Targeting Dynamic Pockets of HIV-1 Protease by Structure-Based Computational Screening for Allosteric Inhibitors

The structural, dynamic, and thermodynamic basis of darunavir resistance of a heavily mutated HIV-1 protease using molecular dynamics simulation

The human immunodeficiency virus type 1 protease (HIV-1 PR) is an important enzyme in the life cycle of the HIV virus. It cleaves inactive pre-proteins of the virus and changes them into active proteins. Darunavir (DRV) suppresses the wild-type HIV-1 PR (WT-Pr) activity but cannot inhibit some mutant resistant forms (MUT-Pr). Increasing knowledge about the resistance mechanism can be helpful for designing more effective inhibitors. In this study, the mechanism of resistance of a highly MUT-Pr strain against DRV was investigated. For this purpose, complexes of DRV with WT-Pr (WT-Pr-D) and MUT-Pr (MUT-Pr-D) were studied by all-atom molecular dynamics simulation in order to extract the dynamic and energetic properties. Our data revealed that mutations increased the flap-tip flexibility due to the reduction of the flap-flap hydrophobic interactions. So, the protease’s conformation changed from a closed state to a semi-open state that can facilitate the disjunction of DRV from the active site. On the other hand, energy analysis limited to the final basins of the energy landscape indicated that the entropy of binding of DRV to MUT-Pr was more favorable than that of WT-Pr. However, the enthalpy penalty overcomes it and makes binding more unfavorable relative to the WT-Pr. The unfavorable interaction of DRV with R8, I50, I84, D25′, and A28′ residues in MUT-Pr-D relative to WT-Pr-D is the reason for this enthalpy penalty. Thus, mutations drive resistance to DRV. The hydrogen bond analysis showed that compared with WT-Pr, the hydrogen bonds between DRV and the active-site residues of MUT-Pr were disrupted.

Mechanism of darunavir binding to monomeric HIV-1 protease: a step forward in the rational design of dimerization inhibitors

HIV protease (HIVPR) is a key target in AIDS therapeutics. All ten FDA-approved drugs that compete with substrates in binding to this dimeric enzyme's active site have become ineffective due to the emergence of drug resistant mutants. Blocking the dimerization interface of HIVPR is thus being explored as an alternate strategy. The latest drug, darunavir (DRV), which exhibited a high genetic barrier to viral resistance, is said to have a dual mode of action - (i) binding to the dimeric active site, and (ii) preventing the dimerization by binding to the HIVPR monomer. Despite several reports on DRV complexation with dimeric HIVPR, the mode and mechanism of the binding of DRV to the HIVPR monomer are poorly understood. In this study, we utilized all-atomic MD simulations and umbrella sampling techniques to identify the best possible binding mode of DRV to the monomeric HIVPR and its mechanism of association. The results suggest that DRV binds between the active site and the flap of the monomer, and the flap plays a crucial role in directing the drug to bind and driving the other protein domains to undergo induced fit changes for stronger complexation. The obtained binding mode of DRV was validated by comparing with various mutational data from clinical isolates to reported in vitro mutations. The identified binding pose was also able to successfully reproduce the experimental K_i value in the picomolar range. The residue-level information extracted from this study could accelerate the structure-based drug designing approaches targeting HIVPR dimerization.

Inhibition of the activity of HIV-1 protease through antibody binding and mutations probed by molecular dynamics simulations

HIV-1 protease is an essential enzyme in the life cycle of the HIV-1 virus. The conformational dynamics of the flap region of the protease is critical for the ligand binding mechanism, as well as for the catalytic activity. The monoclonal antibody F11.2.32 raised against HIV-1 protease inhibits its activity on binding. We have studied the conformational dynamics of protease in its free, inhibitor ritonavir and antibody bound forms using molecular dynamics simulations. We find that upon Ab binding to the epitope region (residues 36-46) of protease, the overall flexibility of the protease is decreased including the flap region and the active site, which is similar to the decrease in flexibility observed by inhibitor binding to the protease. This suggests an allosteric mechanism to inhibit protease activity. Further, the protease mutants G40E and G40R are known to have decreased activity and were also subjected to MD simulations. We find that the loss of flexibility in the mutants is similar to that observed in the protease bound to the Ab/inhibitor. These insights highlight the role played by dynamics in the function of the protease and how control of flexibility through Ab binding and site specific mutations can inhibit protease activity.

