Company type | Private |
---|---|
Industry | Cheminformatics and bioinformatics software |
Headquarters | Montreal, Quebec, Canada |
Key people | Paul Labute - President, CEO |
Products | MOE, PSILO |
Number of employees | 30+ |
Website | www |
Chemical Computing Group is a software company specializing in research software for computational chemistry, bioinformatics, cheminformatics, docking, pharmacophore searching and molecular simulation. The company's main customer base consists of pharmaceutical and biotechnology companies, as well as academic research groups. It is a private company that was founded in 1994; it is based in Montreal, Quebec, Canada. Its main product, Molecular Operating Environment (MOE), is written in a self-contained programming system, the Scientific Vector Language (SVL).
MOE is a drug discovery software platform that integrates visualization, modeling, and simulations, as well as methodology development. MOE scientific applications are used by biologists, medicinal chemists and computational chemists in pharmaceutical, biotechnology and academic research. MOE runs on Windows, Linux, Unix, and MAC OS X.
Main application areas: Structure-Based Design, Fragment-Based Design, Pharmacophore Discovery, Medicinal Chemistry Applications, Biologics Applications, Protein and Antibody Modeling, Molecular Modeling and Simulations, Cheminformatics & QSAR
PSILO is a protein structure database system that provides a repository for macromolecular and protein-ligand structural information. It allows research organizations to track, register and search both experimental and computational macromolecular structural data. A web-browser interface facilitates the searching and accessing of public and private structural data.
A chemical database is a database specifically designed to store chemical information. This information is about chemical and crystal structures, spectra, reactions and syntheses, and thermophysical data.
Cheminformatics refers to the use of physical chemistry theory with computer and information science techniques—so called "in silico" techniques—in application to a range of descriptive and prescriptive problems in the field of chemistry, including in its applications to biology and related molecular fields. Such in silico techniques are used, for example, by pharmaceutical companies and in academic settings to aid and inform the process of drug discovery, for instance in the design of well-defined combinatorial libraries of synthetic compounds, or to assist in structure-based drug design. The methods can also be used in chemical and allied industries, and such fields as environmental science and pharmacology, where chemical processes are involved or studied.
Drug design, often referred to as rational drug design or simply rational design, is the inventive process of finding new medications based on the knowledge of a biological target. The drug is most commonly an organic small molecule that activates or inhibits the function of a biomolecule such as a protein, which in turn results in a therapeutic benefit to the patient. In the most basic sense, drug design involves the design of molecules that are complementary in shape and charge to the biomolecular target with which they interact and therefore will bind to it. Drug design frequently but not necessarily relies on computer modeling techniques. This type of modeling is sometimes referred to as computer-aided drug design. Finally, drug design that relies on the knowledge of the three-dimensional structure of the biomolecular target is known as structure-based drug design. In addition to small molecules, biopharmaceuticals including peptides and especially therapeutic antibodies are an increasingly important class of drugs and computational methods for improving the affinity, selectivity, and stability of these protein-based therapeutics have also been developed.
Quantitative structure–activity relationship models are regression or classification models used in the chemical and biological sciences and engineering. Like other regression models, QSAR regression models relate a set of "predictor" variables (X) to the potency of the response variable (Y), while classification QSAR models relate the predictor variables to a categorical value of the response variable.
Medicinal or pharmaceutical chemistry is a scientific discipline at the intersection of chemistry and pharmacy involved with designing and developing pharmaceutical drugs. Medicinal chemistry involves the identification, synthesis and development of new chemical entities suitable for therapeutic use. It also includes the study of existing drugs, their biological properties, and their quantitative structure-activity relationships (QSAR).
In medicinal chemistry and molecular biology, a pharmacophore is an abstract description of molecular features that are necessary for molecular recognition of a ligand by a biological macromolecule. IUPAC defines a pharmacophore to be "an ensemble of steric and electronic features that is necessary to ensure the optimal supramolecular interactions with a specific biological target and to trigger its biological response". A pharmacophore model explains how structurally diverse ligands can bind to a common receptor site. Furthermore, pharmacophore models can be used to identify through de novo design or virtual screening novel ligands that will bind to the same receptor.
Molecule mining is the process of data mining, or extracting and discovering patterns, as applied to molecules. Since molecules may be represented by molecular graphs, this is strongly related to graph mining and structured data mining. The main problem is how to represent molecules while discriminating the data instances. One way to do this is chemical similarity metrics, which has a long tradition in the field of cheminformatics.
Virtual screening (VS) is a computational technique used in drug discovery to search libraries of small molecules in order to identify those structures which are most likely to bind to a drug target, typically a protein receptor or enzyme.
