Single or Multiple Access Channels to the CYP450s Active Site? An Answer from Free Energy Simulations of the Human Aromatase Enzyme

Influence of tumor microenvironment on the different breast cancer subtypes and applied therapies

Despite the significant improvements made in breast cancer therapy during the last decades, this disease still has increasing incidence and mortality rates. Different targets involved in general processes, like cell proliferation and survival, have become alternative therapeutic options for this disease, with some of them already used in clinic, like the CDK4/6 inhibitors for luminal A tumors treatment. Nevertheless, there is a demand for novel therapeutic strategies focused not only on tumor cells, but also on their microenvironment. Tumor microenvironment (TME) is a very complex and dynamic system that, more than surrounding and supporting tumor cells, actively participates in tumor development and progression. During the last decades, it has become clear that the cellular and acellular components of TME differ between the various breast cancer subtypes and shape the differences regarding their severity and prognosis. The pivotal role of the TME in controlling tumor growth and influencing responses to therapy represents a potential source for novel targets and therapeutic strategies. In this review, we present a description of the multiple therapeutic options used for different breast cancer subtypes, as well as the influence that the TME may exert on the development of the disease and on the response to the distinct therapies, which in some cases may explain their failure by the occurrence of relapses and resistance. Furthermore, the ongoing studies focused on the use of TME components for developing potential cancer treatments are described.

Emerging Promise of Computational Techniques in Anti-Cancer Research: At a Glance

Research on the immune system and cancer has led to the development of new medicines that enable the former to attack cancer cells. Drugs that specifically target and destroy cancer cells are on the horizon; there are also drugs that use specific signals to stop cancer cells multiplying. Machine learning algorithms can significantly support and increase the rate of research on complicated diseases to help find new remedies. One area of medical study that could greatly benefit from machine learning algorithms is the exploration of cancer genomes and the discovery of the best treatment protocols for different subtypes of the disease. However, developing a new drug is time-consuming, complicated, dangerous, and costly. Traditional drug production can take up to 15 years, costing over USD 1 billion. Therefore, computer-aided drug design (CADD) has emerged as a powerful and promising technology to develop quicker, cheaper, and more efficient designs. Many new technologies and methods have been introduced to enhance drug development productivity and analytical methodologies, and they have become a crucial part of many drug discovery programs; many scanning programs, for example, use ligand screening and structural virtual screening techniques from hit detection to optimization. In this review, we examined various types of computational methods focusing on anticancer drugs. Machine-based learning in basic and translational cancer research that could reach new levels of personalized medicine marked by speedy and advanced data analysis is still beyond reach. Ending cancer as we know it means ensuring that every patient has access to safe and effective therapies. Recent developments in computational drug discovery technologies have had a large and remarkable impact on the design of anticancer drugs and have also yielded useful insights into the field of cancer therapy. With an emphasis on anticancer medications, we covered the various components of computer-aided drug development in this paper. Transcriptomics, toxicogenomics, functional genomics, and biological networks are only a few examples of the bioinformatics techniques used to forecast anticancer medications and treatment combinations based on multi-omics data. We believe that a general review of the databases that are now available and the computational techniques used today will be beneficial for the creation of new cancer treatment approaches.

4th generation nonsteroidal aromatase inhibitors: An iterative SAR-guided design, synthesis, and biological evaluation towards picomolar dual binding inhibitors

One in every eight women will be diagnosed with breast cancer during their lifetime and approximately 70% of all patients are oestrogen receptor (ER) positive depending upon oestrogen for their growth accounting for third generation aromatase (CYP19A1) inhibitors being the mainstay in the treatment of ER-positive breast cancer. Despite the success of current aromatase inhibitors, acquired resistance occurs after prolonged therapy. Although the precise mechanisms of resistance are not known, lack of cross resistance among aromatase inhibitors drives the need for a newer generation of inhibitors to overcome this resistance alongside minimising toxicity and adverse effects. Novel triazole-based inhibitors were designed based on previously published parent compound 5a, making use of the now available crystal structure of CYP19A1 (PDB 3S79), to make modifications at specific sites to explore the potential of dual binding at both the active site and the access channel. Modifications included adding long chain substituents e.g. but-2-ynyloxy and pent-2-ynyloxy at different positions including the most active compound 13h with IC₅₀ value in the low picomolar range (0.09 nM). Aromatase inhibition results paired with molecular dynamics studies provided a clear structure activity relationship and favourable dual binding mode was verified. Toxicity assays and CYP selectivity profile studies for some example compounds were performed to assess the safety profile of the prepared inhibitors providing the basis for the 4th generation nonsteroidal aromatase inhibitors.

