Virtual screening of HIV-1 protease inhibitors against human cytomegalovirus protease using docking and molecular dynamics

Accurate Prediction of Inhibitor Binding to HIV-1 Protease Using CANDOCK

The human immunodeficiency virus 1 (HIV-1) protease is an important target for treating HIV infection. Our goal was to benchmark a novel molecular docking protocol and determine its effectiveness as a therapeutic repurposing tool by predicting inhibitor potency to this target. To accomplish this, we predicted the relative binding scores of various inhibitors of the protease using CANDOCK, a hierarchical fragment-based docking protocol with a knowledge-based scoring function. We first used a set of 30 HIV-1 protease complexes as an initial benchmark to optimize the parameters for CANDOCK. We then compared the results from CANDOCK to two other popular molecular docking protocols Autodock Vina and Smina. Our results showed that CANDOCK is superior to both of these protocols in terms of correlating predicted binding scores to experimental binding affinities with a Pearson coefficient of 0.62 compared to 0.48 and 0.49 for Vina and Smina, respectively. We further leveraged the Database of Useful Decoys: Enhanced (DUD-E) HIV protease set to ascertain the effectiveness of each protocol in discriminating active versus decoy ligands for proteases. CANDOCK again displayed better efficacy over the other commonly used molecular docking protocols with area under the receiver operating characteristic curve (AUROC) of 0.94 compared to 0.71 and 0.74 for Vina and Smina. These findings support the utility of CANDOCK to help discover novel therapeutics that effectively inhibit HIV-1 and possibly other retroviral proteases.

Exploring Polypharmacology in Drug Discovery and Repurposing Using the CANDO Platform

BACKGROUND

Traditional drug discovery approaches focus on a limited set of target molecules for treatment against specific indications/diseases. However, drug absorption, dispersion, metabolism, and excretion (ADME) involve interactions with multiple protein systems. Drugs approved for particular indication(s) may be repurposed as novel therapeutics for others. The severely declining rate of discovery and increasing costs of new drugs illustrate the limitations of the traditional reductionist paradigm in drug discovery.

METHODS

We developed the Computational Analysis of Novel Drug Opportunities (CANDO) platform based on a hypothesis that drugs function by interacting with multiple protein targets to create a molecular interaction signature that can be exploited for therapeutic repurposing and discovery. We compiled a library of compounds that are human ingestible with minimal side effects, followed by an 'all-compounds' vs 'all-proteins' fragment-based multitarget docking with dynamics screen to construct compound-proteome interaction matrices that were then analyzed to determine similarity of drug behavior. The proteomic signature similarity of drugs is then ranked to make putative drug predictions for all indications in a shotgun manner.

RESULTS

We have previously applied this platform with success in both retrospective benchmarking and prospective validation, and to understand the effect of druggable protein classes on repurposing accuracy. Here we use the CANDO platform to analyze and determine the contribution of multitargeting (polypharmacology) to drug repurposing benchmarking accuracy. Taken together with the previous work, our results indicate that a large number of protein structures with diverse fold space and a specific polypharmacological interactome is necessary for accurate drug predictions using our proteomic and evolutionary drug discovery and repurposing platform.

CONCLUSION

These results have implications for future drug development and repurposing in the context of polypharmacology.

Mathematical and computational modeling in biology at multiple scales

A variety of topics are reviewed in the area of mathematical and computational modeling in biology, covering the range of scales from populations of organisms to electrons in atoms. The use of maximum entropy as an inference tool in the fields of biology and drug discovery is discussed. Mathematical and computational methods and models in the areas of epidemiology, cell physiology and cancer are surveyed. The technique of molecular dynamics is covered, with special attention to force fields for protein simulations and methods for the calculation of solvation free energies. The utility of quantum mechanical methods in biophysical and biochemical modeling is explored. The field of computational enzymology is examined.

