Solvents to Fragments to Drugs: MD Applications in Drug Design

Defelipe, Lucas A.; Arcon, Juan Pablo; Modenutti, Carlos P.; Martí, Marcelo A.; Turjanski, Adrián; Barril, Xavier

doi:10.3390/molecules23123269

Cited by 31 publications

(28 citation statements)

References 112 publications

(135 reference statements)

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“…Computational analysis of protein-ligand interactions is a key issue in structure-based, rational drug discovery. 1) Through long history of this direction of scientific research, a variety of theoretical approaches based on molecular docking, [2][3][4] molecular dynamics [5][6][7] and quantum chemical calculations 1) have been developed. In these approaches, physicochemical properties such as scoring function, 8) binding free energy, 9) ligand-residue interaction and interaction fingerprint 10) have been employed to quantitatively represent the affinity between protein and ligand molecules.…”

Section: Introductionmentioning

confidence: 99%

Dynamical Cooperativity of Ligand-Residue Interactions Evaluated with the Fragment Molecular Orbital Method

Tanaka

Tokutomi²,

Hatada³

et al. 2021

Preprint

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By the splendid advance in computation power realized with Fugaku supercomputer, it has become possible to perform ab initio fragment molecular orbital (FMO) calculations for thousands of dynamical structures of a protein-ligand complex in a parallelized way. We have thus carried out the electron-correlated FMO calculations for a complex of the 3C-like (3CL) main protease (Mpro) of the new coronavirus (SARS-CoV-2) and its inhibitor N3 incorporating the structural fluctuations sampled by classical molecular dynamics (MD) simulation in hydrated condition. Along with a statistical evaluation of inter-fragment interaction energies (IFIEs) between the N3 ligand and surrounding amino-acid residues for a thousand of dynamical structure samples, we have applied in this study a novel approach based on the principal component analysis (PCA) and the singular value decomposition (SVD) to the analysis of IFIE data in order to extract the dynamically cooperative interactions between the ligand and residues. We have found that the relative importance of each residue is modified via the structural fluctuations and that the ligand is bound in the pharmacophore in a dynamical manner through collective interactions formed by multiple residues, thus providing a new insight into structure-based drug discovery

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Section: Introductionmentioning

confidence: 99%

Dynamical Cooperativity of Ligand-Residue Interactions Evaluated with the Fragment Molecular Orbital Method

Tanaka

Tokutomi²,

Hatada³

et al. 2021

Preprint

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“…For the cosolvent MD simulations, we used the Mixed Solvent MD workflow that comes with the Desmond simulation engine [67]. As probe molecules, isopropanol, acetonitrile, and pyrimidine at a concentration of 5% (by volume) were selected since these solvents are water-miscible, offer a low potential for aggregation, and, therefore, do not require the application of repulsive forces [34,69]. In addition to the recommended simulation protocol with apo structures, we ran simulations with the cocrystallized ligand remaining in the orthosteric binding pocket.…”

Section: Simulations and Evaluationmentioning

confidence: 99%

Allosteric Binding Sites On Nuclear Receptors: Focus On Drug Efficacy and Selectivity