Binding site matching in rational drug design: algorithms and applications

Interactions between proteins and small molecules are critical for biological functions. These interactions often occur in small cavities within protein structures, known as ligand-binding pockets. Understanding the physicochemical qualities of binding pockets is essential to improve not only our basic knowledge of biological systems, but also drug development procedures. In order to quantify similarities among pockets in terms of their geometries and chemical properties, either bound ligands can be compared to one another or binding sites can be matched directly. Both perspectives routinely take advantage of computational methods including various techniques to represent and compare small molecules as well as local protein structures. In this review, we survey 12 tools widely used to match pockets. These methods are divided into five categories based on the algorithm implemented to construct binding-site alignments. In addition to the comprehensive analysis of their algorithms, test sets and the performance of each method are described. We also discuss general pharmacological applications of computational pocket matching in drug repurposing, polypharmacology and side effects. Reflecting on the importance of these techniques in drug discovery, in the end, we elaborate on the development of more accurate meta-predictors, the incorporation of protein flexibility and the integration of powerful artificial intelligence technologies such as deep learning.

Perspective: The promises of a holistic view of proteins-impact on antibody engineering and drug discovery

The reductionist approach is prevalent in biomedical science. However, increasing evidence now shows that biological systems cannot be simply considered as the sum of its parts. With experimental, technological, and computational advances, we can now do more than view parts in isolation, thus we propose that an increasing holistic view (where a protein is investigated as much as a whole as possible) is now timely. To further advocate this, we review and discuss several studies and applications involving allostery, where distant protein regions can cross-talk to influence functionality. Therefore, we believe that an increasing big picture approach holds great promise, particularly in the areas of antibody engineering and drug discovery in rational drug design.

The influence of substituents on the reactivity and cytotoxicity of imidazothiazolotriazinones

A series of tetrahydroimidazo[4,5-e]thiazolo[3,2-b]-1,2,4-triazine-2,7(1H, 6H)-diones were synthesized via the reaction of imidazotriazinethiones and bromoacetic acid followed by condensation with isatins. Amidine skeletal rearrangement of 3,3a,9,9a-tetrahydroimidazo[4,5-e]thiazolo[3,2-b]-1,2,4-triazine-2,7 (1H, 6H)-diones into 1,3a,4,9a-tetrahydroimidazo[4,5-e]thiazolo[2,3-c]-1,2,4-triazine-2,8 (3H, 7H)-diones under KOH treatment has been studied. The influence of substituents at positions 1,3,3a,6,9a of imidazothiazolotriazine on the ability to undergo rearrangement was analyzed based on experimental data and theoretical calculations. Both imidazothiazolo[3,2-b]triazines and their rearrangement products were evaluated for their cytotoxic activity against rhabdomyosarcoma, A549, HCT116 and MCF7 human cancer cell lines by MTT assay. Among the derivatives, 1,3-diethyl-6-[1-(2-propyl)-2-oxoindolin-3-ylidene]-3,3a,9,9a-tetrahydroimidazo [4,5-e]thiazolo[3,2-b]-1,2,4-triazine-2,7(1H, 6H)-dione 4i was found to have the highest antiproliferative activity toward the tested cell lines (4i: [Formula: see text], 2.29, 0.47 and [Formula: see text], respectively). The [Formula: see text] value of compound 4i against normal human embryonic kidney cells HEK293 was [Formula: see text], which appeared to be 6-41-fold higher than [Formula: see text] values of 4i against human cancer cells.

