Resistant mechanism against nelfinavir of human immunodeficiency virus type 1 proteases

Diversity of HIV-1 subtypes and transmitted drug-resistance mutations among minority HIV-1 variants in a Turkish cohort

BACKGROUND

The World Health Organization (WHO) recommends the surveillance of transmitted drug resistance mutations (TDRMs) to ensure the effectiveness and sustainability of HIV treatment programs.

OBJECTIVE

Our aim was to determine the TDRMs and evaluate the distribution of HIV-1 subtypes using and compared next-generation sequencing (NGS) and Sanger-based sequencing (SBS) in a cohort of 44 antiretroviral treatment-naïve patients.

METHODS

All samples that were referred to the microbiology laboratory for HIV drug resistance analysis between December 2016 and February 2018 were included in the study. After exclusions, 44 treatment-naive adult patients with a viral load of >1000 copies/mL were analyzed. DNA sequencing for reverse transcriptase and protease regions was performed using both DeepChek ABL single round kit and Sanger-based ViroSeq HIV-1 Genotyping System. The mutations and HIV-1 subtypes were analyzed using the Stanford HIVdb version 8.6.1 Genotypic Resistance software, and TDRMs were assessed using the WHO surveillance drug-resistance mutation database. HIV-1 subtypes were confirmed by constructing a maximum-likelihood phylogenetic tree using Los Alamos IQ-Tree software.

RESULTS

NGS identified nucleos(t)ide reverse transcriptase inhibitor (NRTI)-TDRMs in 9.1% of the patients, non-nucleos(t)ide reverse transcriptase inhibitor (NNRTI)-TDRMs in 6.8% of the patients, and protease inhibitor (PI)-TDRMs in 18.2% of the patients at a detection threshold of ≥1%. Using SBS, 2.3% and 6.8% of the patients were found to have NRTI- and NNRTI-TDRMs, respectively, but no major PI mutations were detected. M41L, L74I, K65R, M184V, and M184I related to NRTI, K103N to NNRTI, and N83D, M46I, I84V, V82A, L24I, L90M, I54V to the PI sites were identified using NGS. Most mutations were found in low-abundance (frequency range: 1.0% - 4.7%) HIV-1 variants, except M41L and K103N. The subtypes of the isolates were found as follows; 61.4% subtype B, 18.2% subtype B/CRF02_AG recombinant, 13.6% subtype A, 4.5% CRF43_02G, and 2.3% CRF02_AG. All TDRMs, except K65R, were detected in HIV-1 subtype B isolates.

CONCLUSION

The high diversity of protease site TDRMs in the minority HIV-1 variants and prevalence of CRFs were remarkable in this study. All minority HIV-1 variants were missed by conventional sequencing. TDRM prevalence among minority variants appears to be decreasing over time at our center.

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.

Exploring the potency of currently used drugs against HIV-1 protease of subtype D variant by using multiscale simulations

Acquired immune deficiency syndrome (AIDS) is caused by the human immunodeficiency virus (HIV), type 1 and 2. Further, the diversity in HIV-1 has given rise to many serotypes and recombinant strains. The currently used protease inhibitors have been developed for subtype B, although non-B subtype strains account for ∼ 90% of the global HIV infections. Subtype D is spreading rapidly and infecting a large population in North Africa and the Middle East. In the current study, molecular dynamics simulations in conjunction with the molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) scheme was used to investigate the potency of four drugs, namely atazanavir (ATV), darunavir (DRV), lopinavir (LPV) and tipranavir (TPV) against the subtype D variant. Our calculations predicted that the potency of the inhibitors decreased in the order TPV > ATV > DRV > LPV. TPV was found to be the most potent against subtype D due to an increase in van der Waals and electrostatic interactions and reduction in the desolvation energy compared to other inhibitors. This result is further supported by the hydrogen bond interactions between inhibitors and protease. Furthermore, our analyses suggested that the binding of TPV induced a more closed conformation of the flap compared to apo or other complexes. It was observed that TPV/PR^D has a lower cavity volume relative to the other three complexes leading to a tighter binding. The open conformation of the flap was observed for LPV/PR^D. We expect that this study might be useful for designing more potent inhibitors against HIV-1 subtype D. Communicated by Ramaswamy H. Sarma.

