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,[1] fragment-based design,[2] 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.
The Molecular Operating Environment was developed by the Chemical Computing Group under the supervision of President/CEO Paul Labute.[3] Founded in 1994[4] and based in Montreal, Quebec, Canada, this private company is dedicated to developing computation software that will challenge, revolutionize, and aid in the scientific methodology. The Chemical Computing Group contains a team of mathematicians, scientists, and software engineers constantly altering and updating MOE in order to improve the fields of theoretical/computational chemistry and biology, molecular modeling, and computer-driven molecular design.[5] Researchers specializing in pharmaceutics (drug-discovery); computational chemistry; biotechnology; bioinformatics; cheminformatics; molecular dynamics, simulations, and modeling are the main clients of the Chemical Computing Group.
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As discussed before, MOE is a versatile software with main applications in 3D molecular visualization; structure-based protein-ligand design; antibody and biologics design, structure-based protein engineering; SAR and SPR visualization; ligand-based design; protein, DNA/RNA modeling; virtual screening; 3D pharmacophore screening; fragment-based discovery; structural bioinformatics; molecular mechanics and dynamics; peptide modeling; structural biology; cheminformatics and QSAR.[5]
The protein structure file is downloaded from the PDB and opened in a molecular docking software. There are many programs that can facilitate molecular docking such as AutoDock, DOCK, FlexX, HYDRO, LIGPLOT, SPROUT, STALK,[15] and Molegro Virtual Docker.[16] Alternatively, some protein structures have not been experimentally determined through the use of X-ray crystallography and therefore, are not found on the PDB. In order to produce a protein molecule that can be used for docking, scientists can use the amino acid sequence of a protein and a program named UniProt to find protein structures in the PDB that have similar amino acid sequences.[17] The amino acid sequence of the protein that is being constructed is then used in combination with the protein structure found in the PDB with the highest percent similarity (template protein) in order to create the target protein used in docking. Although this method does not produce an exact model of the target protein, it allows scientists to produce the closest possible structure in order to conduct computational methods and gain some insight into the behavior of a protein. After constructing the necessary molecules for docking, they are imported into a computational docking software such as MOE. In this program, proteins can be visualized and certain parts of the molecule can be isolated in order to obtain more precise data for a region of interest. A cavity, or region where the molecular docking will take place, is set around the binding site, which is the region in the receptor protein where the ligand attaches to. After specifying the cavity, molecular docking settings are configured and the program is run in order to determine the binding energy of the complex.
The size scaling behavior of geometric of volumes of proteins and comparison of the volumes calculated using ProteinVolume with other software packages. Panel A. Dependence of the molecular surface volume (circles, VMS), the van der Waals volume (triangles, VVDW) and void volumes (upside-down triangles, VVoid) on number of amino acid residues in proteins (Naar) from ultra-high crystallographic resolution (0.7-1.2 Å) set (red symbols) and high crystallographic resolution (1.2-1.7 Å) set (open symbols) calculated using ProteinVolume. The linear regression lines for ProteinVolume calculations on ultra-high and high resolution sets are indistinguishable, indicating that ProteinVolume results are not dependent on crystallographic resolution. The results from ProteinVolume are also compared to relevant volumes calculated using McVol (blue squares) and MSROLL (green triangles). The van der Waals (VVDW) volumes calculated by VOIDOO are shown in cyan circles. Panel B. Dependence of fraction of void volume on protein size for ultra-high crystallographic resolution (0.7-1.2 Å) set (red circles) and high crystallographic resolution (1.2-1.7 Å) set (open squares) calculated using ProteinVolume.
Lab Goals:The Ellington lab is attempting to develop novel synthetic organisms based on altering the translation apparatus and developing modular nucleic acid software. Translation engineering centers on the introduction of novel amino acids into proteins that have the capability to base-pair, and is being pursued using a variety of techniques, including directed evolution, computational design, and high-throughput synthesis. This latter capacity is abetted by a Gene Synthesis Facility capable of producing multiple kilobases of DNA per week. In parallel, DNA circuits based on strand exchange reactions and capable of executing embedded algorithms are being developed, using tools such as aptamers and DNA nanotechnology. The first application of these circuits will be in point-of-care diagnostics, but eventually these circuits should form the basis of a new, modular cellular operating system. We anticipate this operating system should also prove useful in cell-to-cell communication and drug delivery in organisms, and are actively pursuing in vivo studies. In order to enhance both engineering translation and installing DNA circuitry into cells, we have developed tools to directly synthesize operons, enable facile horizontal transfer, and edit genomes, and are interested in how such tools can be used to engineer cellular consortiums, including biofilms.
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