Determination of Multidirectional Pathways for Ligand Release from the Receptor: A New Approach Based on Differential Evolution

Steered molecular dynamics (SMD) simulation is a powerful method in computer-aided drug design as it can be used to access the relative binding affinity with high precision but with low computational cost. The success of SMD depends on the choice of the direction along which the ligand is pulled from the receptor-binding site. In most simulations, the unidirectional pathway was used, but in some cases, this choice resulted in the ligand colliding with the complex surface of the exit tunnel. To overcome this difficulty, several variants of SMD with multidirectional pulling have been proposed, but they are not completely devoid of disadvantages. Here, we have proposed to determine the direction of pulling with a simple scoring function that minimizes the receptor–ligand interaction, and an optimization algorithm called differential evolution is used for energy minimization. The effectiveness of our protocol was demonstrated by finding expulsion pathways of Huperzine A and camphor from the binding site of Torpedo California acetylcholinesterase and P450cam proteins, respectively, and comparing them with the previous results obtained using memetic sampling and random acceleration molecular dynamics. In addition, by applying this protocol to a set of ligands bound with LSD1 (lysine specific demethylase 1), we obtained a much higher correlation between the work of pulling force and experimental data on the inhibition constant IC50 compared to that obtained using the unidirectional approach based on minimal steric hindrance.

Molecular Lego of Human Cytochrome P450: The Key Role of Heme Domain Flexibility for the Activity of the Chimeric Proteins

The cytochrome P450 superfamily are heme-thiolate enzymes able to carry out monooxygenase reactions. Several studies have demonstrated the feasibility of using a soluble bacterial reductase from Bacillus megaterium, BMR, as an artificial electron transfer partner fused to the human P450 domain in a single polypeptide chain in an approach known as ‘molecular Lego’. The 3A4-BMR chimera has been deeply characterized biochemically for its activity, coupling efficiency, and flexibility by many different biophysical techniques leading to the conclusion that an extension of five glycines in the loop that connects the two domains improves all the catalytic parameters due to improved flexibility of the system. In this work, we extend the characterization of 3A4-BMR chimeras using differential scanning calorimetry to evaluate stabilizing role of BMR. We apply the ‘molecular Lego’ approach also to CYP19A1 (aromatase) and the data show that the activity of the chimeras is very low (<0.003 min−1) for all the constructs tested with a different linker loop length: ARO-BMR, ARO-BMR-3GLY, and ARO-BMR-5GLY. Nevertheless, the fusion to BMR shows a remarkable effect on thermal stability studied by differential scanning calorimetry as indicated by the increase in Tonset by 10 °C and the presence of a cooperative unfolding process driven by the BMR protein domain. Previously characterized 3A4-BMR constructs show the same behavior of ARO-BMR constructs in terms of thermal stabilization but a higher activity as a function of the loop length. A comparison of the ARO-BMR system to 3A4-BMR indicates that the design of each P450-BMR chimera should be carefully evaluated not only in terms of electron transfer, but also for the biophysical constraints that cannot always be overcome by chimerization.

The prediction of protein-ligand unbinding for modern drug discovery

INTRODUCTION

Drug-target thermodynamic and kinetic information have perennially important roles in drug design. The prediction of protein-ligand unbinding, which can provide important kinetic information, in experiments continues to face great challenges. Uncovering protein-ligand unbinding through molecular dynamics simulations has become efficient and inexpensive with the progress and enhancement of computing power and sampling methods.

AREAS COVERED

In this review, various sampling methods for protein-ligand unbinding and their basic principles are firstly briefly introduced. Then, their applications in predicting aspects of protein-ligand unbinding, including unbinding pathways, dissociation rate constants, residence time and binding affinity, are discussed.

EXPERT OPINION

Although various sampling methods have been successfully applied in numerous systems, they still have shortcomings and deficiencies. Most enhanced sampling methods require researchers to possess a wealth of prior knowledge of collective variables or reaction coordinates. In addition, most systems studied at present are relatively simple, and the study of complex systems in real drug research remains greatly challenging. Through the combination of machine learning and enhanced sampling methods, prediction accuracy can be further improved, and some problems encountered in complex systems also may be solved.

Computing Metal-Binding Proteins for Therapeutic Benefit

Over one third of biomolecules rely on metal ions to exert their cellular functions. Metal ions can play a structural role by stabilizing the structure of biomolecules, a functional role by promoting a wide variety of biochemical reactions, and a regulatory role by acting as messengers upon binding to proteins regulating cellular metal-homeostasis. These diverse roles in biology ascribe critical implications to metal-binding proteins in the onset of many diseases. Hence, it is of utmost importance to exhaustively unlock the different mechanistic facets of metal-binding proteins and to harness this knowledge to rationally devise novel therapeutic strategies to prevent or cure pathological states associated with metal-dependent cellular dysfunctions. In this compendium, we illustrate how the use of a computational arsenal based on docking, classical, and quantum-classical molecular dynamics simulations can contribute to extricate the minutiae of the catalytic, transport, and inhibition mechanisms of metal-binding proteins at the atomic level. This knowledge represents a fertile ground and an essential prerequisite for selectively targeting metal-binding proteins with small-molecule inhibitors aiming to (i) abrogate deregulated metal-dependent (mis)functions or (ii) leverage metal-dyshomeostasis to selectively trigger harmful cells death.