Structural studies on molecular mechanisms of Nelfinavir resistance caused by non-active site mutation V77I in HIV-1 protease

Background

The human immunodeficiency virus (HIV-1) is a retrovirus causing acquired immunodeficiency syndrome (AIDS), which has become a serious problem across the world and has no cure reported to date. Human immunodeficiency virus (HIV-1) protease is an attractive target for antiviral treatment and a number of therapeutically useful inhibitors have been designed against it. The emergence of drug resistant mutants of HIV-1 poses a serious problem for conventional therapies that have been used so far. Until now, thirteen protease inhibitors (PIs), major mutation sites and many secondary mutations have been listed in the HIV Drug Resistance Database. In this study, we have studied the effect of the V77I mutation in HIV-PR along with the co-occurring mutations L33F and K20T through multi-nanosecond molecular dynamics simulations. V77I is known to cause Nelfinavir (NFV) resistance in the subtype B population of HIV-1 protease. We have for the first time reported the effect of this clinically relevant mutation on the binding of Nelfinavir and the conformational flexibility of the protease.

Results

Two HIV-PR mutants have been considered in this study - the Double Mutant Protease (DBM) V77I-L33F and Triple Mutant Protease (TPM) V77I-K20T-L33F. The molecular dynamics simulation studies were carried out and the RMSD trajectories of the unliganded wild type and mutated protease were found to be stable. The binding affinity of NFV with wild type HIV-PR was very high with a Glide XP docking score of -9.3 Kcal/mol. NFV showed decreased affinity towards DBM with a docking score of -8.0 Kcal/mol, whereas its affinity increased towards TPM (Glide XP score: -10.3). Prime/MM-GBSA binding free energy of the wild type, DBM and TPM HIV-PR docked structures were calculated as -38.9, -11.1 and -42.6 Kcal/mol respectively. The binding site cavity volumes of wild type, DBM and TPM protease were 1186.1, 1375.5 and 1042.5 ų respectively.

Conclusion

In this study, we have studied the structural roles of the two HIV-PR mutations by conducting molecular dynamics simulation studies of the wild type and mutant HIV-1 PRs. The present study proposes that DBM protease showed greater flexibility and the flap separation was greater with respect to the wild type protease. The cavity size of the MD-stabilized DBM was also found to be increased, which may be responsible for the decreased interaction of Nelfinavir with the cavity residues, thus explaining the decreased binding affinity. On the other hand, the binding affinity of NFV for TPM was found to be enhanced, accounted for by the decrease in cavity size of the mutant which facilitated strong interactions with the flap residues. The flap separation of TPM was less than the wild type protease and the decreased cavity size may be responsible for its lower resistance, and hence, may be the reason for its lower clinical relevance.

Inhibition Profiling of Retroviral Protease Inhibitors Using an HIV-2 Modular System

Retroviral protease inhibitors (PIs) are fundamental pillars in the treatment of HIV infection and acquired immunodeficiency syndrome (AIDS). Currently used PIs are designed against HIV-1, and their effect on HIV-2 is understudied. Using a modular HIV-2 protease cassette system, inhibition profiling assays were carried out for protease inhibitors both in enzymatic and cell culture assays. Moreover, the treatment-associated resistance mutations (I54M, L90M) were introduced into the modular system, and comparative inhibition assays were performed to determine their effect on the susceptibility of the protease. Our results indicate that darunavir, saquinavir, indinavir and lopinavir were very effective HIV-2 protease inhibitors, while tipranavir, nelfinavir and amprenavir showed a decreased efficacy. I54M, L90M double mutation resulted in a significant reduction in the susceptibility to most of the inhibitors with the exception of tipranavir. To our knowledge, this modular system constitutes a novel approach in the field of HIV-2 protease characterization and susceptibility testing.

Protein folding: understanding the role of water and the low Reynolds number environment as the peptide chain emerges from the ribosome and folds

