conor parks
YOU?
Author Swipe
View article: Mining for Potent Inhibitors through Artificial Intelligence and Physics: A Unified Methodology for Ligand Based and Structure Based Drug Design
Mining for Potent Inhibitors through Artificial Intelligence and Physics: A Unified Methodology for Ligand Based and Structure Based Drug Design Open
Determining the viability of a new drug molecule is a time- and resource-intensive task that makes computer-aided assessments a vital approach to rapid drug discovery. Here we develop a machine learning algorithm, iMiner, that generates no…
View article: Mining for Potent Inhibitors through Artificial Intelligence and Physics: A Unified Methodology for Ligand Based and Structure Based Drug Design
Mining for Potent Inhibitors through Artificial Intelligence and Physics: A Unified Methodology for Ligand Based and Structure Based Drug Design Open
The viability of a new drug molecule is a time and resource intensive task that makes computer-aided assessments a vital approach to rapid drug discovery. Here we develop a machine learning algorithm, iMiner, that generates novel inhibitor…
View article: An Analysis of Proteochemometric and Conformal Prediction Machine Learning Protein-Ligand Binding Affinity Models
An Analysis of Proteochemometric and Conformal Prediction Machine Learning Protein-Ligand Binding Affinity Models Open
Protein-ligand binding affinity is a key pharmacodynamic endpoint in drug discovery. Sole reliance on experimental design, make, and test cycles is costly and time consuming, providing an opportunity for computational methods to assist. He…
View article: An Analysis of Proteochemometric and Conformal Prediction Machine Learning Protein-Ligand Binding Affinity Models
An Analysis of Proteochemometric and Conformal Prediction Machine Learning Protein-Ligand Binding Affinity Models Open
Protein-ligand binding affinity is a key pharmacodynamic endpoint in drug discovery. Sole reliance on experimental design, make, and test cycles is costly and time consuming, providing an opportunity for computational methods to assist. He…
View article: An Analysis of Proteochemometric and Conformal Prediction Machine Learning Protein-Ligand Binding Affinity Models
An Analysis of Proteochemometric and Conformal Prediction Machine Learning Protein-Ligand Binding Affinity Models Open
Protein-ligand binding affinity is a key pharmacodynamic endpoint in drug discovery. Sole reliance on experimental design, make, and test cycles is costly and time consuming, providing an opportunity for computational methods to assist. He…
View article: D3R grand challenge 4: blind prediction of protein–ligand poses, affinity rankings, and relative binding free energies
D3R grand challenge 4: blind prediction of protein–ligand poses, affinity rankings, and relative binding free energies Open
View article: D3R Grand Challenge 4: Blind Prediction of Protein-Ligand Poses, Affinity Rankings, and Relative Binding Free Energies
D3R Grand Challenge 4: Blind Prediction of Protein-Ligand Poses, Affinity Rankings, and Relative Binding Free Energies Open
The Drug Design Data Resource (D3R) aims to identify best practice methods for computer aided drug design through blinded ligand pose prediction and affinity challenges. Herein, we report on the results of Grand Challenge 4 (GC4). GC4 focu…
View article: D3R Grand Challenge 4: Blind Prediction of Protein-Ligand Poses, Affinity Rankings, and Relative Binding Free Energies
D3R Grand Challenge 4: Blind Prediction of Protein-Ligand Poses, Affinity Rankings, and Relative Binding Free Energies Open
The Drug Design Data Resource (D3R) aims to identify best practice methods for computer aided drug design through blinded ligand pose prediction and affinity challenges. Herein, we report on the results of Grand Challenge 4 (GC4). GC4 focu…
View article: Machine Learning for Acute Oral System Toxicity Regression and Classification
Machine Learning for Acute Oral System Toxicity Regression and Classification Open
In vivotoxicity testing remains a costly and time-consuming component of any pre-clinical drug development campaign. In particular, LD50 measurements require the loss of animal life but remain a critical component in preventing leth…
View article: Machine Learning for Acute Oral System Toxicity Regression and Classification
Machine Learning for Acute Oral System Toxicity Regression and Classification Open
In vivo toxicity testing remains a costly and time-consuming component of any pre-clinical drug development campaign. In particular, LD50 measurements require the loss of animal life but remain a critical component in preventing lethal com…
View article: Evaluation of Binding Site Comparison Algorithms and Proteometric Machine Learning Models in the Detection of Protein Pockets Capable of Binding the Same Ligand
Evaluation of Binding Site Comparison Algorithms and Proteometric Machine Learning Models in the Detection of Protein Pockets Capable of Binding the Same Ligand Open
Non linearities of biological networks present ample opportunity for synergistic protein targeting combinations. Yet, to date, our ability to design multi-target inhibitors and predict polypharmacology binding profiles remains limited. …
View article: Evaluation of Binding Site Comparison Algorithms and Proteometric Machine Learning Models in the Detection of Protein Pockets Capable of Binding the Same Ligand
Evaluation of Binding Site Comparison Algorithms and Proteometric Machine Learning Models in the Detection of Protein Pockets Capable of Binding the Same Ligand Open
Non linearities of biological networks present ample opportunity for synergistic protein targeting combinations. Yet, to date, our ability to design multi-target inhibitors and predict polypharmacology binding profiles remains limited. Her…
View article: Exploring New Crystal Structures of Glycine via Electric Field-Induced Structural Transformations with Molecular Dynamics Simulations
Exploring New Crystal Structures of Glycine via Electric Field-Induced Structural Transformations with Molecular Dynamics Simulations Open
Being able to control polymorphism of a crystal is of great importance to many industries, including the pharmaceutical industry, since the crystal’s structure determines significant physical properties of a material. While there are many …
View article: Extending the Crystal Landscape Through Electric Field Controlled Crystallization – a Molecular Dynamics Case Study
Extending the Crystal Landscape Through Electric Field Controlled Crystallization – a Molecular Dynamics Case Study Open
Through molecular dynamics simulations, we report on a new development concerned with creating hitherto unknown polymorphs by influencing crystallization with a suitably constituted electric field. The methodology has the potential to add …
View article: Extending the Crystal Landscape Through Electric Field Controlled Crystallization – a Molecular Dynamics Case Study
Extending the Crystal Landscape Through Electric Field Controlled Crystallization – a Molecular Dynamics Case Study Open
Through molecular dynamics simulations, we report on a new development concerned with creating hitherto unknown polymorphs by influencing crystallization with a suitably constituted electric field. The methodology has the potential to add …
View article: D3R Grand Challenge 3: Blind Prediction of Protein-Ligand Poses and Affinity Rankings
D3R Grand Challenge 3: Blind Prediction of Protein-Ligand Poses and Affinity Rankings Open
The Drug Design Data Resource aims to test and advance the state of the art in protein-ligand modeling, by holding community-wide blinded, prediction challenges. Here, we report on our third major round, Grand Challenge 3 (GC3). Held 2017-…
View article: D3R Grand Challenge 3: Blind Prediction of Protein-Ligand Poses and Affinity Rankings
D3R Grand Challenge 3: Blind Prediction of Protein-Ligand Poses and Affinity Rankings Open
The Drug Design Data Resource aims to test and advance the state of the art in protein-ligand modeling, by holding community-wide blinded, prediction challenges. Here, we report on our third major round, Grand Challenge 3 (GC3). Held 2017-…