Combination of multiple computational methods revealing specific sub-sectional recognition and hydrogen-bond dependent transportation of CKII peptide fragment in O-GlcNAc transferase

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Mechanism of CKII peptide recognition, transportation and binding in OGT is obtained.

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Peptide delivery is strong exothermic, highly dependent on hydrogen bond network.

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Typical ‘spread’ & ‘V’ conformation change noticed for peptide accompanies stable OGT.

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Specific subsection of peptide has diverse performance in its recognition and delivery.

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Multiple methods combination may be used in other bio-system with flexible substrate.

O-linked β-N-acetyl-D-glucosamine (O-GlcNAc) transferase (OGT) is an essential enzyme in many cellular physiological catalytic reactions that regulates protein O-GlcNAcylation. Aberrant O-GlcNAcylation is related to insulin resistance, diabetic complications, cancer and neurodegenerative diseases. Understanding the peptide delivery in OGT is significant in comprehending enzymatic catalytic process, target-protein recognition and pathogenic mechanism. Herein extensive molecular dynamics (MD) simulations combined with various techniques are utilized to study the recognizing and binding mechanism of peptide fragment extracted from casein kinase II by OGT from atomic level. The residues of His496, His558, Thr633, Lys634, and Pro897 are demonstrated to play a dominant role in the peptide stabilization via hydrogen bonds and σ-π interaction, whose van der Waals and non-polar solvent effects provide the main driving force. In addition, two channels are identified. The delivery mode, mechanism together with thermodynamic and dynamic characterizations for the most favorable channel are determined. The peptide is more inclined to be recognized by OGT through the cavity comprised of residues 799–812, 893–899, and 865–871, and Tyr13-terminal is prior recognized to Met26-terminal. The transportation process is accompanied with conformation changes between the “spread” and “V” shapes. The whole process is strong exothermic that is highly dependent on the variation of hydrogen bond interactions between peptide and OGT as well as the performance of different subsections of peptide. Besides that, multiple computational methods combinations may contribute meaningfully to calculation of similar bio-systems with long and flexible substrate.

Frontiers of metal-coordinating drug design

Introduction: The occurrence of metal ions in biomolecules is required to exert vital cellular functions. Metal-containing biomolecules can be modulated by small-molecule inhibitors targeting their metal-moiety. As well, the discovery of cisplatin ushered the rational discovery of metal-containing-drugs. The use of both drug types exploiting metal-ligand interactions is well established to treat distinct pathologies. Therefore, characterizing and leveraging metal-coordinating drugs is a pivotal, yet challenging, part of medicinal chemistry.Area covered: Atomic-level simulations are increasingly employed to overcome the challenges met by traditional drug-discovery approaches and to complement wet-lab experiments in elucidating the mechanisms of drugs' action. Multiscale simulations, allow deciphering the mechanism of metal-binding inhibitors and metallo-containing-drugs, enabling a reliable description of metal-complexes in their biological environment. In this compendium, the authors review selected applications exploiting the metal-ligand interactions by focusing on understanding the mechanism and design of (i) inhibitors targeting iron and zinc-enzymes, and (ii) ruthenium and gold-based anticancer agents targeting the nucleosome and aquaporin protein, respectively.Expert opinion: The showcased applications exemplify the current role and the potential of atomic-level simulations and reveal how their synergic use with experiments can contribute to uncover fundamental mechanistic facets and exploit metal-ligand interactions in medicinal chemistry.

Reconsidering Aromatase for Breast Cancer Treatment: New Roles for an Old Target

The current therapeutic approach for the treatment of hormone dependent breast cancer includes interference with estrogen receptors via either selective modulators or estrogens deprivation, by preventing their biosynthesis with aromatase inhibitors. Severe side effects and acquired resistance are drawbacks of both drug classes, and the efforts to overcome these issues still allow for research in this field to be animated. This review reports on recent findings that have opened new avenues for reconsidering the role of aromatase enzymes (and estrogen receptors) leading to the possibility of looking at well-known targets in a new perspective.

Molecular Dynamics Revealing a Detour-Forward Release Mechanism of Tacrine: Implication for the Specific Binding Characteristics in Butyrylcholinesterase

