Structure-based discovery and in-parallel optimization of novel competitive inhibitors of thymidylate synthase

Intersite communication in dimeric enzymes highlighted by structural and thermodynamic analysis of didansyltyrosine binding to thymidylate synthases

Intersite communication in dimeric enzymes, triggered by ligand binding, represents both a challenge and an opportunity in enzyme inhibition strategy. Though often understestimated, it can impact on the in vivo biological mechansim of an inhibitor and on its pharmacokinetics. Thymidylate synthase (TS) is a homodimeric enzyme present in almost all living organisms that plays a crucial role in DNA synthesis and cell replication. While its inhibition is a valid strategy in the therapy of several human cancers, designing specific inhibitors of bacterial TSs poses a challenge to the development of new anti-infective agents. N,O-didansyl-l-tyrosine (DDT) inhibits both Escherichia coli TS (EcTS) and Lactobacillus casei TS (LcTS). The available X-ray structure of the DDT:dUMP:EcTS ternary complex indicated an unexpected binding mode for DDT to EcTS, involving a rearrangement of the protein and addressing the matter of communication between the two active sites of an enzyme dimer. Combining molecular-level information on DDT binding to EcTS and LcTS extracted from structural and FRET-based fluorometric evidence with a thermodynamic characterization of these events obtained by fluorometric and calorimetric titrations, this study unveiled a negative cooperativity between the DDT bindings to the two monomers of each enzyme dimer. This result, complemented by the species-specific thermodynamic signatures of the binding events, implied that communication across the protein dimer was triggered by the first DDT binding. These findings could challenge the conventional understanding of TS inhibition and open the way for the development of novel TS inhibitors with a different mechanism of action and enhanced efficacy and specificity.

Drug Repurposing against Novel Therapeutic Targets in Plasmodium falciparum for Malaria: The Computational Perspective

Malaria remains one of the most challenging tropical diseases. Since malaria cases are reportedly alarming in terms of infections and mortality, urgent attention is needed for addressing the issues of drug resistance in falciparum malaria. High throughput screening methods have paved way for rapid identification of anti-malarial. Furthermore, drug repurposing helps in shortening the time required for drug safety approvals. Hence, discovery of new antimalarials by drug repurposing is a promising approach for combating the disease. This article summarizes the recent computational approaches used for identifying novel antimalarials by using drug target interaction tools followed by pharmacokinetic studies.

A Family of [Zn6] Complexes from the Carboxylate-Bridge-Supported Assembly of [Zn2] Building Units: Synthetic, Structural, Spectroscopic, and Systematic Biological Studies

The three discrete [Zn₆] complexes [Na₃Zn₆(cpdp)₃(μ-Bz)₃(CH₃OH)₆][ZnCl₄][ZnCl₃(H₂O)]·3CH₃OH·1.5H₂O (1), [Na₃Zn₆(cpdp)₃(μ-p-OBz)₃(CH₃OH)₆]·2H₂O (2), and [Na₃Zn₆(cpdp)₃(μ-p-NO₂Bz)₃(CH₃OH)₆]Cl₃·2H₂O (3), supported by the carboxylate-based multidentate ligand N,N'-bis[2-carboxybenzomethyl]-N,N'-bis[2-pyridylmethyl]-1,3-diaminopropan-2-ol (H₃cpdp), have been successfully synthesized and fully characterized (Bz = benzoate; p-OBz = dianion of p-hydroxybenzoic acid; p-NO₂Bz = p-nitrobenzoate). The complexes have been characterized by elemental analysis, FTIR, UV-vis, NMR spectroscopy, PXRD, and thermal analysis, including single-crystal X-ray crystallography of 1 and 2. The molecular architectures of 1-3 are built from the self-assembly of their corresponding [Zn₂] units, which are interconnected to the central [Na₃(CH₃OH)₆]³⁺ core by six endogenous benzoate groups, with each linking one Zn(II) and one Na(I) ion in a μ₂:η¹:η¹-syn-anti bidentate fashion. The composition of the (cpdp^3-)₃/(Zn²⁺)₆ complexes in 1-3 has been observed to be 1:2, on the basis of the UV-vis titration and NMR spectroscopic results, which is further supported by X-ray crystallography. Systematic biological studies performed with a mice model suggested possible antidiabetic efficacy as well as anticancer activities of the complexes. When complexes 1-3 were administered intraperitoneally in mice, 1 showed a lowering in the blood glucose level, overall maintenance of the pancreatic tissue mass, restriction of DNA damage in pancreatic cells, and retention of lipid droplet (LD) frequency, whereas 2 and 3 showed hepatic tissue mass consistency by inhibiting the DNA damage in hepatic cells, prior to the exposure to a potent diabetic inducer, alloxan (ALX). Similar trends of results were observed in inhibiting the generation of reactive oxygen species (ROS) in the pancreatic and hepatic cells, as examined by spectrofluorometric methods. Thus, 1 seems to be a better compound for overall diabetic management and control, whereas 2 and 3 seem to be promising compounds for designing chemopreventive drugs against hepatic carcinoma.