Differential Protein Dynamics of Regulators of G-Protein Signaling: Role in Specificity of Small-Molecule Inhibitors

Small-molecule inhibitor selectivity may be influenced by variation in dynamics among members of a protein family. Regulator of G-protein Signaling (RGS) proteins are a family that plays a key role in G-Protein Coupled Receptor (GPCR) signaling by binding to active Gα subunits and accelerating GTP hydrolysis, thereby terminating activity. Thiadiazolidinones (TDZDs) inhibit the RGS-Gα interaction by covalent modification of cysteine residues in RGS proteins. Some differences in specificity may be explained by differences in the complement of cysteines among RGS proteins. However, key cysteines shared by RGS proteins inhibited by TDZDs are not exposed on the protein surface, and differences in potency exist among RGS proteins containing only buried cysteines. We hypothesize that differential exposure of buried cysteine residues among RGS proteins partially drives TDZD selectivity. Hydrogen-deuterium exchange (HDX) studies and molecular dynamics (MD) simulations were used to probe the dynamics of RGS4, RGS8, and RGS19, three RGS proteins inhibited at a range of potencies by TDZDs. When these proteins were mutated to contain a single, shared cysteine, RGS19 was found to be most potently inhibited. HDX studies revealed differences in α4 and α6 helix flexibility among RGS isoforms, with particularly high flexibility in RGS19. This could cause differences in cysteine exposure and lead to differences in potency of TDZD inhibition. MD simulations of RGS proteins revealed motions that correspond to solvent exposure observed in HDX, providing further evidence for a role of protein dynamics in TDZD selectivity.

Computational Exploration of Conformational Transitions in Protein Drug Targets

Protein drug targets vary from highly structured to completely disordered; either way dynamics governs function. Hence, understanding the dynamical aspects of how protein targets function can enable improved interventions with drug molecules. Computational approaches offer highly detailed structural models of protein dynamics which are becoming more predictive as model quality and sampling power improve. However, the most advanced and popular models still have errors owing to imperfect parameter sets and often cannot access longer timescales of many crucial biological processes. Experimental approaches offer more certainty but can struggle to detect and measure lightly populated conformations of target proteins and subtle allostery. An emerging solution is to integrate available experimental data into advanced molecular simulations. In the future, molecular simulation in combination with experimental data may be able to offer detailed models of important drug targets such that improved functional mechanisms or selectivity can be accessed.

In-silico profiling of the biological activities of Amaryllidaceae alkaloids

OBJECTIVES

The large number of publications about Amaryllidaceae alkaloids reflects the abundance and variety in biological activity of these alkaloids. An in-silico approach was implemented in this work to rationalize the individual alkaloids to molecular biological activity.

METHODS

A database was generated containing 313 Amaryllidaceae alkaloids which were then subjected to in-silico-validated structure-based virtual screening using extra precision (XP) approach of Glide docking program. Further pharmacophore detection of the high scorers resulted in a hybrid model considering the structural and spatial characteristics of the molecules. The focus was laid on representative targets against viral infections, acetylcholinesterase and cancer. BEDROC studies were used for validation of the accuracy of docking methods.

KEY FINDINGS

As expected, galanthamine-type alkaloids were the most active against hACHE; yet, lycorenine- and tazettine-type alkaloids contributed significantly, while lycorine-type alkaloids dominated the hit list against HIV-1 PR target protein and were significantly active against HIV-1 RT and influenza NA. Surprisingly, belladine-type alkaloids showed the highest number of hits against HDAC2, while lycorine- and narciclasine-type alkaloids dominated the hit lists against Aurora kinase A and VEGFR2.

CONCLUSIONS

This report provides useful information on Amaryllidaceae alkaloids and serves as a starting point to access their undiscovered biological activity.

