Explore the Chemical Space

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Navigate through vast Chemical Spaces at unprecedented speed.
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Understand similarity in a glimpse, with intuitive color-coding.
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Self-explanatory interface. Simply drag your query and get started.

Explore the Chemical Space

Let’s start with a thought experiment: If you fill an Olympic-size swimming pool with sand, you need a volume equal to approximately 10,000,000 cups of coffee. This volume, in turn, contains approximately 1013 grains of sand. Now, think of these individual grains of sand to represent possible drug candidates and you are looking for the one golden molecule. High-throughput virtual screening (HTVS) usually involves around five to ten millions of compounds which would be the same as looking for one specific grain in five to ten cups of sand. But who can guarantee that the perfect molecule is in one of the 5-10 cups you take from the pool? Chances at best are 1 in a million... Wouldn’t it be better and more promising if you can search in the whole pool or even thousands of them?
This is what infiniSee and Chemical Spaces are all about.

What infiniSee Does

discover infinisee

Discover unseen possibilities

Find molecules in unprecedented, large spaces of 1014 structures and more, or search your own in-house library for actives.
similarities infinisee

See hidden similarities

Similarity between a query and hit molecules is pleasingly visualized for you to select compounds effortlessly. infiniSee will show you why it considers something alike.
neighbors infinisee

Distant neighbors in action

Mine compound libraries for interesting scaffold hops. infiniSee finds molecules which are distant at first sight, yet very close in chemistry and pharmacophore-based action.
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Unlimited accessibles

From virtual to vial within days! Only what is highly likely to be formed in the lab will be proposed during infiniSee’s Chemical Space navigation. Collaboration with our partners allows delivery of desired hits within few weeks.

What infiniSee Does

Find hidden similarities

With infiniSee you can finally compare apples and oranges. The underlying concept of infiniSee is strikingly easy: Instead of searching already “assembled” molecules, we instead perform a combinatorial build-up of compounds from “fragments”. Sources of fragments can be either combinatorial libraries or any fragment-generating procedure. infiniSee opens the possibility to screen billions of compounds through its similarity search technology by navigating vast Chemical Spaces and searching for distant neighbors of a query molecule. Results will be delivered within typically less than a minute on a standard laptop. Optionally, you can define fuzzy pharmacophores to increase the diversity of scaffolds or request important molecular structures to be present in the hits.

Your molecule can be anywhere

The ingenious twist of infiniSee is the possibility of searching not only in colossal Chemical Spaces, but the ability to also comb through spaces of different origins. The number of identical structures in sets from different spaces was found to be extremely low (Lessel et al. 2019) due to the design and setup of the spaces, as well as the diversity of the employed building blocks. No matter how big your in-house library and no matter how many compounds you acquire to add to it, it will only be a tiny fraction of what your chemists are capable of synthesizing. Involving distinct Chemical Spaces increases your chances of finding accessible molecules you would have missed otherwise.

Create your own Chemical Space

Sometimes the perfect solution is within reach in your own compound library without realization. You can design your own Chemical Space with your accumulated, in-house knowledge and resources. Reactions and building blocks can be defined to create massive numbers of virtual compounds. Multiple big pharma companies built their own, in-house Chemical Spaces to search for scaffold alternatives to reduce costs and time.

Five reasons for infiniSee

Chemical Spaces
infiniSee opens the possibility to screen billions of compounds through its similarity search technology. Search in one of our partners’ Chemical Spaces to obtain commercially available compounds (eXplore, Freedom Space, GalaXi, CHEMriya and REAL Space) or literature-based virtual Chemical Space with high likelihood of synthetic accessibility (KnowledgeSpace).
Desired compounds of our partners can be purchased and delivered to your table within weeks.

Create your own Chemical Space with CoLibri


infiniSee Version 5.1 — Artemis

Time to experience the thrill of the hunt with infiniSee 5 — Artemis!

Version 5.1 introduces the well-know Bemis-Murcko scaffold and skeleton clustering to the Analyzer Mode which augments the compound selection and prioritization process: Given a set of molecules, infiniSee calculates prominent molecular motifs which can be used to group compounds into subsets. A powerful tool to spot frequent and unique patterns to enrich the chemical diversity for subsequent purposes.
Furthermore, visual highlighting is introduced to the Analog Hunter. Running the SpaceLight algorithm, Analog Hunter retrieves close analogs to a query compound from Chemical Spaces based on Tanimoto molecular fingerprint similarity. The colorful depiction helps users to understand the fingerprint alignment of the building block substructures to the query molecule to spot areas of high similarity and differences.

Important note: In order to run the Analog Hunter infiniSee requires the latest versions of the Chemical Spaces (as of March 8th).