Butyrylcholinesterase (BChE) is a non-specific enzyme with clinical pharmacological and toxicological significance, which was a renewed interest as therapeutic target in Alzheimer's disease (AD) nowadays. Here, all-atom molecular dynamics simulations of butyrylcholinesterase with tacrine complex were designed to characterize inhibitor binding modes, strengths, and the hydrogen-bond dependent non-covalent release mechanism. Four possible release channels were identified, and the most favorable channel was determined by random acceleration molecular dynamics molecular dynamics (RAMD MD) simulations. The thermodynamic and dynamic properties as well as the corresponding Detour-forward delivery mechanism were determined according to the classical molecular dynamics (MD) simulations accompanied with umbrella sampling. The free energy barrier of the tacrine release process for the most beneficial pathway is about 10.95 kcal/mol, which is related to the non-covalent interactions from the surrounding residues, revealing the specific binding characteristics in the active site. The residues including Asp70, Ser79, Trp82, Gly116, Thr120, Tyr332, and His438 were identified to play major roles in the stabilization of tacrine in the pocket of BChE, where hydrogen bonding and π-π interactions are significant factors. Tyr332 and Asp70, which act as gate keepers, play crucial roles in the substrate delivery. The present results provide a basic understanding for the ligand transport mechanism depending on the BChE enzymatic environment, which is useful for the design of BChE inhibitors in the future.

Molecular Basis for Endocrine Disruption by Pesticides Targeting Aromatase and Estrogen Receptor

The intensive use of pesticides has led to their increasing presence in water, soil, and agricultural products. Mounting evidence indicates that some pesticides may be endocrine disrupting chemicals (EDCs), being therefore harmful for the human health and the environment. In this study, three pesticides, glyphosate, thiacloprid, and imidacloprid, were tested for their ability to interfere with estrogen biosynthesis and/or signaling, to evaluate their potential action as EDCs. Among the tested compounds, only glyphosate inhibited aromatase activity (up to 30%) via a non-competitive inhibition or a mixed inhibition mechanism depending on the concentration applied. Then, the ability of the three pesticides to induce an estrogenic activity was tested in MELN cells. When compared to 17β-estradiol, thiacloprid and imidacloprid induced an estrogenic activity at the highest concentrations tested with a relative potency of 5.4 × 10⁻¹⁰ and 3.7 × 10⁻⁹, respectively. Molecular dynamics and docking simulations predicted the potential binding sites and the binding mode of the three pesticides on the structure of the two key targets, providing a rational for their mechanism as EDCs. The results demonstrate that the three pesticides are potential EDCs as glyphosate acts as an aromatase inhibitor, whereas imidacloprid and thiacloprid can interfere with estrogen induced signaling.

Effector role of cytochrome P450 reductase for androstenedione binding to human aromatase

Cytochromes P450 constitute a large superfamily of monooxygenases involved in many metabolic pathways. Most of them are not self-sufficient and need a reductase protein to provide the electrons necessary for catalysis. It was shown that the redox partner plays a role in the modulation of the structure and function of some bacterial P450 enzymes. Here, the effect of NADPH-cytochrome reductase (CPR) on human aromatase (Aro) is studied for what concerns its role in substrate binding. Pre-steady-state kinetic experiments indicate that both the substrate binding rates and the percentage of spin shift detected for aromatase are increased when CPR is present. Moreover, aromatase binds the substrate through a conformational selection mechanism, suggesting a possible effector role of CPR. The thermodynamic parameters for the formation of the CPR-Aro complex were studied by isothermal titration calorimetry. The dissociation constant of the complex formation is 4.5 folds lower for substrate-free compared to the substrate-bound enzyme. The enthalpy change observed when the CPR-Aro complex forms in the absence of the substrate are higher than in its presence, indicating that more interactions are formed/broken in the former case. Taken together, our data confirm that CPR has a role in promoting aromatase conformation optimal for substrate binding.

Targeting Orthosteric and Allosteric Pockets of Aromatase via Dual-Mode Novel Azole Inhibitors

Breast cancer (BC) is the most diffused cancer type in women and the second leading cause of death among the female population. Effective strategies to fight estrogen responsive (ER+) BC, which represents 70% of all BC cases, rely on estrogen deprivation, via the inhibition of the aromatase enzyme, or the modulation of its cognate estrogen receptor. Current clinical therapies significantly increased patient survival time. Nevertheless, the onset of resistance in metastatic BC patients undergoing prolonged treatments is becoming a current clinical challenge, urgently demanding to devise innovative strategies. In this context, here we designed, synthesized, and performed in vitro inhibitory tests on the aromatase enzyme and distinct ER+/ER- BC cell line types of novel azole bridged xanthones. These compounds are active in the low μM range and behave as dual-mode inhibitors, targeting both the orthosteric and the allosteric sites of the enzyme placed along one access channel. Classical and quantum-classical molecular dynamics simulations of the new compounds, as compared with selected steroidal and nonsteroidal inhibitors, provide a rationale to the observed inhibitory potency and supply the guidelines to boost the activity of inhibitors able to exploit coordination to iron and occupation of the access channel to modulate estrogen production.

Estrogen receptor-positive (ER+) breast cancer treatment: Are multi-target compounds the next promising approach?