Effect of allosteric molecules on structure and drug affinity of HIV-1 protease by molecular dynamics simulations

Recent experiments show that small molecules can bind onto the allosteric sites of HIV-1 protease (PR), which provides a starting point for developing allosteric inhibitors. However, the knowledge of the effect of such binding on the structural dynamics and binding free energy of the active site inhibitor and PR is still lacking. Here, we report 200ns long molecular dynamics simulation results to gain insight into the influences of two allosteric molecules (1H-indole-6-carboxylic acid, 1F1 and 2-methylcyclohexano, 4D9). The simulations demonstrate that both allosteric molecules change the PR conformation and stabilize the structures of PR and the inhibitor; the residues of the flaps are sensitive to the allosteric molecules and the flexibility of the residues is pronouncedly suppressed; the additions of the small molecules to the allosteric sites strengthen the binding affinities of 3TL-PR by about 12-15kal/mol in the binding free energy, which mainly arises from electrostatic term. Interestingly, it is found that the action mechanisms of 1F1 and 4D9 are different, the former behaviors like a doorman that keeps the inhibitor from escape and makes the flaps (door) partially open; the latter is like a wedge that expands the allosteric space and meanwhile closes the flaps. Our data provide a theoretical support for designing the allosteric inhibitor.

Role of Conformational Motions in Enzyme Function: Selected Methodologies and Case Studies

It is now common knowledge that enzymes are mobile entities relying on complex atomic-scale dynamics and coordinated conformational events for proper ligand recognition and catalysis. However, the exact role of protein dynamics in enzyme function remains either poorly understood or difficult to interpret. This mini-review intends to reconcile biophysical observations and biological significance by first describing a number of common experimental and computational methodologies employed to characterize atomic-scale residue motions on various timescales in enzymes, and second by illustrating how the knowledge of these motions can be used to describe the functional behavior of enzymes and even act upon it. Two biologically relevant examples will be highlighted, namely the HIV-1 protease and DNA polymerase β enzyme systems.

Protein Binding Pocket Dynamics

The dynamics of protein binding pockets are crucial for their interaction specificity. Structural flexibility allows proteins to adapt to their individual molecular binding partners and facilitates the binding process. This implies the necessity to consider protein internal motion in determining and predicting binding properties and in designing new binders. Although accounting for protein dynamics presents a challenge for computational approaches, it expands the structural and physicochemical space for compound design and thus offers the prospect of improved binding specificity and selectivity. A cavity on the surface or in the interior of a protein that possesses suitable properties for binding a ligand is usually referred to as a binding pocket. The set of amino acid residues around a binding pocket determines its physicochemical characteristics and, together with its shape and location in a protein, defines its functionality. Residues outside the binding site can also have a long-range effect on the properties of the binding pocket. Cavities with similar functionalities are often conserved across protein families. For example, enzyme active sites are usually concave surfaces that present amino acid residues in a suitable configuration for binding low molecular weight compounds. Macromolecular binding pockets, on the other hand, are located on the protein surface and are often shallower. The mobility of proteins allows the opening, closing, and adaptation of binding pockets to regulate binding processes and specific protein functionalities. For example, channels and tunnels can exist permanently or transiently to transport compounds to and from a binding site. The influence of protein flexibility on binding pockets can vary from small changes to an already existent pocket to the formation of a completely new pocket. Here, we review recent developments in computational methods to detect and define binding pockets and to study pocket dynamics. We introduce five different classes of protein pocket dynamics: (1) appearance/disappearance of a subpocket in an existing pocket; (2) appearance/disappearance of an adjacent pocket on the protein surface in the direct vicinity of an already existing pocket; (3) pocket breathing, which may be caused by side-chain fluctuations or backbone or interdomain vibrational motion; (4) opening/closing of a channel or tunnel, connecting a pocket inside the protein with solvent, including lid motion; and (5) the appearance/disappearance of an allosteric pocket at a site on a protein distinct from an already existing pocket with binding of a ligand to the allosteric binding site affecting the original pocket. We suggest that the class of pocket dynamics, as well as the type and extent of protein motion affecting the binding pocket, should be factors considered in choosing the most appropriate computational approach to study a given binding pocket. Furthermore, we examine the relationship between pocket dynamics classes and induced fit, conformational selection, and gating models of ligand binding on binding kinetics and thermodynamics. We discuss the implications of protein binding pocket dynamics for drug design and conclude with potential future directions for computational analysis of protein binding pocket dynamics.

