Predicting neurological Adverse Drug Reactions based on biological, chemical and phenotypic properties of drugs using machine learning models

Adverse drug reactions (ADRs) have become one of the primary reasons for the failure of drugs and a leading cause of deaths. Owing to the severe effects of ADRs, there is an urgent need for the generation of effective models which can accurately predict ADRs during early stages of drug development based on integration of various features of drugs. In the current study, we have focused on neurological ADRs and have used various properties of drugs that include biological properties (targets, transporters and enzymes), chemical properties (substructure fingerprints), phenotypic properties (side effects (SE) and therapeutic indications) and a combinations of the two and three levels of features. We employed relief-based feature selection technique to identify relevant properties and used machine learning approach to generated learned model systems which would predict neurological ADRs prior to preclinical testing. Additionally, in order to explain the efficiency and applicability of the models, we tested them to predict the ADRs for already existing anti-Alzheimer drugs and uncharacterized drugs, respectively in side effect resource (SIDER) database. The generated models were highly accurate and our results showed that the models based on chemical (accuracy 93.20%), phenotypic (accuracy 92.41%) and combination of three properties (accuracy 94.18%) were highly accurate while the models based on biological properties (accuracy 82.11%) were highly informative.

Dynamics of fluoroquinolones induced resistance in DNA gyrase of Mycobacterium tuberculosis

DNA gyrase is a validated target of fluoroquinolones which are key components of multidrug resistance tuberculosis (TB) treatment. Most frequent occurring mutations associated with high level of resistance to fluoroquinolone in clinical isolates of TB patients are A90V, D94G, and A90V-D94G (double mutant [DM]), present in the larger subunit of DNA Gyrase. In order to explicate the molecular mechanism of drug resistance corresponding to these mutations, molecular dynamics (MD) and mechanics approach was applied. Structure-based molecular docking of complex comprised of DNA bound with Gyrase A (large subunit) and Gyrase C (small subunit) with moxifloxacin (MFX) revealed high binding affinity to wild type with considerably high Glide XP docking score of -7.88 kcal/mol. MFX affinity decreases toward single mutants and was minimum toward the DM with a docking score of -3.82 kcal/mol. Docking studies were also performed against 8-Methyl-moxifloxacin which exhibited higher binding affinity against wild and mutants DNA gyrase when compared to MFX. Molecular Mechanics/Generalized Born Surface Area method predicted the binding free energy of the wild, A90V, D94G, and DM complexes to be -55.81, -25.87, -20.45, and -12.29 kcal/mol, respectively. These complexes were further subjected to 30 ns long MD simulations to examine significant interactions and conformational flexibilities in terms of root mean square deviation, root mean square fluctuation, and strength of hydrogen bond formed. This comparative drug interaction analysis provides systematic insights into the mechanism behind drug resistance and also paves way toward identifying potent lead compounds that could combat drug resistance of DNA gyrase due to mutations.

Mechanistic Insights into the Binding of Class IIa HDAC Inhibitors toward Spinocerebellar Ataxia Type-2: A 3D-QSAR and Pharmacophore Modeling Approach

