Author

A. Rizzi

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Biophysics· 5 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 4 Approach:statistical model· 4 Approach:deep learning· 3 Assay:bulk RNA-seq· 1 Research Focus:cancer & tumor microenvironment· 1 Approach:experimental assay· 1 Organism:human· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

J. D. Chodera· 6 shared D. L. Mobley· 4 shared M. K. Gilson· 3 shared M. Isık· 2 shared M. R. Shirts· 2 shared A. Chow· 1 shared A. Dickson· 1 shared A. S. Rustenburg· 1 shared

Activity by Year

2018-2020 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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6 shared papersBiophysics

J. D. Chodera

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Author profile →

6 papers

Recent·Most cited

Overview of the SAMPL6 pKa Challenge: Evaluating small molecule microscopic and macroscopic pKa predictions

M. Isık, A. S. Rustenburg, A. Rizzi, M. R. Gunner, D. L. Mobley, J. D. Chodera

The paper evaluates pKa prediction methods for drug-like molecules, finding that top submissions achieved RMSE of 0.7-1.0 pKa units, but significant inaccuracies remain, especially for sulfur-containing heterocycles and multiprotic molecules.

bioRxiv · Oct 15, 2020Biophysics

Assessing the accuracy of octanol-water partition coefficient predictions in the SAMPL6 Part II log P Challenge

M. Isık, T. D. Bergazin, T. Fox, A. Rizzi, J. D. Chodera, D. L. Mobley

This paper evaluates the accuracy of octanol-water partition coefficient predictions in the SAMPL6 log P Challenge, finding improved performance compared to previous challenges and highlighting the effectiveness of various methods.

bioRxiv · Jan 20, 2020Biophysics

The SAMPL6 SAMPLing challenge: Assessing the reliability and efficiency of binding free energy calculations

A. Rizzi, T. Jensen, D. R. Slochower, M. Aldeghi, V. Gapsys, D. Ntekoumes, S. Bosisio, M. Papadourakis, N. M. Henriksen, B. L. de Groot, Z. Cournia, A. Dickson, J. Michel, M. K. Gilson, M. R. Shirts, , J. D. Chodera

This study evaluates binding free energy calculation methods using the SAMPL6 challenge, finding variations in efficiency and reproducibility across different systems and methods.

bioRxiv · Jan 3, 2020Biophysics

Small-molecule targeting of MUSASHI RNA-binding activity in acute myeloid leukemia

G. Minuesa, S. K. Albanese, A. Chow, A. Schurer, S.-M. Park, C. Z. Rotsides, J. Taggart, A. Rizzi, L. N. Naden, T. Chou, S. Gourkanti, D. Cappel, M. C. Passarelli, L. Fairchild, C. Adura, , M. G. Kharas

This study identifies Ro 08-2750 as a small molecule that targets MSI2 RNA-binding activity, inducing differentiation, apoptosis, and reduced disease burden in AML models.

Nature Communications · Jun 19, 2019Peer-reviewedCancer Biology

Overview of the SAMPL6 host-guest binding affinity prediction challenge

A. Rizzi, S. Murkli, J. N. McNeill, W. Yao, M. Sullivan, M. K. Gilson, M. W. Chiu, L. Isaacs, B. C. Gibb, D. L. Mobley, J. D. Chodera

This paper provides an overview of the SAMPL6 host-guest binding affinity prediction challenge, highlighting methodological improvements and remaining challenges in predicting binding affinities.

bioRxiv · Sep 25, 2018Biophysics

Open Force Field Consortium: Escaping atom types using direct chemical perception with SMIRNOFF v0.1

D. Mobley, C. C. Bannan, A. Rizzi, C. I. Bayly, J. D. Chodera, V. T. Lim, N. M. Lim, K. A. Beauchamp, M. R. Shirts, M. K. Gilson, P. K. Eastman

The paper introduces a new approach to molecular mechanics force fields using direct chemical perception, reducing parameter count while maintaining accuracy.

bioRxiv · Jul 13, 2018 · PreprintBiophysics