Theoretical models of inhibitory activity for inhibitors of protein–protein interactions: targeting menin–mixed lineage leukemia with small molecules
| Autor: | Trupta Purohit, Edyta Dyguda-Kazimierowicz, Tomasz Cierpicki, Wiktoria Jedwabny, Jolanta Grembecka, Szymon Klossowski |
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| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Pharmacology Lineage (genetic) 010405 organic chemistry Drug discovery Stereochemistry Chemistry Organic Chemistry Ab initio Pharmaceutical Science Interaction energy Computational biology Inhibitory postsynaptic potential 01 natural sciences Biochemistry Small molecule 0104 chemical sciences Protein–protein interaction 03 medical and health sciences 030104 developmental biology MIXED LINEAGE LEUKEMIA Drug Discovery Molecular Medicine |
| Zdroj: | MedChemComm. 8:2216-2227 |
| ISSN: | 2040-2511 2040-2503 |
| DOI: | 10.1039/c7md00170c |
| Popis: | Development and binding affinity predictions of inhibitors targeting protein-protein interactions (PPI) still represent a major challenge in drug discovery efforts. This work reports application of a predictive non-empirical model of inhibitory activity for PPI inhibitors, exemplified here for small molecules targeting the menin-mixed lineage leukemia (MLL) interaction. Systematic ab initio analysis of menin-inhibitor complexes was performed, revealing the physical nature of these interactions. Notably, the non-empirical protein-ligand interaction energy comprising electrostatic multipole and approximate dispersion terms (E(10)El,MTP + EDas) produced a remarkable correlation with experimentally measured inhibitory activities and enabled accurate activity prediction for new menin-MLL inhibitors. Importantly, this relatively simple and computationally affordable non-empirical interaction energy model outperformed binding affinity predictions derived from commonly used empirical scoring functions. This study demonstrates high relevance of the non-empirical model we developed for binding affinity prediction of inhibitors targeting protein-protein interactions that are difficult to predict using empirical scoring functions. |
| Databáze: | OpenAIRE |
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