Computer-Aided Drug Design

Computational approaches represent powerful tools to interpret and guide experiments that can expedite the antibiotic drug discovery and design process. Several CHARM faculty members are computer scientists who are developing and deploying next generation techniques to structure-based and ligand-based drug design, and work in close collaboration with our pharmacologists and infectious diseases scientists to take on the most urgent and vexing antibiotic-resistant superbug challenges. 

Viewing Drugs and Drug Targets at the Atomic Level

CHARM investigators work closely with the UC San Diego Center for Drug Discovery Innovation (cDDI) to apply X-ray crystallography and other biophysical techniques to get a highly detailed view of classical antibiotic targets or how microbial virulence factors interact with host cell receptors. Computer methods are then used identify key sites and interactions that are important for biological functions. This information is then used in virtual screens of drug candidates or chemical libraries to identify or optimize antibiotic leads that can compete with essential molecular interactions to interrupt biological pathways essential for bacterial survival or disease pathogenesis. 


From Laptop to Bench to Bedside


CHARM investigators in computer-aided drug design are accelerating antibiotic drug discovery by improving the realism, speed and accuracy of the fundamental computational simulations. These new in silico methods apply to all aspects of contemporary antibiotic discovery, including lead identification, lead optimization, ADMET prediction and drug repurposing. Comprehensive sets of ligand pockets (the "Pocketome") competing for ligands and metabolites in different organisms are identified, and these data  used for target identification and multi-target pharmacology profiling where FDA-approved drugs, leads and environmental chemicals can be docked. Parallel supercomputers and sophisticated computer graphics systems allow for the visualization of the atomic dynamics in solutions or protein molecules by virtual reality methods

Challenges and Opportunities

Computer-aided drug design succeeds when placed in an iterative paradigm with collaborating scientists positioned to validate hits in detailed in vitro pharmacological testing or test drug efficacy in established models of infectious disease pathogenesis. Target proteins of interest include enzymes and ligand binding proteins including antibody molecules. Importantly, a substrate may be attracted to the active site of an enzyme by electrostatic interactions, and  the atoms within an enzyme move to participate in the catalytic transformation of a bound substrate. New methods to model the dynamic events in fluid environments allow the rational design of new drugs that bind strongest to their receptors.


Confronting HCV Resistance

170 million people around the world are infected with hepatitis virus (HCV). CHARM investigators chose a subpocket to reduce mutation-related drug resistance, three-dimensional (3D) modeling, computational docking, cell-based assays, and enzymatic assays to identify compounds that inhibit both the wild-type NS3/4A protease and drug-resistant D168A mutant strains. 

Read the Article at ACS Omega