Spinocerebellar ataxia (SCA-2) type-2 is a rare neurological disorder among the nine polyglutamine disorders, mainly caused by polyQ (CAG) trinucleotide repeats expansion within gene coding ataxin-2 protein. The expanded trinucleotide repeats within the ataxin-2 protein sequesters transcriptional cofactors i.e., CREB-binding protein (CBP), Ataxin-2 binding protein 1 (A2BP1) leading to a state of hypo-acetylation and transcriptional repression. Histone de-acetylases inhibitors (HDACi) have been reported to restore transcriptional balance through inhibition of class IIa HDAC's, that leads to an increased acetylation and transcription as demonstrated through in-vivo studies on mouse models of Huntington's. In this study, 61 di-aryl cyclo-propanehydroxamic acid derivatives were used for developing three dimensional (3D) QSAR and pharmacophore models. These models were then employed for screening and selection of anti-ataxia compounds. The chosen QSAR model was observed to be statistically robust with correlation coefficient (r²) value of 0.6774, cross-validated correlation coefficient (q²) of 0.6157 and co-relation coefficient for external test set (pred_r²) of 0.7570. A high F-test value of 77.7093 signified the robustness of the model. Two potential drug leads ZINC 00608101 (SEI) and ZINC 00329110 (ACI) were selected after a coalesce procedure of pharmacophore based screening using the pharmacophore model ADDRR.20 and structural analysis using molecular docking and dynamics simulations. The pharmacophore and the 3D-QSAR model generated were further validated for their screening and prediction ability using the enrichment factor (EF), goodness of hit (GH), and receiver operating characteristics (ROC) curve analysis. The compounds SEI and ACI exhibited a docking score of −10.097 and −9.182 kcal/mol, respectively. An evaluation of binding conformation of ligand-bound protein complexes was performed with MD simulations for a time period of 30 ns along with free energy binding calculations using the g_mmpbsa technique. Prediction of inhibitory activities of the two lead compounds SEI (7.53) and ACI (6.84) using the 3D-QSAR model reaffirmed their inhibitory characteristics as potential anti-ataxia compounds.

Computational Screening and Exploration of Disease-Associated Genes in Alzheimer's Disease

Alzheimer's is a neurodegenerative disease affecting large populations worldwide characterized mainly by progressive loss of memory along with various other symptoms. The foremost cause of the disease is still unclear, however various mechanisms have been proposed to cause the disease that include amyloid hypothesis, tau hypothesis, and cholinergic hypothesis in addition to genetic factors. Various genes have been known to be involved which are APOE, PSEN1, PSEN2, and APP among others. In the present study, we have used computational methods to examine the pathogenic effects of non-synonymous single nucleotide polymorphisms (SNPs) associated with ABCA7, CR1, MS4A6A, CD2AP, PSEN1, PSEN2, and APP genes. The SNPs were obtained from dbSNP database followed by identification of deleterious SNPs and prediction of their functional impact. Prediction of disease-associated mutations was performed and the impact of the mutations on the stability of the protein was carried out. To study the structural significance of the computationally prioritized mutations on the proteins, molecular dynamics simulation studies were carried out. On analysis, the SNPs with IDs rs76282929 ABCA7; CR1 rs55962594; MS4A6A rs601172; CD2AP rs61747098; PSEN1 rs63750231, rs63750265, rs63750526, rs63750577, rs63750687, rs63750815, rs63750900, rs63751037, rs63751163, rs63751399; PSEN2 rs63749851; and APP rs63749964, rs63750066, rs63750734, and rs63751039 were predicted to be deleterious and disease-associated having significant structural impact on the proteins. The current study proposes a precise computational methodology for the identification of disease-associated SNPs. J. Cell. Biochem. 118: 1471-1479, 2017. © 2016 Wiley Periodicals, Inc.

Correlation of compliance to statin therapy with lipid profile and serum HMGCoA reductase levels in dyslipidemic patients

BACKGROUND

The efficacy of statin therapy may be lost or vary with reduction in compliance and intensity of statin therapy.

OBJECTIVE

To study and correlate the quantitative effect of compliance on lipid profile and 3-hydroxyl-3-methylglutaryl coenzyme A reductase (HMGCoA-R) levels in dyslipidemic patients.

METHODS

Compliance to different intensity of statin therapy assessed by pill count was correlated with serum levels of total cholesterol (TC), low density lipoprotein-cholesterol (LDL-C), high density lipoprotein-cholesterol (HDL-C), triglycerides (TG), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB) and HMGCoA-R.

RESULTS

Out of 200 patients, 160 received moderate intensity statin therapy whereas 40 were on high intensity statin therapy. The overall mean compliance of patients was 56.7%. The compliance of patients on moderate intensity statin therapy was higher (56.8%) than those on high intensity (56.4%) (p=0.92). There was significant inverse correlation (p<0.05) between compliance and TC, TG, LDL-C and HMGCoA-R levels and positive correlation (p<0.05) with HDL-C levels. The mean serum HMGCoA-R levels did not fall below 9-10ng/mL when compliance to either moderate or high intensity statin therapy was increased above 60%.