Endocrine therapy is currently the main therapeutic approach for estrogen receptor-positive (ER⁺) breast cancer, the most frequent subtype of breast cancer in women worldwide. For this subtype of tumors, the current clinical treatment includes aromatase inhibitors (AIs) and anti-estrogenic compounds, such as Tamoxifen and Fulvestrant, being AIs the first-line treatment option for post-menopausal women. Moreover, the recent guidelines also suggest the use of these compounds by pre-menopausal women after suppressing ovaries function. However, besides its therapeutic efficacy, the prolonged use of this type of therapies may lead to the development of several adverse effects, as well as, endocrine resistance, limiting the effectiveness of such treatments. In order to surpass this issues and clinical concerns, during the last years, several studies have been suggesting alternative therapeutic approaches, considering the function of aromatase, ERα and ERβ. Here, we review the structural and functional features of these three targets and their importance in ER⁺ breast cancer treatment, as well as, the current treatment strategies used in clinic, emphasizing the importance of the development of multi-target compounds able to simultaneously modulate these key targets, as a novel and promising therapeutic strategy for this type of cancer.

How Computational Chemistry and Drug Delivery Techniques Can Support the Development of New Anticancer Drugs

The early and late development of new anticancer drugs, small molecules or peptides can be slowed down by some issues such as poor selectivity for the target or poor ADME properties. Computer-aided drug design (CADD) and target drug delivery (TDD) techniques, although apparently far from each other, are two research fields that can give a significant contribution to overcome these problems. Their combination may provide mechanistic understanding resulting in a synergy that makes possible the rational design of novel anticancer based therapies. Herein, we aim to discuss selected applications, some also from our research experience, in the fields of anticancer small organic drugs and peptides.

All-Atom Simulations Disclose How Cytochrome Reductase Reshapes the Substrate Access/Egress Routes of Its Partner CYP450s

Cytochromes P450 enzymes (CYP450s) promote the oxidative metabolism of a variety of substrates via the electrons supplied by the cytochrome P450 reductase (CPR) and upon formation of a CPR/CYP450 adduct. In spite of the pivotal regulatory importance of this process, the impact of CPR binding on the functional properties of its partner CYP450 remains elusive. By performing multiple microsecond-long all-atom molecular dynamics simulations of a 520 000-atom model of a CPR/CYP450 adduct embedded in a membrane mimic, we disclose the molecular terms for their interactions, considering the aromatase (HA) enzyme as a proxy of the CYP450 family. Our study strikingly unveils that CPR binding alters HA's functional motions, bolstering a change in the shape and type of the channels traveled by substrates/products during their access/egress to/from the enzyme's active site. Our outcomes unprecedentedly contribute to extricate the many entangled facets of the CYP450 metabolon, redrafting its intricate panorama from an atomic-level perspective.

Dynamics Insights Into the Gain of Flexibility by Helix-12 in ESR1 as a Mechanism of Resistance to Drugs in Breast Cancer Cell Lines

Incidents of breast cancer (BC) are on the rise on a daily basis and have proven to be the most prevelant cause of death for women in both developed and developing countries. Among total BC cases diagnosed after menopause, 70% of cases are Estrogen Receptor (ER) positive (ER-positive or ER+). Mutations in the LBD (ligand-binding domain) of the ER have recently been reported to be the major cause of resistance to potent antagonists. In this study, the experimentally reported mutations K303R, E380Q, V392I, S463P, V524E, P535H, P536H, Y537C, Y537N, Y537S, and D538G were analyzed, and the most significant mutations were shortlisted based on multiple analyses. Initial analyses, such as mCSM stability, occluded depth analysis, mCSM-binding affinity, and FoldX energy changes shortlisted only six mutations as being highly resistant. Finally, simulations of force field-based molecular dynamics (MD on wild type (WT) ERα) on six mERα variants (E380Q, S463P, Y537S, Y537C, Y537N, and D538G) were carried out to justify mechanism of the resistance. It was observed that these mutations increased the flexibility of the H12. A bonding analysis suggested that previously reported important residue His524 lost bonding upon mutation. Other parameters, such as PCA (principal component analysis), DCCM (dynamics cross-correlation), and FEL (free energy landscape), verified that the shortlisted mutations affect the H12 helix, which opens up the co-activator binding conformation. These results provide deep insight into the mechanism of relative resistance posed to fulvestrant due to mutations in breast cancer. This study will facilitate further understanding of the important aspects of designing specific and more effective drugs.

