Design of new plasmepsin inhibitors: a virtual high throughput screening approach on the EGEE grid

Though different species of the genus Plasmodium may be responsible for malaria, the variant caused by P. falciparum is often very dangerous and even fatal if untreated. Hemoglobin degradation is one of the key metabolic processes for the survival of the Plasmodium parasite in its host. Plasmepsins, a family of aspartic proteases encoded by the Plasmodium genome, play a prominent role in host hemoglobin cleavage. In this paper we demonstrate the use of virtual screening, in particular molecular docking, employed at a very large scale to identify novel inhibitors for plasmepsins II and IV. A large grid infrastructure, the EGEE grid, was used to address the problem of large computation resources required for docking hundreds of thousands of chemical compounds on different plasmepsin targets of P. falciparum. A large compound library of about 1 million chemical compounds was docked on 5 different targets of plasmepsins using two different docking software, namely FlexX and AutoDock. Several strategies were employed to analyze the results of this virtual screening approach including docking scores, ideal binding modes, and interactions to key residues of the protein. Three different classes of structures with thiourea, diphenylurea, and guanidino scaffolds were identified to be promising hits. While the identification of diphenylurea compounds is in accordance with the literature and thus provides a sort of "positive control", the identification of novel compounds with a guanidino scaffold proves that high throughput docking can be effectively used to identify novel potential inhibitors of P. falciparum plasmepsins. Thus, with the work presented here, we do not only demonstrate the relevance of computational grids in drug discovery but also identify several promising small molecules which have the potential to serve as candidate inhibitors for P. falciparum plasmepsins. With the use of the EGEE grid infrastructure for the virtual screening campaign against the malaria causing parasite P. falciparum we have demonstrated that resource sharing on an eScience infrastructure such as EGEE provides a new model for doing collaborative research to fight diseases of the poor.     

Substrate-based design of the first class of angiotensin-converting enzyme-related carboxypeptidase (ACE2) inhibitors

Angiotensin-converting enzyme-related carboxypeptidase (ACE2) is a recently identified zinc metalloprotease with carboxypeptidase activity that was identified using our genomics platform. We implemented a rational design approach to identify potent and selective ACE2 inhibitors. To this end, picomolar inhibitors of ACE2 were designed and synthesized.     

Comparative virtual screening and novelty detection for NMDA-GlycineB antagonists

Identification of novel compound classes for a drug target is a challenging task for cheminformatics and drug design when considerable research has already been undertaken and many potent lead structures have been identified, which leaves limited unclaimed chemical space for innovation. We validated and successfully applied different state-of-the-art techniques for virtual screening (Bayesian machine learning, automated molecular docking, pharmacophore search, pharmacophore QSAR and shape analysis) of 4.6 million unique and readily available chemical structures to identify promising new and competitive antagonists of the strychnine-insensitive Glycine binding site (Glycine_B site) of the NMDA receptor. The novelty of the identified virtual hits was assessed by scaffold analysis, putting a strong emphasis on novelty detection. The resulting hits were tested in vitro and several novel, active compounds were identified. While the majority of the computational methods tested were able to partially discriminate actives from structurally similar decoy molecules, the methods differed substantially in their prospective applicability in terms of novelty detection. The results demonstrate that although there is no single best computational method, it is most worthwhile to follow this concept of focused compound library design and screening, as there still can new bioactive compounds be found that possess hitherto unexplored scaffolds and interesting variations of known chemotypes.     

Structure-based pharmacophore design and virtual screening for novel angiotensin converting enzyme 2 inhibitors

The metallopeptidase Angiotensin Converting Enzyme (ACE) is an important drug target for the treatment of hypertension, heart, kidney, and lung disease. Recently, a close and unique human ACE homologue termed ACE2 has been identified and found to be an interesting new cardiorenal disease target. With the recently resolved inhibitor-bound ACE2 crystal structure available, we have attempted a structure-based approach to identify novel potent and selective inhibitors. Computational approaches focus on pharmacophore-based virtual screening of large compound databases. Selectivity was ensured by initial screening for ACE inhibitors within an internal database and the Derwent World Drug Index, which could be reduced to zero false positives and 0.1% hit rate, respectively. An average hit reduction of 0.44% was achieved with a five feature hypothesis, searching approximately 3.8 million compounds from various commercial databases. Seventeen compounds were selected based on high fit values as well as diverse structure and subjected to experimental validation in a bioassay. We show that all compounds displayed an inhibitory effect on ACE2 activity, the six most promising candidates exhibiting IC50 values in the range of 62-179 microM.     

