Halogen bonding has been known in material science for decades, but until recently, halogen bonds in protein-ligand interactions were largely the result of serendipitous discovery rather than rational design. In this Perspective, we provide insights into the phenomenon of halogen bonding, with special focus on its role in drug discovery. We summarize the theoretical background defining its strength and directionality, provide a systematic analysis of its occurrence and interaction geometries in protein-ligand complexes, and give recent examples where halogen bonding has been successfully harnessed for lead identification and optimization. In light of these data, we discuss the potential and limitations of exploiting halogen bonds for molecular recognition and rational drug design.
The tumor suppressor p53 is mutationally inactivated in Ϸ50% of human cancers. Approximately one-third of the mutations lower the melting temperature of the protein, leading to its rapid denaturation. Small molecules that bind to those mutants and stabilize them could be effective anticancer drugs. The mutation Y220C, which occurs in Ϸ75,000 new cancer cases per annum, creates a surface cavity that destabilizes the protein by 4 kcal/mol, at a site that is not functional. We have designed a series of binding molecules from an in silico analysis of the crystal structure using virtual screening and rational drug design. One of them, a carbazole derivative (PhiKan083), binds to the cavity with a dissociation constant of Ϸ150 M. It raises the melting temperature of the mutant and slows down its rate of denaturation. We have solved the crystal structure of the proteinPhiKan083 complex at 1.5-Å resolution. The structure implicates key interactions between the protein and ligand and conformational changes that occur on binding, which will provide a basis for lead optimization. The Y220C mutant is an excellent ''druggable'' target for developing and testing novel anticancer drugs based on protein stabilization. We point out some general principles in relationships between binding constants, raising of melting temperatures, and increase of protein half-lives by stabilizing ligands.NMR screen ͉ oncogenic mutant ͉ protein stabilization ͉ virtual drug design ͉ crystal structure
The destabilizing p53 cancer mutation Y220C creates a druggable surface crevice. We developed a strategy exploiting halogen bonding for lead discovery to stabilize the mutant with small molecules. We designed halogen-enriched fragment libraries (HEFLibs) as starting points to complement classical approaches. From screening of HEFLibs and subsequent structure-guided design, we developed substituted 2-(aminomethyl)-4-ethynyl-6-iodophenols as p53-Y220C stabilizers. Crystal structures of their complexes highlight two key features: (i) a central scaffold with a robust binding mode anchored by halogen bonding of an iodine with a main-chain carbonyl and (ii) an acetylene linker, enabling the targeting of an additional subsite in the crevice. The best binders showed induction of apoptosis in a human cancer cell line with homozygous Y220C mutation. Our structural and biophysical data suggest a more widespread applicability of HEFLibs in drug discovery.
The application of molecular benchmarking sets helps to assess the actual performance of virtual screening (VS) workflows. To improve the efficiency of structure-based VS approaches, the selection and optimization of various parameters can be guided by benchmarking. With the DEKOIS 2.0 library, we aim to further extend and complement the collection of publicly available decoy sets. Based on BindingDB bioactivity data, we provide 81 new and structurally diverse benchmark sets for a wide variety of different target classes. To ensure a meaningful selection of ligands, we address several issues that can be found in bioactivity data. We have improved our previously introduced DEKOIS methodology with enhanced physicochemical matching, now including the consideration of molecular charges, as well as a more sophisticated elimination of latent actives in the decoy set (LADS). We evaluate the docking performance of Glide, GOLD, and AutoDock Vina with our data sets and highlight existing challenges for VS tools. All DEKOIS 2.0 benchmark sets will be made accessible at http://www.dekois.com.
Halogen bonds are specific embodiments of the sigma hole bonding paradigm. They represent directional interactions between the halogens chlorine, bromine, or iodine and an electron donor as binding partner. Using quantum chemical calculations at the MP2 level, we systematically explore how they can be used in molecular design to address the omnipresent carbonyls of the protein backbone. We characterize energetics and directionality and elucidate their spatial variability in sub-optimal geometries that are expected to occur in protein-ligand complexes featuring a multitude of concomitant interactions. By deriving simple rules, we aid medicinal chemists and chemical biologists in easily exploiting them for scaffold decoration and design. Our work shows that carbonyl-halogen bonds may be used to expand the patentable medicinal chemistry space, redefining halogens as key features. Furthermore, this data will be useful for implementing halogen bonds into pharmacophore models or scoring functions making the QM information available for automatic molecular recognition in virtual high throughput screening.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.