions in a containerised environment, with quality checkpoints and method comparison where that is informative.

Step 05

Report and Follow-Up

You receive the ranked results, the documented methods, the limitations and a proposed validation plan, plus support in interpreting them.

Is This the Right Service for You?

Choose this service when

A screening collection must be assembled for a new programme or target class

An internal collection needs standardising, filtering and gap analysis

A follow-up set is needed around confirmed hits for SAR exploration

Consider another service when

You want to screen computationally rather than buy compounds

High-Throughput Virtual Screening

Novel chemistry must be designed rather than selected

De Novo Small Molecule Design

What Goes Wrong, and How We Handle It

The failure modes that produce confident-looking results which do not survive the next experiment. Each one is designed against rather than discovered afterwards.

Diversity and coverage statistics are computed, so size is not mistaken for breadth.

Case Studies

The situation

The team could buy roughly 5,000 compounds and wanted the best coverage for a kinase programme.

What the work involved

Catalogues were standardised and filtered, target-class pharmacophores were applied, structure-based filtering was used against the specific pocket, and the selection was clustered for diversity before sourcing.

What came back

A 5,000-compound list spanning the privileged hinge-binding chemotypes with coverage statistics reported, roughly 900 compounds removed as interference-prone before purchase.

Illustrative of the shape this work takes. Details are generalised, no client or target is identified, and scope and outcome vary with the system in question.

Questions We Are Asked Before Scoping

Note: ICDMO delivers computational (in silico) services. Results prioritise hypotheses for testing; they do not by themselves establish binding, biological activity, efficacy or safety. All deliverables are for research use only and are not intended for diagnostic or therapeutic use. Downstream experimental work is scoped separately and executed through qualified partners.

Get in Touch
about Focused Small Molecule Library Design

Tell us about the target, the data you hold and the decision the result needs to support. A scientist reviews every enquiry and replies within one business day.

Feasibility reviewed before any scope or price is fixed

Methods, parameters, confidence and limitations in every report

Confidentiality agreement available before data is shared