日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

PRosettaC outperforms AlphaFold3 for modeling PROTAC ternary complexes

在模拟PROTAC三元复合物方面,PRosettaC的性能优于AlphaFold3。

Schulz, Joseph M; Schürer, Sarah I; Reynolds, Robert C; Schürer, Stephan C

Benchmarking the Builders: A Comparative Analysis of PRosettaC and AlphaFold3 for Predicting PROTAC Ternary Complexes

构建器性能对比分析:PRosettaC 和 AlphaFold3 在预测 PROTAC 三元复合物方面的比较分析

Schulz, Joseph M; Schürer, Sarah I; Reynolds, Robert C; Schürer, Stephan C

Targeted degrader technologies as prospective SARS-CoV-2 therapies

靶向降解技术作为潜在的SARS-CoV-2疗法

Khurshid, Rabia; Schulz, Joseph M; Hu, Jiaming; Snowden, Timothy S; Reynolds, Robert C; Schürer, Stephan C

Molecule Property Analyses of Active Compounds for Mycobacterium tuberculosis

结核分枝杆菌活性化合物的分子性质分析

Makarov, Vadim; Salina, Elena; Reynolds, Robert C; Kyaw Zin, Phyo Phyo; Ekins, Sean

Comparing and Validating Machine Learning Models for Mycobacterium tuberculosis Drug Discovery.

比较和验证用于结核分枝杆菌药物发现的机器学习模型

Lane Thomas, Russo Daniel P, Zorn Kimberley M, Clark Alex M, Korotcov Alexandru, Tkachenko Valery, Reynolds Robert C, Perryman Alexander L, Freundlich Joel S, Ekins Sean

Oxazole and thiazole analogs of sulindac for cancer prevention

舒林酸的噁唑和噻唑类似物用于癌症预防

Mathew, Bini; Hobrath, Judith V; Connelly, Michele C; Guy, R Kiplin; Reynolds, Robert C

A small diversity library of α-methyl amide analogs of sulindac for probing anticancer structure-activity relationships

构建了一个包含舒林酸α-甲基酰胺类似物的小型多样性化合物库,用于探索抗癌化合物的构效关系。

Mathew, Bini; Snowden, Timothy S; Connelly, Michele C; Guy, R Kiplin; Reynolds, Robert C

Diverse amide analogs of sulindac for cancer treatment and prevention

用于癌症治疗和预防的舒林酸多种酰胺类似物

Mathew, Bini; Hobrath, Judith V; Connelly, Michele C; Kiplin Guy, R; Reynolds, Robert C

Screening and Development of New Inhibitors of FtsZ from M. Tuberculosis

结核分枝杆菌FtsZ新抑制剂的筛选与开发

Mathew, Bini; Hobrath, Judith Varady; Ross, Larry; Connelly, Michele C; Lofton, Hava; Rajagopalan, Malini; Guy, R Kiplin; Reynolds, Robert C

Open Source Bayesian Models. 1. Application to ADME/Tox and Drug Discovery Datasets

开源贝叶斯模型。1. 在 ADME/Tox 和药物发现数据集上的应用

Clark, Alex M; Dole, Krishna; Coulon-Spektor, Anna; McNutt, Andrew; Grass, George; Freundlich, Joel S; Reynolds, Robert C; Ekins, Sean