CONCLUSIONS

It is appropriate to improve the compliance to existing statin therapy than switching over to higher intensity statin therapy. Estimation of HMGCoA-R levels may be explored as a surrogate marker to monitor and assess the compliance of patients to statin therapy.

Novel group-based QSAR and combinatorial design of CK-1δ inhibitors as neuroprotective agents

Background

Tar DNA binding protein 43 (TDP-43) hyperphosphorylation, caused by Casein kinase 1 (CK-1) protein isoforms, is associated with the onset and progression of Amyotrophic Lateral Sclerosis (ALS). Among the reported isoforms and splice variants of CK-1 protein superfamily, CK-1δ is known to phosphorylate different serine and threonine sites on TDP-43 protein in vitro and thus qualifies as a potential target for ALS treatment.

Results

The developed GQSAR (group based quantitative structure activity relationship) model displayed satisfactory statistical parameters for the dataset of experimentally reported N-Benzothiazolyl-2-Phenyl Acetamide derivatives. A combinatorial library of molecules was also generated and the activities were predicted using the statistically sound GQSAR model. Compounds with higher predicted inhibitory activity were screened against CK-1δ that resulted in to the potential novel leads for CK-1δ inhibition.

Conclusions

In this study, a robust fragment based QSAR model was developed on a congeneric set of experimentally reported molecules and using combinatorial library approach, a series of molecules were generated from which we report two top scoring, CK-1δ inhibitors i.e., CHC (6-benzyl-2-cyclopropyl-4-{[(4-cyclopropyl-6-ethyl-1,3-benzothiazol-2-yl)carbamoyl]methyl}j-3-fluorophenyl hydrogen carbonate) and DHC (6-benzyl-4-{[(4-cyclopropyl-6-ethyl-1,3-benzothiazol-2-yl)carbamoyl]methyl}-2-(decahydronaphthalen-1-yl)-3-hydroxyphenyl hydrogen carbonate) with binding energy of −6.11 and −6.01 kcal/mol, respectively.

Integrating network, sequence and functional features using machine learning approaches towards identification of novel Alzheimer genes

Background

Alzheimer’s disease (AD) is a complex progressive neurodegenerative disorder commonly characterized by short term memory loss. Presently no effective therapeutic treatments exist that can completely cure this disease. The cause of Alzheimer’s is still unclear, however one of the other major factors involved in AD pathogenesis are the genetic factors and around 70 % risk of the disease is assumed to be due to the large number of genes involved. Although genetic association studies have revealed a number of potential AD susceptibility genes, there still exists a need for identification of unidentified AD-associated genes and therapeutic targets to have better understanding of the disease-causing mechanisms of Alzheimer’s towards development of effective AD therapeutics.

Results

In the present study, we have used machine learning approach to identify candidate AD associated genes by integrating topological properties of the genes from the protein-protein interaction networks, sequence features and functional annotations. We also used molecular docking approach and screened already known anti-Alzheimer drugs against the novel predicted probable targets of AD and observed that an investigational drug, AL-108, had high affinity for majority of the possible therapeutic targets. Furthermore, we performed molecular dynamics simulations and MM/GBSA calculations on the docked complexes to validate our preliminary findings.

Conclusions

To the best of our knowledge, this is the first comprehensive study of its kind for identification of putative Alzheimer-associated genes using machine learning approaches and we propose that such computational studies can improve our understanding on the core etiology of AD which could lead to the development of effective anti-Alzheimer drugs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3108-1) contains supplementary material, which is available to authorized users.

