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Journal of Medicinal Chemistry
|
December 13, 2002
AutoDocking dinucleotides to the HIV-1 integrase core domain: exploring possible binding sites for viral and genomic DNA
Alexander L Perryman, J Andrew McCammon
Plos Neglected Tropical Diseases
|
October 21, 2016
OpenZika: An IBM World Community Grid Project to Accelerate Zika Virus Drug Discovery
Sean Ekins, Alexander L Perryman, Carolina Horta Andrade
Chemical Biology & Drug Design
|
June 21, 2006
Optimization and computational evaluation of a series of potential active site inhibitors of the V82F/I84V drug-resistant mutant of HIV-1 protease: an application of the relaxed complex method of structure-based drug design
Alexander L Perryman, Jung-Hsin Lin, J Andrew McCammon
Protein Science : a Publication of the Protein Society
|
March 27, 2004
HIV-1 protease molecular dynamics of a wild-type and of the V82F/I84V mutant: possible contributions to drug resistance and a potential new target site for drugs
Alexander L Perryman, Jung-Hsin Lin, J Andrew McCammon
Biopolymers
|
March 2, 2006
Restrained molecular dynamics simulations of HIV-1 protease: the first step in validating a new target for drug design
Alexander L Perryman, Jung-Hsin Lin, J Andrew McCammon
Pharmaceutical Research
|
September 30, 2015
Predicting Mouse Liver Microsomal Stability with "Pruned" Machine Learning Models and Public Data
Alexander L Perryman, Thomas P Stratton, Sean Ekins, et al.
Biopolymers
|
February 13, 2003
The relaxed complex method: Accommodating receptor flexibility for drug design with an improved scoring scheme
Jung-Hsin Lin, Alexander L Perryman, Julie R Schames, et al.
Journal of the American Chemical Society
|
May 16, 2002
Computational drug design accommodating receptor flexibility: the relaxed complex scheme
Jung-Hsin Lin, Alexander L Perryman, Julie R Schames, et al.
ACS Omega
|
July 21, 2020
Pruned Machine Learning Models to Predict Aqueous Solubility
Alexander L Perryman, Daigo Inoyama, Jimmy S Patel, et al.
Journal of Chemical Information and Modeling
|
June 24, 2016
Machine Learning Model Analysis and Data Visualization with Small Molecules Tested in a Mouse Model of Mycobacterium tuberculosis Infection (2014-2015)
Sean Ekins, Alexander L Perryman, Alex M Clark, et al.
Page
of 4
Search research articles
Search
Showing results (1-10 of 40) with videos related to
Sort By:
Page
of 4
Journal of Medicinal Chemistry
|
December 13, 2002
AutoDocking dinucleotides to the HIV-1 integrase core domain: exploring possible binding sites for viral and genomic DNA
Alexander L Perryman, J Andrew McCammon
Plos Neglected Tropical Diseases
|
October 21, 2016
OpenZika: An IBM World Community Grid Project to Accelerate Zika Virus Drug Discovery
Sean Ekins, Alexander L Perryman, Carolina Horta Andrade
Chemical Biology & Drug Design
|
June 21, 2006
Optimization and computational evaluation of a series of potential active site inhibitors of the V82F/I84V drug-resistant mutant of HIV-1 protease: an application of the relaxed complex method of structure-based drug design
Alexander L Perryman, Jung-Hsin Lin, J Andrew McCammon
Protein Science : a Publication of the Protein Society
|
March 27, 2004
HIV-1 protease molecular dynamics of a wild-type and of the V82F/I84V mutant: possible contributions to drug resistance and a potential new target site for drugs
Alexander L Perryman, Jung-Hsin Lin, J Andrew McCammon
Biopolymers
|
March 2, 2006
Restrained molecular dynamics simulations of HIV-1 protease: the first step in validating a new target for drug design
Alexander L Perryman, Jung-Hsin Lin, J Andrew McCammon
Pharmaceutical Research
|
September 30, 2015
Predicting Mouse Liver Microsomal Stability with "Pruned" Machine Learning Models and Public Data
Alexander L Perryman, Thomas P Stratton, Sean Ekins, et al.
Biopolymers
|
February 13, 2003
The relaxed complex method: Accommodating receptor flexibility for drug design with an improved scoring scheme
Jung-Hsin Lin, Alexander L Perryman, Julie R Schames, et al.
Journal of the American Chemical Society
|
May 16, 2002
Computational drug design accommodating receptor flexibility: the relaxed complex scheme
Jung-Hsin Lin, Alexander L Perryman, Julie R Schames, et al.
ACS Omega
|
July 21, 2020
Pruned Machine Learning Models to Predict Aqueous Solubility
Alexander L Perryman, Daigo Inoyama, Jimmy S Patel, et al.
Journal of Chemical Information and Modeling
|
June 24, 2016
Machine Learning Model Analysis and Data Visualization with Small Molecules Tested in a Mouse Model of Mycobacterium tuberculosis Infection (2014-2015)
Sean Ekins, Alexander L Perryman, Alex M Clark, et al.
Page
of 4