Molecular dynamics simulations of the free and inhibitor-bound cruzain systems in aqueous solvent: insights on the inhibition mechanism in acidic pH

The major cysteine protease of Trypanosoma cruzi, cruzain (CRZ), has been described as a therapeutic target for Chagas' disease, which affects millions of people worldwide. Thus, a series of CRZ inhibitors has been studied, including a new competitive inhibitor, Nequimed176 (NEQ176). Nevertheless, the structural and dynamic basis for CRZ inhibition remains unclear. Hoping to contribute to this ever-growing understanding of timescale dynamics in the CRZ inhibition mechanism, we have performed the first study using 100 ns of molecular dynamics (MD) simulations of two CRZ systems in an aqueous solvent under pH 5.5: CRZ in the apo form (ligand free) and CRZ complexed to NEQ176. According to the MD simulations, the enzyme adopts an open conformation in the apo form and a closed conformation in the NEQ176-CRZ complex. We also suggest that this closed conformation is related to the hydrogen-bonding interactions between NEQ176 and CRZ, which occurs through key residues, mainly Gly66, Met68, Asn69, and Leu160. In addition, the cross-correlation analysis shows evidence of the correlated motions among Ala110-Asp140, Leu160-Gly189, and Glu190-Gly215 subdomains, as well as, the movements related to Ala1-Thr59 and Asp60-Pro90 regions seem to be crucial for CRZ activity.

Anti-HIV Drug Discovery and Development: Current Innovations and Future Trends

The early effectiveness of combinatorial antiretroviral therapy (cART) in the treatment of HIV infection has been compromised to some extent by rapid development of multidrug-resistant HIV strains, poor bioavailability, and cumulative toxicities, and so there is a need for alternative strategies of antiretroviral drug discovery and additional therapeutic agents with novel action modes or targets. From this perspective, we first review current strategies of antiretroviral drug discovery and optimization, with the aid of selected examples from the recent literature. We highlight the development of phosphate ester-based prodrugs as a means to improve the aqueous solubility of HIV inhibitors, and the introduction of the substrate envelope hypothesis as a new approach for overcoming HIV drug resistance. Finally, we discuss future directions for research, including opportunities for exploitation of novel antiretroviral targets, and the strategy of activation of latent HIV reservoirs as a means to eradicate the virus.

Fragment-based approaches to anti-HIV drug discovery: state of the art and future opportunities

INTRODUCTION

The search for additional drugs to treat HIV infection is a continuing effort due to the emergence and spread of HIV strains resistant to nearly all current drugs. The recent literature reveals that fragment-based drug design/discovery (FBDD) has become an effective alternative to conventional high-throughput screening strategies for drug discovery.

AREAS COVERED

In this critical review, the authors describe the state of the art in FBDD strategies for the discovery of anti-HIV drug-like compounds. The article focuses on fragment screening techniques, direct fragment-based design and early hit-to-lead progress.

EXPERT OPINION

Rapid progress in biophysical detection and in silico techniques has greatly aided the application of FBDD to discover candidate agents directed at a variety of anti-HIV targets. Growing evidence suggests that structural insights on key proteins in the HIV life cycle can be applied in the early phase of drug discovery campaigns, providing valuable information on the binding modes and efficiently prompting fragment hit-to-lead progression. The combination of structural insights with improved methodologies for FBDD, including the privileged fragment-based reconstruction approach, fragment hybridization based on crystallographic overlays, fragment growth exploiting dynamic combinatorial chemistry, and high-speed fragment assembly via diversity-oriented synthesis followed by in situ screening, offers the possibility of more efficient and rapid discovery of novel drugs for HIV-1 prevention or treatment. Though the use of FBDD in anti-HIV drug discovery is still in its infancy, it is anticipated that anti-HIV agents developed via fragment-based strategies will be introduced into the clinic in the future.