The mechanism of protein folding during early stages of the process has three determinants. First, moving water molecules obey the rules of low Reynolds number physics without an inertial component. Molecular movement is instantaneous and size insensitive. Proteins emerging from the ribosome move and rotate without an external force if they change shape, forming and propagating helical structures that increases translocational efficiency. Forward motion ceases when the shape change or propelling force ceases. Second, application of quantum field theory to water structure predicts the spontaneous formation of low density coherent units of fixed size that expel dissolved atmospheric gases. Structured water layers with both coherent and non-coherent domains, form a sheath around the new protein. The surface of exposed hydrophobic amino acids is protected from water contact by small nanobubbles of dissolved atmospheric gases, 5 or 6 molecules on average, that vibrate, attracting even widely separated resonating nanobubbles. This force results from quantum effects, appearing only when the system is within and interacts with an oscillating electromagnetic field. The newly recognized quantum force sharply bends the peptide and is part of a dynamic field determining the pathway of protein folding. Third, the force initiating the tertiary folding of proteins arises from twists at the position of each hydrophobic amino acid, that minimizes surface exposure of the hydrophobic amino acids and propagates along the protein. When the total bend reaches 360°, the leading segment of water sheath intersects the trailing segment. This steric self-intersection expels water from overlapping segments of the sheath and by Newton׳s second law moves the polypeptide chain in an opposite direction. Consequently, with very few exceptions that we enumerate and discuss, tertiary structures are absent from proteins without hydrophobic amino acids, which control the early stages of protein folding and the overall shape of protein. Consequently, proteins only adopt a limited number of forms. The formation of quaternary structures is not necessarily prevented by the absence of hydrophobic amino acids.

A single E105K mutation far from the active site of influenza B virus neuraminidase contributes to reduced susceptibility to multiple neuraminidase-inhibitor drugs

Drugs inhibiting the enzymatic activity of influenza virus neuraminidase (NA) are the cornerstone of therapy for influenza virus infection. The emergence of drug-resistant variants may limit the benefits of antiviral therapy. Here we report the recovery of an influenza B virus with reduced susceptibilities to NA inhibitors from a human patient with no history of antiviral drug treatment. The virus, designated B/Kochi/61/2011, was isolated by inoculating Madin-Darby canine kidney (MDCK) cells with respiratory specimens from the patient. NA inhibition assays demonstrated that the B/Kochi/61/2011 isolate showed a remarkable reduction in susceptibility to peramivir. The isolate also exhibited low to moderately reduced sensitivity to oseltamivir, laninamivir, and zanamivir. A sequence analysis of viruses propagated in MDCK cells revealed that the isolate contained a mutation (E105K) not previously associated with reduced susceptibility to NA inhibitors. However, pyrosequencing analysis showed that the NA E105K mutation was below a detectable level in the original clinical specimens, suggesting that the mutant virus may be preferably selected during propagation in MDCK cells. Analysis of the three-dimensional model of E105 and K105 NAs with peramivir suggested that the E105K mutation at the monomer-monomer interface of the NA tetramer may destabilize the tetrameric form of NA, leading to decreased susceptibility to NA inhibitors. These results have implications for understanding the mechanism of resistance against NA-inhibitor drugs.

Molecular dynamics simulation in virus research

Virus replication in the host proceeds by chains of interactions between viral and host proteins. The interactions are deeply influenced by host immune molecules and anti-viral compounds, as well as by mutations in viral proteins. To understand how these interactions proceed mechanically and how they are influenced by mutations, one needs to know the structures and dynamics of the proteins. Molecular dynamics (MD) simulation is a powerful computational method for delineating motions of proteins at an atomic-scale via theoretical and empirical principles in physical chemistry. Recent advances in the hardware and software for biomolecular simulation have rapidly improved the precision and performance of this technique. Consequently, MD simulation is quickly extending the range of applications in biology, helping to reveal unique features of protein structures that would be hard to obtain by experimental methods alone. In this review, we summarize the recent advances in MD simulations in the study of virus–host interactions and evolution, and present future perspectives on this technique.

[Bioinformatics studies on drug resistance against anti-HIV-1 drugs]

More than 20 drugs have been available for anti-HIV-1 treatment in Japan. Combination therapy with these drugs dramatically decreases in morbidity and mortality of AIDS. However, due to high mutation rate of HIV-1, treatment with ineffective drugs toward patients infected with HIV-1 causes accumulation of mutations in the virus, and emergence of drug resistant viruses. Thus, to achieve appropriate application of the drugs toward the respective patients living with HIV-1, methods for predicting the level of drug-resistance using viral sequence information has been developed on the basis of bioinformatics. Furthermore, ultra-deep sequencing by next-generation sequencer whose data analysis is also based on bioinformatics, or in silico structural modeling have been achieved to understand drug resistant mechanisms. In this review, I overview the bioinformatics studies about drug resistance against anti-HIV-1 drugs.

The effect of clade-specific sequence polymorphisms on HIV-1 protease activity and inhibitor resistance pathways

The majority of HIV-1 infections around the world result from non-B clade HIV-1 strains. The CRF01_AE (AE) strain is seen principally in Southeast Asia. AE protease differs by approximately 10% in amino acid sequence from clade B protease and carries several naturally occurring polymorphisms that are associated with drug resistance in clade B. AE protease has been observed to develop resistance through a nonactive-site N88S mutation in response to nelfinavir (NFV) therapy, whereas clade B protease develops both the active-site mutation D30N and the nonactive-site mutation N88D. Structural and biochemical studies were carried out with wild-type and NFV-resistant clade B and AE protease variants. The relationship between clade-specific sequence variations and pathways to inhibitor resistance was also assessed. AE protease has a lower catalytic turnover rate than clade B protease, and it also has weaker affinity for both NFV and darunavir (DRV). This weaker affinity may lead to the nonactive-site N88S variant in AE, which exhibits significantly decreased affinity for both NFV and DRV. The D30N/N88D mutations in clade B resulted in a significant loss of affinity for NFV and, to a lesser extent, for DRV. A comparison of crystal structures of AE protease shows significant structural rearrangement in the flap hinge region compared with those of clade B protease and suggests insights into the alternative pathways to NFV resistance. In combination, our studies show that sequence polymorphisms within clades can alter protease activity and inhibitor binding and are capable of altering the pathway to inhibitor resistance.

Structural and energetic analysis on the complexes of clinically isolated subtype C HIV-1 proteases and approved inhibitors by molecular dynamics simulation

HIV-1 has a large genetic diversity. Subtype B HIV-1 is commonly found in patients in developed countries. In contrast, an increasing number of patients are infected with the non-B subtype viruses, especially with subtype C HIV-1, in developing countries. It remains to be clarified how mutations or polymorphisms in non-B subtype HIV-1 influence the efficacy of the approved inhibitors. In this study, we have performed molecular dynamics simulations on clinically isolated subtype C HIV-1 proteases in complex with three kinds of approved inhibitors. From the structural and energetic viewpoints, we identified the polymorphisms influencing on the binding of the inhibitors. The effect of the V82I mutation on the association with chemicals and the reason for rare appearance of the D30N mutation in subtype C HIV-1 were discussed in terms of the change of geometry of the residues in HIV-1 protease.

HIV-1 Protease: Structural Perspectives on Drug Resistance

Antiviral inhibitors of HIV-1 protease are a notable success of structure-based drug design and have dramatically improved AIDS therapy. Analysis of the structures and activities of drug resistant protease variants has revealed novel molecular mechanisms of drug resistance and guided the design of tight-binding inhibitors for resistant variants. The plethora of structures reveals distinct molecular mechanisms associated with resistance: mutations that alter the protease interactions with inhibitors or substrates; mutations that alter dimer stability; and distal mutations that transmit changes to the active site. These insights will inform the continuing design of novel antiviral inhibitors targeting resistant strains of HIV.

Drug-resistant molecular mechanism of CRF01_AE HIV-1 protease due to V82F mutation

Human immunodeficiency virus type 1 protease (HIV-1 PR) is one of the major targets of anti-AIDS drug discovery. The circulating recombinant form 01 A/E (CRF01_AE, abbreviated AE) subtype is one of the most common HIV-1 subtypes, which is infecting more humans and is expanding rapidly throughout the world. It is, therefore, necessary to develop inhibitors against subtype AE HIV-1 PR. In this work, we have performed computer simulation of subtype AE HIV-1 PR with the drugs lopinavir (LPV) and nelfinavir (NFV), and examined the mechanism of resistance of the V82F mutation of this protease against LPV both structurally and energetically. The V82F mutation at the active site results in a conformational change of 79's loop region and displacement of LPV from its proper binding site, and these changes lead to rotation of the side-chains of residues D25 and I50'. Consequently, the conformation of the binding cavity is deformed asymmetrically and some interactions between PR and LPV are destroyed. Additionally, by comparing the interactive mechanisms of LPV and NFV with HIV-1 PR we discovered that the presence of a dodecahydroisoquinoline ring at the P1' subsite, a [2-(2,6-dimethylphenoxy)acetyl]amino group at the P2' subsite, and an N2 atom at the P2 subsite could improve the binding affinity of the drug with AE HIV-1 PR. These findings are helpful for promising drug design.