Chemaxon is a cheminformatics and bioinformatics software development company, headquartered in Budapest with 250 employees. The company also has offices in Cambridge, San Diego, Basel and Prague, and distributors in China, India, Japan, South Korea, Singapore, and Australia.
Materials Studio is software for simulating and modeling materials. It is developed and distributed by BIOVIA, a firm specializing in research software for computational chemistry, bioinformatics, cheminformatics, molecular dynamics simulation, and quantum mechanics.
SMILES arbitrary target specification (SMARTS) is a language for specifying substructural patterns in molecules. The SMARTS line notation is expressive and allows extremely precise and transparent substructural specification and atom typing.
Chemical similarity refers to the similarity of chemical elements, molecules or chemical compounds with respect to either structural or functional qualities, i.e. the effect that the chemical compound has on reaction partners in inorganic or biological settings. Biological effects and thus also similarity of effects are usually quantified using the biological activity of a compound. In general terms, function can be related to the chemical activity of compounds.
Inte:Ligand was founded in Maria Enzersdorf, Lower Austria (Niederösterreich) in 2003. They established the company headquarters on Mariahilferstrasse in Vienna, Austria that same year.
LigandScout is computer software that allows creating three-dimensional (3D) pharmacophore models from structural data of macromolecule–ligand complexes, or from training and test sets of organic molecules. It incorporates a complete definition of 3D chemical features that describe the interaction of a bound small organic molecule (ligand) and the surrounding binding site of the macromolecule. These pharmacophores can be overlaid and superimposed using a pattern-matching based alignment algorithm that is solely based on pharmacophoric feature points instead of chemical structure. From such an overlay, shared features can be interpolated to create a so-called shared-feature pharmacophore that shares all common interactions of several binding sites/ligands or extended to create a so-called merged-feature pharmacophore. The software has been successfully used to predict new lead structures in drug design, e.g., predicting biological activity of novel human immunodeficiency virus (HIV) reverse transcriptase inhibitors.
Computational Resources for Drug Discovery (CRDD) is an important module of the in silico module of Open Source for Drug Discovery (OSDD). The CRDD web portal provides computer resources related to drug discovery, predicting inhibitors, and predicting the ADME-Tox properties of molecules on a single platform. It caters to researchers researching computer-aided drug design by providing computational resources, and hosting a discussion forum. One of the major objectives of CRDD is to promote open source software in the field of cheminformatics and pharmacoinformatics.
Discovery Studio is a suite of software for simulating small molecule and macromolecule systems. It is developed and distributed by Dassault Systemes BIOVIA.
Sean Ekins is a British pharmacologist and expert in the fields of ADME/Tox, computational toxicology and cheminformatics at Collaborations in Chemistry, a division of corporate communications firm Collaborations in Communications. He is also the editor of four books and a book series for John Wiley & Sons.
Matched molecular pair analysis (MMPA) is a method in cheminformatics that compares the properties of two molecules that differ only by a single chemical transformation, such as the substitution of a hydrogen atom by a chlorine one. Such pairs of compounds are known as matched molecular pairs (MMP). Because the structural difference between the two molecules is small, any experimentally observed change in a physical or biological property between the matched molecular pair can more easily be interpreted. The term was first coined by Kenny and Sadowski in the book Chemoinformatics in Drug Discovery.
Yvonne Connolly Martin is an American cheminformatics and computer-aided drug design expert who rose to the rank of Senior Volwiler Research Fellow at Abbott Laboratories. Trained in chemistry at Northwestern University, she became a leader in collaborative science aimed at discovering and developing bioactive molecules as therapeutic agents, with her contributions proceeding from application of methods to understand how descriptors of molecular shapes and physicochemical properties relate to their biological activity. She is the author of a seminal volume in cheminformatics, Quantitative Drug Design, and has been the recipient of numerous awards in her field, including being named as a fellow of the American Association for the Advancement of Science (1985) and of the International Union of Pure and Applied Chemistry (2000), and receiving the Herman Skolnik Award (2009) and the Award for Computers in Chemical and Pharmaceutical Research (2017) from the American Chemical Society.
Molecular Operating Environment (MOE) is a drug discovery software platform that integrates visualization, modeling and simulations, as well as methodology development, in one package. MOE scientific applications are used by biologists, medicinal chemists and computational chemists in pharmaceutical, biotechnology and academic research. MOE runs on Windows, Linux, Unix, and macOS. Main application areas in MOE include structure-based design, fragment-based design, ligand-based design, pharmacophore discovery, medicinal chemistry applications, biologics applications, structural biology and bioinformatics, protein and antibody modeling, molecular modeling and simulations, virtual screening, cheminformatics & QSAR. The Scientific Vector Language (SVL) is the built-in command, scripting and application development language of MOE.