Systematic molecular dynamics, MM-PBSA, and ab initio approaches to the saquinavir resistance mechanism in HIV-1 PR due to 11 double and multiple mutations

Multiple Molecular Dynamics Simulations and Energy Analysis Unravel the Dynamic Properties and Binding Mechanism of Mutants HIV-1 Protease with DRV and CA-p2

PRS17, a variant of human immunodeficiency virus type I protease (HIV-1 PR), has 17 mutated residues showing high levels of multidrug resistance. To describe the effects of these mutated residues on the dynamic properties and the binding mechanism of PR with substrate and inhibitor, focused on six systems (two complexes of WT PR and PRS17 with inhibitor Darunavir (DRV), two complexes of WT PR and PRS17 with substrate analogue CA-p2, two unligand WT PR and PRS17), we performed multiple molecular dynamics (MD) simulations combined with MM-PBSA and solvated interaction energy (SIE) methods. For both the unligand PRs and ligand-PR complexes, the results from simulations revealed 17 mutated residues alter the flap-flap distance, the distance from flap regions to catalytic sites, and the curling degree of the flap tips. These mutated residues changed the flexibility of the flap region in PR, and thus affected its binding energy with DRV and CA-p2, resulting in differences in sensitivity. Hydrophobic cavity makes an important contribution to the binding of PR and ligands. And most noticeable of all, the binding of the guanidine group in CA-p2 and Arg8' of PRS17 is useful for increasing their binding ability. These results have important guidance for the further design of drugs against multidrug resistant PR. IMPORTANCE Developing effective anti-HIV inhibitors is the current requirement to cope with the emergence of the resistance of mutants. Compared with the experiments, MD simulations along with energy calculations help reduce the time and cost of designing new inhibitors. Based on our simulation results, we propose two factors that may help design effective inhibitors against HIV-1 PR: (i) importance of hydrophobic cavity, and (ii) introduction of polar groups similar to the guanidine group.

Multiple Molecular Dynamics Simulations and Free-Energy Predictions Uncover the Susceptibility of Variants of HIV-1 Protease against Inhibitors Darunavir and KNI-1657

HIV-1 protease (PR) is considered to be the main targets of anti-AIDS drug design because of its role in the proteolytic processing of viral polyproteins. However, the emergence of drug-resistant HIV has become a major problem in the therapy of HIV-1-infected patients. Focused on the complexes of wild type (WT) PR and two mutant PRs (V32I/L33F/I54M/V82I and V32I/L33F/I54M/I84 V) with inhibitors Darunavir (DRV) and KNI-1657 (KNI), respectively, we have conducted research on the conformational dynamics and the resistance mechanism caused by residue mutations through multiple molecular dynamics (MD) simulations combined with an energy (MM-PBSA and solvated interaction energy (SIE)) prediction. The results indicate that mutated residues of PR alter the distance between flap regions and catalytic sites, the volume of the inner catalytic site, and the curling degree of the flap tips, thereby affecting DRV and KNI inhibitor binding to PR. These mutated residues reduced the binding affinity of the two mutant PRs to DRV, resulting in drug resistance, whereas the two mutant PRs increase the binding affinity with KNI, indicating they enhance the sensitivity to KNI. Compared with the WT PR, the changes in van der Waals interaction and electrostatic interaction in the two variant PRs play a vital part in the binding of PR with DRV and KNI. These results may supply valuable guidance for the design of anti-AIDS drugs targeting PR.

Multiple Molecular Dynamics Simulations of the Inhibitor GRL-02031 Complex with Wild Type and Mutant HIV-1 Protease Reveal the Binding and Drug-Resistance Mechanism

Human immunodeficiency virus type 1 (HIV-1) protease is regarded as a fascinating target for drug development against HIV infection. However, mutations causing drug resistance severely limit the efficiency of the recently marketed drugs in the treatment of HIV replication. To elucidate the binding mechanism of HIV-1 protease with promising inhibitor GRL-02031 and further to probe the resistance mechanism associated with mutations (I47V, L76V, V82A, and N88D) to the inhibitor, we applied multiple molecular dynamics (MMD) simulations along with energy analysis by the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) and solvated interaction energy (SIE) methodology on specific HIV-1 protease with GRL-0231 complexes. On the basis of detail analysis of the simulations, we revealed key characteristics that constitute the drug resistance of four mutation HIV-1 proteases toward GRL-02031: substitution of the side chain in these four mutation residues leads to a change in the distances between the flaps and catalytic sites, thereby reducing the affinity for GRL-02031 with these four mutation proteases, even though the L76V and N88D residues cannot directly contact GRL-02031. The results of energy analysis according to the MM-PBSA and SIE methods further indicated that hydrophobic interaction was considered to be the prime driving force for inhibitor GRL-02031 binding to protease and the decrease in van der Waals interactions between inhibitor GRL-02031 and mutant proteases as the primary cause of the drug resistance. Analyses of the hydrogen bonds and atomic interactions further provided detailed explanations for the resistance of these four mutation proteases toward inhibitor GRL-02031. The present study provides potential guidance on the structure-based inhibitors' design targeting HIV-1 protease.