Optimal drug cocktail design: methods for targeting molecular ensembles and insights from theoretical model systems

Drug resistance is a significant obstacle in the effective treatment of diseases with rapidly mutating targets, such as AIDS, malaria, and certain forms of cancer. Such targets are remarkably efficient at exploring the space of functional mutants and at evolving to evade drug binding while still maintaining their biological role. To overcome this challenge, drug regimens must be active against potential target variants. Such a goal may be accomplished by one drug molecule that recognizes multiple variants or by a drug "cocktail"--a small collection of drug molecules that collectively binds all desired variants. Ideally, one wants the smallest cocktail possible due to the potential for increased toxicity with each additional drug. Therefore, the task of designing a regimen for multiple target variants can be framed as an optimization problem--find the smallest collection of molecules that together "covers" the relevant target variants. In this work, we formulate and apply this optimization framework to theoretical model target ensembles. These results are analyzed to develop an understanding of how the physical properties of a target ensemble relate to the properties of the optimal cocktail. We focus on electrostatic variation within target ensembles, as it is one important mechanism by which drug resistance is achieved. Using integer programming, we systematically designed optimal cocktails to cover model target ensembles. We found that certain drug molecules covered much larger regions of target space than others, a phenomenon explained by theory grounded in continuum electrostatics. Molecules within optimal cocktails were often dissimilar, such that each drug was responsible for binding variants with a certain electrostatic property in common. On average, the number of molecules in the optimal cocktails correlated with the number of variants, the differences in the variants' electrostatic properties at the binding interface, and the level of binding affinity required. We also treated cases in which a subset of target variants was to be avoided, modeling the common challenge of closely related host molecules that may be implicated in drug toxicity. Such decoys generally increased the size of the required cocktail and more often resulted in infeasible optimizations. Taken together, this work provides practical optimization methods for the design of drug cocktails and a theoretical, physics-based framework through which useful insights can be achieved.

Multiple independent origins of a protease inhibitor resistance mutation in salvage therapy patients

BACKGROUND

Combination anti-viral therapies have reduced treatment failure rates by requiring multiple specific mutations to be selected on the same viral genome to impart high-level drug resistance. To determine if the common protease inhibitor resistance mutation L90M is only selected once or repeatedly on different HIV genetic backbones during the course of failed anti-viral therapies we analyzed a linked region of the viral genome during the evolution of multi-drug resistance.

RESULTS

Using L90M allele specific PCR we amplified and sequenced gag-pro regions linked to very early L90M containing HIV variants prior to their emergence and detection as dominant viruses in 15 failed salvage therapy patients. The early minority L90M linked sequences were then compared to those of the later L90M viruses that came to dominate the plasma quasispecies. Using Bayesian evolutionary analysis sampling trees the emergence of L90M containing viruses was seen to take place on multiple occasion in 5 patients, only once for 2 patients and an undetermined number of time for the remaining 8 patients.

CONCLUSION

These results indicate that early L90M mutants can frequently be displaced by viruses carrying independently selected L90M mutations rather than by descendents of the earlier mutants.

Mutational patterns and correlated amino acid substitutions in the HIV-1 protease after virological failure to nelfinavir- and lopinavir/ritonavir-based treatments

Human immunodeficiency virus type 1 (HIV-1) antiviral drug resistance is a major consequence of therapy failure and compromises future therapeutic options. Nelfinavir and lopinavir/ritonavir-based therapies have been widely used in the treatment of HIV-infected patients, in combination with reverse transcriptase inhibitors. The aim of this observational study was the identification and characterization of mutations or combinations of mutations associated with resistance to nelfinavir and lopinavir/ritonavir in treated patients. Nucleotide sequences of 1,515 subtype B HIV-1 isolates from 1,313 persons with different treatment histories (including naïve and treated patients) were collected in 31 Spanish hospitals over the years 2002-2005. Chi-square contingency tests were performed to detect mutations associated with failure to protease inhibitor-based therapies, and correlated mutations were identified using statistical methods. Virological failure to nelfinavir was associated with two different mutational pathways. D30N and N88D appeared mostly in patients without previous exposure to protease inhibitors, while K20T was identified as a secondary resistance mutation in those patients. On the other hand, L90M together with L10I, I54V, A71V, G73S, and V82A were selected in protease inhibitor-experienced patients. A series of correlated mutations including L10I, M46I, I54V, A71V, G73S, and L90M appeared as a common cluster of amino acid substitutions, associated with failure to lopinavir/ritonavir-based treatments. Despite the relatively high genetic barrier of some protease inhibitors, a relatively small cluster of mutations, previously selected under drug pressure, can seriously compromise the efficiency of nelfinavir- and lopinavir/ritonavir-based therapies.

Molecular analysis of the HIV-1 resistance development: enzymatic activities, crystal structures, and thermodynamics of nelfinavir-resistant HIV protease mutants

Human immunodeficiency virus (HIV) encodes an aspartic protease (PR) that cleaves viral polyproteins into mature proteins, thus leading to the formation of infectious particles. Protease inhibitors (PIs) are successful virostatics. However, their efficiency is compromised by antiviral resistance. In the PR sequence of viral variants resistant to the PI nelfinavir, the mutations D30N and L90M appear frequently. However, these two mutations are seldom found together in vivo, suggesting that there are two alternative evolutionary pathways leading to nelfinavir resistance. Here we analyze the proteolytic activities, X-ray structures, and thermodynamics of inhibitor binding to HIV-1 PRs harboring the D30N and L90M mutations alone and in combination with other compensatory mutations. Vitality values obtained for recombinant mutant proteases and selected PR inhibitors confirm the crucial role of mutations in positions 30 and 90 for nelfinavir resistance. The combination of the D30N and L90M mutations significantly increases the enzyme vitality in the presence of nelfinavir, without a dramatic decrease in the catalytic efficiency of the recombinant enzyme. Crystal structures, molecular dynamics simulations, and calorimetric data for four mutants (D30N, D30N/A71V, D30N/N88D, and D30N/L90M) were used to augment our kinetic data. Calorimetric analysis revealed that the entropic contribution to the mutant PR/nelfinavir interaction is less favorable than the entropic contribution to the binding of nelfinavir by wild-type PR. This finding is supported by the structural data and simulations; nelfinavir binds most strongly to the wild-type protease, which has the lowest number of protein-ligand hydrogen bonds and whose structure exhibits the greatest degree of fluctuation upon inhibitor binding.

Computational simulations of HIV-1 proteases--multi-drug resistance due to nonactive site mutation L90M

Human immunodeficiency virus type 1 protease (HIV-1 PR) is one of the proteins that currently available anti-HIV-1 drugs target. Inhibitors of HIV-1 PR have become available, and they have lowered the rate of mortality from acquired immune deficiency syndrome (AIDS) in advanced countries. However, the rate of emergence of drug-resistant HIV-1 variants is quite high because of their short retroviral life cycle and their high mutation rate. Serious drug-resistant mutations against HIV-1 PR inhibitors (PIs) frequently appear at the active site of PR. Exceptionally, some other mutations such as L90M cause drug resistance, although these appear at nonactive sites. The mechanism of resistance due to nonactive site mutations is difficult to explain. In this study, we carried out computational simulations of L90M PR in complex with each of three kinds of inhibitors and one typical substrate, and we clarified the mechanism of resistance. The L90M mutation causes changes in interaction between the side chain atoms of the 90th residue and the main chain atoms of the 25th residue, and a slight dislocation of the 25th residue causes rotation of the side chain at the 84th residue. The rotation of the 84th residue leads to displacement of the inhibitor from the appropriate binding location, resulting in a collision with the flap or loop region. The difference in levels of resistance to the three inhibitors has been explained from energetic and structural viewpoints, which provides the suggestion for promising drugs keeping its efficacy even for the L90M mutant.

Computational characterization of structural role of the non-active site mutation M36I of human immunodeficiency virus type 1 protease

A prominent characteristic of human immunodeficiency virus type 1 (HIV-1) is its high genetic variability, which generates diversity of the virus and often causes a serious problem of the emergence of drug-resistant mutants. Subtype B HIV-1 is dominant in advanced countries, and the mortality rate due to subtype B HIV-1 has been decreased during the past decade. In contrast, the number of patients with non-subtype B viruses is still increasing in developing countries. One of the reasons for the prevalence of non-subtype B viruses is lack of information about the biological and therapeutic differences between subtype B and non-subtype B viruses. M36I is the most frequently observed polymorphism in non-subtype B HIV-1 proteases. However, since the 36th residue is located at a non-active site of the protease and has no direct interaction with any ligands, the structural role of M36I remains unclear. Here, we performed molecular dynamics (MD) simulations of M36I protease in complex with nelfinavir and revealed the influence of the M36I mutation. The results show that M36I regulates the size of the binding cavity of the protease. The reason for the rare emergence of D30N variants in non-subtype B HIV-1 proteases was also clarified from our computational analysis.

Implementation of π-π interactions in molecular dynamics simulation

No explicit pi-pi interaction term has been incorporated in the conventional molecular dynamics (MD) simulation programs in spite of its significant role in the folding of biomolecules and the clustering of organic chemicals. In this article, we propose a technique to emphasize the effect of pi-pi interactions using a function of energy and implement it into an MD simulation program. Several trial calculations show that the pi-pi incorporated program gives improved results consistent with experimental data on atom geometry and has no unfavorable interference with the conventional computational framework. This indicates an importance of the explicit consideration of pi-pi interactions in MD simulation.

Computational Analysis of the Proton Translocation from Asp96 to Schiff Base in Bacteriorhodopsin

The potential energy change during the M --> N process in bacteriorhodopsin has been evaluated by ab initio quantum chemical and advanced quantum chemical calculations following molecular dynamics (MD) simulations. Many previous experimental studies have suggested that the proton transfer from Asp96 to the Schiff base occurs under the following two conditions: (1) the hydrogen bond between Thr46 and Asp96 breaks and Thr46 is detached from Asp96 and (2) a stable chain of four water molecules spans an area from Asp96 --> Schiff base. In this work, we successfully reproduced the proton-transfer process occurring under these two conditions by molecular dynamics and quantum chemical calculations. The quantum chemical computation revealed that the proton transfer from Asp96 to Shiff base occurs in two-step reactions via an intermediate in which an H(3)O(+) appears around Ala215. The activation energy for the proton transfer in the first reaction was calculated to be 9.7 kcal/mol, which enables fast and efficient proton pump action. Further QM/MM (quantum mechanical/molecular mechanical) and FMO (fragment molecular orbital) calculations revealed that the potential energy change during the proton transfer is tightly regulated by the composition and the geometry of the surrounding amino acid residues of bacteriorhodopsin. Here, we report in detail the Asp96 --> Schiff base proton translocation mechanism of bacteriorhodopsin. Additionally, we discuss the effectiveness of combining quantum chemical calculations with truncated cluster models followed by advanced quantum chemical calculations applied to a whole protein to elucidate its reaction mechanism.

Insights into amprenavir resistance in E35D HIV-1 protease mutation from molecular dynamics and binding free-energy calculations

Drug resistance is a very important factor contributing to the failure of current HIV therapies. The ability to understand the resistance mechanism of HIV-protease mutants may be useful in developing more effective and longer lasting treatment regimens. In this paper, we report the first computational study of the clinically relevant E35D mutation of HIV-1 protease in its unbound conformation and complexed with the clinical inhibitor amprenavir and a sample substrate (Thr-Ile-Met-Met-Gln-Arg). Our data, collected from 10 ns molecular-dynamics simulations, show that the E35D mutation results in an increased flexibility of the flaps, thereby affecting the conformational equilibrium between the closed and semi-open conformations of the free protease. The E35D mutation also causes a significant reduction of the calculated binding free energies both for substrate and amprenavir, thus giving a plausible explanation for its ability to increase the level of resistance. One possible explanation for the emergence of this mutation, despite its unfavorable effect on substrate affinity, might be the role of E35D as an escape mutation, which favors escape from the immune system in addition to conferring drug resistance.

[RNA viruses and mutations]

Actively replicating RNA viruses in nature are continually changing their genetic information by spontaneous mutations. These changes often result in alterations in immune-sensitivity, drug-sensitivity, cell-tropism, and host-range, causing uncontrollability of the pathogen and emerging/re-emerging infections. To better understand the virus changes and develop effective methods to control the moving targets, it is essential to obtain information on changes in viral genomes and proteins. Although information on genetic changes is being accumulated very rapidly, assessment of changes in protein structure and function still requires time-consuming works. In this review, we will overview mutation studies of human immunodeficiency virus and other RNA viruses. In addition, we will introduce recent advances in the computational science and its application on mutation studies and drug development.