Molecular Dynamics Simulation Framework to Probe the Binding Hypothesis of CYP3A4 Inhibitors

The Cytochrome P450 family of heme-containing proteins plays a major role in catalyzing phase I metabolic reactions, and the CYP3A4 subtype is responsible for the metabolism of many currently marketed drugs. Additionally, CYP3A4 has an inherent affinity for a broad spectrum of structurally diverse chemical entities, often leading to drug-drug interactions mediated by the inhibition or induction of the metabolic enzyme. The current study explores the binding of selected highly efficient CYP3A4 inhibitors by docking and molecular dynamics (MD) simulation protocols and their binding free energy calculated using the WaterSwap method. The results indicate the importance of binding pocket residues including Phe57, Arg105, Arg106, Ser119, Arg212, Phe213, Thr309, Ser312, Ala370, Arg372, Glu374, Gly481 and Leu483 for interaction with CYP3A4 inhibitors. The residue-wise decomposition of the binding free energy from the WaterSwap method revealed the importance of binding site residues Arg106 and Arg372 in the stabilization of all the selected CYP3A4-inhibitor complexes. The WaterSwap binding energies were further complemented with the MM(GB/PB)SA results and it was observed that the binding energies calculated by both methods do not differ significantly. Overall, our results could guide towards the use of multiple computational approaches to achieve a better understanding of CYP3A4 inhibition, subsequently leading to the design of highly specific and efficient new chemical entities with suitable ADMETox properties and reduced side effects.

Structural, Thermodynamic, and Kinetic Traits of Antiestrogen-Compounds Selectively Targeting the Y537S Mutant Estrogen Receptor α Transcriptional Activity in Breast Cancer Cell Lines

The most frequently diagnosed cancers in women are the estrogen receptor (ER)-positive breast cancer subtypes, which are characterized by estrogen dependency for their growth. The mainstay of clinical treatment for this tumor relies on the modulation of ERα action or on the suppression of estrogen biosynthesis via the administration of Selective ERα Modulators/Down-regulators (SERMs/SERDs) or aromatase inhibitors, respectively. Nevertheless, de novo and acquired resistance to these therapies frequently occurs and represents a major clinical concern for patient survival. Recently, somatic mutations affecting the hormone-binding domain of ERα (i.e., Y537S, Y537N, D538G) have been associated with endocrine resistance, disease relapse and increased mortality rates. Hence, devising novel therapies against these ERα isoforms represents a daunting challenge. Here, we identified five molecules active on recurrent Y537S ERα polymorphism by employing in silico virtual screening on commercial databases of molecules, complemented by ER-transactivation and MTT assays in MCF7 and MDA-MB-231 breast cancer cells expressing wild type or mutated ERα. Among them, one molecule selectively targets Y537S ERα without inducing any cytotoxicity in breast cell lines. Multi-microseconds (4.5 μs) of biased and unbiased molecular dynamics provided an atomic-level picture of the structural, thermodynamics (i.e., binding free energies) and the kinetic (i.e., dissociation free energy barriers) of these active ligands as compared to clinically used SERM/SERDs upon binding to wild type and distinct ERα variants (Y537S, Y537N, D538G). This study contributes to a dissection of the key molecular traits needed by drug-candidates to hamper the agonist (active)-like conformation of ERα, normally selected by those polymorphic variants. This information can be useful to discover mutant specific drug-candidates, enabling to move a step forward toward tailored approaches for breast cancer treatment.

Human cytochrome P450 enzymes 5-51 as targets of drugs and natural and environmental compounds: mechanisms, induction, and inhibition - toxic effects and benefits

Cytochrome P450 (P450, CYP) enzymes have long been of interest due to their roles in the metabolism of drugs, pesticides, pro-carcinogens, and other xenobiotic chemicals. They have also been of interest due to their very critical roles in the biosynthesis and metabolism of steroids, vitamins, and certain eicosanoids. This review covers the 22 (of the total of 57) human P450s in Families 5-51 and their substrate selectivity. Furthermore, included is information and references regarding inducibility, inhibition, and (in some cases) stimulation by chemicals. We update and discuss important aspects of each of these 22 P450s and questions that remain open.

Post-Translational Regulation of CYP450s Metabolism As Revealed by All-Atoms Simulations of the Aromatase Enzyme

Phosphorylation by kinases enzymes is a widespread regulatory mechanism able of rapidly altering the function of target proteins. Among these are cytochrome P450s (CYP450), a superfamily of enzymes performing the oxidation of endogenous and exogenous substrates thanks to the electron supply of a redox partner. In spite of its pivotal role, the molecular mechanism by which phosphorylation modulates CYP450s metabolism remains elusive. Here by performing microsecond-long all-atom molecular dynamics simulations, we disclose how phosphorylation regulates estrogen biosynthesis, catalyzed by the Human Aromatase (HA) enzyme. Namely, we unprecedentedly propose that HA phosphorylation at Y361 markedly stabilizes its adduct with the flavin mononucleotide domain of CYP450s reductase (CPR), the redox partner of microsomal CYP450s, and a variety of other proteins. With CPR present at physiological conditions in a limiting ratio with respect to its multiple oxidative partners, the enhanced stability of the CPR/HA adduct may favor HA in the competition with the other proteins requiring CPR's electron supply, ultimately facilitating the electron transfer and estrogen biosynthesis. As a result, our work elucidates at atomic-level the post-translational regulation of CYP450s catalysis. Given the potential for rational clinical management of diseases associated with steroid metabolism disorders, unraveling this mechanism is of utmost importance, and raises the intriguing perspective of exploiting this knowledge to devise novel therapies.