Fischer

Smieško

2020

IJMS

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Nuclear receptors (NRs) are highly relevant drug targets in major indications such as oncologic, metabolic, reproductive, and immunologic diseases. However, currently, marketed drugs designed towards the orthosteric binding site of NRs often suffer from resistance mechanisms and poor selectivity. The identification of two superficial allosteric sites, activation function-2 (AF-2) and binding function-3 (BF-3), as novel drug targets sparked the development of inhibitors, while selectivity concerns due to a high conservation degree remained. To determine important pharmacophores and hydration sites among AF-2 and BF-3 of eight hormonal NRs, we systematically analyzed over 10 µs of molecular dynamics simulations including simulations in explicit water and solvent mixtures. In addition, a library of over 300 allosteric inhibitors was evaluated by molecular docking. Based on our results, we suggest the BF-3 site to offer a higher potential for drug selectivity as opposed to the AF-2 site that is more conserved among the selected receptors. Detected similarities among the AF-2 sites of various NRs urge for a broader selectivity assessment in future studies. In combination with the Supplementary Material, this work provides a foundation to improve both selectivity and potency of allosteric inhibitors in a rational manner and increase the therapeutic applicability of this promising compound class. , glucocorticoid receptor (GR), progesterone receptor (PR), and minearlocorticoid receptor (MR) share a common domain architecture as well as a similar fold regarding their ligand binding domain (LBD), the selectivity concern for allosteric NR inhibitors remains ( Figure 1B). For example, it has been reported that the AF-2 and BF-3 sites of AR and GR have a sequence identity of approximately 50% [9,28]. Further on, drug-like mimetics of coactivator peptides at the AF-2 site have the potential to disrupt protein-protein interactions for multiple NRs and, ultimately, promote off-target toxicity [16,29].While several structures with cocrystallized ligands have been determined for the AR, targeting superficial binding sites such as AF-2 and BF-3 of other receptors remains a challenge due to their comparably large size, shallowness, and high flexibility [30,31]. Knowledge regarding binding hotspots and distinct pharmacophores among structurally similar NRs is crucial for the design of effective and selective inhibitory compounds [31][32][33][34]. In this regard, cosolvent molecular dynamics (MD) simulations are a suitable computational tool to determine hotspots and assess their druggability, as well as to obtain detailed information on potentially useful pharmacophores to improve drug potency and selectivity for the site of interest. In this simulation protocol, which was inspired by crystallographic observations of small fragments binding to protein surfaces, organic solvent molecules mimicking drug fragments are added to the aqueous phase to monitor and quantify their interaction with a protein. Compared to similar methods for bi...

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“…In this methodology, solvent layers are also computed, and include water molecules. Despite still being limited by computational requirements, MD simulation have massively improved, in both quality and computational system requirements, becoming an invaluable tool in modern science [24]. This review will focus on how structural biology provides insight into targets for NSCLC treatment and their potential interaction with available drugs to address the emergence of resistance mutations in the clinical setting.…”

Section: Introductionmentioning

confidence: 99%

Making NSCLC Crystal Clear: How Kinase Structures Revolutionized Lung Cancer Treatment

et al. 2020

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The parallel advances of different scientific fields provide a contemporary scenario where collaboration is not a differential, but actually a requirement. In this context, crystallography has had a major contribution on the medical sciences, providing a “face” for targets of diseases that previously were known solely by name or sequence. Worldwide, cancer still leads the number of annual deaths, with 9.6 million associated deaths, with a major contribution from lung cancer and its 1.7 million deaths. Since the relationship between cancer and kinases was unraveled, these proteins have been extensively explored and became associated with drugs that later attained blockbuster status. Crystallographic structures of kinases related to lung cancer and their developed and marketed drugs provided insight on their conformation in the absence or presence of small molecules. Notwithstanding, these structures were also of service once the initially highly successful drugs started to lose their effectiveness in the emergence of mutations. This review focuses on a subclassification of lung cancer, non-small cell lung cancer (NSCLC), and major oncogenic driver mutations in kinases, and how crystallographic structures can be used, not only to provide awareness of the function and inhibition of these mutations, but also how these structures can be used in further computational studies aiming at addressing these novel mutations in the field of personalized medicine.

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Solvents to Fragments to Drugs: MD Applications in Drug Design

Cited by 31 publications

References 112 publications

Dynamical Cooperativity of Ligand-Residue Interactions Evaluated with the Fragment Molecular Orbital Method

Dynamical Cooperativity of Ligand-Residue Interactions Evaluated with the Fragment Molecular Orbital Method

Allosteric Binding Sites On Nuclear Receptors: Focus On Drug Efficacy and Selectivity

Making NSCLC Crystal Clear: How Kinase Structures Revolutionized Lung Cancer Treatment

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