• Currently, chemical substances including only C, H, N, O, and S atoms are available.
• Extending to other atoms is under way.

The number of currently available chemical compounds is more than 2.5 million (constantly expanding). Compounds are categorized as follows:

Hydrocarbons 958,000+ compounds

• Alkanes (Paraffins)
• Alkenes (Olefins)
• Alkynes
• Aromatics
• Cycloalkanes (Naphthenes/Cycloparaffins)
• Cycloalkenes (Cycloolefins)
• Cycloalkynes

Non-hydrocarbons 1,442,000+ compounds

• Alcohols
• Aldehydes
• Amides
• Amines
• Amino Acids
• Carbolic Acids
• Carboxylic Acids
• Cyanides Disulfides
• Esters
• Ethers
• Furans
• Heterocyclics
• Imines
• Ketones
• Nitriles
• Phenic Acids
• Phenols
• Piperidines
• Pyrans
• Pyridines
• Pyrroles
• Pyrrolidines
• Thioethers
• Thiols
• Thiophenes
• Thiopyrans

Drug-like Chemicals1,279,000+ compounds

Combustion Engineering1,349,000+ compounds

Free Radicals384,000+ compounds

Soot Aromatics248,000+ compounds

Fuel Compounds

• Gasoline 105,000+ compounds
• Jet-fuel 171,000+ compounds
• Diesel 735,000+ compounds
• Bio-diesel 672,000+ compounds

Chemical, Petrochemical, Refinery, Oil & Gas Processes

• Naphtha 273,000+ compounds
• Isomerization 231,000+ compounds
• Thermal Cracking 491,000+ compounds
• GTL (Gas-To-Liquid) or Catalytic Cracking 798,000+ compounds
• Fischer-Tropsch 857,000+ compounds
• Catalytic Reforming 408,000+ compounds
• MTO (Methanol-To-Olefin) or Hydro Cracking 768,000+ compounds
• MTG (Methanol-To-Gasoline) 688,000+ compounds
• Desulfurization 1,012,000+ compounds
• CTL (Coal-To-Liquid) 1,248,000+ compounds

Compounds in Mol-Instincts contain the following physical & chemical, thermodynamic, thermochemical, thermophysical, physicochemical, and drug-related properties data tables. Spectra data and other fundamental information are available as well:

Thermo-Physico-Chemical, Thermodynamic, and Transport Properties

• Acentric Factor
• Entropy
• Liquid Density
• Surface Tension
• Boiling Point
• Flammability
• Liquid Molar Volume
• Thermal Conductivity
• Compressibility Factor
• Flash Point
• Magnetic Susceptibility
• Van Der Waals Area
• Critical Pressure
• Gibbs Free Energy
• Parachor
• Van Der Waals Volume
• Critical Temperature
• Heat Capacity
• Polarizability
• Vapor Pressure
• Critical Volume
• Heat of Formation
• Radius of Gyration
• Viscosity
• DipoleMoment
• Heat of Vaporization
• Refractive Index
• Electron Affinity
• Ionization Energy
• Second Virial Coefficient
• Enthalpy
• Ionization Potential
• Solubility Parameter

Drug-related Properties

• Activity Score for GPCR
• Ligands Lipinski Alert Index
• Activity Score for Ion Channel Modulators
• LogP (Octanol-Water Partition Coefficient)
• Activity Score for Kinase Inhibitors
• LogS (Water Solubility)
• Activity Score for Nuclear Receptor Ligands
• Moriguchi Octanol-Water Partition Coefficient (logP)
• Drug-likeness
• Number of Acceptor Atoms for H-bonds
• Ghose-Crippen Molar Refractivity
• Number of Donor Atoms for H-bonds
• Ghose-Crippen Octanol-Water Partition Coefficient (logP)

Spectra Data

IR (Infrared), NMR (Nuclear Magnetic Resonance), and VCD (Vibrational Circular Dichroism) spectrum peak charts are available.

Fundamental Molecular Information

• Molecular Geometry
• Optimized 3D Structure
• Bond Angle
• Bond Length
• Vibrational Frequency
• Molecular Descriptors
• Quantum Mechanical Information
• Molecular Orbitals e.g., HOMO & LUMO (Highest Occupied & Lowest Unoccupied Molecular Orbital)

As of July, 2014, over 88 million chemical compounds have been registered in chemical abstracts service (CAS). Millions of unregistered hydrocarbon isomers exist in today's chemical processes and fuels. There are tens of millions of compounds that are the candidates for the medical applications. Although the property data of those compounds are critical to almost all types of chemical and related industries, there have been less than 45,000 chemical compounds whose property data are partially available in history of chemistry. The “45,000” means lower than 0.05% of the CAS registered chemicals, i.e., no data is available at all for the rest 99.95 % of the compounds even if only CAS registered compounds are considered. This is because the property data have traditionally been determined by experimentation, which is time consuming, expensive, and frequently impossible to perform due to the impurity, toxicity, and instability of chemicals.

Due to the limitation of experiments, many estimation methods have been developed for decades, but those are mostly based on empirical correlations such as group-contribution methods, yielding too low level of prediction accuracy. Mol-Instincts technologies combines quantum mechanics, fundamental scientific approaches, statistical thermodynamics, QSPR (Quantitative Structure-Property Relationships), and modern mathematical modeling approaches such as SVRC (Scaled Variable Reduced Coordinates), and ANN (Artificial Neural Network) with a proprietary over-fitting prevention algorithm. Since Mol-Instincts approach is based on the fundamental understanding of chemical compounds through quantum mechanics, the prediction quality is incomparable to that of existing estimation methods.

Mol-Instincts is fundamentally different from the existing chemical compound databases. They are mostly based on the experimental data collected data from the literature, providing less than only 0.05% of the required data. Those products rely entirely on other’s publications and cannot produce the data themselves. Mol-Instincts is based on self-generating data, which is currently around 100 times larger than the existing databases. Most of the data are available nowhere else.

The property data produced by Mol-Instincts technologies have fully been verified with existing experimental data to date. To perform the verification, millions of experimental data were collected from every possible source, including journals, scientific books, and existing databases for more than 5 years. Examples are available under the "Accuracy" menu of Mol-Instincts website. When experimental data are unavailable, the predicted data were analyzed and inspected systematically using chemical analysis methods, e.g., similarity analysis, to confirm the quality of the predicted data.