How Good is Jarzynski's Equality for Computer-Aided Drug Design?
Kiet HoDuc Toan TruongMai Suan LiPublished in: The journal of physical chemistry. B (2020)
Accurate determination of the binding affinity of the ligand to the receptor remains a difficult problem in computer-aided drug design. Here, we study and compare the efficiency of Jarzynski's equality (JE) combined with steered molecular dynamics and the linear interaction energy (LIE) method by assessing the binding affinity of 23 small compounds to six receptors, including β-lactamase, thrombin, factor Xa, HIV-1 protease (HIV), myeloid cell leukemia-1, and cyclin-dependent kinase 2 proteins. It was shown that Jarzynski's nonequilibrium binding free energy ΔGneqJar correlates with the available experimental data with the correlation levels R = 0.89, 0.86, 0.83, 0.80, 0.83, and 0.81 for six data sets, while for the binding free energy ΔGLIE obtained by the LIE method, we have R = 0.73, 0.80, 0.42, 0.23, 0.85, and 0.01. Therefore, JE is recommended to be used for ranking binding affinities as it provides accurate and robust results. In contrast, LIE is not as reliable as JE, and it should be used with caution, especially when it comes to new systems.
Keyphrases
- molecular dynamics
- antiretroviral therapy
- binding protein
- dna binding
- hiv positive
- hiv infected
- human immunodeficiency virus
- bone marrow
- acute myeloid leukemia
- hiv testing
- hepatitis c virus
- escherichia coli
- hiv aids
- electronic health record
- magnetic resonance imaging
- high resolution
- men who have sex with men
- immune response
- multidrug resistant
- signaling pathway
- computed tomography
- cell death
- stem cells
- deep learning
- gram negative
- contrast enhanced
- solid phase extraction
- klebsiella pneumoniae
- molecularly imprinted