Supporting data and code for: Machine Learning analysis of protein-ligand interaction fingerprints (IF) extracted from tau-RAMD dissociation trajectories for inhibitors of HSP90

Advanced computational and machine learning tools in pharmaceutical informatics

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Supporting data and code for: Machine Learning analysis of protein-ligand interaction fingerprints (IF) extracted from tau-RAMD dissociation trajectories for inhibitors of HSP90

Daria B. Kokh
Tom Kaufmann
Bastian Kister
Rebecca C. Wade

March 2019

Supporting data and code for the manuscript: "Machine learning analysis of tauRAMD trajectories to ...

Machine Learning Analysis of τRAMD Trajectories to Decipher Molecular Determinants of Drug-Target Residence Times

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Tom Kaufmann
Bastian Kister
Rebecca C. Wade

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Daria B. Kokh (1486933)
Tom Kaufmann (6643430)
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Drug-target residence times can impact drug efficacy and safety, and are therefore increasingly bein...

Table_1_Machine Learning Analysis of τRAMD Trajectories to Decipher Molecular Determinants of Drug-Target Residence Times.XLSX

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Drug-target residence times can impact drug efficacy and safety, and are therefore increasingly bein...

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Accurate identification of drug targets is a crucial part of any drug development program. We mined ...

Data set for validation of a Python script for computation of Protein-Ligand Interaction Fingerprints

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Data set for validation of a Python script for computation of Protein-Ligand Interaction Fingerprints

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Data of "Chemistrees: Data-Driven Identification of Reaction Pathways via Machine Learning"

Roet, Sander
Daub, Christopher D
Riccardi, Enrico

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This is the data and assosiated in-house code for the paper: Chemistrees: Data-Driven Identificatio...

G-Protein Coupled Receptor-Ligand Dissociation Rates and Mechanisms from tauRAMD Simulations

Daria B. Kokh
Rebecca C. Wade

May 2021

Data and Python scripts used for analysis of RAMD dissociation trajectories for several GPCR compl...

Advanced computational and machine learning tools in pharmaceutical informatics

Maddipati, Sridhar V. V. S

January 2007

Computational and informatics approaches are of immediate necessity in the drug discovery research t...

Code and data for "Discovery of senolytics using machine learning"

Smer-Barreto, Vanessa
Quintanilla, Andrea
Elliot, Richard J. R.
Dawson, John C.
Sun, Jiugeng
Lorente-Macías, Álvaro
Unciti-Broceta, Asier
Carragher, Neil O.
Acosta, Juan Carlos
Oyarzún, Diego A.

April 2023

Code and data for paper "Discovery of senolytics using machine learning" by Smer-Barreto et al, 2023...

Machine Learning Models to Predict Protein–Protein Interaction Inhibitors

Bárbara I. Díaz-Eufracio
José L. Medina-Franco

November 2022

Protein–protein interaction (PPI) inhibitors have an increasing role in drug discovery. It is hypoth...

Supporting data and code for: Machine Learning analysis of protein-ligand interaction fingerprints (IF) extracted from tau-RAMD dissociation trajectories for inhibitors of HSP90

Daria B. Kokh
Tom Kaufmann
Bastian Kister
Rebecca C. Wade

March 2019

Supporting data and code for the manuscript: "Machine learning analysis of tauRAMD trajectories to ...

Machine Learning Analysis of τRAMD Trajectories to Decipher Molecular Determinants of Drug-Target Residence Times

Daria B. Kokh
Tom Kaufmann
Bastian Kister
Rebecca C. Wade

March 2019

The manuscript, supporting data and codes for the manuscript: "Machine learning analysis of tauRAMD...

Data_Sheet_1_Machine Learning Analysis of τRAMD Trajectories to Decipher Molecular Determinants of Drug-Target Residence Times.pdf

Daria B. Kokh (1486933)
Tom Kaufmann (6643430)
Bastian Kister (6643433)
Rebecca C. Wade (170810)

May 2019

Drug-target residence times can impact drug efficacy and safety, and are therefore increasingly bein...

