Understanding the impact of binding free energy and kinetics calculations in modern drug discovery

ABSTRACT

Introduction

For rational drug design, it is crucial to understand the receptor-drug binding processes and mechanisms. A new era for the use of computer simulations in predicting drug-receptor interactions at an atomic level has begun with remarkable advances in supercomputing and methodological breakthroughs.

Areas covered

End-point free energy calculation methods such as Molecular Mechanics/Poisson Boltzmann Surface Area (MM/PBSA) or Molecular-Mechanics/Generalized Born Surface Area (MM/GBSA), free energy perturbation (FEP), and thermodynamic integration (TI) are commonly used for binding free energy calculations in drug discovery. In addition, kinetic dissociation and association rate constants ($k_{\mathit{off}}$ and $k_{\mathit{on}}$) play critical roles in the function of drugs. Nowadays, Molecular Dynamics (MD) and enhanced sampling simulations are increasingly being used in drug discovery. Here, the authors provide a review of the computational techniques used in drug binding free energy and kinetics calculations.

Expert opinion

The applications of computational methods in drug discovery and design are expanding, thanks to improved predictions of the binding free energy and kinetic rates of drug molecules. Recent microsecond-timescale enhanced sampling simulations have made it possible to accurately capture repetitive ligand binding and dissociation, facilitating more efficient and accurate calculations of ligand binding free energy and kinetics.

KEYWORDS:

• Computer-aided drug design
• molecular dynamics
• enhanced sampling
• free energy
• kinetics

Article highlights

• Drug discovery and development is a costly and time-consuming process with a new drug taking 10–12 years to reach the consumer market.

• Pharmacodynamics prediction using computer simulations is growing rapidly in the field of drug design and discovery.

• Accurate prediction of $k_{\mathit{on}}$ and $k_{\mathit{off}}$ using computational techniques is currently trending in the field of drug design.

• MM/PBSA, MM/GBSA, FEP, and TI are common techniques used in free energy calculations.

• Enhanced sampling methods are advantageous in exploring drug binding and dissociation pathways and kinetics.

List of Abbreviations

3CLpro	=	3C-like protease
ABF	=	Adaptive Biasing Force
ACE2	=	Angiotensin-Converting Enzyme 2
AMBER	=	Assisted Model Building with Energy Refinement
aMD	=	Accelerated Molecular Dynamics
AMINO	=	Automatic Mutual Information Noise Omission
AUC	=	Area under Curve
BAR	=	Bennett Acceptance Ratio
Bcl-2	=	B-cell Lymphoma 2
BD	=	Brownian dynamics
CPU	=	Central processing Unit
CV	=	Collective variables
dcTMD	=	Dissipation-corrected targeted MD
DUD	=	Database of Useful Decoys
EGFR	=	Epidermal Growth Factor Receptor
FEP	=	Free Energy Perturbation
FKBP	=	FK506 Binding Protein
GaMD	=	Gaussian Accelerated Molecular Dynamics
GPCR	=	G protein-coupled receptor
GPU	=	Graphics Processing Unit
IE	=	Interaction Energy
LiGaMD	=	Ligand Gaussian Accelerated Molecular Dynamics
LiGaMD2	=	Ligand Gaussian Accelerated Molecular Dynamics
MAE	=	Mean absolute error
MBAR	=	Multistate Bennett Acceptance Ratio
MetaD	=	Metadynamics
MD	=	Molecular Dynamics
ML	=	Machine Learning
MM	=	Molecular Mechanics
MM/GBSA	=	Molecular-Mechanics/Generalized Born Surface Area
MM/PBSA	=	Molecular Mechanics/Poisson Boltzmann Surface Area
MMVT	=	Markovian Milestoning with Voronoi tessellation
MPU	=	Mean of prediction uncertainty
NAMD	=	Nanoscal molecular dynamics
OpenMM	=	Open Molecular Mechanics
OPLS	=	Optimized Potentials for Liquid Simulations
RAVE	=	Reweighted Autoencoded Variational Bayes for Enhanced Sampling
RBD	=	Receptor Binding Domain
RBFE	=	Relative Binding Free Energy
REMD	=	Replica Exchange Molecular Dynamics
REST	=	Replica Exchange Solute Tempering
SARs-CoV-2	=	Severe Acute Respiratory Syndrome Coronavirus 2
SEEKR	=	Simulation enabled estimation of kinetic rates
TIES	=	Thermodynamic Integration Ensemble-based sampling
TI	=	Thermodynamic Integration
TMD	=	Targeted MD
$\mathit{\tau }$RAMD	=	$\mathit{\tau }$random accelerated molecular dynamics
VES	=	Varaitional enhanced sampling

Declaration of interest

The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Additional information

Funding

This work was supported in part by the National Institutes of Health [R01GM132572], the National Science Foundation [2121063] and through startup funding at University of North Carolina-Chapel Hill.