scholarly journals Hit-to-lead and lead optimization binding free energy calculations for G protein-coupled receptors

2020 ◽  
Vol 10 (6) ◽  
pp. 20190128 ◽  
Author(s):  
Shunzhou Wan ◽  
Andrew Potterton ◽  
Fouad S. Husseini ◽  
David W. Wright ◽  
Alexander Heifetz ◽  
...  
Keyword(s):  
G Protein ◽  
Binding Free Energy ◽  
Absolute Error ◽  
Free Energy Calculations ◽  
Lead Optimization ◽  
Receptor Protein ◽  
Enhanced Sampling ◽  
Free Energies ◽  
G Protein Coupled ◽  
Binding Free Energies

We apply the hit-to-lead ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and lead-optimization TIES (thermodynamic integration with enhanced sampling) methods to compute the binding free energies of a series of ligands at the A 1 and A 2A adenosine receptors, members of a subclass of the GPCR (G protein-coupled receptor) superfamily. Our predicted binding free energies, calculated using ESMACS, show a good correlation with previously reported experimental values of the ligands studied. Relative binding free energies, calculated using TIES, accurately predict experimentally determined values within a mean absolute error of approximately 1 kcal mol −1 . Our methodology may be applied widely within the GPCR superfamily and to other small molecule–receptor protein systems.

scholarly journals Automation of absolute protein-ligand binding free energy calculations for docking refinement and compound evaluation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Germano Heinzelmann ◽  
Michael K. Gilson
Keyword(s):  
Free Energy ◽  
Early Stage ◽  
Binding Free Energy ◽  
Low Cost ◽  
Free Energy Calculations ◽  
Free Energies ◽  
Energy Calculations ◽  
Drug Candidates ◽  
Binding Free Energy Calculations ◽  
Binding Free Energies

AbstractAbsolute binding free energy calculations with explicit solvent molecular simulations can provide estimates of protein-ligand affinities, and thus reduce the time and costs needed to find new drug candidates. However, these calculations can be complex to implement and perform. Here, we introduce the software BAT.py, a Python tool that invokes the AMBER simulation package to automate the calculation of binding free energies for a protein with a series of ligands. The software supports the attach-pull-release (APR) and double decoupling (DD) binding free energy methods, as well as the simultaneous decoupling-recoupling (SDR) method, a variant of double decoupling that avoids numerical artifacts associated with charged ligands. We report encouraging initial test applications of this software both to re-rank docked poses and to estimate overall binding free energies. We also show that it is practical to carry out these calculations cheaply by using graphical processing units in common machines that can be built for this purpose. The combination of automation and low cost positions this procedure to be applied in a relatively high-throughput mode and thus stands to enable new applications in early-stage drug discovery.

scholarly journals Alchemical Absolute Protein-Ligand Binding Free Energies for Drug Design

2021 ◽  
Author(s):  
Yuriy Khalak ◽  
Gary Tresdern ◽  
Matteo Aldeghi ◽  
Hannah Magdalena Baumann ◽  
David L. Mobley ◽  
...  
Keyword(s):  
Free Energy ◽  
Drug Discovery ◽  
Drug Design ◽  
Ligand Binding ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Free Energies ◽  
Energy Calculations ◽  
Binding Free Energy Calculations ◽  
Binding Free Energies

The recent advances in relative protein-ligand binding free energy calculations have shown the value of alchemical methods in drug discovery. Accurately assessing absolute binding free energies, although highly desired, remains...

scholarly journals Predicting binding free energies: Frontiers and benchmarks

2016 ◽  
Author(s):  
David L. Mobley ◽  
Michael K. Gilson
Keyword(s):  
Molecular Design ◽  
Early Stage ◽  
Binding Free Energy ◽  
Research Community ◽  
Free Energy Calculations ◽  
Binding Affinities ◽  
Free Energies ◽  
Biomolecular Complexes ◽  
Binding Free Energy Calculations ◽  
Binding Free Energies

Binding free energy calculations based on molecular simulations provide predicted affinities for biomolecular complexes. These calculations begin with a detailed description of a system, including its chemical composition and the interactions between its components. Simulations of the system are then used to compute thermodynamic information, such as binding affinities. Because of their promise for guiding molecular design, these calculations have recently begun to see widespread applications in early stage drug discovery. However, many challenges remain to make them a robust and reliable tool. Here, we briefly explain how the calculations work, highlight key challenges, and argue for the development of accepted benchmark test systems that will help the research community generate and evaluate progress.Manuscript version 1.1.1 pre-release See https://github.com/mobleylab/benchmarksets for all versions.

scholarly journals A replica exchange umbrella sampling (REUS) approach to predict host–guest binding free energies in SAMPL8 challenge

2021 ◽  
Author(s):  
Mahdi Ghorbani ◽  
Phillip S. Hudson ◽  
Michael R. Jones ◽  
Félix Aviat ◽  
Rubén Meana-Pañeda ◽  
...  
Keyword(s):  
Free Energy ◽  
Binding Free Energy ◽  
Umbrella Sampling ◽  
Free Energy Calculations ◽  
Replica Exchange ◽  
Free Energies ◽  
Guest Binding ◽  
Binding Free Energy Calculations ◽  
Force Field Parameters ◽  
Binding Free Energies