For older versions and an elaborate changelog please visit here.



Let’s compare Chemical Spaces to sauerkraut. The concept of fermented cabbage exists in many world cuisines; kimchi in Korea, kapusta kiszona in Poland, curtido in El Salvador. Although they follow similar preparational steps, the taste varies greatly due to the local ingredients used. Chemical Spaces behave alike: The knowledge and building blocks used to build up the Chemical Space differ between companies and methods involved. The overlaps between two Chemical Spaces can be surprisingly miniscule (Lessel et al. 2019 and Rarey et al. 2021).
By searching in several Chemical Spaces you will maximize your success rate to find a diverse, promising molecules.
infiniSee is an easy-to-use app that searches superbig, combinatorial on-demand Chemical Spaces such as Enamine's REAL Space within seconds. We think this is unique.
And it comes with two core comparison algorithms. That by itself is a nice thing:
One is tuned to hop away in the molecular structure, yet stay "similar" to your query molecule. This is the Scaffold Hopper Mode: Its results obtained from a chemist's point of view are that the molecules are 'aligned' without using any 3D coordinates. This means the chemist can understand why the molecules are awarded a certain similarity. Also, the fuzziness of the descriptor makes it ideal for finding scaffold hops.
The other Mode is the Analog Hunter Mode, introduced in May 2023: This lets you investigate the close analogs "around" a query molecule. It uses the well-known ECFP4 similarity descriptor — but applied to the superbig on demand Chemical Spaces.
After performing a search with infiniSee your results will be presented in a table. The column "Source" tells you the origin of the Chemical Space that contains your solution; the ID of the respective result molecule is shown in the "Name" column.
Compounds can be ordered by sending a quote request to the compound vendor with the following information:
Requested structures in SMILES or SD format, Compound ID (concatenated), and amount requested.

For compounds from Ambinter's AMBrosia Space, send your request to
For compounds from eMolecule's eXplore Space, send your request to
For compounds from Enamine's REAL Space, send your request to
For compounds from WuXi's GalaXi Space please send your request to
For compounds from OTAVA's CHEMriya Space please send your request to
For compounds from Chemspace's Freedom Space please send your request to
Any usage with a graphical user interface requires a local graphics card, i.e., a local computer. This can therefore not work from remote.
Commandline and KNIME runs however can be triggered from remote.
Please contact us if you need to work from home during the Corona pandemic.
  1. RAM: 16 GB would be good, anything beyond is better.
  2. CPU: Our tools are not very hungry — yet they profit from multiple CPUs, because they have parallelized algorithms implemented. If in doubt rather choose more slower CPUs than one faster one.
  3. Graphics: It is important to know that a local graphics card is mandatory for infiniSee and SeeSAR.

Update to the latest driver, and check — even if Windows tells you that you are up-to-date. Lenovo and other computers with onboard graphics, please navigate to this link to check if there is a newer driver available for you.
An elaborated list of the respective operating system (OS) requirements can be found here.
infiniSee can calculate and predict following parameters of a molecule that can be further used for filtering steps and compound assessment: HYDE-based (Lipophilic) ligand efficacy (LE/LLE), molecular weight, logP, total polar surface area (TPSA) of a compound, H-bonds, H-bond acceptors and donators, heavy atoms, aromatic rings, maximum ring size, total charge, and presence of covalent warheads. You can also calculcate and filter for following numbers: odd torsions, heavy atoms, (aromatic) rings, aromatic atoms, nitrogen and oxygen atoms, halogens, stereo centers, stereo bonds, and rotatble bonds. With this you can easily tailor your filters for particular compound features and
Furthermore, infiniSee supports the Optribrium expansion to predict a variety of important ADME parameters for further compound assessment:
ADME parameter
Cytochrome P450 CYP2C9 pKi prediction. Affinity prediction of the compound to bind at the enzyme involved in several metabolic drug pathways.
Cytochrome P450 CYP2D6 classification. Compounds are predicted to be in one of four categories: ‘low’ for compounds with a pKi<5, ‘medium for compounds with a pKi between 5 and 6, ‘high for compounds with a pKi between 6 and 7, and ‘very high’ for compounds with a pKi>7.
Classification of compounds into ‘+’-category if log([brain]:[blood])≥-0.5 and ‘-’category if log([brain]:[blood])<-0.5.
Logarithm of brain-blood partition coefficient of a compound. Can be used as indicator for CNS active compounds.
Human intestinal absorption classification. Compound which are predicted to be absorbed ≥30% are classified with ‘+’, compounds which are predicted to be absorbed <30% are classified with ‘-’.
P-glycoprotein 1 (also known as multidrug resistance protein 1 (MDR1) and ATP-binding cassette sub-family B member 1 (ABCB1)) transport classification. Predicts if a compound is a substrate of P-gp.
Plasma protein binding classification. Predicts a classification of ‘low’ for compounds which are <90% bound and high for compounds which are >90% bound.
Prediction of pIC50 values for inhibition of human Ether-a-go-go Related Gene (hERG) potassium channels expressed in mammalian cells.
Logarithm of n-octanol-water partition coefficient (also known as n-octanol-water partition ratio) at fixed physiological pH 7.4. Used to describe the relationship between lipophilicity and hydrophilicity of an ionized compound.
Logarithm of n-octanol-water partition coefficient. Used to describe the relationship between lipophilicity and hydrophilicity of a neutral compound.
Logarithm of intrinsic aqueous solubility in µM for neutral compounds.
Logarithm of intrinsic aqueous solubility at physiological pH 7.4 in µM for ionized compounds.