Can multiscale simulations unravel the function of metallo-enzymes to improve knowledge-based drug discovery?

Metallo-enzymes are a large class of biomolecules promoting specialized chemical reactions. Quantum-classical quantum mechanics/molecular mechanics molecular dynamics, describing the metal site at quantum mechanics level, while accounting for the rest of system at molecular mechanics level, has an accessible time-scale limited by its computational cost. Hence, it must be integrated with classical molecular dynamics and enhanced sampling simulations to disentangle the functions of metallo-enzymes. In this review, we provide an overview of these computational methods and their capabilities. In particular, we will focus on some systems such as CYP19A1 a Fe-dependent enzyme involved in estrogen biosynthesis, and on Mg2+-dependent DNA/RNA processing enzymes/ribozymes and the spliceosome, a protein-directed ribozyme. This information may guide the discovery of drug-like molecules and genetic manipulation tools.

Escape of a Small Molecule from Inside T4 Lysozyme by Multiple Pathways

The T4 lysozyme L99A mutant is often used as a model system to study small-molecule binding to proteins, but pathways for ligand entry and exit from the buried binding site and the associated protein conformational changes have not been fully resolved. Here, molecular dynamics simulations were employed to model benzene exit from its binding cavity using the weighted ensemble (WE) approach to enhance sampling of low-probability unbinding trajectories. Independent WE simulations revealed four pathways for benzene exit, which correspond to transient tunnels spontaneously formed in previous simulations of apo T4 lysozyme. Thus, benzene unbinding occurs through multiple pathways partially created by intrinsic protein structural fluctuations. Motions of several α-helices and side chains were involved in ligand escape from metastable microstates. WE simulations also provided preliminary estimates of rate constants for each exit pathway. These results complement previous works and provide a semiquantitative characterization of pathway heterogeneity for binding of small molecules to proteins.

The Catalytic Mechanism of Steroidogenic Cytochromes P450 from All-Atom Simulations: Entwinement with Membrane Environment, Redox Partners, and Post-Transcriptional Regulation

Cytochromes P450 (CYP450s) promote the biosynthesis of steroid hormones with major impact on the onset of diseases such as breast and prostate cancers. By merging distinct functions into the same catalytic scaffold, steroidogenic CYP450s enhance complex chemical transformations with extreme efficiency and selectivity. Mammalian CYP450s and their redox partners are membrane-anchored proteins, dynamically associating to form functional machineries. Mounting evidence signifies that environmental factors are strictly intertwined with CYP450s catalysis. Atomic-level simulations have the potential to provide insights into the catalytic mechanism of steroidogenic CYP450s and on its regulation by environmental factors, furnishing information often inaccessible to experimental means. In this review, after an introduction of computational methods commonly employed to tackle these systems, we report the current knowledge on three steroidogenic CYP450s—CYP11A1, CYP17A1, and CYP19A1—endowed with multiple catalytic functions and critically involved in cancer onset. In particular, besides discussing their catalytic mechanisms, we highlight how the membrane environment contributes to (i) regulate ligand channeling through these enzymes, (ii) modulate their interactions with specific protein partners, (iii) mediate post-transcriptional regulation induced by phosphorylation. The results presented set the basis for developing novel therapeutic strategies aimed at fighting diseases originating from steroid metabolism dysfunction.

How phosphorylation influences E1 subunit pyruvate dehydrogenase: A computational study

Pyruvate (PYR) dehydrogenase complex (PDC) is an enzymatic system that plays a crucial role in cellular metabolism as it controls the entry of carbon into the Krebs cycle. From a structural point of view, PDC is formed by three different subunits (E1, E2 and E3) capable of catalyzing the three reaction steps necessary for the full conversion of pyruvate to acetyl-CoA. Recent investigations pointed out the crucial role of this enzyme in the replication and survival of specific cancer cell lines, renewing the interest of the scientific community. Here, we report the results of our molecular dynamics studies on the mechanism by which posttranslational modifications, in particular the phosphorylation of three serine residues (Ser-264-α, Ser-271-α, and Ser-203-α), influence the enzymatic function of the protein. Our results support the hypothesis that the phosphorylation of Ser-264-α and Ser-271-α leads to (1) a perturbation of the catalytic site structure and dynamics and, especially in the case of Ser-264-α, to (2) a reduction in the affinity of E1 for the substrate. Additionally, an analysis of the channels connecting the external environment with the catalytic site indicates that the inhibitory effect should not be due to the occlusion of the access/egress pathways to/from the active site.

