Evaluating the use of absolute binding free energy in the fragment optimisation process

Alibay, I; Magarkar, A; Seeliger, D; Biggin, PC

AI Collection

Journal article

Evaluating the use of absolute binding free energy in the fragment optimisation process

Abstract:: The work presented in this thesis focuses on the use of molecular dynamics (MD) and enhanced sampling methods for investigating ligand binding poses and determining protein-ligand binding affinity. Good pre diction of the arrangement of these complexes and their strength is crucial for successful structure based drug design (SBDD) efforts so this thesis makes a significant contribution in furthering the use of computational tools in SBDD. First, chapter 3 presents OpenBPMD, an open-source Python re implementation of binding pose metadynamics (BPMD), a MD-based tool for ranking ligand poses from a set of candidates derived from dock ing. The role of accurate water positioning on the performance of the algorithm is also investigated, showed how the combination with a grand canonical Monte Carlo algorithm improves the accuracy of the predic tions. Then chapter 4 explains how the funnel metadynamics (fun-metaD) algorithm was implemented on a high-performance MD engine, OpenMM. This implementation was validated on host-guest systems. Afterwards a larger data set is interrogated, examining the effects on host-guest bind ing by varying the water model (TIP3P, OPC3 and OPC) and the partial atomic charge assignment methods, AM1-BCC and RESP. Finally, chapter 5 investigates the binding of fragment-like ligands in three different protein targets by applying fun-metaD. Advancements are made on funnel-shaped restraint automation and a new set of collective variables (CV) is tested as well. However, a lack of convergence due to an excess of metadynamic bias and missing slow degrees of freedom is observed. In order to address these issues, chapter 6 delves into apply ing a neural network-based CV, called Deep-LDA, and a novel enhanced sampling algorithm, termed on-the-fly probability-enhanced sampling. Although smooth converging, some issues in pose discrimination still re main

Publication status:: Published

Peer review status:: Peer reviewed

Actions

Email

Email this record

Send the bibliographic details of this record to your email address.

Your Email
Please enter the email address that the record information will be sent to.

-
Your message (optional)
Please add any additional information to be included within the email.
Share
Cite

Cite this record

APA Style

Alibay, I., Magarkar, A., Seeliger, D., & Biggin, P. C. (2022). Evaluating the use of absolute binding free energy in the fragment optimisation process. Communications Chemistry, 5(1), 105–105.

MLA Style

Alibay, I, et al. “Evaluating the Use of Absolute Binding Free Energy in the Fragment Optimisation Process.” Communications Chemistry, vol. 5, no. 1, 2022, pp. 105–05.

Chicago Style

Alibay, I, A Magarkar, D Seeliger, and PC Biggin. 2022. “Evaluating the Use of Absolute Binding Free Energy in the Fragment Optimisation Process.” Communications Chemistry 5 (1): 105–.
Print