Kinetic Characterization of Fragment Binding in AmpC β‑Lactamase by High-Throughput Molecular Simulations

Small molecules used in fragment-based drug discovery form multiple, promiscuous binding complexes difficult to capture experimentally. Here, we identify such binding poses and their associated energetics and kinetics using molecular dynamics simulations on AmpC β-lactamase. Only one of the crystallographic binding poses was found to be thermodynamically favorable; however, the ligand shows several binding poses within the pocket. This study demonstrates free-binding molecular simulations in the context of fragment-to-lead development and its potential application in drug design

Kinetic Characterization of Fragment Binding in AmpC β‑Lactamase by High-Throughput Molecular Simulations

Small molecules used in fragment-based drug discovery form multiple, promiscuous binding complexes difficult to capture experimentally. Here, we identify such binding poses and their associated energetics and kinetics using molecular dynamics simulations on AmpC β-lactamase. Only one of the crystallographic binding poses was found to be thermodynamically favorable; however, the ligand shows several binding poses within the pocket. This study demonstrates free-binding molecular simulations in the context of fragment-to-lead development and its potential application in drug design

Fully Flexible Binding of Taxane-Site Ligands to Tubulin via Enhanced Sampling MD Simulations

Microtubules (MTs) are cytoskeleton components involved in a plenty of cellular functions such as transport, motility, and mitosis. Being polymers made up of α/β-tubulin heterodimers, in order to accomplish these functions, they go through large variations in their spatial arrangement switching between polymerization and depolymerization phases. Because of their role in cellular division, interfering with MTs dynamic behavior has been proven to be suitable for anticancer therapy as tubulin-binding agents induce mitotic arrest and cell death by apoptosis. However, how microtubule-stabilizing agents like taxane-site ligands act to promote microtubule assembly and stabilization is still argument of debate. As in the case of tubulin, traditional docking techniques lack the necessary capabilities of treating protein flexibility that are central to certain binding processes. For this reason, the aim of this project is to put in place a protocol for dynamic docking of taxane-site ligands to β-tubulin by means of enhanced sampling MD simulation techniques. Firstly, the behavior of the binding pocket has been investigated with classical MD simulations. It has been observed that the most flexible part of the taxane site is the so-called “M-loop”, the one involved into the lateral associations of tubulin heterodimers and that is supposed to be stabilized by taxane-site ligands. Secondly, the protocol for the dynamic docking has been put in place using the MD-Binding technique developed by BiKi Technologies. It showed to be effective in reproducing the binding mode of epothilone A and discodermolide as in their X-ray crystal structures. Finally, the protocol has been tested against paclitaxel, a drug for which no X-ray crystal structure is currently available. These results showed the potential of such an approach and strengthen the belief that in the future dynamic docking will replace traditional static docking in the drug discovery and development process

Dynamic Docking, Path Analysis and Free Energy Computation in Protein-Ligand Binding

Comprehending how drugs interact with biological macromolecules to form a complex with consequent biological response is particularly relevant in drug design to guide a rational design of new active compounds. The establishment and the duration of the protein-ligand binding complex is principally determined by thermodynamics and kinetics of the dynamical process of molecular recognition. Thus, an accurate characterization of the free-energy governing the formation of the protein-ligand complex is of fundamental importance to deeply understand each contribution to the establishment of the molecular complex. Experimental biophysical techniques proved to be efficient in characterizing both thermodynamics and kinetics of protein-ligand binding. However, a detailed description of the whole binding process on a mechanistic level is not possible since only a quantitative estimation is allowed. Conversely, from the computational point of view, plain molecular dynamics, which has been increasingly considered as the method of choice to investigate the entire dynamic process upon complex formation and to predict the associated thermodynamic and kinetic observables, cannot be applied in a routinely drug discovery pipeline because of the high computational cost. In this context, this PhD thesis wants to address specific aspects of the protein-ligand binding process. In particular, it will deal with dynamic docking, thermodynamics and kinetics of protein-ligand binding by devising respectively three different computational protocols. We developed a dynamic docking protocol based on potential-scaled (sMD) simulations, in which the protein and the ligand are let completely flexible in order to predict the protein-ligand binding pose within a reasonable computational time. Then, we investigated the applicability of sMD in describing the kinetic behavior of a series of drug-like molecules and we devised a fully automated method to analyze the unbinding trajectories. Finally, we develop a semi-automated protocol based on path collective variables combined with well-tempered metadynamics to estimate free-energies along a binding path