scholarly journals The Druggable Genome as Seen from the Protein Data Bank

2020 ◽  
Author(s):  
Jiayan Wang ◽  
Setayesh Yazdani ◽  
Ana Han ◽  
Matthieu Schapira

AbstractAlmost twenty years after the human genome was sequenced, the wealth of data produced by the international human genome project has not translated into a significantly improved drug discovery enterprise. This is in part because small molecule modulators that could be used to explore the cellular function of their target proteins and to discover new therapeutic opportunities are only available for a limited portion of the human proteome. International efforts are underway to develop such chemical tools for a few, specific protein families, and a “Target 2035” call to enable, expand and federate these efforts towards a comprehensive chemical coverage of the druggable genome was recently announced. But what is the druggable genome? Here, we systematically review structures of human proteins bound to drug-like ligands available from the protein databank (PDB) and use ligand desolvation upon binding as a druggability metric to draw a landscape of the human druggable genome. We show that the vast majority of druggable protein families, including some highly populated and deeply associated with cancer according to genomic screens, are almost orphan of small molecule ligands, and propose a list of 46 druggable domains representing 3440 human proteins that could be the focus of large chemical probe discovery efforts.

2018 ◽  
Vol 46 (5) ◽  
pp. 1367-1379 ◽  
Author(s):  
Tracy L. Nero ◽  
Michael W. Parker ◽  
Craig J. Morton

The first protein structures revealed a complex web of weak interactions stabilising the three-dimensional shape of the molecule. Small molecule ligands were then found to exploit these same weak binding events to modulate protein function or act as substrates in enzymatic reactions. As the understanding of ligand–protein binding grew, it became possible to firstly predict how and where a particular small molecule might interact with a protein, and then to identify putative ligands for a specific protein site. Computer-aided drug discovery, based on the structure of target proteins, is now a well-established technique that has produced several marketed drugs. We present here an overview of the various methodologies being used for structure-based computer-aided drug discovery and comment on possible future developments in the field.


Genes ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 546 ◽  
Author(s):  
Matthew D. Strub ◽  
Paul B. McCray, Jr.

Cystic fibrosis (CF) is a lethal autosomal recessive disease caused by mutations in the CF transmembrane conductance regulator (CFTR) gene. The diversity of mutations and the multiple ways by which the protein is affected present challenges for therapeutic development. The observation that the Phe508del-CFTR mutant protein is temperature sensitive provided proof of principle that mutant CFTR could escape proteosomal degradation and retain partial function. Several specific protein interactors and quality control checkpoints encountered by CFTR during its proteostasis have been investigated for therapeutic purposes, but remain incompletely understood. Furthermore, pharmacological manipulation of many CFTR interactors has not been thoroughly investigated for the rescue of Phe508del-CFTR. However, high-throughput screening technologies helped identify several small molecule modulators that rescue CFTR from proteosomal degradation and restore partial function to the protein. Here, we discuss the current state of CFTR transcriptomic and biogenesis research and small molecule therapy development. We also review recent progress in CFTR proteostasis modulators and discuss how such treatments could complement current FDA-approved small molecules.


Author(s):  
Nolan M. Dvorak ◽  
Paul A. Wadsworth ◽  
Pingyuan Wang ◽  
Jia Zhou ◽  
Fernanda Laezza

: Given their primacy in governing the action potential (AP) of excitable cells, voltage-gated Na+ (Nav) channels are important pharmacological targets of therapeutics for a diverse array of clinical indications. Despite historically being a traditional drug target, therapeutics targeting Nav channels lack isoform selectivity, giving rise to off-target side effects. To develop isoform-selective modulators of Nav channels with improved target-specificity, the identification and pharmacological targeting of allosteric sites that display structural divergence among Nav channel isoforms represents an attractive approach. Despite the high homology among Nav channel α subunit isoforms (Nav1.1-Nav1.9), there is considerable amino acid sequence divergence among their constituent C-terminal domains (CTD), which enables structurally and functionally specific protein: protein interaction (PPI) with auxiliary proteins. Although pharmacological targeting of such PPI interfaces between the CTDs of Nav channels and auxiliary proteins represents an innovate approach for developing isoform-selective modulators of Nav channels, appreciable modulation of PPIs using small molecules has conventionally been difficult to achieve. After briefly discussing the challenges of modulating PPIs using small molecules, this current frontier review that follows subsequently expounds on approaches for circumventing such difficulties in the context of developing small molecule modulators of PPIs between transmembrane ion channels and their auxiliary proteins. In addition to broadly discussing such approaches, the implementation of such approaches is specifically discussed in the context of developing small molecule modulators between the CTD of Nav channels and auxiliary proteins. Developing allosteric modulators of ion channels by targeting their PPI interfaces with auxiliary proteins represents an innovative and promising strategy in ion channel drug discovery that could expand the “druggable genome” and usher in first-in-class PPI-targeting therapeutics for a multitude of channelopathies.


Structure ◽  
2022 ◽  
Author(s):  
Chenghua Shao ◽  
John D. Westbrook ◽  
Changpeng Lu ◽  
Charmi Bhikadiya ◽  
Ezra Peisach ◽  
...  

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