A Molecular Structure and Modeling Core laboratory has been established to provide technical services to support faculty researchers involved in cancer research and drug design at Xavier University. Drug design methods use molecular structure information and modeling methods to determine structure patterns among active and inactive compounds, identify and compare potential active sites, and screen databases to identify new leads. X-ray crystallography provides structure coordinates for druglike, organic compounds and small peptides. The goal of this core laboratory is to provide small molecule X-ray crystallographic services as well as to support ligand-based and structure-based drug design projects at any stage. The long term goal is to develop resources in order to enhance cancer related biomedical research capability at Xavier University. To achieve this goal, the Molecular Structure and Modeling Core Laboratory has set the following specific aims:
1. To provide salary support for a Core Scientist to provide molecular modeling services and training in support of Xavier faculty research projects
2. To establish new collaborations with faculty at other local and RCMI institutions who might benefit from molecular modeling services
3. To provide small molecule x-ray crystallography services
4. To provide support and maintenance costs for equipment in the MSM Core
Mottamal, Madhu, Ph.D.
Role: Research Scientist
With an Oxford desktop cooler.
These are optimized super computing workstations, which are utilized for molecular and computational modeling techniques.
Provide services that have access to Cambridge Structural Database, Chinese Medicine, Asinex, NCI, ZINC, Chem Abstracts databases, and more. We use these databases to identify potential inhibitors of target proteins by virtual screening of chemical libraries.
A method to construct a reasonable model of a target protein structure from its amino acid sequence with an accuracy comparable to experimental three-dimensional structure. Homology models can be constructed if the structure of the target protein or receptor is unknown but has a high sequence similarity to a protein of known structure. Homology models are very useful for structure-based drug design, fold recognition, finding potential inhibitors, predictive protein-ligand interactive simulations and more, especially when the crystallographic structure of a target protein is not available.
Ligand based drug design (LBDD) is one of the most preferred and accepted approaches for drug discovery and lead optimization, especially if the 3D structures of potential drug targets are not available. Quantitative structure activity relationships (both 2D-QSAR and 3D-QSAR) and pharmacophore modeling are the most important and extensively used tools in the ligand-based approach to drug design. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA) are the two established tools for building three dimensional QSAR models. All of these methods give critical insights into the nature of the interactions between the drug molecule and its target, which in turn helps to develop predictive models appropriate for lead optimization. LBDD involves the development of new drug candidates from databases of existing compounds with biological activity. Ligand based drug design requires the knowledge of 20 or more known structures with biological activity to determine the structural requirements for activity (pharmacophore), identify structure patterns related to activity (QSAR), and screen databases for new leads.
Molecular dynamics simulations have become one of the essential tools for the investigation of biological macromolecules and also for the process of computer aided drug design. It provides time dependent behavior of a molecular system and in turn offers molecular level insight into structure and function of biological molecules. This technique is routinely used for the study of complex dynamic process that occurs in biological systems such as conformational changes, protein folding, molecular recognition and protein-drug interactions, and provide the means to carry out drug design.
Structure-based drug design (SBDD) has emerged as an integral part of the modern drug design and discovery process. It is very useful in the development of new drug leads. SBDD uses three dimensional structure of target proteins in order to identify or design lead molecules by docking or virtual screening of chemical libraries. Homology models are used when 3D structures of the target proteins are unavailable. Hence the SBDD requires knowledge of the X-ray structure of a drug target or high sequence identity of a similar target with a known structure in order to determine potential interaction sites for drug modulators, screen databases for new lead candidates, and design potential inhibitors for the target receptor.
Provides structural information that is useful in the process of drug design. The X-ray crystal structure can be used to provide reference structural information for determination of pharmacophore, QSAR, and substrate docking. X-ray crystallography requires a good quality single crystal and can be used to determine detailed 3D structural information including absolute configuration.
"The AMBER software suite provides a set of programs for applying the AMBER forcefields to simulations of biomolecules.
Amber is developed in an active collaboration of David Case at Rutgers University, Tom Cheatham at the University of Utah, Ken Merz and Adrian Roitberg at Florida, Carlos Simmerling at SUNY-Stony Brook, Ray Luo at UC Irvine, Junmei Wang at UT Southwestern, Ross Walker at UC San Diego, and many others. Amber was originally developed under the leadership of Peter Kollman."
"CHARMM (Chemistry at HARvard Macromolecular Mechanics):
• is a versatile and widely used molecular simulation program with broad application to many-particle systems
• has been developed with a primary focus on the study of molecules of biological interest, including peptides, proteins, prosthetic groups, small molecule ligands, nucleic acids, lipids, and carbohydrates, as they occur in solution, crystals, and membrane environments
• provides a large suite of computational tools that encompass numerous conformational and path sampling methods, free energy estimates, molecular minimization, dynamics, and analysis techniques, and model-building capabilities
• is useful for a much broader class of many-particle systems
• can be utilized with various energy functions and models, from mixed quantum mechanical-molecular mechanical force fields, to all-atom classical potentials with explicit solvent and various boundary conditions, to implicit solvent and membrane models
• has been ported to numerous platforms in both serial and parallel architectures"
"Gaussian provides state-of-the-art capabilities for electronic structure modeling. Gaussian is licensed for a wide variety of computer systems. All versions of Gaussian contain every scientific/modeling feature, and none imposes any artifical limitations on calculations other than your computing resources and patience."