Clinical relevance of the plasma load of cytomegalovirus in patients infected with HIV--a survival analysis

To investigate whether asymptomatic cytomegalovirus (CMV) viraemia impact the course of human immunodeficiency virus (HIV) infection, this study evaluated the effect of CMV replication on progression of newly-diagnosed HIV infected individuals towards AIDS events and death. In a 3-year prospective study on co-infected patients, clinical, immunological, and virological tests were performed in a national reference hospital quarterly. CMV viraemia was quantified by RoboGene® HCMV DNA Quantification Kit (Analytik Jena, Germany), on ABI Prism® 7000 Sequence Detection System (Applied Biosystems, USA). One hundred and five patients were enrolled with a balanced sex distribution and a median age of 30.7 years. Median CD4(+) cell count at enrollment was 164/mm(3) and median HIV RNA 4.6 log10 copies/ml. Detectable CMV viraemia was found in 25.7% of the patients. Kaplan-Meier analysis showed progression of HIV infection to be significantly increased in those with active CMV replication and/or low CD4(+) cell count. Cox regression indicated the risk of developing new AIDS events was 2.6 times greater in patients with detectable CMV viraemia versus those without (CI95% 1-6.6; P = 0.04). Also in multivariate analysis, the overall risk of progression to AIDS events or death was 3-fold higher in those with detectable CMV viraemia (CI95% 1.3-6.7; P = 0.008) and 2.3-fold higher if CD4(+) cell count was below 100/mm(3) (CI95% 1-5.1; P = 0.04). In these young Romanian HIV-seropositives, active CMV replication increased morbidity, even when treated with combination antiretroviral therapy. Further studies are needed to evaluate if serial quantitative CMV-DNA levels might correlate with non-infectious inflammation-related risks in patients with HIV and active CMV infection.

CANDO and the infinite drug discovery frontier

The Computational Analysis of Novel Drug Opportunities (CANDO) platform (http://protinfo.org/cando) uses similarity of compound-proteome interaction signatures to infer homology of compound/drug behavior. We constructed interaction signatures for 3733 human ingestible compounds covering 48,278 protein structures mapping to 2030 indications based on basic science methodologies to predict and analyze protein structure, function, and interactions developed by us and others. Our signature comparison and ranking approach yielded benchmarking accuracies of 12-25% for 1439 indications with at least two approved compounds. We prospectively validated 49/82 'high value' predictions from nine studies covering seven indications, with comparable or better activity to existing drugs, which serve as novel repurposed therapeutics. Our approach may be generalized to compounds beyond those approved by the FDA, and can also consider mutations in protein structures to enable personalization. Our platform provides a holistic multiscale modeling framework of complex atomic, molecular, and physiological systems with broader applications in medicine and engineering.

Structure and ligand based drug design strategies in the development of novel 5- LOX inhibitors

Lipoxygenases (LOXs) are non-heme iron containing dioxygenases involved in the oxygenation of polyunsaturated fatty acids (PUFAs) such as arachidonic acid (AA). Depending on the position of insertion of oxygen, LOXs are classified into 5-, 8-, 9-, 12- and 15-LOX. Among these, 5-LOX is the most predominant isoform associated with the formation of 5-hydroperoxyeicosatetraenoic acid (5-HpETE), the precursor of non-peptido (LTB₄) and peptido (LTC₄, LTD₄, and LTE₄) leukotrienes. LTs are involved in inflammatory and allergic diseases like asthma, ulcerative colitis, rhinitis and also in cancer. Consequently 5-LOX has become target for the development of therapeutic molecules for treatment of various inflammatory disorders. Zileuton is one such inhibitor of 5-LOX approved for the treatment of asthma.

In the recent times, computer aided drug design (CADD) strategies have been applied successfully in drug development processes. A comprehensive review on structure based drug design strategies in the development of novel 5-LOX inhibitors is presented in this article. Since the crystal structure of 5-LOX has been recently solved, efforts to develop 5-LOX inhibitors have mostly relied on ligand based rational approaches. The present review provides a comprehensive survey on these strategies in the development of 5-LOX inhibitors.

