Chris Mallory

DockoMatic 2.0: High Throughput Inverse Virtual Screening and Homology Modeling

DockoMatic is a free and open source application that unifies a suite of software programs within a user-friendly graphical user interface (GUI) to facilitate molecular docking experiments. Here we describe the release of DockoMatic 2.0; significant software advances include the ability to (1) conduct high throughput inverse virtual screening (IVS); (2) construct 3D homology models; and (3) customize the user interface. Users can now efficiently setup, start, and manage IVS experiments through the DockoMatic GUI by specifying receptor(s), ligand(s), grid parameter file(s), and docking engine (either AutoDock or AutoDock Vina). DockoMatic automatically generates the needed experiment input files and output directories and allows the user to manage and monitor job progress. Upon job completion, a summary of results is generated by Dockomatic to facilitate interpretation by the user. DockoMatic functionality has also been expanded to facilitate the construction of 3D protein homology models using the Timely Integrated Modeler (TIM) wizard. The wizard TIM provides an interface that accesses the basic local alignment search tool (BLAST) and MODELER programs and guides the user through the necessary steps to easily and efficiently create 3D homology models for biomacromolecular structures. The DockoMatic GUI can be customized by the user, and the software design makes it relatively easy to integrate additional docking engines, scoring functions, or third party programs. DockoMatic is a free comprehensive molecular docking software program for all levels of scientists in both research and education.

Acetylcholine promotes binding of α-conotoxin MII at α3 β2 nicotinic acetylcholine receptors.

α‐Conotoxin MII (α‐CTxMII) is a 16‐residue peptide with the sequence GCCSNPVCHLEHSNLC, containing Cys2–Cys8 and Cys3–Cys16 disulfide bonds. This peptide, isolated from the venom of the marine cone snail Conus magus, is a potent and selective antagonist of neuronal nicotinic acetylcholine receptors (nAChRs). To evaluate the impact of channel–ligand interactions on ligand‐binding affinity, homology models of the heteropentameric α3β2‐nAChR were constructed. The models were created in MODELLER with the aid of experimentally characterized structures of the Torpedo marmorata‐nAChR (Tm‐nAChR, PDB ID: 2BG9) and the Aplysia californica‐acetylcholine binding protein (Ac‐AChBP, PDB ID: 2BR8) as templates for the α3‐ and β2‐subunit isoforms derived from rat neuronal nAChR primary amino acid sequences. Molecular docking calculations were performed with AutoDock to evaluate interactions of the heteropentameric nAChR homology models with the ligands acetylcholine (ACh) and α‐CTxMII. The nAChR homology models described here bind ACh with binding energies commensurate with those of previously reported systems, and identify critical interactions that facilitate both ACh and α‐CTxMII ligand binding. The docking calculations revealed an increased binding affinity of the α3β2‐nAChR for α‐CTxMII with ACh bound to the receptor, and this was confirmed through two‐electrode voltage clamp experiments on oocytes from Xenopus laevis. These findings provide insights into the inhibition and mechanism of electrostatically driven antagonist properties of the α‐CTxMIIs on nAChRs.

Homology Modeling and Molecular Docking for the Science Curriculum

DockoMatic 2.0 is a powerful open source software program (downloadable from sourceforge.net) that allows users to utilize a readily accessible computational tool to explore biomolecules and their interactions. This manuscript describes a practical tutorial for use in the undergraduate curriculum that introduces students to macromolecular structure creation, ligand binding calculations, and visualization of docking results. A student procedure is provided that illustrates the use of DockoMatic to create a homology model for the amino propeptide region (223 amino acids with two disulfide bonds) of collagen α1 (XI), followed by molecular docking of the commercial drug Arixtra® to the homology model of α1 (XI), and finally, analysis of the results of the docking experiment. The activities and Supporting Information described are intended to educate students in the use of computational tools to create and investigate homology models for other systems of interest and to train students to perform and analyze molecular docking studies. The tutorial also serves as a foundation for investigators seeking to explore the viability of using computational biochemistry to study their receptor–ligand binding motifs.

Modification of cellular DNA by synthetic aziridinomitosenes

Two synthetic aziridinomitosenes (AZMs), Me-AZM and H-AZM, structurally related to mitomycin C (MC) were evaluated for their anticancer activity against six cancer cell lines (HeLa, Jurkat, T47D, HepG2, HL-60, and HuT-78) and tested for their DNA-modifying abilities in Jurkat cells. Cytotoxicity assays showed that Me-AZM is up to 72-fold and 520-fold more potent than MC and H-AZM, respectively. Me-AZM also demonstrated increased DNA modification over MC and H-AZM in alkaline COMET and Hoechst fluorescence assays that measured crosslinks in cellular DNA. Me-AZM and H-AZM treatment of Jurkat cells was found to sponsor significant DNA-protein crosslinks using a K-SDS assay. The results clearly indicate that the AZM C6/C7 substitution pattern plays an important role in drug activity and supports both DNA-DNA and DNA-protein adduct formation as mechanisms for inducing cytotoxic effects.