KID: A Kinase-Focused Interaction Database and Its Application in the Construction of Kinase-Focused Molecule Databases

Abstract

Protein kinases are important drug targets for the treatment of several diseases. The interaction between kinases and ligands is vital in the process of small-molecule kinase inhibitor (SMKI) design. In this study, we propose a method to extract fragments and amino acid residues from crystal structures for kinase–ligand interactions. In addition, core fragments that interact with the important hinge region of kinases were extracted along with their decorations. Based on the superimposed structural data of kinases from the kinase–ligand interaction fingerprint and structure database, we obtained two libraries, namely, a hinge-unfocused fragment–amino acid pair library (FAP Lib) that contains 6672 pairs of fragments and corresponding amino-acids, and a hinge-focused hinge binder library (HB Lib) of 3560 pairs of hinge-binding scaffolds with their corresponding decorations. These two libraries constitute a kinase-focused interaction database (KID). In depth analysis was conducted on KID to explore important characteristics of fragments in the design of SMKIs. With KID, we built two kinase-focused molecule databases, one called Recomb_DB, which contains 1,72,346 molecules generated through fragment recombination based on the FAP Lib, and another called RsdHB_DB, which contains 93,030 molecules generated based on our HB Lib using molecular generation methods. Compared with five databases both commercial and non-commercial, these two databases both ranked top 3 in scaffold diversity, top 4 in molecule fingerprint diversity, and are more focused on the chemical space of kinase inhibitors. Hence, KID presents a useful addition to existing databases for the exploration of novel SMKIs.

Computational Approaches to Enzyme Inhibition by Marine Natural Products in the Search for New Drugs

“…To this end, kinome-wide inhibitory selectivity profiling is necessary because small assay panels cannot provide a robust measure of selectivity [ 193 ]. Binding site similarity searches, as performed in the KinomeFEATURE ( , accessed on 20 December 2022) [ 194 ] and KID [ 195 ] databases, along with machine learning models that map the activity profile of inhibitors across the entire human kinome [ 196 ], as exemplified by Drug Discovery Maps [ 197 ], can be of help not only to gain insight into the structural basis of kinase cross-inhibition, but also to predict the binding affinities of novel kinase inhibitors.…”

In silico construction of a focused fragment library facilitating exploration of chemical space**

“…For example, Dai et al. [8] collected thousands of pairs of fragments with their corresponding amino acid residues in the kinase database KLIFS, and Li et al. [9] recorded the interaction patterns of the fragments contained in existing GPCR ligand.…”

“…Breaking through the limitations of specific chemical bonds while maintaining the integrity of the ring system has become a new 'breaking rules' that can identify important fragments through interactions with receptors. For example, Dai et al [8] collected thousands of pairs of fragments with their corresponding amino acid residues in the kinase database KLIFS, and Li et al [9] recorded the interaction patterns of the fragments contained in existing GPCR ligand. However, the studies conducted by Dai et al and Li et al requires the crystal structure of the complex, which inherently restricts the diversity of the final fragment libraries.…”