Discovery of a potent,selective protein tyrosine phosphatase 1B inhibitor using a linked-fragment strategy

Protein tyrosine phosphatase 1B (PTP1B) is an enzyme that downregulates the insulin receptor. Inhibition of PTP1B is expected to improve insulin action, and the design of small molecule PTP1B inhibitors to treat type II diabetes has received considerable attention. In this work, NMR-based screening identified a nonselective competitive inhibitor of PTP1B. A second site ligand was also identified by NMR-based screening and then linked to the catalytic site ligand by rational design. X-ray data confirmed that the inhibitor bound with the catalytic site in the native, "open" conformation. The final compound displayed excellent potency and good selectivity over many other phosphatases. The modular approach to drug design described in this work should be applicable for the design of potent and selective inhibitors of other therapeutically relevant protein tyrosine phosphatases.     

Structure based pharmacophore study to identify possible natural selective PARP-1 trapper as anti-cancer agent

Inhibition of poly(ADP-ribose) polymerase-1 (PARP-1) has turned out an innovative approach for cancer therapy due to its involvement in DNA repair pathways. Although several potent PARP-1 inhibitors have been identified, they exhibit high toxicity, resistivity and diverse pharmacological profile in clinical trials, which necessitate for extensive investigation and development of selective inhibitors. Therefore, the study aimed to identify selective natural PARP-1 inhibitors to reduce toxicity and resistivity with high potency. Accordingly, the combined approach of structure-based pharmacophore and molecular docking study was performed. Hence, the two hits (SN00167272 and STOCK1N-92279) were identified to have all the pharmacophoric features that showed interaction with key residues (Gly863, Ser904, Tyr896, and Tyr907) and least conserved residues (Tyr889 and Asp766). Additionally, these inhibitors represented interactions with unique selective residues (Asp756, Val762, Glu763 and Val886) and exhibited strong interaction with PARP-1 through binding free energy and molecular dynamics study. Hence, the identified hits could further considered for experimental investigations as they may reduce off-target and resistivity of currently available inhibitors and developed as potential anti-cancer agents in the future. Also, the study provides a specific structural insight which could further help to design selective and potent PARP-1 inhibitors.     

A highly potent non-nucleoside adenosine deaminase inhibitor: efficient drug discovery by intentional lead hybridization

We disclose herein the rapid discovery of the first highly potent (Ki = 7.7 nM) non-nucleoside adenosine deaminase (ADA) inhibitor based on the rational hybridization of two structurally distinct leads. Two micromolar inhibitors were discovered by a parallel rational design and random screening program, and individual crystal structures of bovine ADA in complexation with these inhibitors revealed several unknown binding sites and distinct binding modes. Using this information as the starting point, highly effective lead hybridization was achieved in only two structure-based drug design iterations. The conceptual approach illustrated by this example promises to be broadly useful in the search for new chemical entities and can contribute greatly to improve the overall efficiency and speed of drug discovery.     

Discovering New Classes of <Emphasis Type="Italic">Brugia malayi</Emphasis> Asparaginyl-tRNA Synthetase Inhibitors and Relating Specificity to Conformational Change

SLIDE software, which models the flexibility of protein and ligand side chains while docking, was used to screen several large databases to identify inhibitors of Brugia malayi asparaginyl-tRNA synthetase (AsnRS), a target for anti-parasitic drug design. Seven classes of compounds identified by SLIDE were confirmed as micromolar inhibitors of the enzyme. Analogs of one of these classes of inhibitors, the long side-chain variolins, cannot bind to the adenosyl pocket of the closed conformation of AsnRS due to steric clashes, though the short side-chain variolins identified by SLIDE␣apparently bind isosterically with adenosine. We hypothesized that an open conformation of the motif 2 loop also permits the long side-chain variolins to bind in the adenosine pocket and that their selectivity for Brugia relative to human AsnRS can be explained by differences in the sequence and conformation of this loop. Loop flexibility sampling using Rigidity Optimized Conformational Kinetics (ROCK) confirms this possibility, while scoring of the relative affinities of the different ligands by SLIDE correlates well with the compounds’ ranks in inhibition assays. Combining ROCK and SLIDE provides a promising approach for exploiting conformational flexibility in structure-based screening and design of species selective inhibitors.     

