Next Article in Journal
Organocatalytic Michael Addition to (D)-Mannitol-Derived Enantiopure Nitroalkenes: A Valuable Strategy for the Synthesis of Densely Functionalized Chiral Molecules
Previous Article in Journal
Kleeb Bua Daeng, a Thai Traditional Herbal Formula, Ameliorated Unpredictable Chronic Mild Stress-Induced Cognitive Impairment in ICR Mice
Previous Article in Special Issue
Structure–Activity Relationships of 7-Substituted Dimethyltyrosine-Tetrahydroisoquinoline Opioid Peptidomimetics
Open AccessFeature PaperArticle

Rigorous Computational and Experimental Investigations on MDM2/MDMX-Targeted Linear and Macrocyclic Peptides

1
CMDBioscience, 5 Park Avenue, New Haven, CT 06511, USA
2
Venenum BioDesign, LLC, 8 Black Forest Road, Hamilton, NJ 08691, USA
3
ChemModeling, LLC, Suite 101, 500 Huber Park Ct, Weldon Spring, MO 63304, USA
4
Kleo Pharmaceuticals, 25 Science Park, Ste 235, New Haven, CT 06511, USA
5
A*STAR, p53 Laboratory, Singapore 138648, Singapore
6
MSD International GmbH, Singapore 138665, Singapore
7
Merck Research Laboratories, 33 Avenue Louis Pasteur, Boston, MA 02115, USA
8
College of Arts and Sciences, Department of Chemistry, Sacred Heart University, 5151 Park Avenue, Fairfield, CT 06825, USA
*
Authors to whom correspondence should be addressed.
Molecules 2019, 24(24), 4586; https://doi.org/10.3390/molecules24244586
Received: 24 November 2019 / Revised: 11 December 2019 / Accepted: 12 December 2019 / Published: 14 December 2019
There is interest in peptide drug design, especially for targeting intracellular protein–protein interactions. Therefore, the experimental validation of a computational platform for enabling peptide drug design is of interest. Here, we describe our peptide drug design platform (CMDInventus) and demonstrate its use in modeling and predicting the structural and binding aspects of diverse peptides that interact with oncology targets MDM2/MDMX in comparison to both retrospective (pre-prediction) and prospective (post-prediction) data. In the retrospective study, CMDInventus modules (CMDpeptide, CMDboltzmann, CMDescore and CMDyscore) were used to accurately reproduce structural and binding data across multiple MDM2/MDMX data sets. In the prospective study, CMDescore, CMDyscore and CMDboltzmann were used to accurately predict binding affinities for an Ala-scan of the stapled α-helical peptide ATSP-7041. Remarkably, CMDboltzmann was used to accurately predict the results of a novel D-amino acid scan of ATSP-7041. Our investigations rigorously validate CMDInventus and support its utility for enabling peptide drug design. View Full-Text
Keywords: peptide design; free energy calculation; d-amino acid scan; alanine scan peptide design; free energy calculation; d-amino acid scan; alanine scan
Show Figures

Figure 1

MDPI and ACS Style

Diller, D.J.; Swanson, J.; Bayden, A.S.; Brown, C.J.; Thean, D.; Lane, D.P.; Partridge, A.W.; Sawyer, T.K.; Audie, J. Rigorous Computational and Experimental Investigations on MDM2/MDMX-Targeted Linear and Macrocyclic Peptides. Molecules 2019, 24, 4586.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop