Evaluating the potency of HIV-1 protease drugs to combat resistance

Multi-Epitopic Peptide Vaccine Against Newcastle Disease Virus: Molecular Dynamics Simulation and Experimental Validation

BACKGROUND

Newcastle disease virus (NDV) is a highly contagious and economically devastating pathogen affecting poultry worldwide, leading to significant losses in the poultry industry. Despite existing vaccines, outbreaks continue to occur, highlighting the need for more effective vaccination strategies. Developing a multi-epitopic peptide vaccine offers a promising approach to enhance protection against NDV.

OBJECTIVES

Here, we aimed to design and evaluate a multi-epitopic vaccine against NDV using molecular dynamics (MD) simulation.

METHODOLOGY

We retrieved NDV sequences for the fusion (F) protein and hemagglutinin-neuraminidase (HN) protein. Subsequently, B-cell and T-cell epitopes were predicted. The top potential epitopes were utilized to design the vaccine construct, which was subsequently docked against chicken TLR4 and MHC1 receptors to assess the immunological response. The resulting docked complex underwent a 1 microsecond (1000 ns) MD simulation. For experimental evaluation, the vaccine's efficacy was assessed in mice and chickens using a controlled study design, where animals were randomly divided into groups receiving either a local ND vaccine or the peptide vaccine or a control treatment.

RESULTS

The 40 amino acid peptide vaccine demonstrated strong binding affinity and stability within the TLR4 and MHC1 receptor-peptide complexes. The root mean square deviation of peptide vaccine and TLR4 receptor showed rapid stabilization after an initial repositioning. The root mean square fluctuation revealed relatively low fluctuations (below 3 Å) for the TLR4 receptor, while the peptide exhibited higher fluctuations. The overall binding energy of the peptide vaccine with TLR4 and MHC1 receptors amounted to -15.7 kcal·mol-1 and -36.8 kcal·mol-1, respectively. For experimental evaluations in mice and chicken, the peptide vaccine was synthesized using services of GeneScript Biotech® (Singapore) PTE Limited. Experimental evaluations showed a significant immune response in both mice and chickens, with the vaccine eliciting robust antibody production, as evidenced by increasing HI titers over time. Statistical analysis was performed using an independent t-test with Type-II error to compare the groups, calculating the p-values to determine the significance of the immune response between different groups.

CONCLUSIONS

Multi-epitopic peptide vaccine has demonstrated a good immunological response in natural hosts.

Accelerated molecular dynamics study of the interaction mechanism between small molecule inhibitors and phosphoglycerate mutase 1

In 2020, cancer-related deaths reached 9.96 million globally, of which China accounted for 3 million, ranking first in the world. Phosphoglycerate mutase 1 (PGAM1) is a key metabolic enzyme in glycolysis, catalysing the conversion of 3-phosphoglycerate to 2-phosphoglycerate. Based on the excellent anticancer activity of PGMI-004A and HKB99, new small molecules with an anthraquinone core were synthesised to inhibit tumour growth. Developing small molecules with an anthraquinone core targeting PGAM1 may be an effective strategy for treating cancer. In this study, accelerated molecular dynamics (aMD) simulation, dynamic cross-correlation map (DCCM) calculation, principal component analysis (PCA) and free energy landscape (FEL) analysis were used to analyse conformational changes of PGAM1 caused by binding of inhibitors 8KX, 9HU and HKB. DCCM calculations and PCA showed that inhibitor binding significantly affected the kinetic behaviour of PGAM1 and conformational rearrangement of PGAM1. The binding ability and mechanism of 8KX, 9HU and HKB to PGAM1 were studied using the molecular mechanics generalised Born surface area (MM-GBSA) method. The results showed that compared with 8KX, the binding ability of 9HU and HKB to PGAM1 was enhanced by sulphonamide reversal and aminocarboxyl trifluoromethyl substitution. There were several hydrophobic interactions between inhibitors and PGAM1, providing significant contributions for inhibitor binding. Calculation of residue-based free energy decomposition revealed that F22, R90, Y92, L95, V112, W115, R116, V121, P123, P124, R191 and M206 were key residues of the PGAM1-inhibitor interaction and could be used as effective targets for designing drugs that inhibit the activity of PGAM1.

Pharmacophore-Assisted Covalent Docking Identifies a Potential Covalent Inhibitor for Drug-Resistant Genotype 3 Variants of Hepatitis C Viral NS3/4A Serine Protease

The emergence of drug-resistance-inducing mutations in Hepatitis C virus (HCV) coupled with genotypic heterogeneity has made targeting NS3/4A serine protease difficult. In this work, we investigated the mutagenic variations in the binding pocket of Genotype 3 (G3) HCV NS3/4A and evaluated ligands for efficacious inhibition. We report mutations at 14 positions within the ligand-binding residues of HCV NS3/4A, including H57R and S139P within the catalytic triad. We then modelled each mutational variant for pharmacophore-based virtual screening (PBVS) followed by covalent docking towards identifying a potential covalent inhibitor, i.e., cpd-217. The binding stability of cpd-217 was then supported by molecular dynamic simulation followed by MM/GBSA binding free energy calculation. The free energy decomposition analysis indicated that the resistant mutants alter the HCV NS3/4A-ligand interaction, resulting in unbalanced energy distribution within the binding site, leading to drug resistance. Cpd-217 was identified as interacting with all NS3/4A G3 variants with significant covalent docking scores. In conclusion, cpd-217 emerges as a potential inhibitor of HCV NS3/4A G3 variants that warrants further in vitro and in vivo studies. This study provides a theoretical foundation for drug design and development targeting HCV G3 NS3/4A.

FMO-guided design of darunavir analogs as HIV-1 protease inhibitors

The prevalence of HIV-1 infection continues to pose a significant global public health issue, highlighting the need for antiretroviral drugs that target viral proteins to reduce viral replication. One such target is HIV-1 protease (PR), responsible for cleaving viral polyproteins, leading to the maturation of viral proteins. While darunavir (DRV) is a potent HIV-1 PR inhibitor, drug resistance can arise due to mutations in HIV-1 PR. To address this issue, we developed a novel approach using the fragment molecular orbital (FMO) method and structure-based drug design to create DRV analogs. Using combinatorial programming, we generated novel analogs freely accessible via an on-the-cloud mode implemented in Google Colab, Combined Analog generator Tool (CAT). The designed analogs underwent cascade screening through molecular docking with HIV-1 PR wild-type and major mutations at the active site. Molecular dynamics (MD) simulations confirmed the assess ligand binding and susceptibility of screened designed analogs. Our findings indicate that the three designed analogs guided by FMO, 19-0-14-3, 19-8-10-0, and 19-8-14-3, are superior to DRV and have the potential to serve as efficient PR inhibitors. These findings demonstrate the effectiveness of our approach and its potential to be used in further studies for developing new antiretroviral drugs.

Free energy landscape and thermodynamics properties of novel mutations in PncA of pyrazinamide resistance isolates of Mycobacterium tuberculosis

Pyrazinamide (PZA) is one of the first-line antituberculosis therapy, active against non-replicating Mycobacterium tuberculosis (Mtb). The conversion of PZA into pyrazinoic acid (POA), the active form, required the activity of pncA gene product pyrazinamidase (PZase) activity. Mutations occurred in pncA are the primary cause behind the PZA resistance. However, the resistance mechanism is important to explore using high throughput computational approaches. Here we aimed to explore the mechanism of PZA resistance behind novel P62T, L120R, and V130M mutations in PZase using 200 ns molecular dynamics (MD) simulations. MD simulations were performed to observe the structural changes for these three mutants (MTs) compared to the wild types (WT). Root means square fluctuation, the radius of gyration, free energy landscape, root means square deviation, dynamic cross-correlation motion, and pocket volume were found in variation between WT and MTs, revealing the effects of P62T, L120R, and V130M. The free energy conformational landscape of MTs differs significantly from the WT system, lowering the binding of PZA. The geometric shape complementarity of the drug (PZA) and target protein (PZase) further confirmed that P62T, L120R, and V130M affect the protein structure. These effects on PZase may cause vulnerability to convert PZA into POA.Communicated by Ramaswamy H. Sarma.

Engineering human JMJD2A tudor domains for an improved understanding of histone peptide recognition

JMJD2A is a histone lysine demethylase which recognizes and demethylates H3K9me3 and H3K36me3 residues and is overexpressed in various cancers. It utilizes a tandem tudor domain to facilitate its own recruitment to histone sites, recognizing various di- and tri-methyl lysine residues with moderate affinity. In this study, we successfully engineered the tudor domain of JMJD2A to specifically bind to H4K20me3 with a 20-fold increase of affinity and improved selectivity. To reveal the molecular basis, we performed molecular dynamics and free energy decomposition analysis on the human JMJD2A tandem tudor domains bound to H4K20me2, H4K20me3, and H3K23me3 peptides to uncover the residues and conformational changes important for the enhanced binding affinity and selectivity toward H4K20me2/3. These analyses revealed new insights into understanding chromatin reader domains recognizing histone modifications and improving binding affinity and selectivity of these domains. Furthermore, we showed that the tight binding of JMJD2A to H4K20me2/3 is not sufficient to improve the efficiency of CRISPR-CAS9 mediated homology directed repair (HDR), suggesting a complicated relationship between JMJD2A and the DNA damage response beyond binding affinity toward the H4K20me2/3 mark.

Decoding drug resistant mechanism of V32I, I50V and I84V mutations of HIV-1 protease on amprenavir binding by using molecular dynamics simulations and MM-GBSA calculations

Mutations V32I, I50V and I84V in the HIV-1 protease (PR) induce drug resistance towards drug amprenavir (APV). Multiple short molecular dynamics (MSMD) simulations and molecular mechanics generalized Born surface area (MM-GBSA) method were utilized to investigate drug-resistant mechanism of V32I, I50V and I84V towards APV. Dynamic information arising from MSMD simulations suggest that V32I, I50V and I84V highly affect structural flexibility, motion modes and conformational behaviours of two flaps in the PR. Binding free energies calculated by MM-GBSA method suggest that the decrease in binding enthalpy and the increase in binding entropy induced by mutations V32I, I50V and I84V are responsible for drug resistance of the mutated PRs on APV. The energetic contributions of separate residues on binding of APV to the PR show that V32I, I50V and I84V highly disturb the interactions of two flaps with APV and mostly drive the decrease in binding ability of APV to the PR. Thus, the conformational changes of two flaps in the PR caused by V32I, I50V and I84V play key roles in drug resistance of three mutated PR towards APV. This study can provide useful dynamics information for the design of potent inhibitors relieving drug resistance.

Systematic analysis and molecular profiling of EGFR allosteric inhibitor cross-reactivity across the proto-oncogenic ErbB family kinases by integrating dynamics simulation, energetics calculation and biochemical assay

Human ErbB family of proteins contains four receptor tyrosine kinases (EGFR, Her2, Her3 and Her4) and has been established as a group of attractive druggable targets against diverse cancers. Over the past decades, a variety of ATP-competitive inhibitors have been discovered to target the orthosteric site of EGFR, which, however, would eventually develop acquired drug resistance due to the missense mutations T790M/C797S occurring in orthosteric site. In recent years, a number of forth-generation inhibitors have been successfully designed to overcome the T790M/C797S-induced drug resistance by targeting EGFR allosteric site instead of orthosteric site. Considering that the four proto-oncogenic ErbB kinases share a high conservation in sequence, structure and function, we herein attempted to investigate the binding potency and cross-reactivity of cognate EGFR allosteric inhibitors over noncognate Her2, Her3 and Her4 kinases--they are closely related to gynecological tumors such as ovarian cancer but no allosteric inhibitors have been reported specifically for them to date. A systematic affinity profile of 12 allosteric inhibitors and 4 orthosteric inhibitors to the 4 ErbB kinases was created by integrating dynamics simulations, energetics calculations and biochemical assays, which was then used to derive a systematic inhibitor selectivity profile for EGFR over other three kinases. It is found that allosteric and orthosteric inhibitors exhibit moderate and modest cross-reactivity across the ErbB family, respectively, but the former generally has a higher binding potency than the latter due to the additional energy cost used for inducing kinase conformational change. Moreover, most allosteric inhibitors can be sensitized by Her2 T798M gatekeeper mutation, a counterpart of EGFR T790M gatekeeper mutation that has been previously reported to cause generic drug resistance for orthosteric inhibitors.

Deciphering binding mechanism of inhibitors to SARS-COV-2 main protease through multiple replica accelerated molecular dynamics simulations and free energy landscapes

The pneumonia outbreak caused by the SARS-CoV-2 virus poses a serious threat to human health and the world economy. Development of safe and highly effective antiviral drugs is of great...

Decoding molecular mechanism underlying binding of drugs to HIV-1 protease with molecular dynamics simulations and MM-GBSA calculations

HIV-1 protease (PR) is thought to be efficient targets of anti-AIDS drug design. Molecular dynamics (MD) simulations and multiple post-processing analysis technologies were applied to decipher molecular mechanism underlying binding of three drugs Lopinavir (LPV), Nelfinavir (NFV) and Atazanavir (ATV) to the PR. Binding free energies calculated by molecular mechanics generalized Born surface area (MM-GBSA) suggest that compensation between binding enthalpy and entropy plays a vital role in binding of drugs to PR. Dynamics analyses show that binding of LPV, NFV and ATV highly affects structural flexibility, motion modes and dynamics behaviour of the PR, especially for two flaps. Computational alanine scanning and interaction network analysis verify that although three drugs have structural difference, they share similar binding modes to the PR and common interaction clusters with the PR. The current findings also confirm that residues located interaction clusters, such as Asp25/Asp25', Gly27/Gly27', Ala28/Ala28', Asp29, Ile47/Ile47', Gly49/Gly49', Ile50/Ile50', Val82/Val82' and Ile84/Ile84, can be used as efficient targets of clinically available inhibitors towards the PR.

Insights into effect of the Asp25/Asp25' protonation states on binding of inhibitors Amprenavir and MKP97 to HIV-1 protease using molecular dynamics simulations and MM-GBSA calculations

The protonation states of two aspartic acids in the catalytic strands of HIV-1 protease (PR) remarkably affect bindings of inhibitors to PR. It is requisite for the design of potent inhibitors towards PR to investigate the influences of Asp25/Asp25' protonated states on dynamics behaviour of PR and binding mechanism of inhibitors to PR. In this work, molecular dynamics (MD) simulations, MM-GBSA method and principal component (PC) analysis were coupled to explore the effect of Asp25/Asp25' protonation states on conformational changes of PR and bindings of Amprenavir and MKP97 to PR. The results show that the Asp25/Asp25' protonation states exert different impacts on structural fluctuations, flexibility and motion modes of PR. Dynamics analysis verifies that Asp25/Asp25' protonated states highly affect conformational dynamics of two flaps in PR. The binding free energy calculations results suggest that the Asp25/Asp25' protonated states obviously strengthen bindings of inhibitors to PR compared to the non-protonation state. Calculations of residue-based free energy decomposition indicate that the Asp25/Asp25' protonation not only disturbs the interaction network of inhibitors with PR but also stabilizes bindings of inhibitors to PR by cancelling the electrostatic repulsive interaction. Therefore, special attentions should be paid to the Asp25/Asp25' protonation in the design of potent inhibitors towards PR.

Binding Selectivity of Inhibitors toward Bromodomains BAZ2A and BAZ2B Uncovered by Multiple Short Molecular Dynamics Simulations and MM-GBSA Calculations

Two Bromodomain-Containing proteins BAZ2A and BAZ2B are responsible for remodeling chromatin and regulating noncoding RNAs. As for our current studies, integration of multiple short molecular dynamics simulations (MSMDSs) with molecular mechanics generalized Born surface area (MM-GBSA) method is adopted for insights into binding selectivity of three small molecules D8Q, D9T and UO1 to BAZ2A against BAZ2B. The calculations of MM-GBSA unveil that selectivity of inhibitors toward BAZ2A and BAZ2B highly depends on the enthalpy changes and the details uncover that D8Q has better selectivity toward BAZ2A than BAZ2B, D9T more favorably bind to BAZ2B than BAZ2A, and UO1 does not show obvious selectivity toward these two proteins. The analysis of interaction network between residues and inhibitors indicates that seven residues are mainly responsible for the selectivity of D8Q, six residues for D9T and four residues provide significant contributions to associations of UO1 with two proteins. Moreover the analysis of interaction network not only reveals warm spots of inhibitor bindings to BAZ2A and BAZ2B but also unveils that common residue pairs, including (W1816, W1887), (P1817, P1888), (F1818, F1889), (V1822, V1893), (N1823, N1894),(L1826, L1897), (V1827, V1898), (F1872, F1943), (N1873, N1944) and (V1879, I1950) belonging to (BAZ2A, BAZ2B), induce mainly binding differences of inhibitors to BAZ2A and BAZ2B. Hence, insights from our current studies offer useful dynamics information relating with conformational alterations and structure-affinity relationship at atomistic levels for novel therapeutic strategies toward BAZ2A and BAZ2B.

Deciphering Complex Mechanisms of Resistance and Loss of Potency through Coupled Molecular Dynamics and Machine Learning

Drug resistance threatens many critical therapeutics through mutations in the drug target. The molecular mechanisms by which combinations of mutations, especially those remote from the active site, alter drug binding to confer resistance are poorly understood and thus difficult to counteract. A machine learning strategy was developed that coupled parallel molecular dynamics simulations with experimental potency to identify specific conserved mechanisms underlying resistance. Physical features were extracted from the simulations, analyzed, and integrated into one consistent and interpretable elastic network model. To rigorously test this strategy, HIV-1 protease variants with diverse mutations were used, with potencies ranging from picomolar to micromolar to the drug darunavir. Feature reduction resulted in a model with four specific features that predicts for both the training and test sets inhibitor binding free energy within 1 kcal/mol of the experimental value over this entire range of potency. These predictive features are physically interpretable, as they vary specifically with affinity and diagonally transverse across the protease homodimer. This physics-based strategy of parallel molecular dynamics and machine learning captures mechanisms by which complex combinations of mutations confer resistance and identify critical features that serve as bellwethers of affinity, which will be critical in future drug design.

Mechanistic analysis of A46V, H57Y, and D129N in pyrazinamidase associated with pyrazinamide resistance

Pyrazinamide (PZA) is a component of first-line drugs, active against latent Mycobacterium tuberculosis (MTB) isolates. The prodrug is activated into the active form, pyrazinoic acid (POA) via pncA gene-encoded pyrazinamidase (PZase). Mutations in pncA have been reported, most commonly responsible for PZA-resistance in more than 70% of the resistant cases. In our previous study, we detected many mutations in PZase among PZA-resistance MTB isolates including A46V, H71Y, and D129N. The current study was aimed to investigate the molecular mechanism of PZA-resistance behind mutants (MTs) A46V, H71Y, and D129N in comparison with the wild type (WT) through molecular dynamic (MD) simulation. MTB positive samples were subjected to PZA drug susceptibility testing (DST) against critical concentration (100ug/ml). The resistant samples were subjected to pncA sequencing. Thirty-six various mutations have been observed in the coding region of pncA of PZA-resistant isolates (GenBank accession No. MH461111) including A46V, H71Y, and D129N. The post-simulation analysis revealed a significant variation in MTs structural dynamics as compared to the WT. Root means square deviations (RMSD) and Root means square fluctuation (RMSF) has been found in variation between WT and MTs. Folding effect and pocket volume were altered in MTs when compared with WT. Geometric matching supports the effect of mutation A46V, H71Y, and D129N on PZase structure that may have an insight effect on PZase dynamics, making them vulnerable to convert pro-PZA into active form, POA. In conclusion, the current analyses will provide useful information behind PZA-resistance for better management of drug-resistant TB.

Pyrazinamide resistance of novel mutations in pncA and their dynamic behavior

Pyrazinamide (PZA) is one of the essential anti-mycobacterium drugs, active against non-replicating Mycobacterium tuberculosis (MTB) isolates. PZA is converted into its active state, called pyrazinoic acid (POA), by action of pncA encoding pyrazinamidase (PZase). In the majority of PZA-resistance isolates, pncA harbored mutations in the coding region. In our recent report, we detected a number of novel variants in PZA-resistance (PZA^R) MTB isolates, whose resistance mechanisms were yet to be determined. Here we performed several analyses to unveil the PZA^R mechanism of R123P, T76P, G150A, and H71R mutants (MTs) through molecular dynamics (MD) simulations. In brief, culture positive MTB isolates were subjected to PZA susceptibility tests using the WHO recommended concentration of PZA (100 μg ml⁻¹). The PZA^R samples were screened for mutations in pncA along sensitive isolates through polymerase chain reactions and sequencing. A large number of variants (GeneBank accession no. MH461111), including R123P, T76P, G150A, and H71R, have been spotted in more than 70% of isolates. However, the mechanism of PZA^R for mutants (MTs) R123P, T76P, G150A, and H71R was unknown. For the MTs and native PZase structures (WT), thermodynamic properties were compared using molecular dynamics simulations for 100 ns. The MTs structural activity was compared to the WT. Folding effect and pocket volume variations have been detected when comparing between WT and MTs. Geometric matching further confirmed the effect of R123P, T76P, G150A, and H71R mutations on PZase dynamics, making them vulnerable for activating the pro-drug into POA. This study offers a better understanding for management of PZA^R TB. The results may be used as alternative diagnostic tools to infer PZA resistance at a structural dynamics level.

We performed several analyses to unveil the pyrazinamide-resistance mechanism of R123P, T76P, G150A, and H71R mutants through molecular dynamics simulations.

The recent application of 3D-QSAR and docking studies to novel HIV-protease inhibitor drug discovery

INTRODUCTION

Despite the availability of FDA approved inhibitors of HIV protease, numerous efforts are still ongoing to achieve 'near-perfect' drugs devoid of characteristic adverse side effects, toxicities, and mutational resistance. While experimental methods have been plagued with huge consumption of time and resources, there has been an incessant shift towards the use of computational simulations in HIV protease inhibitor drug discovery.

AREAS COVERED

Herein, the authors review the numerous applications of 3D-QSAR modeling methods over recent years relative to the design of new HIV protease inhibitors from a series of experimentally derived compounds. Also, the augmentative contributions of molecular docking are discussed.

EXPERT OPINION

Efforts to optimize 3D QSAR and molecular docking for HIV-1 drug discovery are ongoing, which could further incorporate inhibitor motions at the active site using molecular dynamics parameters. Also, highly predictive machine learning algorithms such as random forest, K-means, decision trees, linear regression, hierarchical clustering, and Bayesian classifiers could be employed.

Use of Molecular Dynamics Simulations in Structure-Based Drug Discovery

BACKGROUND

Traditional drug discovery is a lengthy process which involves a huge amount of resources. Modern-day drug discovers various multidisciplinary approaches amongst which, computational ligand and structure-based drug designing methods contribute significantly. Structure-based drug designing techniques require the knowledge of structural information of drug target and drug-target complexes. Proper understanding of drug-target binding requires the flexibility of both ligand and receptor to be incorporated. Molecular docking refers to the static picture of the drug-target complex(es). Molecular dynamics, on the other hand, introduces flexibility to understand the drug binding process.

OBJECTIVE

The aim of the present study is to provide a systematic review on the usage of molecular dynamics simulations to aid the process of structure-based drug design.

METHOD

This review discussed findings from various research articles and review papers on the use of molecular dynamics in drug discovery. All efforts highlight the practical grounds for which molecular dynamics simulations are used in drug designing program. In summary, various aspects of the use of molecular dynamics simulations that underline the basis of studying drug-target complexes were thoroughly explained.

RESULTS

This review is the result of reviewing more than a hundred papers. It summarizes various problems that use molecular dynamics simulations.

CONCLUSION

The findings of this review highlight how molecular dynamics simulations have been successfully implemented to study the structure-function details of specific drug-target complexes. It also identifies the key areas such as stability of drug-target complexes, ligand binding kinetics and identification of allosteric sites which have been elucidated using molecular dynamics simulations.

Gibbs Free Energy Calculation of Mutation in PncA and RpsA Associated With Pyrazinamide Resistance

A central approach for better understanding the forces involved in maintaining protein structures is to investigate the protein folding and thermodynamic properties. The effect of the folding process is often disturbed in mutated states. To explore the dynamic properties behind mutations, molecular dynamic (MD) simulations have been widely performed, especially in unveiling the mechanism of drug failure behind mutation. When comparing wild type (WT) and mutants (MTs), the structural changes along with solvation free energy (SFE), and Gibbs free energy (GFE) are calculated after the MD simulation, to measure the effect of mutations on protein structure. Pyrazinamide (PZA) is one of the first-line drugs, effective against latent Mycobacterium tuberculosis isolates, affecting the global TB control program 2030. Resistance to this drug emerges due to mutations in pncA and rpsA genes, encoding pyrazinamidase (PZase) and ribosomal protein S1 (RpsA) respectively. The question of how the GFE may be a measure of PZase and RpsA stabilities, has been addressed in the current review. The GFE and SFE of MTs have been compared with WT, which were already found to be PZA-resistant. WT structures attained a more stable state in comparison with MTs. The physiological effect of a mutation in PZase and RpsA may be due to the difference in energies. This difference between WT and MTs, depicted through GFE plots, might be useful in predicting the stability and PZA-resistance behind mutation. This study provides useful information for better management of drug resistance, to control the global TB problem.

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.

Molecular mechanism of inhibitor bindings to bromodomain-containing protein 9 explored based on molecular dynamics simulations and calculations of binding free energies

Recently, bromodomain-containing protein 9 (BRD9) has been a prospective therapeutic target for anticancer drug design. Molecular dynamics (MD) simulations combined with molecular mechanics generalized Born surface area (MM-GBSA) method were adopted to explore binding modes of three inhibitors (5SW, 5U2, and 5U6) to BRD9 and identify the hot spot of the inhibitor-BRD9 binding. The results indicate that the inhibitor 5SW has the strongest binding ability to BRD9 among the current three inhibitors. Furthermore, the rank of the binding free energies predicted by MM-GBSA approach agrees with that determined by the experimental values. In addition, inhibitor-residue interactions were computed by using residue-based free-energy decomposition method and the results suggest that residue His42 produces the CH-H interactions, residues Asn100, Ile53 and Val49 produce the CH-[Formula: see text] interactions with three inhibitors and Tyr106, Phe45 and Phe44 generate the π-π interactions with inhibitors. Notably, the residue Asn140 forms hydrogen bonding interactions with three inhibitors. This research is expected to provide useful molecular basis and dynamics information at atomic levels for the design of potent inhibitors inhibiting the activity of BRD9.

Design and development of high affinity dual anticancer peptide-inhibitors against p53-MDM2/X interaction

AIMS

Inhibition of P53-MDM2/X interaction is known as an effective cancer therapy strategy. In this regard, pDI peptide was introduced previously with the potential of targeting MDM2. In this research, the large-scale peptide mutation screening was used to achieve the best sequence of pDI with the highest affinity for inhibition activity against MDM2/X.

MAIN METHODS

Three mutant peptides of pDI as dual inhibitor peptides including single mutations of pDIm/4W, pDIm/11M and double mutations of pDIdm/4W11M were presented with the high affinities to inhibit both MDM2/X. The selected mutants were then evaluated comprehensively to confirm their ability as potent MDM2/X inhibitors, using a theoretical simulation approach.

KEY FINDINGS

MD simulations analyses confirmed their dual inhibition potential against both MDM2/X interactions with p53 protein. The developed pDIm and mainly pDIdm peptides showed stable conformations over the simulation time with conserved secondary structure and effective interaction with MDM2/X by physical binding such as hydrogen bonding. Besides, umbrella sampling free energy calculation indicated higher binding energy, ΔG_binding, of pDIm-MDM2/X and pDIdm-MDM2/X compared to pDI-MDM2/X.

SIGNIFICANCE

The optimized and improved mutant pDI, pDIdm, with more effective ΔG_binding values of -30 and -25 kcal/mol to MDMX and MDM2, respectively, is recommended as a promising anticancer agent and suitable candidate for experimental evaluations.

Molecular mechanism with regard to the binding selectivity of inhibitors toward FABP5 and FABP7 explored by multiple short molecular dynamics simulations and free energy analyses

Recently, fatty acid binding proteins 5 and 7 (FABP5 and FABP7) have been regarded as the prospective targets for clinically treating multiple diseases related to FABPs.

Exploration of the effects of sequence variations between HIV-1 and HIV-2 proteases on their three-dimensional structures

HIV protease inhibitors (PIs) approved by the FDA (US Food and Drug Administration) are a major class of antiretroviral. HIV-2 protease (PR2) is naturally resistant to most of them as PIs were designed for HIV-1 protease (PR1). In this study, we explored the impact of amino-acid substitutions between PR1 and PR2 on the structure of protease (PR) by comparing the structural variability of 13 regions using 24 PR1 and PR2 structures complexed with diverse ligands. Our analyses confirmed structural rigidity of the catalytic region and highlighted the important role of three regions in the conservation of the catalytic region conformation. Surprisingly, we showed that the flap region, corresponding to a flexible region, exhibits similar conformations in PR1 and PR2. Furthermore, we identified regions exhibiting different conformations in PR1 and PR2, which could be explained by the intrinsic flexibility of these regions, by crystal packing, or by PR1 and PR2 substitutions. Some substitutions induce structural changes in the R2 and R4 regions that could have an impact on the properties of PI-binding site and could thus modify PI binding mode. Substitutions involved in structural changes in the elbow region could alter the flexibility of the PR2 flap regions relative to PR1, and thus play a role in the transition from the semi-open form to the closed form, and have an impact on ligand binding. These results improve the understanding of the impact of sequence variations between PR1 and PR2 on the natural resistance of HIV-2 to commercially available PIs.Communicated by Ramaswamy H. Sarma.

Structural Dynamics Behind Clinical Mutants of PncA-Asp12Ala, Pro54Leu, and His57Pro of Mycobacterium tuberculosis Associated With Pyrazinamide Resistance

Pyrazinamide (PZA) is one of the main FDA approved drugs to be used as the first line of defense against Mycobacterium Tuberculosis (MTB). It is activated into pyrazinoic acid (POA) via MTB's pncA gene-encoded pyrazinamidase (PZase). Mutations are most commonly responsible for PZA-resistance in nearly 70% of the resistant samples. In the present work, MTB positive samples were chosen for PZA drug susceptibility testing (DST) against critical concentration (100 ug/ml) of PZA. The resistant samples were subjected to pncA sequencing. As a result, 36 various mutations have been observed in the PZA resistant samples, uploaded to the NCBI (GeneBank accession no. MH461111). Here we report the mechanism of PZA resistance behind the three mutants (MTs), Asp12Ala, Pro54Leu, and His57Pro in comparison with the wild type (WT) through molecular dynamics simulation to unveil how these mutations affect the overall conformational stability. The post-simulation analyses revealed notable deviations as compared to the WT structure. Molecular docking studies of PZA with MTs and WT, pocket volume inspection and overall shape complementarity analysis confirmed the deleterious nature of these mutations and gave an insight into the mechanism behind PZA-resistance. These analyses provide vital information regarding MTB drug resistance and could be extremely useful in therapy management and overcoming its global burden.

Revealing binding selectivity of ligands toward murine double minute 2 and murine double minute X based on molecular dynamics simulations and binding free energy calculations

It is well known that the interactions of p53 with murine double minute 2 and murine double minute X, namely MDM2 and MDMX, have been significant targets of efficient anti-cancer drug design. In this study, molecular dynamics (MD) simulations, principal component (PC) analysis and binding free energy calculations are combined to recognize binding selectivity of three ligands to MDM2 and MDMX. The binding free energies were estimated by using molecular mechanics generalized Born surface area (MM-GBSA) method and the obtained results display that the increase in the binding enthalpy of three ligands to MDM2 relative to MDMX mainly drives the binding selectivity of them toward MDM2 and MDMX. The information obtained from PC analysis shows that the associations of ligands exert important impacts on internal dynamics of MDM2 and MDMX. Meanwhile, the calculations of residue-based free energy decomposition not only identify the hot interaction spots of ligands with MDM2 and MDMX, but also show the residues (L54, M53), (Y67, Y66), (V93, V92), (H96, P95), (I99, I98) and (Y100, Y99) in (MDM2, MDMX) are responsible for most contributions to the binding selectivity of three ligands toward MDM2 and MDMX. It is believed that this work can provide useful information for design of highly selective and dual inhibitors targeting MDM2 and MDMX.Communicated by Ramaswamy H. Sarma.

Structural dynamics behind variants in pyrazinamidase and pyrazinamide resistance

Pyrazinamide (PZA) is an important component of first-line anti-tuberculosis (anti-TB) drugs. The anti-TB agent is activated into an active form, pyrazinoic acid (POA), by Mycobacterium tuberculosis (MTB) pncA gene encoding pyrazinamidase (PZase). The major cause of PZA-resistance has been associated with mutations in the pncA gene. We have detected several novel mutations including V131F, Q141P, R154T, A170P, and V180F (GeneBank Accession No. MH461111) in the pncA gene of PZA-resistant isolates during PZA drug susceptibility testing followed by pncA gene sequencing. Here, we investigated molecular mechanism of PZA-resistance by comparing the results of experimental and molecular dynamics. The mutants (MTs) and wild type (WT) PZase structures in apo and complex with PZA were subjected to molecular dynamic simulations (MD) at the 40 ns. Multiple factors, including root mean square deviations (RMSD), binding pocket, total energy, dynamic cross correlation, and root mean square fluctuations (RMSF) of MTs and WT were compared. The MTs attained a high deviation and fluctuation compared to WT. Binding pocket volumes of the MTs, were found, lower than the WT, and the docking scores were high than WT while shape complementarity scores were lower than that of the WT. Residual motion in MTs are seemed to be dominant in anti-correlated motion. Mutations at locations, V131F, Q141P, R154T, A170P, and V180F, might be involved in the structural changes, possibly affecting the catalytic property of PZase to convert PZA into POA. Our study provides useful information that will enhance the understanding for better management of TB. AbbreviationsDSTdrug susceptibility testingΔelecelectrostatic energyLJLowenstein-Jensen mediumMGITmycobacterium growth indicator tubesMTsmutantsMDmolecular dynamic simulationsMTBMycobacterium tuberculosisNALC-NaOHN-acetyl-l-cysteine-sodium hydroxideNIHNational Institutes of HealthNPTamount of substance (N), pressure (P) temperature (T)NVTmoles (N), volume (V) temperature (T)PZasepyrazinamidaseΔpspolar solvation energyPTRLProvincial Tuberculosis Reference LaboratoryRMSDroot mean square deviationsRMSFroot mean square fluctuationsΔSASAsolvent accessible surface area energyTBtuberculosisGTotaltotal binding free energyΔvdWVan der Waals energyWTwild typeCommunicated by Ramaswamy H. Sarma.

Structural and free energy landscape of novel mutations in ribosomal protein S1 (rpsA) associated with pyrazinamide resistance

Resistance to key first-line drugs is a major hurdle to achieve the global end tuberculosis (TB) targets. A prodrug, pyrazinamide (PZA) is the only drug, effective in latent TB, recommended in drug resistance and susceptible Mycobacterium tuberculosis (MTB) isolates. The prodrug conversion into active form, pyrazinoic acid (POA), required the activity of pncA gene encoded pyrazinamidase (PZase). Although pncA mutations have been commonly associated with PZA resistance but a small number of resistance cases have been associated with mutationss in RpsA protein. Here in this study a total of 69 PZA resistance isolates have been sequenced for pncA mutations. However, samples that were found PZA resistant but pncA wild type (pncAWT), have been sequenced for rpsA and panD genes mutation. We repeated a drug susceptibility testing according to the WHO guidelines on 18 pncAWT MTB isolates. The rpsA and panD genes were sequenced. Out of total 69 PZA resistant isolates, 51 harbored 36 mutations in pncA gene (GeneBank Accession No. MH46111) while, fifteen different mutations including seven novel, were detected in the fourth S1 domain of RpsA known as C-terminal (MtRpsACTD) end. We did not detect any mutations in panD gene. Among the rpsA mutations, we investigated the molecular mechanism of resistance behind mutations, D342N, D343N, A344P, and I351F, present in the MtRpsACTD through molecular dynamic simulations (MD). WT showed a good drug binding affinity as compared to mutants (MTs), D342N, D343N, A344P, and I351F. Binding pocket volume, stability, and fluctuations have been altered whereas the total energy, protein folding, and geometric shape analysis further explored a significant variation between WT and MTs. In conclusion, mutations in MtRpsACTD might be involved to alter the RpsA activity, resulting in drug resistance. Such molecular mechanism behind resistance may provide a better insight into the resistance mechanism to achieve the global TB control targets.

Importance of Incorporating Protein Flexibility in Molecule Modeling: A Theoretical Study on Type I1/2 NIK Inhibitors

NF-κB inducing kinase (NIK), which is considered as the central component of the non-canonical NF-κB pathway, has been proved to be an important target for the regulation of the immune system. In the past few years, NIK inhibitors with various scaffolds have been successively reported, among which type I^1/2 inhibitors that can not only bind in the ATP-binding pocket at the DFG-in state but also extend into an additional back pocket, make up the largest proportion of the NIK inhibitors, and are worthy of more attention. In this study, an integration protocol that combines molecule docking, MD simulations, ensemble docking, MM/GB(PB)SA binding free energy calculations, and decomposition was employed to understand the binding mechanism of 21 tricyclic type I^1/2 NIK inhibitors. It is found that the docking accuracy is largely dependent on the selection of docking protocols as well as the crystal structures. The predictions given by the ensemble docking based on multiple receptor conformations (MRCs) and the MM/GB(PB)SA calculations based on MD simulations showed higher linear correlations with the experimental data than those given by conventional rigid receptor docking (RRD) methods (Glide, GOLD, and Autodock Vina), highlighting the importance of incorporating protein flexibility in predicting protein–ligand interactions. Further analysis based on MM/GBSA demonstrates that the hydrophobic interactions play the most essential role in the ligand binding to NIK, and the polar interactions also make an important contribution to the NIK-ligand recognition. A deeper comparison of several pairs of representative derivatives reveals that the hydrophobic interactions are vitally important in the structural optimization of analogs as well. Besides, the H-bond interactions with some key residues and the large desolvation effect in the back pocket devote to the affinity distinction. It is expected that our study could provide valuable insights into the design of novel and potent type I^1/2 NIK inhibitors.

AIMMS suite: a web server dedicated for prediction of drug resistance on protein mutation

Drug resistance is one of the most intractable issues for successful treatment in current clinical practice. Although many mutations contributing to drug resistance have been identified, the relationship between the mutations and the related pharmacological profile of drug candidates has yet to be fully elucidated, which is valuable both for the molecular dissection of drug resistance mechanisms and for suggestion of promising treatment strategies to counter resistant. Hence, effective prediction approach for estimating the sensitivity of mutations to agents is a new opportunity that counters drug resistance and creates a high interest in pharmaceutical research. However, this task is always hampered by limited known resistance training samples and accurately estimation of binding affinity. Upon this challenge, we successfully developed Auto In Silico Macromolecular Mutation Scanning (AIMMS), a web server for computer-aided de novo drug resistance prediction for any ligand-protein systems. AIMMS can qualitatively estimate the free energy consequences of any mutations through a fast mutagenesis scanning calculation based on a single molecular dynamics trajectory, which is differentiated with other web services by a statistical learning system. AIMMS suite is available at http://chemyang.ccnu.edu.cn/ccb/server/AIMMS/.

The impact of interior dielectric constant and entropic change on HIV-1 complex binding free energy prediction

At present, the calculated binding free energy obtained using the molecular mechanics/Poisson-Boltzmann (Generalized-Born) surface area (MM/PB(GB)SA) method is overestimated due to the lack of knowledge of suitable interior dielectric constants in the simulation on the interaction of Human Immunodeficiency Virus (HIV-1) protease systems with inhibitors. Therefore, the impact of different values of the interior dielectric constant and the entropic contribution when using the MM/PB(GB)SA method to calculate the binding free energy was systemically evaluated. Our results show that the use of higher interior dielectric constants (1.4-2.0) can clearly improve the predictive accuracy of the MM/PBSA and MM/GBSA methods, and computational errors are significantly reduced by including the effects of electronic polarization and using a new highly efficient interaction entropy (IE) method to calculate the entropic contribution. The suitable range for the interior dielectric constant is 1.4-1.6 for the MM/PBSA method; within this range, the correlation coefficient fluctuates around 0.84, and the mean absolute error fluctuates around 2 kcal/mol. Similarly, an interior dielectric constant of 1.8-2.0 produces a correlation coefficient of approximately 0.76 when using the MM/GBSA method. In addition, the entropic contribution of each individual residue was further calculated using the IE method to predict hot-spot residues, and the detailed binding mechanisms underlying the interactions of the HIV-1 protease, its inhibitors, and bridging water molecules were investigated. In this study, the use of a higher interior dielectric constant and the IE method can improve the calculation accuracy of the HIV-1 system.

Exploring molecular mechanism of allosteric inhibitor to relieve drug resistance of multiple mutations in HIV-1 protease by enhanced conformational sampling

Recently, allosteric regulations of HIV-1 protease (PR) are suggested as a promising approach to relieve drug resistance of mutations toward inhibitors targeting the active site of PR. Replica-exchange molecular dynamics (REMD) simulations and normal mode analysis (NMA) are integrated to enhance conformational sampling of PR. Molecular mechanics generalized Born surface area (MM-GBSA) method was applied to calculate binding free energies of three inhibitors APV, DRV, and NIT to the wild-type (WT) and multidrug resistance (MDR) PRs. The results suggest that binding free energies of APV and DRV are decreased in the MDR PR relative to the WT PR, suggesting drug resistance of mutations on these two inhibitors. However, the binding ability of the allosteric inhibitor NIT is not impaired in the MDR PR. In addition, internal dynamics analysis based on REMD simulations proves that mutations hardly produce obvious effect on the conformation of the MDR PR in comparison to the WT PR. Scanning of hydrophobic contacts and hydrogen bond contacts of inhibitors with residues of PRs on the concatenated trajectories of REMD demonstrates that mutations change the symmetric interaction networks of APV and DRV with PR, but do not generate obvious influence on the asymmetric interaction network of NIT with PR. In summary, allosteric inhibitor NIT can adapt the MDR PR better than those inhibitors toward the active site of PR, thus allosteric inhibitors of PR may be a possible channel to overcome drug resistance of PR.

Dynamics revelation of conformational changes and binding modes of heat shock protein 90 induced by inhibitor associations

Heat shock protein 90 (Hsp90) has been an attractive target of potential drug design for antitumor treatment. The current work integrates molecular dynamics (MD) simulations, calculations of binding free energy, and principal component (PC) analysis with scanning of inhibitor-residue interaction to probe the binding modes of inhibitors YK9, YKJ and YKI to Hsp90 and identify the hot spot of the inhibitor-Hsp90 binding. The results suggest that the introductions of two groups G1 and G2 into YKJ and YKI strengthen the binding ability of YKJ and YKI to Hsp90 compared to YK9. PC analysis based MD trajectories prove that inhibitor bindings exert significant effects on the conformational changes, internal dynamics and motion modes of Hsp90, especially for the helix α2 and the loops L1 and L2. The calculations of residue-based free energy decomposition and scanning of the inhibitor-Hsp90 interaction suggest that six residues L107, G108, F138, Y139, W162 and F170 construct the common hot spot of the inhibitor-residue interactions. Moreover the substitutions of the groups G1 and G2 in YKJ and YKI lead to two additional hydrogen bonding interactions and multiple hydrophobic interactions for bindings of YKJ and YKI to Hsp90. This work is also expected to contribute theoretical hints for the design of potent inhibitors toward Hsp90.

Importance of protein flexibility on molecular recognition: modeling binding mechanisms of aminopyrazine inhibitors to Nek2

NIMA-related kinase 2 (Nek2) plays a significant role in cell cycle regulation, and overexpression of Nek2 has been observed in several types of carcinoma, suggesting it is a potential target for cancer therapy. In this study, we attempted to gain more insight into the binding mechanisms of a series of aminopyrazine inhibitors of Nek2 through multiple molecular modeling techniques, including molecular docking, molecular dynamics (MD) simulations and free energy calculations. The simulation results showed that the induced fit docking and ensemble docking based on multiple protein structures yield better predictions than conventional rigid receptor docking, highlighting the importance of incorporating receptor flexibility into the accurate predictions of the binding poses and binding affinities of Nek2 inhibitors. Additionally, we observed that the Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) calculations did not show better performance than the docking scoring to rank the binding affinities of the studied inhibitors, suggesting that MM/GBSA is system-dependent and may not be the best choice for the Nek2 systems. Moreover, the detailed information on protein-ligand binding was characterized by the MM/GBSA free energy decomposition, and a number of derivatives with improved docking scores were designed. It is expected that our study can provide valuable information for the future rational design of novel and potent inhibitors of Nek2.

Insight into binding mechanisms of inhibitors MKP56, MKP73, MKP86, and MKP97 to HIV-1 protease by using molecular dynamics simulation

HIV-1 protease (PR) has been a significant target for design of potent inhibitors curing acquired immunodeficiency syndrome. Molecular dynamics simulations coupled with molecular mechanics Poisson-Boltzmann surface area method were performed to study interaction modes of four inhibitors MKP56, MKP73, MKP86, and MKP97 with PR. The results suggest that the main force controlling interactions of inhibitors with PR should be contributed by van der Waals interactions between inhibitors and PR. The cross-correlation analyses based on MD trajectories show that inhibitor binding produces significant effect on the flap dynamics of PR. Hydrogen bond analyses indicate that inhibitors can form stable hydrogen bonding interactions with the residues from the catalytic strands of PR. The contributions of separate residues to inhibitor bindings are evaluated by using residue-based free energy decomposition method and the results demonstrate that the CH-π and CH-CH interactions between the hydrophobic groups of inhibitors with residues drive the associations of inhibitors with PR. We expect that this study can provide a significant theoretical aid for design of potent inhibitors targeting PR.

Systematic profiling of substrate binding response to multidrug-resistant mutations in HIV-1 protease: Implication for combating drug resistance

Human immunodeficiency virus 1 (HIV-1) protease (PR) represents one of the primary targets for developing antiviral agents for the treatment of HIV-infected patients. However, a number of multidrug-resistant mutations in the enzyme have been observed over the past decades, largely limiting the application of PR inhibitors in antiviral therapy. A systematic investigation of the intermolecular interaction between the multidrug-resistant mutants of HIV-1 PR and its substrates would help to establish a complete profile of substrate response to PR mutations and to design new antiviral agents combating drug resistance. Here, we describe an integrative method to profile 6 clinical multidrug-resistant PR mutants against a panel of 16 substrate octapeptides that flank 12 distinct PR cleavage sites in viral precursor polyproteins. It is found that most multidrug-resistant mutations have only a modest or moderate effect on substrate peptide binding, although these mutations would cause a large free energy loss in PR inhibitor binding. Structural analysis reveals that the substrate peptides are loosely bound within PR active pocket to form a wide contact interface between them, and thus mutation of just single or few residues seems not to influence PR-substrate binding considerably. In addition, peptides derived from variable cleavage sites are generally more sensitive to the mutations as compared to those derived from conserved sites, supporting the co-evaluation mechanism of HIV-1 PR and its substrates under drug suppression. We also identify 12 functionally conserved key residues around the enzyme's active site, which play crucial role in substrate recognition. In vitro fluorescence anisotropy assays confirm that wild-type PR can bind substrate peptides ARVL/AEAM and NLAF/PQGE with a moderately high affinity (K_D=2 and 16μM, respectively). In contrast, the key residue mutations N25D/D29N can completely eliminate (K_D=n.d.) or largely reduce (K_D=32 and 120μM, respectively) the binding capability of the two peptides, suggesting that these PR residues could be the potential target sites for developing resistance-free anti-HIV agents.

Effect of polarization on HIV-1protease and fluoro-substituted inhibitors binding energies by large scale molecular dynamics simulations

Molecular dynamics simulations in explicit water are carried out to study the binding of six inhibitors to HIV-1 protease (PR) for up to 700 ns using the standard AMBER force field and polarized protein-specific charge (PPC). PPC is derived from quantum mechanical calculation for protein in solution and therefore it includes electronic polarization effect. Our results show that in all six systems, the bridging water W301 drifts away from the binding pocket in AMBER simulation. However, it is very stable in all six complexes systems using PPC. Especially, intra-protease, protease-inhibitor hydrogen bonds are dynamic stabilized in MD simulation. The computed binding free energies of six complexes have a significantly linear correlation with those experiment values and the correlation coefficient is found to be 0.91 in PPC simulation. However, the result from AMBER simulation shows a weaker correlation with the correlation coefficient of −0.51 due to the lack of polarization effect. Detailed binding interactions of W301, inhibitors with PR are further analyzed and discussed. The present study provides important information to quantitative understanding the interaction mechanism of PR-inhibitor and PR-W301 and these data also emphasizes the importance of both the electronic polarization and the bridging water molecule in predicting precisely binding affinities.

Mutation L1196M-induced conformational changes and the drug resistant mechanism of anaplastic lymphoma kinase studied by free energy perturbation and umbrella sampling

Anaplastic lymphoma kinase (ALK) has been regarded as a promising drug target in the treatment of tumors and the mutation L1196M induces different levels of drug resistance toward the existing inhibitors.

Theoretical studies on the selective mechanisms of GSK3β and CDK2 by molecular dynamics simulations and free energy calculations

Glycogen synthase kinase 3 (GSK3) is a serine/threonine protein kinase which is widely involved in cell signaling and controls a broad number of cellular functions. GSK3 contains α and β isoforms, and GSK3β has received more attention and becomes an attractive drug target for the treatment of several diseases. The binding pocket of cyclin-dependent kinase 2 (CDK2) shares high sequence identity to that of GSK3β, and therefore, the design of highly selective inhibitors toward GSK3β remains a big challenge. In this study, a computational strategy, which combines molecular docking, molecular dynamics simulations, free energy calculations, and umbrella sampling simulations, was employed to explore the binding mechanisms of two selective inhibitors to GSK3β and CDK2. The simulation results highlighted the key residues critical for GSK3β selectivity. It was observed that although GSK3β and CDK2 share the conserved ATP-binding pockets, some different residues have significant contributions to protein selectivity. This study provides valuable information for understanding the GSK3β-selective binding mechanisms and the rational design of selective GSK3β inhibitors.

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.

Identification of potential quinoxalinone-based aldose reductase inhibitors by 3D-QSAR, molecular docking and molecular dynamics

The 3D-QSAR model of aldose reductase (ARIs) inhibitors is built to gain insights into the key structural factors affecting the inhibitory activity. Based on the model, six new potential ARIs were designed.