Identification of potential inhibitors against nuclear Dam1 complex subunit Ask1 of Candida albicans using virtual screening and MD simulations

Identification of hit compounds against specific target form the starting point for a drug discovery program. A consistent decline of new chemical entities (NCEs) in recent years prompted a challenge to explore newer approaches to discover potential hit compounds that in turn can be converted into leads, and ultimately drug with desired therapeutic efficacy. The vast amount of omics and activity data available in public databases offers an opportunity to identify novel targets and their potential inhibitors. State of the art in silico methods viz., clustering of compounds, virtual screening, molecular docking, MD simulations and MMPBSA calculations were employed in a pipeline to identify potential ‘hits’ against those targets as well whose structures, as of now, could only predict through threading approaches. In the present work, we have started from scratch, amino acid sequence of target and compounds retrieved from PubChem compound database, modeled it in such a way that led to the identification of possible inhibitors of Dam1 complex subunit Ask1 of Candida albicans. We also propose a ligand based binding site determination approach. We have identified potential inhibitors of Ask1 subunit of a Dam1 complex of C. albicans, which is required to prevent precocious spindle elongation in pre-mitotic phases. The proposed scheme may aid to find virtually potential inhibitors of other unique targets against candida.     

De novo design based identification of potential HIV-1 integrase inhibitors: A pharmacoinformatics study

In the present study, pharmacoinformatics paradigms include receptor-based de novo design, virtual screening through molecular docking and molecular dynamics (MD) simulation are implemented to identify novel and promising HIV-1 integrase inhibitors. The de novodrug/ligand/molecule design is a powerful and effective approach to design a large number of novel and structurally diverse compounds with the required pharmacological profiles. A crystal structure of HIV-1 integrase bound with standard inhibitor BI-224436 is used and a set of 80,000 compounds through the de novo approach in LigBuilder is designed. Initially, a number of criteria including molecular docking, in-silico toxicity and pharmacokinetics profile assessments are implied to reduce the chemical space. Finally, four de novo designed molecules are proposed as potential HIV-1 integrase inhibitors based on comparative analyses. Notably, strong binding interactions have been identified between a few newly identified catalytic amino acid residues and proposed HIV-1 integrase inhibitors. For evaluation of the dynamic stability of the protein-ligand complexes, a number of parameters are explored from the 100 ns MD simulation study. The MD simulation study suggested that proposed molecules efficiently retained their molecular interaction and structural integrity inside the HIV-1 integrase. The binding free energy is calculated through the Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) approach for all complexes and it also explains their thermodynamic stability. Hence, proposed molecules through de novo design might be critical to inhibiting the HIV-1 integrase.     

7-Aminoalkoxy-Quinazolines from Epigenetic Focused Libraries Are Potent and Selective Inhibitors of DNA Methyltransferase 1

Inhibitors of epigenetic writers such as DNA methyltransferases (DNMTs) are attractive compounds for epigenetic drug and probe discovery. To advance epigenetic probes and drug discovery, chemical companies are developing focused libraries for epigenetic targets. Based on a knowledge-based approach, herein we report the identification of two quinazoline-based derivatives identified in focused libraries with sub-micromolar inhibition of DNMT1 (30 and 81 nM), more potent than S-adenosylhomocysteine. Also, both compounds had a low micromolar affinity of DNMT3A and did not inhibit DNMT3B. The enzymatic inhibitory activity of DNMT1 and DNMT3A was rationalized with molecular modeling. The quinazolines reported in this work are known to have low cell toxicity and be potent inhibitors of the epigenetic target G9a. Therefore, the quinazoline-based compounds presented are attractive not only as novel potent inhibitors of DNMTs but also as dual and selective epigenetic agents targeting two families of epigenetic writers.     

Understanding and modulating cyclin-dependent kinase inhibitor specificity: molecular modeling and biochemical evaluation of pyrazolopyrimidinones as CDK2/cyclin A and CDK4/cyclin D1 inhibitors

Summary Cyclin-dependent kinases (CDKs) play a key role in regulating the cell cycle. The cyclins, their activating agents, and endogenous CDK inhibitors are frequently mutated in human cancers, making CDKs interesting targets for cancer chemotherapy. Our aim is the discovery of selective CDK4/cyclin D1 inhibitors. An ATP-competitive pyrazolopyrimidinone CDK inhibitor was identified by HTS and docked into a CDK4 homology model. The resulting binding model was consistent with available SAR and was validated by a subsequent CDK2/inhibitor crystal structure. An iterative cycle of chemistry and modeling led to a 70-fold improvement in potency. Small substituent changes resulted in large CDK4/CDK2 selectivity changes. The modeling revealed that selectivity is largely due to hydrogen-bonded interactions with only two kinase residues. This demonstrates that small differences between enzymes can efficiently be exploited in the design of selective inhibitors.     