Revealing the binding and drug resistance mechanism of amprenavir, indinavir, ritonavir, and nelfinavir complexed with HIV-1 protease due to double mutations G48T/L89M by molecular dynamics simulations and free energy analyses

MD simulations, MM-PBSA, and SIE analyses were used to investigate the drug resistance mechanisms of two mutations G48T and L89M in HIV-1 protease toward four inhibitors.

Effective estimation of the inhibitor affinity of HIV-1 protease via a modified LIE approach

The inhibition of the Human Immunodeficiency Virus Type 1 Protease (HIV-1 PR) can prevent the synthesis of new viruses. Computer-aided drug design (CADD) would enhance the discovery of new therapies, through which the estimation of ligand-binding affinity is critical to predict the most efficient inhibitor. A time-consuming binding free energy method would reduce the usefulness of CADD. The modified linear interaction energy (LIE) approach emerges as an appropriate protocol that performs this task. In particular, the polar interaction free energy, which is obtained via numerically resolving the linear Poisson–Boltzmann equation, plays as an important role in driving the binding mechanism of the HIV-1 PR + inhibitor complex. The electrostatic interaction energy contributes to the attraction between two molecules, but the vdW interaction acts as a repulsive factor between the ligand and the HIV-1 PR. Moreover, the ligands were found to adopt a very strong hydrophobic interaction with the HIV-1 PR. Furthermore, the results obtained corroborate the high accuracy and precision of computational studies with a large correlation coefficient value R = 0.83 and a small RMSE δ_RMSE = 1.25 kcal mol⁻¹. This method is less time-consuming than the other end-point methods, such as the molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) and free energy perturbation (FEP) approaches. Overall, the modified LIE approach would provide ligand-binding affinity with HIV-1 PR accurately, precisely, and rapidly, resulting in a more efficient design of new inhibitors.

The inhibition of the Human Immunodeficiency Virus Type 1 Protease (HIV-1 PR) can prevent the synthesis of new viruses.

Recent Developments and Applications of the MMPBSA Method

The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach has been widely applied as an efficient and reliable free energy simulation method to model molecular recognition, such as for protein-ligand binding interactions. In this review, we focus on recent developments and applications of the MMPBSA method. The methodology review covers solvation terms, the entropy term, extensions to membrane proteins and high-speed screening, and new automation toolkits. Recent applications in various important biomedical and chemical fields are also reviewed. We conclude with a few future directions aimed at making MMPBSA a more robust and efficient method.

Compilation of Data and Modelling of Nanoparticle Interactions and Toxicity in the NanoPUZZLES Project

The particular properties of nanomaterials have led to their rapidly increasing use in diverse fields of application. However, safety assessment is not keeping pace and there are still gaps in the understanding of their hazards. Computational models predicting nanotoxicity, such as (quantitative) structure-activity relationships ((Q)SARs), can contribute to safety evaluation, in line with general efforts to apply alternative methods in chemical risk assessment. Their development is highly dependent on the availability of reliable and high quality experimental data, both regarding the compounds' properties as well as the measured toxic effects. In particular, "nano-QSARs" should take the nano-specific characteristics into account. The information compiled needs to be well organized, quality controlled and standardized. Integrating the data in an overarching, structured data collection aims to (a) organize the data in a way to support modelling, (b) make (meta)data necessary for modelling available, and (c) add value by making a comparison between data from different sources possible.Based on the available data, specific descriptors can be derived to parameterize the nanomaterial-specific structure and physico-chemical properties appropriately. Furthermore, the interactions between nanoparticles and biological systems as well as small molecules, which can lead to modifications of the structure of the active nanoparticles, need to be described and taken into account in the development of models to predict the biological activity and toxicity of nanoparticles. The EU NanoPUZZLES project was part of a global cooperative effort to advance data availability and modelling approaches supporting the characterization and evaluation of nanomaterials.