The HIV protease inhibitor nelfinavir inhibits Kaposi's sarcoma-associated herpesvirus replication in vitro

Kaposi's sarcoma (KS) is the most common HIV-associated cancer worldwide and is associated with high levels of morbidity and mortality in some regions. Antiretroviral (ARV) combination regimens have had mixed results for KS progression and resolution. Anecdotal case reports suggest that protease inhibitors (PIs) may have effects against KS that are independent of their effect on HIV infection. As such, we evaluated whether PIs or other ARVs directly inhibit replication of Kaposi's sarcoma-associated herpesvirus (KSHV), the gammaherpesvirus that causes KS. Among a broad panel of ARVs tested, only the PI nelfinavir consistently displayed potent inhibitory activity against KSHV in vitro as demonstrated by an efficient quantitative assay for infectious KSHV using a recombinant virus, rKSHV.294, which expresses the secreted alkaline phosphatase. This inhibitory activity of nelfinavir against KSHV replication was confirmed using virus derived from a second primary effusion lymphoma cell line. Nelfinavir was similarly found to inhibit in vitro replication of an alphaherpesvirus (herpes simplex virus) and a betaherpesvirus (human cytomegalovirus). No activity was observed with nelfinavir against vaccinia virus or adenovirus. Nelfinavir may provide unique benefits for the prevention or treatment of HIV-associated KS and potentially other human herpesviruses by direct inhibition of replication.

Searching the Tritryp genomes for drug targets

The recent publication of the complete genome sequences of Leishmania major, Trypanosoma brucei and Trypanosoma cruzi revealed that each genome contains 8300-12,000 protein-coding genes, of which approximately 6500 are common to all three genomes, and ushers in a new, post-genomic, era for trypanosomatid drug discovery. This vast amount of new information makes possible more comprehensive and accurate target identification using several new computational approaches, including identification of metabolic "choke-points", searching the parasite proteomes for orthologues of known drug targets, and identification of parasite proteins likely to interact with known drugs and drug-like small molecules. In this chapter, we describe several databases (such as GENEDB, BRENDA, KEGG, METACYC, the THERAPEUTIC TARGET DATABASE, and CHEMBANK) and algorithms (including PATHOLOGIC, PATHWAY HUNTER TOOL, AND AUToDOCK) which have been developed to facilitate the bioinformatic analyses underlying these approaches. While target identification is only the first step in the drug development pipeline, these new approaches give rise to renewed optimism for the discovery of new drugs to combat the devastating diseases caused by these parasites. Traditionally, drug discovery in the trypanosomatids (and other organisms) has proceeded from two different starting points: screening large numbers of existing compounds for activity against whole parasites or more focused screening of compounds for activity against defined molecular targets. Most existing anti-trypanosomatids drugs were developed using the former approach, although the latter has gained much attention in the last twenty years under the rubric of "rational drug design". Until recently, one of the major bottlenecks in anti-trypanosomatid drug development has been our ability to identify good targets, since only a very small percentage of the total number of trypanosomatid genes were known. That has now changed forever, with the recent (July, 2005) publication of the "Tritryp" (Trypanosoma brucei, Trypanosoma cruzi and Leishmania major) genome sequences. This vast amount of information now makes possible several new approaches for target identification and ushers in a post-genomic era for trypanosomatid drug discovery.

Human subcutaneous adipose tissue LPIN1 expression in obesity, type 2 diabetes mellitus, and human immunodeficiency virus--associated lipodystrophy syndrome

The aim of this study was to analyze LPIN1 adipose tissue gene expression levels in 3 clinical insulin-resistant conditions-obesity, type 2 diabetes mellitus, and human immunodeficiency virus (HIV)-associated lipodystrophy-and its relationship with adipogenic and inflammatory markers. Subcutaneous adipose tissue samples were obtained from 2 cohorts: 98 subjects with different degrees of adiposity and with or without the presence of type 2 diabetes mellitus and 37 HIV-infected patients. Real-time polymerase chain reaction was used to measure gene expression of LPIN1 and adipogenic (PPARgamma, SREBP1c) and inflammatory markers (IL6, TNFalpha, TNFR1, and TNFR2). LPIN1 messenger RNA expression levels were significantly lower in the obese group (P = .002), were similar in type 2 diabetes mellitus patients and control subjects (P = .211), and were significantly higher in HIV-infected patients (P < .001). LPIN1 messenger RNA levels positively correlated with insulin sensitivity in all subjects. Moreover, an inverse correlation with proinflammatory cytokines was observed.