Couldn’t find what you are looking for?
Visit our elaborative FAQ section or the first aid section



SpaceMACS is a substructure search tool for combinatorial Chemical Spaces. It mines the ultra-large compound collections for molecules containing a molecular motif of interest. Setting itself apart from typical exact substructure search methods, SpaceMACS possesses the capability to uncover closely-related molecules with minor deviations when an exact match is not found. SpaceMACS was developed in collaboration with the University of Hamburg (ZBH). Find out more about SpaceMACS here (PDF).


SpaceLight is a Chemical Space exploration tool which screens vast combinatorial compound spaces for close analogs of a query compound based on Tanimoto-like fingerprint similarity. SpaceLight was developed in collaboration with the University of Hamburg (ZBH). Find out more about SpaceLight here (PDF).


FTrees is a highly efficient software tool for fuzzy similarity searching. It uses the Feature Trees descriptor and is perfect to spot those non-obvious similarities in virtual screening. The Feature Tree descriptor captures a molecule’s overall topology and its pharmacophore properties. The similarity of two such descriptors is based on an alignment (shown above by the color-coding of related functional groups).

Find out more about FTrees here (PDF).

Optibrium - ADME properties prediction

Physicochemical properties are an important factor to consider to decide if a compound is promising drug candidate. Early assessment of ADME parameters can predict toxicity issues and absorption challenges in the early stages of drug discovery saving time and ressources. While infiniSee can calculate a variety of interesting filter parameters (e.g. rotable bonds, molecular weight, TPSA), it also supports ADME parameter predictions by the optional StarDrop module by Optibrium. With this users have the possibility to calculate important parameters like CYP enzyme affinity, blood brain barrier to blood distribution, logS, and many more.

Find out more about Optibrium ADME properties here (PDF).

Recent success stories

This study highlights the potential of precise substructural search with SpaceMACS in vast Chemical Spaces. It features a case study with torasemide as query molecule and search results from indivual tools with different purposes as well as a discussion about overlaps of those.
Maximum Common Substructure Searching in Combinatorial Make-on-Demand Compound Spaces.
Schmidt, R.; Klein, R.; Rarey, M.
J. Chem. Inf. Model. 2021.
Following the NIH virtual workshop on ultralarge chemistry databases, Wendy Warr summarizes talks from about 30 practitioners in the field of ultralarge collections of molecules. Most of the proprietary were created and searched with BioSolveIT tools.
Report on an NIH Workshop on Ultralarge Chemistry Databases.
Warr, W.
ChemRxiv. 2021.
Stefan et al. discovered four novel ABC transporter inhibitors from the ZINC12 database (16,403,865 molecules) by combining FTrees with a computer-aided pattern analysis (C@PA).
Scaffold Fragmentation and Substructure Hopping Reveal Potential, Robustness, and Limits of Computer-Aided Pattern Analysis (C@PA).
Namasivayam, V.; Silbermann, K.; Pahnke, J.; Wiese, M.; Stefan, S.M.
Comput. Struct. Biotechnol. J. 2021.
With captopril as query molecule, Faghri et al. screened the NPASS database (35,032 natural compounds) with infiniSee which finally helped to identify a potential NDM-1 inhibitor.
Discovery of Potential Inhibitors against New Delhi Metallo-β-Lactamase-1 from Natural Compounds: In Silico-Based Methods.
Salari-jazi, A.; Mahnam, K.; Sadeghi, P.; Damavandi, M. S.; Faghri, J.
Sci. Rep. 2021, 11 (1), 1–20.

Get infiniSee and start your journey into vast Chemical Spaces!

How to cite

In publications please cite infiniSee with the respective version number as follows:
infiniSee version 5.1.3; BioSolveIT GmbH, Sankt Augustin, Germany, 2023,