Role of R292K mutation in influenza H7N9 neuraminidase toward oseltamivir susceptibility: MD and MM/PB(GB)SA study

The H7N9 avian influenza virus is a novel re-assortment from at least four different strains of virus. Neuraminidase, which is a glycoprotein on the surface membrane, has been the target for drug treatment. However, some H7N9 strains that have been isolated from patient after drug treatment have a R292K mutation in neuraminidase. This substitution was found to facilitate drug resistance using protein- and virus- assays, in particular it gave a high resistance to the most commonly used drug, oseltamivir. The aim of this research is to understand the source of oseltamivir resistance using MD simulations and the MM/PB(GB)SA binding free energy approaches. Both methods can predict the reduced susceptibility of oseltamivir in good agreement to the IC ₅₀ binding energy, although MM/GBSA underestimates this prediction compared to the MM/PBSA calculation. Electrostatic interaction is the main contribution for oseltamivir binding in terms of both interaction and solvation. We found that the source of the drug resistance is a decrease in the binding interaction combined with the reduction of the dehydration penalty. The smaller K292 mutated residue has a larger binding pocket cavity compared to the wild-type resulting in the loss of drug carboxylate-K292 hydrogen bonding and an increased accessibility for water molecules around the K292 mutated residue. In addition, oseltamivir does not bind well to the R292K mutant complex as shown by the high degree of fluctuation in ligand RMSD during the simulation and the change in angular distribution of bulky side chain groups.

Discovery of HIV Type 1 Aspartic Protease Hit Compounds through Combined Computational Approaches

A combination of computational techniques and inhibition assay experiments was employed to identify hit compounds from commercial libraries with enhanced inhibitory potency against HIV type 1 aspartic protease (HIV PR). Extensive virtual screening with the aid of reliable pharmacophore models yielded five candidate protease inhibitors. Subsequent molecular dynamics and molecular mechanics Poisson-Boltzmann surface area free-energy calculations for the five ligand-HIV PR complexes suggested a high stability of the systems through hydrogen-bond interactions between the ligands and the protease's flaps (Ile50/50'), as well as interactions with residues of the active site (Asp25/25'/29/29'/30/30'). Binding-energy calculations for the three most promising compounds yielded values between -5 and -10 kcal mol(-1) and suggested that van der Waals interactions contribute most favorably to the total energy. The predicted binding-energy values were verified by in vitro inhibition assays, which showed promising results in the high nanomolar range. These results provide structural considerations that may guide further hit-to-lead optimization toward improved anti-HIV drugs.

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.

The Antiviral Activity of Approved and Novel Drugs against HIV-1 Mutations Evaluated under the Consideration of Dose-Response Curve Slope

Objectives

This study was designed to identify common HIV-1 mutation complexes affecting the slope of inhibition curve, and to propose a new parameter incorporating both the IC50 and the slope to evaluate phenotypic resistance.

Methods

Utilizing site-directed mutagenesis, we constructed 22 HIV-1 common mutation complexes. IC50 and slope of 10 representative approved drugs and a novel agent against these mutations were measured to determine the resistance phenotypes. The values of new parameter incorporating both the IC50 and the slope of the inhibition curve were calculated, and the correlations between parameters were assessed.

Results

Depending on the class of drug, there were intrinsic differences in how the resistance mutations affected the drug parameters. All of the mutations resulted in large increases in the IC50s of nucleoside reverse transcriptase inhibitors. The effects of the mutations on the slope were the most apparent when examining their effects on the inhibition of non-nucleoside reverse transcriptase inhibitors and protease inhibitors. For example, some mutations, such as V82A, had no effect on IC50, but reduced the slope. We proposed a new concept, termed IIP_atoxic, on the basis of IC50, slope and the maximum limiting concentrations of the drug. The IIP_atoxic values of 10 approved drugs and 1 novel agent were calculated, and were closely related to the IIP_max values (r > 0.95, p < 0.001).

Conclusions

This study confirms that resistance mutations cannot be accurately assessed by IC50 alone, because it tends to underestimate the degree of resistance. The slope parameter is of very importance in the measurement of drug resistance and the effect can be applied to more complex patterns of resistance. This is the most apparent when testing the effects of the mutations on protease inhibitors activity. We also propose a new index, IIP_atoxic, which incorporates both the IC50 and the slope. This new index could complement current IIP indices, thereby enabling predict the efficacy of pre-clinical drugs for which human pharmacokinetic is not available.