An integrated virtual screening and drug repurposing strategy for the discovery of new antimalarial drugs against Plasmodium falciparum phosphatidylinositol 3-kinase

The emergence and spread of drug resistance in Plasmodium falciparum, the parasite causing the most severe form of human malaria, is a major threat to malaria control and elimination programs around the globe. With P. falciparum having evolved widespread resistance against a number of previously widely used drugs, currently, artemisinin (ART) and its derivatives are the cornerstones of first-line treatments of uncomplicated malaria. However, growing incidences of ART failure reflect the spread of ART-resistant P. falciparum strains. Despite current efforts to understand the primary cause of ART resistance due to mutations in the Kelch 13 gene (PfK13), the mechanism underlying ART resistance is still not completely unclear and no feasible strategies to counteract the causes and thereby restoring the efficiency of ART have been developed. We use a polypharmacology approach to identify potential drugs that can be used for the novel purpose (target). Of note, we have designed a multimodal stratagem to identify approved drugs with a potential antimalarial activity using computational drug reprofiling. Our investigations suggest that oxetacaine, simvastatin, repaglinide, aclidinium, propafenone, and lovastatin could be repurposed for malaria control and prevention.

Intrinsic Fluorescence of the Active and the Inactive Functional Forms of Human Thymidylate Synthase

The observables associated with protein intrinsic fluorescence - spectra, time decays, anisotropies - offer opportunities to monitor in real time and non-invasively a protein's functional form and its interchange with other forms with different functions. We employed these observables to sketch the fluorometric profiles of two functional forms of human thymidylate synthase (hTS), a homodimeric enzyme crucial for cell proliferation and thus targeted by anticancer drugs. The protein takes an active and an inactive form. Stabilization of the latter by peptides that, unlike classical hTS inhibitors, bind it at the monomer/monomer interface offers an alternative inhibition mechanism that promises to avoid the onset of drug resistance in anticancer therapy. The fluorescence features depicted herein can be used as tools to identify and quantify each of the two protein forms in solution, thus making it possible to investigate the kinetic and thermodynamic aspects of the active/inactive conformational interchange. Two examples of fluorometrically monitored interconversion kinetics are provided.

Crystal structures of nematode (parasitic T. spiralis and free living C. elegans), compared to mammalian, thymidylate synthases (TS). Molecular docking and molecular dynamics simulations in search for nematode-specific inhibitors of TS

Three crystal structures are presented of nematode thymidylate synthases (TS), including Caenorhabditis elegans (Ce) enzyme without ligands and its ternary complex with dUMP and Raltitrexed, and binary complex of Trichinella spiralis (Ts) enzyme with dUMP. In search of differences potentially relevant for the development of species-specific inhibitors of the nematode enzyme, a comparison was made of the present Ce and Ts enzyme structures, as well as binary complex of Ce enzyme with dUMP, with the corresponding mammalian (human, mouse and rat) enzyme crystal structures. To complement the comparison, tCONCOORD computations were performed to evaluate dynamic behaviors of mammalian and nematode TS structures. Finally, comparative molecular docking combined with molecular dynamics and free energy of binding calculations were carried out to search for ligands showing selective affinity to T. spiralis TS. Despite an overall strong similarity in structure and dynamics of nematode vs mammalian TSs, a pool of ligands demonstrating predictively a strong and selective binding to TsTS has been delimited. These compounds, the E63 family, locate in the dimerization interface of TsTS where they exert species-specific interactions with certain non-conserved residues, including hydrogen bonds with Thr174 and hydrophobic contacts with Phe192, Cys191 and Tyr152. The E63 family of ligands opens the possibility of future development of selective inhibitors of TsTS and effective agents against trichinellosis.