Molecular Characterization and Enhancement of Anticancer Activity of Caffeic Acid Phenethyl Ester by γ Cyclodextrin

Caffeic Acid Phenethyl Ester (CAPE) is a key component in New Zealand propolis, known for a variety of health promoting and therapeutic potentials. We investigated the molecular mechanism of anticancer and anti-metastasis activities of CAPE. cDNA array performed on the control and CAPE-treated breast cancer cells revealed activation of DNA damage signaling involving upregulation of GADD45α and p53 tumor suppressor proteins. Molecular docking analysis revealed that CAPE is capable of disrupting mortalin-p53 complexes. We provide experimental evidence and demonstrate that CAPE induced disruption of mortalin-p53 complexes led to nuclear translocation and activation of p53 resulting in growth arrest in cancer cells. Furthermore, CAPE-treated cells exhibited downregulation of mortalin and several other key regulators of cell migration accountable for its anti-metastasis activity. Of note, we found that whereas CAPE was unstable in the culture medium (as it gets degraded into caffeic acid by secreted esterases), its complex with gamma cyclodextrin (γCD) showed high efficacy in anti-tumor and anti-metastasis assays in vitro and in vivo (when administered through either intraperitoneal or oral route). The data proposes that CAPE-γCD complex is a potent anti-cancer and anti-metastasis reagent.

Resisting the Resistance in Cancer: Cheminformatics Studies on Short- Path Base Excision Repair Pathway Antagonists Using Supervised Learning Approaches

Survival of cells and maintenance of genome depend on detection and repair of damaged DNA through intricate mechanisms. Cancer treatment relies on chemotherapy or radiation therapy that kills neoplastic cells by causing immense damage to the DNA. In many cases, escalated DNA repair mechanism leads to resistance against these therapies and therefore, there is a need to expand the interest in developing drugs that can sensitize the cells to such therapies by interfering with the DNA repair mechanism. Several studies have suggested a link between over expression of the primary mammalian enzyme, Apurinic/Apyrimidinic Endonuclease (APE1), responsible for abasic (or AP) site removal in the DNA and resistance of these cells to cancer therapy, whereas APE1 down-regulation sensitizes the cells to DNA damaging agents. Thus, the current treatment efficacy can be improved by aiding to selective sensitization of cancer cells and protection of normal cells. In the present study, we have used machine learning based approach by selecting assorted compounds with known activity for APE1 and constructed a range of in silico predictive classification models to discriminate between the inhibitors and non-inhibitors. These models can be applied to numerous other unscreened compounds to select the ones which are more likely to be the inhibitors for APE1. We have further found the common molecular substructures which were associated with the molecular activity of the compounds using a substructure search approach.

Molecular dynamics-based identification of novel natural mortalin-p53 abrogators as anticancer agents

INTRODUCTION

Cancer is one of the leading causes of mortality worldwide that requires attention in terms of extensive study and research. Eradication of mortalin-p53 interaction that leads to the inhibition of transcriptional activation or blocking of p53 from functioning as a suppressor and induction of nuclear translocation of p53 can prove to be one of the useful approaches for cancer management.

RESULTS

In this study, we used structure-based approach to target the p53-binding domain of mortalin in order to prevent mortalin-p53 complex formation. We screened compounds from ZINC database against the modeled mortalin protein using Glide virtual screening. The top two compounds, DTOM (ZINC 28639308) and TTOM (ZINC 38143676) with Glide score of -12.27 and -12.16, respectively, were identified with the potential to abrogate mortalin-p53 interaction. Finally, molecular dynamics simulations were used to analyze the dynamic stability of the ligand-bound complex and it was observed that residues Tyr196, Asn198, Val264 and Thr267 were involved in intermolecular interactions in both the simulated ligand-bound complexes, and thus, these residues may have a paramount role in stabilizing the binding of the ligands with the protein.

CONCLUSION

These detailed insights can further facilitate the development of potent inhibitors against mortalin-p53 complex.