Structure-based discovery of potassium channel blockers from natural products: virtual screening and electrophysiological assay testing

Potassium ion (K(+)) channels are attractive targets for rational drug design. Based upon a three-dimensional model of the eukaryotic K(+) channels, the docking virtual screening approach was employed to search the China Natural Products Database. Compounds were ranked according to the relative binding energy, favorable shape complementarity, and potential of forming hydrogen bonds with the K(+) channel. Four candidate compounds found by virtual screening were investigated by using the whole-cell voltage-clamp recording in rat dissociated hippocampal neurons. When applied extracellularly, compound 1 markedly depressed the delayed rectifier K(+) current (I(K)) and fast transient K(+) current (I(A)), whereas compounds 2, 3, and 4 exerted a more potent and selective inhibitory effect on I(K). Intracellular application of the four compounds had no effect on both the K(+) currents.     

Molecular dynamics simulations on the inhibition of Cyclin-Dependent Kinases 2 and 5 in the presence of activators

Interests in CDK2 and CDK5 have stemmed mainly from their association with cancer and neuronal migration or differentiation related diseases and the need to design selective inhibitors for these kinases. Molecular dynamics (MD) simulations have not only become a viable approach to drug design because of advances in computer technology but are increasingly an integral part of drug discovery processes. It is common in MD simulations of inhibitor/CDK complexes to exclude the activator of the CDKs in the structural models to keep computational time tractable. In this paper, we present simulation results of CDK2 and CDK5 with roscovitine using models with and without their activators (cyclinA and p25). While p25 was found to induce slight changes in CDK5, the calculations support that cyclinA leads to significant conformational changes near the active site of CDK2. This suggests that detailed and structure-based inhibitor design targeted at these CDKs should employ activator-included models of the kinases. Comparisons between P/CDK2/cyclinA/roscovitine and CDK5/p25/roscovitine complexes reveal differences in the conformations of the glutamine around the active sites, which may be exploited to find highly selective inhibitors with respect to CDK2 and CDK5.     

A structural comparative approach to identifying novel antimalarial inhibitors

Malaria continues to affect millions of people annually. With the rise of drug resistant strains, the need for alternative treatments has become increasingly urgent. Recently, PfUCHL3 was identified as an essential deubiquitinating enzyme. The increasing number of drug target structures being solved has increased the feasibility of utilizing a structural comparative approach to identifying novel inhibitors. Using AutoDock Vina, we recently screened the NCI library of about 320,000 compounds against the crystal structure of PfUCHL3. The top hits were subsequently screened against its human ortholog UCHL3 as to identify compounds that could specifically target the PfUCHL3 over its human counterpart. This method was used to identify small molecule inhibitors that can preferentially inhibit the parasitic enzyme. Several compounds were identified that demonstrated significant binding affinity preference for the malaria target over the human enzyme. Two of these compounds demonstrated ng/mL activity.     

Synthesis and Antiplasmodial Activity of Bisindolylcyclobutenediones

Malaria is one of the most dangerous infectious diseases. Because the causative Plasmodium parasites have developed resistances against virtually all established antimalarial drugs, novel antiplasmodial agents are required. In order to target plasmodial kinases, novel N-unsubstituted bisindolylcyclobutenediones were designed as analogs to the kinase inhibitory bisindolylmaleimides. Molecular docking experiments produced favorable poses of the unsubstituted bisindolylcyclobutenedione in the ATP binding pocket of various plasmodial protein kinases. The synthesis of the title compounds was accomplished by sequential Friedel-Crafts acylation procedures. In vitro screening of the new compounds against transgenic NF54-luc P. falciparum parasites revealed a set of derivatives with submicromolar activity, of which some displayed a reasonable selectivity profile against a human cell line. Although the molecular docking studies suggested the plasmodial protein kinase PfGSK-3 as the putative biological target, the title compounds failed to inhibit the isolated enzyme in vitro. As selective submicromolar antiplasmodial agents, the N-unsubstituted bisindolylcyclobutenediones are promising starting structures in the search for antimalarial drugs, albeit for a rational development, the biological target addressed by these compounds has yet to be identified.     