AbstractIn this study, we report binding free energy calculations of various drugs-of-abuse to Cucurbit-[8]-uril as part of the SAMPL8 blind challenge. Force-field parameters were obtained from force-matching with different quantum mechanical levels of theory. The Replica Exchange Umbrella Sampling (REUS) approach was used with a cylindrical restraint to enhance the sampling of host–guest binding. Binding free energy was calculated by pulling the guest molecule from one side of the symmetric and cylindrical host, then into and through the host, and out the other side (bidirectional) as compared to pulling only to the bound pose inside the cylindrical host (unidirectional). The initial results with force-matched MP2 parameter set led to RMSE of 4.68 $${\text{kcal}}/{\text{mol}}$$ kcal / mol from experimental values. However, the follow-up study with CHARMM generalized force field parameters and force-matched PM6-D3H4 parameters resulted in RMSEs from experiment of $$2.65$$ 2.65 and $$1.72 {\text{kcal}}/{\text{mol}}$$ 1.72 kcal / mol , respectively, which demonstrates the potential of REUS for accurate binding free energy calculation given a more suitable description of energetics. Moreover, we compared the free energies for the so called bidirectional and unidirectional free energy approach and found that the binding free energies were highly similar. However, one issue in the bidirectional approach is the asymmetry of profile on the two sides of the host. This is mainly due to the insufficient sampling for these larger systems and can be avoided by longer sampling simulations. Overall REUS shows great promise for binding free energy calculations.

scholarly journals Sensitivity in binding free energies due to protein reorganization

2016 ◽  
Author(s):  
Nathan M. Lim ◽  
Lingle Wang ◽  
Robert Abel ◽  
David L. Mobley
Keyword(s):  
Ligand Binding ◽  
Conformational Changes ◽  
Binding Free Energy ◽  
Binding Pocket ◽  
Free Energy Calculations ◽  
Computer Hardware ◽  
Sampling Techniques ◽  
Free Energies ◽  
Sampling Algorithms ◽  
Binding Free Energies

AbstractTremendous recent improvements in computer hardware, coupled with advances in sampling techniques and force fields, are now allowing protein-ligand binding free energy calculations to be routinely used to aid pharmaceutical drug discovery projects. However, despite these recent innovations, there are still needs for further improvement in sampling algorithms to more adequately sample protein motion relevant to protein-ligand binding. Here, we report our work identifying and studying such clear and remaining needs in the apolar cavity of T4 Lysozyme L99A. In this study, we model recent experimental results that show the progressive opening of the binding pocket in response to a series of homologous ligands.1 Even while using enhanced sampling techniques, we demonstrate that the predicted relative binding free energies (RBFE) are sensitive to the initial protein conformational state. Particularly, we highlight the importance of sufficient sampling of protein conformational changes and demonstrate how inclusion of three key protein residues in the ‘hot’ region of the FEP/REST simulation improves the sampling and resolves this sensitivity.

scholarly journals Alchemical Absolute Protein-Ligand Binding Free Energies for Drug Design

2021 ◽  
Author(s):  
Yuriy Khalak ◽  
Gary Tresadern ◽  
Matteo Aldeghi ◽  
Hannah Magdalena Baumann ◽  
David L. Mobley ◽  
...  
Keyword(s):  
Free Energy ◽  
Drug Discovery ◽  
Ligand Binding ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Free Energies ◽  
Energy Calculations ◽  
Binding Free Energy Calculations ◽  
Binding Free Energies ◽  
Apo State

The recent advances in relative protein-ligand binding free energy calculations have shown the value of alchemical methods in drug discovery. Accurately assessing absolute binding free energies, although highly desired, remains a challenging endeavour, mostly limited to small model cases. Here, we demonstrate accurate first principles based absolute binding free energy estimates for 128 pharmaceutically relevant targets. We use a novel rigorous method to generate protein-ligand ensembles for the ligand in its decoupled state. Not only do the calculations deliver accurate protein-ligand binding affinity estimates, but they also provide detailed physical insight into the structural determinants of binding. We identify subtle rotamer rearrangements between apo and holo states of a protein that are crucial for binding. When compared to relative binding free energy calculations, obtaining absolute binding free energies is considerably more challenging in large part due to the need to explicitly account for the protein in its apo state. In this work we present several approaches to obtain apo state ensembles for accurate absolute ΔG calculations, thus outlining protocols for prospective application of the methods for drug discovery.

scholarly journals An Enhanced Sampling Approach to the Induced Fit Docking Problem in Protein-Ligand Binding: the case of mono-ADP-ribosylation hydrolases inhibitors

2021 ◽  
Author(s):  
Qianqian Zhao ◽  
Riccardo Capelli ◽  
Paolo Carloni ◽  
Bernhard Luescher ◽  
Jinyu Li ◽  
...  
Keyword(s):  
Ligand Binding ◽  
Absolute Error ◽  
Enhanced Sampling ◽  
Free Energies ◽  
Induced Fit ◽  
Adp Ribosylation ◽  
Free Energy Landscapes ◽  
First Time ◽  
Enzyme Complexes ◽  
Binding Free Energies

