Detalhe da pesquisa
1.
MEN1 mutations mediate clinical resistance to menin inhibition.
Nature
; 615(7954): 913-919, 2023 03.
Artigo
em Inglês
| MEDLINE | ID: mdl-36922589
2.
SARS-CoV-2 RBD antibodies that maximize breadth and resistance to escape.
Nature
; 597(7874): 97-102, 2021 09.
Artigo
em Inglês
| MEDLINE | ID: mdl-34261126
3.
Turning high-throughput structural biology into predictive inhibitor design.
Proc Natl Acad Sci U S A
; 120(11): e2214168120, 2023 03 14.
Artigo
em Inglês
| MEDLINE | ID: mdl-36877844
4.
GCN2 kinase activation by ATP-competitive kinase inhibitors.
Nat Chem Biol
; 18(2): 207-215, 2022 02.
Artigo
em Inglês
| MEDLINE | ID: mdl-34949839
5.
Enhancing Protein-Ligand Binding Affinity Predictions Using Neural Network Potentials.
J Chem Inf Model
; 64(5): 1481-1485, 2024 Mar 11.
Artigo
em Inglês
| MEDLINE | ID: mdl-38376463
6.
EspalomaCharge: Machine Learning-Enabled Ultrafast Partial Charge Assignment.
J Phys Chem A
; 2024 May 08.
Artigo
em Inglês
| MEDLINE | ID: mdl-38717302
7.
Acquired resistance to IDH inhibition through trans or cis dimer-interface mutations.
Nature
; 559(7712): 125-129, 2018 07.
Artigo
em Inglês
| MEDLINE | ID: mdl-29950729
8.
Mutation in Abl kinase with altered drug-binding kinetics indicates a novel mechanism of imatinib resistance.
Proc Natl Acad Sci U S A
; 118(46)2021 11 16.
Artigo
em Inglês
| MEDLINE | ID: mdl-34750265
9.
NNP/MM: Accelerating Molecular Dynamics Simulations with Machine Learning Potentials and Molecular Mechanics.
J Chem Inf Model
; 63(18): 5701-5708, 2023 09 25.
Artigo
em Inglês
| MEDLINE | ID: mdl-37694852
10.
Bayesian-Inference-Driven Model Parametrization and Model Selection for 2CLJQ Fluid Models.
J Chem Inf Model
; 62(4): 874-889, 2022 02 28.
Artigo
em Inglês
| MEDLINE | ID: mdl-35129974
11.
Open Force Field BespokeFit: Automating Bespoke Torsion Parametrization at Scale.
J Chem Inf Model
; 62(22): 5622-5633, 2022 11 28.
Artigo
em Inglês
| MEDLINE | ID: mdl-36351167
12.
Overview of the SAMPL6 pKa challenge: evaluating small molecule microscopic and macroscopic pKa predictions.
J Comput Aided Mol Des
; 35(2): 131-166, 2021 02.
Artigo
em Inglês
| MEDLINE | ID: mdl-33394238
13.
Automated high throughput pKa and distribution coefficient measurements of pharmaceutical compounds for the SAMPL8 blind prediction challenge.
J Comput Aided Mol Des
; 35(11): 1141-1155, 2021 11.
Artigo
em Inglês
| MEDLINE | ID: mdl-34714468
14.
Quantum Chemistry Common Driver and Databases (QCDB) and Quantum Chemistry Engine (QCEngine): Automation and interoperability among computational chemistry programs.
J Chem Phys
; 155(20): 204801, 2021 Nov 28.
Artigo
em Inglês
| MEDLINE | ID: mdl-34852489
15.
Is Structure-Based Drug Design Ready for Selectivity Optimization?
J Chem Inf Model
; 60(12): 6211-6227, 2020 12 28.
Artigo
em Inglês
| MEDLINE | ID: mdl-33119284
16.
Octanol-water partition coefficient measurements for the SAMPL6 blind prediction challenge.
J Comput Aided Mol Des
; 34(4): 405-420, 2020 04.
Artigo
em Inglês
| MEDLINE | ID: mdl-31858363
17.
Assessing the accuracy of octanol-water partition coefficient predictions in the SAMPL6 Part II log P Challenge.
J Comput Aided Mol Des
; 34(4): 335-370, 2020 04.
Artigo
em Inglês
| MEDLINE | ID: mdl-32107702
18.
Standard state free energies, not pKas, are ideal for describing small molecule protonation and tautomeric states.
J Comput Aided Mol Des
; 34(5): 561-573, 2020 05.
Artigo
em Inglês
| MEDLINE | ID: mdl-32052350
19.
The SAMPL6 SAMPLing challenge: assessing the reliability and efficiency of binding free energy calculations.
J Comput Aided Mol Des
; 34(5): 601-633, 2020 05.
Artigo
em Inglês
| MEDLINE | ID: mdl-31984465
20.
Quantitative self-assembly prediction yields targeted nanomedicines.
Nat Mater
; 17(4): 361-368, 2018 04.
Artigo
em Inglês
| MEDLINE | ID: mdl-29403054