Perioperative Management of Patients Treated with Angiotensin-Converting Enzyme Inhibitors and Angiotensin II Receptor Blockers: A Quality Improvement Audit

Previous studies have shown that patients continuing angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers on the day of surgery are more likely to have significant intraoperative hypotension, higher rates of postoperative acute kidney injury and lower incidences of postoperative atrial fibrillation. However, many of these studies were prone to bias and confounding, and questions remain over the validity of these outcomes. This observational, before-and-after quality mprovement audit aimed to assess the effect of withholding these medications on the morning of surgery. We recruited 323 participants, with 83 (26%) having their preoperative angiotensin-converting enzyme inhibitor (ACEi) or angiotensin II receptor blocker (ARB) withheld on the day of surgery. There were only very small Spearman rank-order correlations between time since last dose of these medications (rho −0.12, P=0.057) and intraoperative and recovery room intravenous fluid administration (rho −0.11, P=0.042). There was no statistically significant difference between the continued or withheld groups in vasopressor (metaraminol use 3.5 [1.5–8.3] mg versus 3.5 [1.5–8.5] mg, P=0.67) or intravenous fluid administration (1000 ml [800–1500] ml versus 1000 [800–1500] ml, P=0.096), nor rates of postoperative acute kidney injury (13% vs 18%, P=0.25) or atrial fibrillation (15% versus 18%, P=0.71). This audit found no significant differences in measured outcomes between the continued or withheld ACEi/ARB groups. This finding should be interpreted with caution due to the possibility of confounding and an insufficient sample size. However, as the finding is in contrast to many previous studies, future prospective randomised clinical trials are required to answer this important question.

Computational evidence to inhibition of human acetyl cholinesterase by withanolide a for Alzheimer treatment

Alzheimer's disease (AD), a neurodegenerative disorder, is the most common cause of dementia. So far only five drugs have been approved by US FDA that temporarily slow worsening of symptoms for about six to twelve months. The limited number of therapeutic options for AD drives the exploration of new drugs. Enhancement of the central cholinergic function by the inhibition of acetylcholinesterase is a prominent clinically effective approach for the treatment of AD. Recently withanolide A, a secondary metabolite from the ayurvedic plant Withania somnifera has shown substantial neuro-protective ability. The present study is an attempt to elucidate the cholinesterase inhibition potential of withanolide A along with the associated binding mechanism. Our docking simulation results predict high binding affinity of the ligand to the receptor. Further, long de novo simulations for 10 ns suggest that ligand interaction with the residues Thr78, Trp81, Ser120 and His442 of human acetylcholinesterase, all of which fall under one or other of the active sites/subsites, could be critical for its inhibitory activity. The study provides evidence for consideration of withanolide A as a valuable small ligand molecule in treatment and prevention of AD associated pathology. The present information could be of high value for computational screening of AD drugs with low toxicity to normal cells. Accurate knowledge of the 3D structure of human acetylcholinesterase would further enhance the potential of such analysis in understanding the molecular interaction basis between ligand and receptor.

Analyses of methyltransferases across the pathogenicity spectrum of different mycobacterial species point to an extremophile connection

Tuberculosis is a devastating disease, taking one human life every 20 seconds globally. We hypothesize that professional pathogens such as M.tb have acquired specific features that might assist in causing infection, persistence and transmissible pathology in their host. We have identified 121 methyltransferases (MTases) in the M.tb proteome, which use a variety of substrates - DNA, RNA, protein, intermediates of mycolic acid biosynthesis and other fatty acids - that are involved in cellular maintenance within the host. A comparative analysis of the proteome of the virulent strain H37Rv and the avirulent strain H37Ra identified 3 MTases, which displayed significant variations in terms of N-terminal extension/deletion and point mutations, possibly impacting various physicochemical properties. The cross-proteomic comparison of MTases of M.tb H37Rv with 15 different Mycobacterium species revealed the acquisition of novel MTases in a MTB complex as a function of evolution. Phylogenetic analysis revealed that these newly acquired MTases showed common roots with certain extremophiles such as halophilic and acidophilic organisms. Our results establish an evolutionary relationship of M.tb with halotolerant organisms and also the role of MTases of M.tb in withstanding the host osmotic stress, thereby pointing to their likely role in pathogenesis, virulence and niche adaptation.