"GOLD is a program for calculating the docking modes of small molecules in protein binding sites and is provided as part of the GOLD Suite, a package of programs for structure visualisation and manipulation (Hermes), for protein-ligand docking (GOLD) and for post-processing (GoldMine) and visualisation of docking results. Hermes acts as a hub for many of CCDC's products, for more information please refer to the Hermes product page.
The product of a collaboration between the University of Sheffield, GlaxoSmithKline plc and CCDC, GOLD is very highly regarded within the molecular modelling community for its accuracy and reliability.
"Cheminformatics & (HTS) QSAR- MOE provides a suite of applications for manipulating and analyzing large collections of compounds, building property models, consensus models and SD pipeline command line tools." "Medicinal Chemistry Applications- MOE is the ideal system for large scale deployment of molecular modeling and cheminformatics applications to occasional users such as medicinal chemists. MOE has the advantage of having a flexible and customizable interface. MOE applications are easy to use and workflow or customized tools can be added. MOE is ported to a wide variety of computer platforms including Intel computers running Microsoft Windows™, Mac OS and Mac OS X (10.5 and 10.6)." "Protein & Antibody Modeling- MOE's CASP validated applications for protein structure prediction are powerful, intuitive and easy to use, both for experts and occasional users. Powerful homologue identification, alignment technology and refinement methodology make high quality sequence to structure predictions routinely possible." "MOE is a fully integrated drug discovery software package ...that integrates visualization, molecular modeling, protein modeling and bioinformatics, cheminformatics and QSAR, high throughput discovery, pharmacophore modeling and structure based design in one package. In addition to the suite of graphical applications, MOE contains a toolbox for adapting existing applications or creating new applications for Life Sciences. With MOE, expert modelers, application developers and occasional users can benefit from sharing the same software system. Methodology written by application developers can be validated by expert modelers and then deployed to occasional users using either the MOE graphical interface or a Web interface." "Cheminformatics & (HTS) QSAR- MOE provides a suite of applications for manipulating and analyzing large collections of compounds, building property models, consensus models and SD pipeline command line tools." "Molecular Modeling & Simulations- MOE's internal representation of organic chemical structures and flexible architecture provide a solid foundation for molecular modeling and computational chemistry. Intuitive molecular editors, file format handling, choice of validated forcefields, powerful modeling applications and customizability make MOE the most flexible molecular modeling environment in the industry." "Structure-Based Design- Macromolecular crystallographic data, when available, can be a valuable source of information for discovering active ligands. MOE provides a collection of applications for visualizing and understanding details of receptor active sites and receptor-ligand interactions. These applications are used to suggest improvements to ligands or screen ligand databases for candidate binders. " "Pharmacophore Discovery- MOE's pharmacophore modeling methodology is a powerful means to generate and use 3D geometric information to search for novel active compounds, particularly when no receptor geometry is available. Pharmacophore methods use a generalized ligand representation and geometric constraints to bypass the structural or chemical class bias of 2D methods. MOE's pharmacophore applications are powerful, intuitive and easy to use, both for experts and occasional users."
"NAMD is a parallel molecular dynamics program for UNIX platforms designed for high-performance simulations in structural biology."
"Structure-based drug design software suite"
"Small Molecule Modeling and Simulation
SYBYL-X provides capabilities for crucial small molecular modeling and simulation, includng structure-activity relationship modeling, pharmacophore hypothesis generation, molecular alignment, conformational searching, ADME prediction and more.
Macromolecular Modeling and Simulation
SYBYL-X provides capabilities for key macromolecular modeling and simulation, such as homology modeling, sequence alignment, and other key tasks required to understand and model the static and dynamic 3D structural properties of proteins and other biological macromolecules.
SYBYL-X empowers users to extract meaningful information from the volumes of data generated by today's research methods. With core science and integrated applications to address critical tasks such as data mining and structure representation, SYBYL-X users can easily explore the chemical and biological data that is key to the success of drug discovery programs.
SYBYL-X allows researchers to perform critical lead discovery tasks like hit and lead expansion, lead and scaffold hopping, and virtual screening, as well as to consider critical molecular properties or predicted ADME and physical properties early in the discovery process. Key ligand-based design tasks, like structure-activity relationship modeling, pharmacophore hypothesis generation, and molecular alignment, are included in SYBYL-X, as well as structure-based virtual screening to identify promising lead candidates that interact with a receptor of interest.
Using SYBYL-X, researchers can develop ligand-based and/or structure-based models that address the multiple criteria that must be considered in lead optimization. Users can predict he level of biological activity or potency based on structure-activity data, easily model multiple biological endpoints, understand and rationalize a drug’s interactions with its receptor to identify potential new binding interactions that will provide ‘step jumps’ in potency, and much more."