Hybrid Quantum Mechanics/Molecular Mechanics (QM/MM) Simulation: A Tool for Structure-based Drug Design and Discovery

Author(s):  
Prajakta U. Kulkarni ◽  
Harshil Shah ◽  
Vivek K. Vyas

: Quantum mechanics (QM) is physics based theory which explains the physical properties of nature at the level of atoms and sub-atoms. Molecular mechanics (MM) construct molecular systems through the use of classical mechanics. So, hybrid quantum mechanics and molecular mechanics (QM/MM) when combined together can act as computer-based methods which can be used to calculate structure and property data of molecular structures. Hybrid QM/MM combines the strengths of QM with accuracy and MM with speed. QM/MM simulation can also be applied for the study of chemical process in solutions as well as in the proteins, and has a great scope in structure-based drug design (CADD) and discovery. Hybrid QM/MM also applied to HTS, to derive QSAR models and due to availability of many protein crystal structures; it has a great role in computational chemistry, especially in structure- and fragment-based drug design. Fused QM/MM simulations have been developed as a widespread method to explore chemical reactions in condensed phases. In QM/MM simulations, the quantum chemistry theory is used to treat the space in which the chemical reactions occur; however the rest is defined through molecular mechanics force field (MMFF). In this review, we have extensively reviewed recent literature pertaining to the use and applications of hybrid QM/MM simulations for ligand and structure-based computational methods for the design and discovery of therapeutic agents.

2014 ◽  
Vol 16 (38) ◽  
pp. 20639-20649 ◽  
Author(s):  
Petr Štěpánek ◽  
Petr Bouř

Electronic spectra provide a wealth of information on molecular structures. We demonstrate a very satisfactory agreement between experimental and modeled spectra, as obtained by combined molecular mechanics/quantum mechanics computations for three aromatic amino acids.


2018 ◽  
Vol 74 (11) ◽  
pp. 1063-1077 ◽  
Author(s):  
Oleg Borbulevych ◽  
Roger I. Martin ◽  
Lance M. Westerhoff

Conventional macromolecular crystallographic refinement relies on often dubious stereochemical restraints, the preparation of which often requires human validation for unusual species, and on rudimentary energy functionals that are devoid of nonbonding effects owing to electrostatics, polarization, charge transfer or even hydrogen bonding. While this approach has served the crystallographic community for decades, as structure-based drug design/discovery (SBDD) has grown in prominence it has become clear that these conventional methods are less rigorous than they need to be in order to produce properly predictive protein–ligand models, and that the human intervention that is required to successfully treat ligands and other unusual chemistries found in SBDD often precludes high-throughput, automated refinement. Recently, plugins to thePython-based Hierarchical ENvironment for Integrated Xtallography(PHENIX) crystallographic platform have been developed to augment conventional methods with thein situuse of quantum mechanics (QM) applied to ligand(s) along with the surrounding active site(s) at each step of refinement [Borbulevychet al.(2014),Acta CrystD70, 1233–1247]. This method (Region-QM) significantly increases the accuracy of the X-ray refinement process, and this approach is now used, coupled with experimental density, to accurately determine protonation states, binding modes, ring-flip states, water positions and so on. In the present work, this approach is expanded to include a more rigorous treatment of the entire structure, including the ligand(s), the associated active site(s) and the entire protein, using a fully automated, mixed quantum-mechanics/molecular-mechanics (QM/MM) Hamiltonian recently implemented in theDivConpackage. This approach was validated through the automatic treatment of a population of 80 protein–ligand structures chosen from the Astex Diverse Set. Across the entire population, this method results in an average 3.5-fold reduction in ligand strain and a 4.5-fold improvement inMolProbityclashscore, as well as improvements in Ramachandran and rotamer outlier analyses. Overall, these results demonstrate that the use of a structure-wide QM/MM Hamiltonian exhibits improvements in the local structural chemistry of the ligand similar to Region-QM refinement but with significant improvements in the overall structure beyond the active site.


2007 ◽  
Vol 12 (17-18) ◽  
pp. 725-731 ◽  
Author(s):  
Kaushik Raha ◽  
Martin B. Peters ◽  
Bing Wang ◽  
Ning Yu ◽  
Andrew M. Wollacott ◽  
...  

2017 ◽  
Vol 16 (02) ◽  
pp. 1750012 ◽  
Author(s):  
Hang Hu ◽  
Alejandro D. Rey

A density functional theory (DFT) based multi-step simulation method is used to characterize the detailed molecular structure and inter/intra- molecular interactions of two benchmark liquid crystals (LC) 5CB, 8CB and a novel tri-biphenyl ring bent core LC material. The method uses hybrid DFT at the B3LYP/6-31G* level to obtain molecular structure and Raman data. These results are fed to a crystal packing simulation to find possible crystal structures. A pico-second quantum mechanics/molecular mechanics (QM/MM) simulation model is built for the selected structures with lower overall energy as well as optimal density. The stabilized crystal structures are then extended into a super cell, heated and simulated using a mixed force field and nano-second molecular dynamics (MD). The described simulation process sequence provides predictions of molecular Raman spectrum, LC density, isotropic depolarization ratio, ratio of differential polarizability, order parameters, molecular structures, and rotating Raman spectrum of the different mesophases. The Raman spectra, order parameters and depolarization ratios all agree well with existing experimental and previous simulation results. The study of the novel tri-biphenyl ring bent core LC system shows that the ratio of differential polarizability depends on intra-molecular interactions. The findings presented in this manuscript contribute to the on-going efforts to establish links between LC molecular structures and their properties, including optical behavior.


2018 ◽  
Author(s):  
Gydo C.P. van Zundert ◽  
Brandi M. Hudson ◽  
Daniel A. Keedy ◽  
Rasmus Fonseca ◽  
Amelie Heliou ◽  
...  

AbstractProteins and ligands sample a conformational ensemble that governs molecular recognition, activity, and dissociation. In structure-based drug design, access to this conformational ensemble is critical to understand the balance between entropy and enthalpy in lead optimization. However, ligand conformational heterogeneity is currently severely underreported in crystal structures in the Protein Data Bank, owing in part to a lack of automated and unbiased procedures to model an ensemble of protein-ligand states into X-ray data. Here, we designed a computational method, qFit-ligand, to automatically resolve conformationally averaged ligand heterogeneity in crystal structures, and applied it to a large set of protein receptor-ligand complexes. We found that up to 29 % of a dataset of protein crystal structures bound with drug-like molecules present evidence of unmodeled, averaged, relatively isoenergetic conformations in ligand-receptor interactions. In many retrospective cases, these alternate conformations were adventitiously exploited to guide compound design, resulting in improved potency or selectivity. Combining qFit-ligand with high-throughput screening or multi-temperature crystallography could therefore augment the structure-based drug design toolbox.


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