Multistage virtual screening and identification of novel HIV-1 protease inhibitors by integrating SVM, shape, pharmacophore and docking methods

The HIV-1 protease has proven to be a crucial component of the HIV replication machinery and a reliable target for anti-HIV drug discovery. In this study, we applied an optimized hierarchical multistage virtual screening method targeting HIV-1 protease. The method sequentially applied SVM (Support Vector Machine), shape similarity, pharmacophore modeling and molecular docking. Using a validation set (270 positives, 155,996 negatives), the multistage virtual screening method showed a high hit rate and high enrichment factor of 80.47% and 465.75, respectively. Furthermore, this approach was applied to screen the National Cancer Institute database (NCI), which contains 260,000 molecules. From the final hit list, 6 molecules were selected for further testing in an in vitro HIV-1 protease inhibitory assay, and 2 molecules (NSC111887 and NSC121217) showed inhibitory potency against HIV-1 protease, with IC50 values of 62 μM and 162 μM, respectively. With further chemical development, these 2 molecules could potentially serve as HIV-1 protease inhibitors.

Hierarchical virtual screening approaches in small molecule drug discovery

Virtual screening has played a significant role in the discovery of small molecule inhibitors of therapeutic targets in last two decades. Various ligand and structure-based virtual screening approaches are employed to identify small molecule ligands for proteins of interest. These approaches are often combined in either hierarchical or parallel manner to take advantage of the strength and avoid the limitations associated with individual methods. Hierarchical combination of ligand and structure-based virtual screening approaches has received noteworthy success in numerous drug discovery campaigns. In hierarchical virtual screening, several filters using ligand and structure-based approaches are sequentially applied to reduce a large screening library to a number small enough for experimental testing. In this review, we focus on different hierarchical virtual screening strategies and their application in the discovery of small molecule modulators of important drug targets. Several virtual screening studies are discussed to demonstrate the successful application of hierarchical virtual screening in small molecule drug discovery.

Fractal Dimensions of Macromolecular Structures

Quantifying the properties of macromolecules is a prerequisite for understanding their roles in biochemical processes. One of the less-explored geometric features of macromolecules is molecular surface irregularity, or ‘roughness’, which can be measured in terms of fractal dimension (D). In this study, we demonstrate that surface roughness correlates with ligand binding potential. We quantified the surface roughnesses of biological macromolecules in a large-scale survey that revealed D values between 2.0 and 2.4. The results of our study imply that surface patches involved in molecular interactions, such as ligand-binding pockets and protein-protein interfaces, exhibit greater local fluctuations in their fractal dimensions than ‘inert’ surface areas. We expect approximately 22 % of a protein’s surface outside of the crystallographically known ligand binding sites to be ligandable. These findings provide a fresh perspective on macromolecular structure and have considerable implications for drug design as well as chemical and systems biology.

Inhibitor design strategy based on an enzyme structural flexibility: a case of bacterial MurD ligase

Increasing bacterial resistance to available antibiotics stimulated the discovery of novel efficacious antibacterial agents. The biosynthesis of the bacterial peptidoglycan, where the MurD enzyme is involved in the intracellular phase of the UDP-MurNAc-pentapeptide formation, represents a collection of highly selective targets for novel antibacterial drug design. In our previous computational studies, the C-terminal domain motion of the MurD ligase was investigated using Targeted Molecular Dynamic (TMD) simulation and the Off-Path Simulation (OPS) technique. In this study, we present a drug design strategy using multiple protein structures for the identification of novel MurD ligase inhibitors. Our main focus was the ATP-binding site of the MurD enzyme. In the first stage, three MurD protein conformations were selected based on the obtained OPS/TMD data as the initial criterion. Subsequently, a two-stage virtual screening approach was utilized combining derived structure-based pharmacophores with molecular docking calculations. Selected compounds were then assayed in the established enzyme binding assays, and compound 3 from the aminothiazole class was discovered to act as a dual MurC/MurD inhibitor in the micomolar range. A steady-state kinetic study was performed on the MurD enzyme to provide further information about the mechanistic aspects of its inhibition. In the final stage, all used conformations of the MurD enzyme with compound 3 were simulated in classical molecular dynamics (MD) simulations providing atomistic insights of the experimental results. Overall, the study depicts several challenges that need to be addressed when trying to hit a flexible moving target such as the presently studied bacterial MurD enzyme and show the possibilities of how computational tools can be proficiently used at all stages of the drug discovery process.