Table_1_Machine Learning Analysis of τRAMD Trajectories to Decipher Molecular Determinants of Drug-Target Residence Times.XLSX

Daria B. Kokh (1486933)
Tom Kaufmann (6643430)
Bastian Kister (6643433)
Rebecca C. Wade (170810)

May 2019

Drug-target residence times can impact drug efficacy and safety, and are therefore increasingly bein...

RESEARCH ARTICLE Properties of Protein Drug Target Classes

Simon C. Bull
Andrew J. Doig

August 2016

Accurate identification of drug targets is a crucial part of any drug development program. We mined ...

Data set for validation of a Python script for computation of Protein-Ligand Interaction Fingerprints

Daria Kokh

July 2020

Data set for for validation of the Protein-Ligand Interaction Fingerprints, which includes examples...

Checking the STEP-Associated Trafficking and Internalization of Glutamate Receptors for Reduced Cognitive Deficits: A Machine Learning Approach-Based Cheminformatics Study and Its Application for Drug Repurposing

Jamal Salma
Goyal Sukriti
Shanker Asheesh
Grover Abhinav

June 2015

Alzheimer’s disease, a lethal neurodegenerative disorder that leads to progressive memory loss, is t...

Data set for validation of a Python script for computation of Protein-Ligand Interaction Fingerprints

Daria Kokh

November 2020

1. Data set for for validation of the Protein-Ligand Interaction Fingerprints, which includes examp...

Machine learning for target discovery in drug development

Rodrigues, Tiago
Bernardes, Gonçalo J. L.

January 2020

SPLDExtraTrees: Robust machine learning approach for predicting kinase inhibitor resistance

Yang, Ziyi
Ye, Zhaofeng
Xiao, Yijia
Hsieh, Changyu
Zhang, Shengyu

January 2022

Drug resistance is a major threat to the global health and a significant concern throughout the clin...

Data of "Chemistrees: Data-Driven Identification of Reaction Pathways via Machine Learning"

Roet, Sander
Daub, Christopher D
Riccardi, Enrico

September 2021

This is the data and assosiated in-house code for the paper: Chemistrees: Data-Driven Identificatio...

G-Protein Coupled Receptor-Ligand Dissociation Rates and Mechanisms from tauRAMD Simulations

Daria B. Kokh
Rebecca C. Wade

May 2021

Data and Python scripts used for analysis of RAMD dissociation trajectories for several GPCR compl...

Advanced computational and machine learning tools in pharmaceutical informatics

Maddipati, Sridhar V. V. S

January 2007

Computational and informatics approaches are of immediate necessity in the drug discovery research t...

Code and data for "Discovery of senolytics using machine learning"

Smer-Barreto, Vanessa
Quintanilla, Andrea
Elliot, Richard J. R.
Dawson, John C.
Sun, Jiugeng
Lorente-Macías, Álvaro
Unciti-Broceta, Asier
Carragher, Neil O.
Acosta, Juan Carlos
Oyarzún, Diego A.

April 2023

Code and data for paper "Discovery of senolytics using machine learning" by Smer-Barreto et al, 2023...

Machine Learning Models to Predict Protein–Protein Interaction Inhibitors

Bárbara I. Díaz-Eufracio
José L. Medina-Franco

November 2022

Protein–protein interaction (PPI) inhibitors have an increasing role in drug discovery. It is hypoth...

Supporting data and code for: Machine Learning analysis of protein-ligand interaction fingerprints (IF) extracted from tau-RAMD dissociation trajectories for inhibitors of HSP90

Abstract

Extracted data

Supporting data and code for: Machine Learning analysis of protein-ligand interaction fingerprints (IF) extracted from tau-RAMD dissociation trajectories for inhibitors of HSP90

Abstract

Extracted data

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