A variety of enhanced sampling methods can predict free energy landscapes associated with protein/ligand binding events, characterizing in a precise way the intermolecular interactions involved. Unfortunately, these approaches are challenged by not uncommon induced fit mecchanisms. Here, we present a variant of the recently reported volume-based metadynamics (MetaD) method which describes ligand binding even when it affects protein structure. The validity of the approach is established by applying it to a substrate/enzyme complexes of pharmacological relevance: this is the mono-ADP-ribose (ADPr) in complex with mono-ADP-ribosylation hydrolases (MacroD1 and MacroD2), where induced-fit phenomena are known to be operative. The calculated binding free energies are consistent with experiments, with an absolute error less than 0.5 kcal/mol. Our simulations reveal that in all circumstances the active loops, delimiting the boundaries of the binding site, rearrange from an open to a closed conformation upon ligand binding. The calculations further provide, for the first time, the molecular basis of the experimentally observed affinity changes in ADPr binding on passing from MacroD1 to MacroD2 and all its mutants. Our study paves the way to investigate in a completely general manner ligand binding to proteins and receptors.

Validation of AMBER/GAFF for Relative Free Energy Calculations

2019 ◽  
Author(s):  
Lin Song ◽  
Tai-Sung Lee ◽  
Chun Zhu ◽  
Darrin M. York ◽  
Kenneth M. Merz Jr.
Keyword(s):  
Free Energy ◽  
Force Field ◽  
Free Energy Calculations ◽  
Enhanced Sampling ◽  
Free Energies ◽  
Data Set ◽  
Relative Free Energy ◽  
Relative Binding ◽  
Sampling Approach ◽  
Binding Free Energies

We computed relative binding free energies using GPU accelerated Thermodynamic Integration (GPU-TI) on a dataset originally assembled by Schrödinger, Inc.. Using their GPU enabled free energy code (FEP+) and the OPLS2.1 force field combined with REST2 enhanced sampling approach, these authors obtained an overall MUE of 0.9 kcal/mol and an overall RMSD of 1.14 kcal/mol.<b> </b>In our study using GPU-TI of AMBER with the AMBER14SB/GAFF1.8 force field but without enhanced sampling, we obtained an overall MUE of 1.17 kcal/mol and an overall RMSD of 1.50 kcal/mol for the 330 mutations contained in this data set.

Validation of AMBER/GAFF for Relative Free Energy Calculations

2019 ◽  
Author(s):  
Lin Song ◽  
Tai-Sung Lee ◽  
Chun Zhu ◽  
Darrin M. York ◽  
Kenneth M. Merz Jr.
Keyword(s):  
Free Energy ◽  
Force Field ◽  
Free Energy Calculations ◽  
Enhanced Sampling ◽  
Free Energies ◽  
Data Set ◽  
Relative Free Energy ◽  
Relative Binding ◽  
Sampling Approach ◽  
Binding Free Energies

We computed relative binding free energies using GPU accelerated Thermodynamic Integration (GPU-TI) on a dataset originally assembled by Schrödinger, Inc.. Using their GPU enabled free energy code (FEP+) and the OPLS2.1 force field combined with REST2 enhanced sampling approach, these authors obtained an overall MUE of 0.9 kcal/mol and an overall RMSD of 1.14 kcal/mol.<b> </b>In our study using GPU-TI of AMBER with the AMBER14SB/GAFF1.8 force field but without enhanced sampling, we obtained an overall MUE of 1.17 kcal/mol and an overall RMSD of 1.50 kcal/mol for the 330 mutations contained in this data set.

Evaluating the Covalent Binding of Carbapenems on BlaC Using Noncovalent Interactions

2021 ◽  
Author(s):  
Lu Sun ◽  
Hongjun Fan ◽  
Shijun Zhong
Keyword(s):  
Noncovalent Interactions ◽  
Binding Free Energy ◽  
Covalent Binding ◽  
Tight Binding ◽  
Covalent Bonding ◽  
Noncovalent Interaction ◽  
Free Energy Calculations ◽  
Dynamics Simulation ◽  
Free Energies ◽  
Binding Free Energies

Abstract Carbapenems, as irreversible covalent binders and slow substrates to the Class A β-lactamase (BlaC) of Mycobacterium tuberculosis, can inhibit BlaC to hydrolyze the β-lactam drugs which are used to control tuberculosis. Their binding on BlaC involves covalent bonding and noncovalent interaction. We introduce a hypothesis that the noncovalent interactions dominate the difference of binding free energies for covalent ligands based on the assumption that their covalent bonding energies are same. MM/GBSA binding free energies calculated from the noncovalent interactions, provided a threshold with respect to the experimental kinetic data, to select slow carbapenem substrates which were either constructed using the structural units of experimentally identified carbapenems or obtained from the similarity search over the ZINC15 database. Combining molecular docking with consensus scoring and molecular dynamics simulation with MM/GBSA binding free energy calculations, a computational protocol was developed from which several new tight-binding carbapenems were theoretically identified.

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