Alexander Luke Perryman
Affiliations: | 2005 | University of California, San Diego, La Jolla, CA |
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"Alexander Perryman"Mean distance: 8.42 | S | N | B | C | P |
Parents
Sign in to add mentor| J. Andrew McCammon | grad student | 2005 | UCSD | |
| (Computer-aided protein structure studies: Hunting down the hidden secrets of HIV.) | ||||
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Publications
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| Mottin M, de Paula Sousa BK, de Moraes Roso Mesquita NC, et al. (2022) Discovery of New Zika Protease and Polymerase Inhibitors through the Open Science Collaboration Project OpenZika. Journal of Chemical Information and Modeling |
| Pereira JC, Daher SS, Zorn KM, et al. (2020) Machine Learning Platform to Discover Novel Growth Inhibitors of Neisseria gonorrhoeae. Pharmaceutical Research. 37: 141 |
| Silva S, Shimizu JF, Oliveira DM, et al. (2019) A diarylamine derived from anthranilic acid inhibits ZIKV replication. Scientific Reports. 9: 17703 |
| Wang X, Perryman A, Li SG, et al. (2019) Intrabacterial Metabolism Obscures the Successful Prediction of an InhA Inhibitor of Mycobacterium tuberculosis. Acs Infectious Diseases |
| Kumar P, Capodagli GC, Awasthi D, et al. (2018) Synergistic Lethality of a Binary Inhibitor of Mycobacterium tuberculosis KasA. Mbio. 9 |
| Perryman AL, Patel JS, Russo R, et al. (2018) Naïve Bayesian Models for Vero Cell Cytotoxicity. Pharmaceutical Research. 35: 170 |
| Mottin M, Borba JVVB, Braga RC, et al. (2018) The A-Z of Zika drug discovery. Drug Discovery Today |
| Lane T, Russo DP, Zorn KM, et al. (2018) Comparing and Validating Machine Learning Models for Mycobacterium tuberculosis Drug Discovery. Molecular Pharmaceutics |
| Inoyama D, Paget SD, Russo R, et al. (2018) Novel Pyrimidines as Antitubercular Agents. Antimicrobial Agents and Chemotherapy |
| Stratton TP, Perryman AL, Vilchèze C, et al. (2017) Addressing the Metabolic Stability of Antituberculars through Machine Learning. Acs Medicinal Chemistry Letters. 8: 1099-1104 |