Over the past years, rational drug design has gained lots of attention since employing it gave the world targeted therapy and more effective treatment solutions. Structure-based drug design (SBDD) is an excellent tool in rational drug design that takes advantage of accurate methods such as unbiased molecular dynamics (UMD) simulation for designing and optimizing molecular entities by understanding the binding and unbinding pathways of the binders. Supervised molecular dynamics (SuMD) simulation is a branch of UMD in which long-duration simulations are turned into short simulations, called replica, and a specific parameter is monitored throughout the simulation. In this work, we utilized this strategy to reconstruct the unbinding pathway of the anticancer drug dasatinib from its target protein, the c-Src kinase. Several unbinding events with valuable details were achieved. Then, to assess the efficiency and trustworthiness of the SuMD method, the unbinding pathway was also reconstructed by conventional UMD simulation, which uncovered some of the limitations of this method, such as limited sampling of the active site and finding the metastable states in the unbinding pathway. Furthermore, in times like these, when the world is desperate to find treatments for the Covid-19 disease, we think these methods are of exceptional value.Communicated by Ramaswamy H. Sarma.
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http://dx.doi.org/10.1080/07391102.2021.1972839 | DOI Listing |
J Chem Inf Model
January 2025
Institute of Chemistry, Technische Universität Berlin, Straße des 17. Juni 135, Berlin 10623, Germany.
Machine learning (ML) is a powerful tool for the automated data analysis of molecular dynamics (MD) simulations. Recent studies showed that ML models can be used to identify protein-ligand unbinding pathways and understand the underlying mechanism. To expedite the examination of MD simulations, we constructed PathInHydro, a set of supervised ML models capable of automatically assigning unbinding pathways for the dissociation of gas molecules from [NiFe] hydrogenases, using the unbinding trajectories of CO and H from [NiFe] hydrogenase as a training set.
View Article and Find Full Text PDFJ Chem Inf Model
January 2025
Dipartimento di Bioscienze, Università degli Studi di Milano, Milan 20133, Italy.
The computational study of ligand binding to a target protein provides mechanistic insight into the molecular determinants of this process and can improve the success rate of drug design. All-atom molecular dynamics (MD) simulations can be used to evaluate the binding free energy, typically by thermodynamic integration, and to probe binding mechanisms, including the description of protein conformational dynamics. The advantages of MD come at a high computational cost, which limits its use.
View Article and Find Full Text PDFJ Chem Inf Model
December 2024
Computer-Aided Drug Design Center, Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland Baltimore, Baltimore, Maryland 21201, United States.
Drug efficacy often correlates better with dissociation kinetics than binding affinity alone. To study binding kinetics computationally, it is necessary to identify all of the possible ligand dissociation pathways. The site identification by ligand competitive saturation (SILCS) method involves the precomputation of a set of maps (FragMaps), which describe the free energy landscapes of typical chemical functionalities in and around a target protein or RNA.
View Article and Find Full Text PDFJ Phys Chem B
December 2024
Department of Chemistry, the University of Chicago, Chicago, Illinois 60637, United States.
The protein hormone insulin forms a homodimer that must dissociate to bind to its receptor. Understanding the kinetics and mechanism of dissociation is essential for the rational design of therapeutic analogs. In addition to its physiological importance, this dissociation process serves as a paradigm for coupled (un)folding and (un)binding.
View Article and Find Full Text PDFJ Alzheimers Dis
December 2024
Department of Translational Neuroscience, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, USA.
Background: RNA-binding proteins (RBPs) modulate the synaptic proteome and are instrumental in maintaining synaptic homeostasis. Moreover, aberrant expression of an RBP in a disease state would have deleterious downstream effects on synaptic function. While many underlying mechanisms of synaptic dysfunction in Alzheimer's disease (AD) have been proposed, the contribution of RBPs has been relatively unexplored.
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