Design and characterization of a functional library for NMR screening against novel protein targets

In the past few years, NMR has been extensively utilized as a screening tool for drug discovery using various types of compound libraries. The designs of NMR specific chemical libraries that utilize a fragment-based approach based on drug-like characteristics have been previously reported. In this article, a new type of compound library will be described that focuses on aiding in the functional annotation of novel proteins that have been identified from various ongoing genomics efforts. The NMR functional chemical library is comprised of small molecules with known biological activity such as: co-factors, inhibitors, metabolites and substrates. This functional library was developed through an extensive manual effort of mining several databases based on known ligand interactions with protein systems. In order to increase the efficiency of screening the NMR functional library, the compounds are screened as mixtures of 3-4 compounds that avoids the need to deconvolute positive hits by maintaining a unique NMR resonance and function for each compound in the mixture. The functional library has been used in the identification of general biological function of hypothetical proteins identified from the Protein Structure Initiative.     

Automated Docking and the Search for HIV Protease Inhibitors

Abstract

This article will discuss the motivations, technologies, and future directions of computational automated docking in the context of the structure-based rational design of HIV-1 protease inhibitors. Docking simulations are widely used for screening of compound libraries to identify new drug leads, employing a simple model for rapid testing of thousands of compounds. Docking simulations are also useful for lead enhancement, using more detailed models to analyze the atomic interactions between inhibitors and target macromolecules. Major advances have been reported in the development of empirical force fields, which now allow assessment of relative binding strength and drug specificity, and extensions of automated docking techniques allow de novo drug design.     

Approach for the Design of Covalent Protein Kinase Inhibitors via Focused Deep Generative Modeling

Deep machine learning is expanding the conceptual framework and capacity of computational compound design, enabling new applications through generative modeling. We have explored the systematic design of covalent protein kinase inhibitors by learning from kinome-relevant chemical space, followed by focusing on an exemplary kinase of interest. Covalent inhibitors experience a renaissance in drug discovery, especially for targeting protein kinases. However, computational design of this class of inhibitors has thus far only been little investigated. To this end, we have devised a computational approach combining fragment-based design and deep generative modeling augmented by three-dimensional pharmacophore screening. This approach is thought to be particularly relevant for medicinal chemistry applications because it combines knowledge-based elements with deep learning and is chemically intuitive. As an exemplary application, we report for Bruton’s tyrosine kinase (BTK), a major drug target for the treatment of inflammatory diseases and leukemia, the generation of novel candidate inhibitors with a specific chemically reactive group for covalent modification, requiring only little target-specific compound information to guide the design efforts. Newly generated compounds include known inhibitors and characteristic substructures and many novel candidates, thus lending credence to the computational approach, which is readily applicable to other targets.     

The role of in vitro ADME assays in antimalarial drug discovery and development

The high level of attrition of drugs in clinical development has led pharmaceutical companies to increase the efficiency of their lead identification and development through techniques such as combinatorial chemistry and high-throughput (HTP) screening. Since the major reasons for clinical drug candidate failure other than efficacy are pharmacokinetics and toxicity, attention has been focused on assessing properties such as metabolic stability, drug-drug interactions (DDI), and absorption earlier in the drug discovery process. Animal studies are simply too labor-intensive and expensive to use for evaluating every hit, so it has been necessary to develop and implement higher throughput in vitro ADME screens to manage the large number of compounds of interest. The antimalarial drug development program at the Walter Reed Army Institute of Research, Division of Experimental Therapeutics (WRAIR/ET) has adopted this paradigm in its search for a long-term prophylactic for the prevention of malaria. The overarching goal of this program is to develop new, long half-life, orally bioavailable compounds with potent intrinsic activity against liver- and blood-stage parasites. From the WRAIR HTP antimalarial screen, numerous compounds are regularly identified with potent activity. These hits are now immediately evaluated using a panel of in vitro ADME screens to identify and predict compounds that will meet our specific treatment criteria. In this review, the WRAIR ADME screening program for antimalarial drugs is described as well as how we have implemented it to predict the ADME properties of small molecule for the identification of promising drug candidates.