An overview of recent molecular dynamics applications as medicinal chemistry tools for the undruggable site challenge

Molecular dynamics (MD) has become increasingly popular due to the development of hardware and software solutions and the improvement in algorithms, which allowed researchers to scale up calculations in order to speed them up. MD simulations are usually used to address protein folding issues or protein-ligand complex stability through energy profile analysis over time. In recent years, the development of new tools able to deeply explore a potential energy surface (PES) has allowed researchers to focus on the dynamic nature of the binding recognition process and binding-induced protein conformational changes. Moreover, modern approaches have been demonstrated to be effective and reliable in calculating some kinetic and thermodynamic parameters behind the host-guest recognition process. Starting from all of these considerations, several efforts have been made in order to integrate MD within the virtual screening process in drug discovery. Knowledge retrieved from MD can, in fact, be exploited as a starting point to build pharmacophores or docking constraints in the early stage of the screening campaign as well as to define key features, in order to unravel hidden binding modes and help the optimisation of the molecular structure of a lead compound. Based on these outcomes, researchers are nowadays using MD as an invaluable tool to discover and target previously considered undruggable binding sites, including protein-protein interactions and allosteric sites on a protein surface. As a matter of fact, the use of MD has been recognised as vital to the discovery of selective protein-protein interaction modulators. The use of a dynamic overview on how the host-guest recognition occurs and of the relative conformational modifications induced allows researchers to optimise small molecules and small peptides capable of tightly interacting within the cleft between two proteins. In this review, we aim to present the most recent applications of MD as an integrated tool to be used in the rational design of small molecules or small peptides able to modulate undruggable targets, such as allosteric sites and protein-protein interactions.

Exploring the structure characteristics and major channels of cytochrome P450 2A6, 2A13, and 2E1 with pilocarpine

The majority of cytochromes P450 play a critical role in metabolism of endogenous and exogenous substrates, some of its products are carcinogens. Therefore, inhibition of P450 enzymes activity can promote the detoxification and elimination of chemical carcinogens. In this study, molecular dynamics (MD) simulations and adaptive steered molecular dynamics (ASMD) simulations were performed to explore the structure features and channel dynamics of three P450 isoforms 2A6, 2A13, and 2E1 bound with the common inhibitor pilocarpine. The binding free energy results combined with the PMF calculations give a reasonable ranking of binding affinity, which are consistent with the experimental data. Our results uncover how a sequence divergence of different CYP2 enzymes causes individual variations in major channel selections. On the basis of channel bottleneck and energy decomposition analysis, we propose a gating mechanism of their respective major channels in three enzymes, which may be attributed to a reversal of Phe209 in CYP2A6/2A13, as well as the rotation of Phe116 and Phe298 in CYP2E1. The hydrophobic residues not only make strong hydrophobic interactions with inhibitor, but also act as gatekeeper to regulate the opening of channel. The present study provides important insights into the structure-function relationships of three cytochrome P450s and the molecular basis for development of potent inhibitors.

A Computational Assay of Estrogen Receptor α Antagonists Reveals the Key Common Structural Traits of Drugs Effectively Fighting Refractory Breast Cancers

Somatic mutations of the Estrogen Receptor α (ERα) occur with an up to 40% incidence in ER sensitive breast cancer (BC) patients undergoing prolonged endocrine treatments. These polymorphisms are implicated in acquired resistance, disease relapse, and increased mortality rates, hence representing a current major clinical challenge. Here, multi-microseconds (12.5 µs) molecular dynamics simulations revealed that recurrent ERα polymorphisms (i. e. L536Q, Y537S, Y537N, D538G) (mERα) are constitutively active in their apo form and that they prompt the selection of an agonist (active)-like conformation even upon antagonists binding. Interestingly, our simulations rationalize, for the first time, the efficacy profile of (pre)clinically used Selective Estrogen Receptor Modulators/Downregulators (SERMs/SERDs) against these variants, enlightening, at atomistic level of detail, the key common structural traits needed by drugs able to effectively fight refractory BC types. This knowledge represents a key advancement for mechanism-based therapeutics targeting resistant ERα isoforms, potentially allowing the community to move a step closer to ‘precision medicine’ calibrated on patients’ genetic profiles and disease progression.

Thermodynamics of camphor migration in cytochrome P450cam by atomistic simulations

Understanding the mechanisms of ligand binding to enzymes is of paramount importance for the design of new drugs. Here, we report on the use of a novel biased molecular dynamics (MD) methodology to study the mechanism of camphor binding to cytochrome P450cam. Microsecond-long MD simulations allowed us to observe reaction coordinates characterizing ligand diffusion from the active site of cytochrome P450cam to solvent via three egress routes. These atomistic simulations were used to estimate thermodynamic quantities along the reaction coordinates and indicate diverse binding configurations. The results suggest that the diffusion of camphor along the pathway near the substrate recognition site (SRS) is thermodynamically preferred. In addition, we show that the diffusion near the SRS is triggered by a transition from a heterogeneous collection of closed ligand-bound conformers to the basin comprising the open conformations of cytochrome P450cam. The conformational change accompanying this switch is characterized by the retraction of the F and G helices and the disorder of the B' helix. These results are corroborated by experimental studies and provide detailed insight into ligand binding and conformational behavior of the cytochrome family. The presented methodology is general and can be applied to other ligand-protein systems.