VARUNA – Towards a Grid-based Molecular Modeling Environment

CICC/MACE – Meeting May 22, 2006

Mookie Baik

Department of Chemistry & School of Informatics

Chemical Informatics in Academic Research?

Industrial Research: Target Oriented

Not bound to a specific molecular system

Not bound to a method

Not concerned with generality

Aware of Efficiency

Aware of Overall Cost

Aware of Toxicity

Concerned about Formulations

Cares about active MOLECULES

Academic Research: Concept Oriented

Specialized on few molecular families

Method Development is important

Obsessed with generality

Does not care much about Efficiency

Cost is unimportant

Often can’t even assess for Toxicity

Formulation is a minor issue

Cares mostly about REACTIONS, i.e.Ways to GET to a molecule

Consequences for ChemInfo Design for Academia

TWO Strategies are needed:

Making traditional ChemInfo tools that are often available in commercial research available to Academia is in principle straightforward.

New ChemInfo Tools that are CONCEPT centered and include REACTIONS in addition to MOLECULES must be developed.

Our approach: Development of

(a) Quantum Chemical Database

(b) Molecular Modeling Database

Harness the power of recent advances in Molecular Modeling (QM, QM/MM, MM, MD) through information management.

Data-depository for Quantum Chemical Data including both Properties & Mechanisms

Traditional Workflow of Molecular Modeling

SupercomputerResearcherResearcherFORTRAN Code,

Scripts,Visualization Code

Hard DriveDirectory Jungle

Chemical Concepts

Experiments

Highly inefficient workflow (no automation)

Knowledge is human bound (grad student leaves and projects dies)

Incorporation with other DB’s is done in Researcher’s head

Varuna – a new environment for molecular modeling

QMDatabase

Supercomputer

ResearcherResearcher

Simulation ServiceFORTRAN Code,

Scripts

Chemical Concepts

Experiments

QM/MMDatabasePubChem, PDB,

NCI, etc.

Chem-GridChem-Grid

ReactionDB

DB ServiceQueries, Clustering,

Curation, etc.

Automatic Generator of ForceFields (AutoGeFF)

Developing a Stand-Alone Software (in C) that can take ANY drug-like molecule (from PubChem, for example) metal complexes metalloenzymes (from PDB, for example) unnatural or functionalized amino acids, nucleobases (from in-house db)

for which molecular mechanics force fields are not available andautomatically generate FF’s based on High level Quantum Simulations (using Varuna as a Webservice)

for Sophisticated Molecular Mechanics Simulations

Demo: Coding of a specialized Prototype that can reproduce our manually derived novel force fields for Cu-A Alzheimer’s Disease as a Demonstration Study.

Mapping the reaction energy profile for the hydrogen peroxide hypothesis for AD.

Interactions of redox active small molecules with the active Cu-center.

Building the fibril

T = 325 K, P = 1 bartsim = 5ns eq. + 5 ns sim.

Insertion of Cu(II) into the fibril

T = 325 K, P 1 bartsim = 5 ns eq + 5 ns

His 6, 13 14 - Glu 3, 11 - Asp 7 - Tyr 10

QM Calculation Workflow

XYZ File ofa Molecule Input File

Generator

Input Param

Varuna

Job SchedulingService

List ofComputers

Job ScriptService

SSHService

Supercomputers

Automatic Quantum Mechanical Curation of Structure Data

Chemical Research logic is often driven by molecular structure

Large-scale, small molecule DB’s (such as PubChem) have low-resolution structure data

Often key properties are not consistently available: e.g.: Rotation-barriers, Redox Potentials, Polarizabilities, IR frequencies,

reactivity towards nucleophiles

QM web-services will provide tools for generating high-resolution data that will curate the results of traditional ChemInfo studies allow for combinatorial computational chemistry access a database of modeling data