Fragment based G-QSAR and molecular dynamics based mechanistic simulations into hydroxamic-based HDAC inhibitors against spinocerebellar ataxia

Expansion of polyglutamine (CAG) triplets within the coding gene ataxin 2 results in transcriptional repression, forming the molecular basis of the neurodegenerative disorder named spinocerebellar ataxia type-2 (SCA2). HDAC inhibitors (HDACi) have been elements of great interest in polyglutamine disorders such as Huntington's and Ataxia's. In this study, we have selected hydroxamic acid derivatives as HDACi and performed fragment-based G-QSAR, molecular docking studies and molecular dynamics simulations for elucidating the dynamic mode of action of HDACi with His-Asp catalytic dyad of HDAC4. The model was statistically validated to establish its predictive robustness. The model was statistically significant with r(2) value of .6297, cross-validated co-relation coefficient q(2) value of .5905 and pred_r(2) (predicted square co-relation coefficient) value of .85. An F-test value of 56.11 confirms absolute robustness of the model. Two combinatorial libraries comprising of 3180 compounds were created with hydroxamate moiety as the template and their pIC50 activities were predicted based on the G-QSAR model. The combinatorial library created was screened on the basis of predicted activity (pIC50), with two resultant top scoring compounds, HIC and DHC. The interaction of the compounds with His-Asp dyad in terms of H-bond interactions with His802, Asp840, Pro942, and Gly975 residues of HDAC4 was evaluated by docking and 20 ns long molecular dynamics simulations. This study provides valuable leads for structural substitutions required for hydroxamate moiety to exhibit enhanced inhibitory activity against HDAC4. The reported compounds demonstrated good binding and thus can be considered as potent therapeutic leads against ataxia.

Hydrophobic Interactions Are a Key to MDM2 Inhibition by Polyphenols as Revealed by Molecular Dynamics Simulations and MM/PBSA Free Energy Calculations

p53, a tumor suppressor protein, has been proven to regulate the cell cycle, apoptosis, and DNA repair to prevent malignant transformation. MDM2 regulates activity of p53 and inhibits its binding to DNA. In the present study, we elucidated the MDM2 inhibition potential of polyphenols (Apigenin, Fisetin, Galangin and Luteolin) by MD simulation and MM/PBSA free energy calculations. All polyphenols bind to hydrophobic groove of MDM2 and the binding was found to be stable throughout MD simulation. Luteolin showed the highest negative binding free energy value of -173.80 kJ/mol followed by Fisetin with value of -172.25 kJ/mol. It was found by free energy calculations, that hydrophobic interactions (vdW energy) have major contribution in binding free energy.

Molecular principles behind pyrazinamide resistance due to mutations in panD gene in Mycobacterium tuberculosis

The latest resurrection of drug resistance poses serious threat to the treatment and control of the disease. Mutations have been detected in panD gene in the Mycobacterium tuberculosis (Mtb) strains. Mutation of histidine to arginine at residue 21 (H21R) and isoleucine to valine at residue 29 (I49V) in the non-active site of panD gene has led to PZA resistance. This study will help in reconnoitering the mechanism of pyrazinamide (PZA) resistance caused due to double mutation identified in the panD gene of M. tuberculosis clinical isolates. It is known that panD gene encodes aspartate decarboxylase essential for β-alanine synthesis that makes it a potential therapeutic drug target for tuberculosis treatment. The knowledge about the molecular mechanism conferring drug resistance in M. tuberculosis is scarce, which is a significant challenge in designing successful therapeutic drug. In this study, structural and dynamic repercussions of H21R-I49V double mutation in panD complexed with PZA have been corroborated through docking and molecular dynamics based simulation. The double mutant (DM) shows low docking score and thus, low binding affinity for PZA as compared to the native protein. It was observed that the mutant protein exhibits more structural fluctuation at the ligand binding site in comparison to the native type. Furthermore, the flexibility and compactness analyses indicate that the double mutation influence interaction of PZA with the protein. The hydrogen-bond interaction patterns further supported our results. The covariance and PCA analysis elucidated that the double mutation affects the collective motion of residues in phase space. The results have been presented with an explanation for the induced drug resistance conferred by the H21R-I49V double mutation in panD gene and gain valuable insight to facilitate the advent of efficient therapeutics for combating resistance against PZA.

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.