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MOLECULAR DOCKING

Predicts binding location and orientation of small molecules to drug targets.

Evaluation is based on energetics of atomic interactions and search algorithm.

Protein flexibility (blue) accounts for induced fit binding.

Our work focuses on plugging the holes at the foundation of the drug discovery pipeline.

Therapeutic research relies on deep understanding of bio-molecular interactions enhanced by the effectiveness of computational techniques.

Thousands of small molecules are sorted 'in silico' as future therapeutic compounds.

Standard protocols not fully optimized lead to faulty evaluations and contribute to the high failure rate of drugs tested on humans.

We have shown successes in a number of tests concerning cancer, alzheimer's, and Parkinson's disease targets employing this strategy.

We have determined key areas of protein binding site flexibility found within proteins targeted by drug therapy.

Support is needed to initiate a comprehensive and publicly accessible protein flexibility data bank.

The accurate simulation of protein conformational changes is critical to docking studies because it accounts for changes affecting the final binding geometry.

Our Goal...

-Develop a Protein Flexibility Data Bank (PFD)

Utilizing...

Molecular docking

Molecular Dynamics

Data Mining

Result...

-Improved Virtual Screenings

-Efficacious Drug Design

-Cancer, Alzheimer's and Parkinson's Drugs at

Lower Cost

The computer simulation of bio-molecular binding processes is amazingly difficult.

We can only simulate a small portion of total atomic interactions.

Both time dependent (classical molecular dynamics) and time independent (molecular docking) strategies are employed.

Molecular Docking

A large failure rate push costs higher as pharmaceutical companies struggle to produce drugs that are efficacious and safe. Novel protocols are needed to change this dynamic, making life saving drugs available and affordable.

Computational methodologies represent an essential, cost effective tool for discovery and development of small molecules purposed as therapeutics.

Drugs in the form of large antibodies are introduced to activate immune pathway.

There are several types of immunotherapy, including:

Monoclonal antibodies

Non-specific immunotherapies

Oncolytic virus therapy

T-cell therapy

Cancer vaccines

Computational simulation of protein flexibility is limited due to an exponential increase in conformational search space resulting in additional computational time, cost and reduction in accuracy.

When relevant rotatable bonds are not activated:

1) Many suitable drugs can potentially be "downgraded"

in terms of potential due to low scoring.

2) Drugs can be screened and selected for further research

despite the fact that they may not be the most promising,

due to high scoring when residues were not activated.

We tackle the problem with two-prong approach:

1) We take all binding site rotatable bonds in full consideration as

part of a comprehensive approach.

2) To avoid the large number of trials, we employ data mining to

determine which rotatable bonds are "expressive" and

only utilize those as part of the screening.

Currently, most docking studies fail to model protein flexibility, instead relying on a flexible ligand/rigid receptor protocol. This leads to exclusion of promising drug leads and false positives only to be discovered further down the drug discovery pipeline.

WE ARE ALSO WORKING ON...

Classical Molecular Dynamics

Through comprehensive docking, molecular dynamics, and data mining studies, we can provide future researchers with an easily accessible guide for improving not only high throughput screenings, but more focused docking studies with promising lead compounds.

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