WITHDRAWN: Improving classification of protein binders for virtual drug screening by novel swarm-based feature selection techniques

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Discovery of potential ALK inhibitors by virtual screening approach

Crizotinib is an anticancer drug used for the treatment of non-small cell lung cancer. Evidences available suggest that there is a development of an acquired resistance against crizotinib action due to the emergence of several mutations in the ALK gene. It is therefore necessary to develop potent anti-cancer drugs for the treatment of crizotinib resistance non-small cell lung cancer types. In the present study, a novel class of lead molecule was identified using virtual screening, molecular docking and molecular dynamic approach. The virtual screening analysis was done using PubChem database by employing crizotinib as query and the data reduction was carried out by using molecular docking techniques. The bioavailability of the lead compounds was examined with the help of Lipinski rule of five. The screened lead molecules were analyzed for toxicity profiles, drug-likeness and other physico-chemical properties of drugs by OSIRIS program. Finally, molecular dynamics simulation was also performed to validate the binding property of the lead compound. Our analysis clearly indicates that CID 11562217, a nitrile containing compound (pyrazole-substituted aminoheteroaryl), could be the potential ALK inhibitor certainly helpful to overcome the drug resistance in non-small cell lung cancer.

Perturbation of genome integrity to fight pathogenic microorganisms

BACKGROUND

Resistance against antibiotics is unfortunately still a major biomedical challenge for a wide range of pathogens responsible for potentially fatal diseases.

SCOPE OF REVIEW

In this study, we aim at providing a critical assessment of the recent advances in design and use of drugs targeting genome integrity by perturbation of thymidylate biosynthesis.

MAJOR CONCLUSION

We find that research efforts from several independent laboratories resulted in chemically highly distinct classes of inhibitors of key enzymes within the routes of thymidylate biosynthesis. The present article covers numerous studies describing perturbation of this metabolic pathway in some of the most challenging pathogens like Mycobacterium tuberculosis, Plasmodium falciparum, and Staphylococcus aureus.

GENERAL SIGNIFICANCE

Our comparative analysis allows a thorough summary of the current approaches to target thymidylate biosynthesis enzymes and also include an outlook suggesting novel ways of inhibitory strategies. This article is part of a Special Issue entitled "Science for Life" Guest Editor: Dr. Austen Angell, Dr. Salvatore Magazù and Dr. Federica Migliardo.

Discovery of Potential, Non-Toxic Influenza Virus Inhibitor by Computational Techniques

Influenza infection continues to be a major problem in many parts of the world. Rimantadine is a first-line drug used to treat the influenza infection by targeting M2 proton channel. However, S31N mutation in M2 proton channel diminishes the efficiency of rimantadine and creates resistance. To address this issue, the present study was aimed to screen the effective lead candidate against drug resistance strain of influenza from DrugBank database. Initially, the lead molecules were filtered using Lipinski rule of five and the drug likeliness property. Subsequently, the data reduction was carried out by employing molecular docking study. Finally, molecular dynamics simulations techniques were performed to validate the lead compound. Most importantly, the -p LD50 of the screened lead molecule was calculated using CORAL software to estimate the Rat oral toxicity. Accordingly, memantine may possibly become a promising lead compound of rimantadine-resistant influenza virus strain.

Identification of potential inhibitors of H5N1 influenza A virus neuraminidase by ligand-based virtual screening approach

The neuraminidase (NA) of the influenza virus is the target of antiviral drug, oseltamivir. Recently, cases were reported that influenza virus becoming resistant to oseltamivir, necessitating the development of new long-acting antiviral compounds. In this report, a novel class of lead molecule with potential NA inhibitory activity was identified using a combination of virtual screening (VS), molecular docking, and molecular dynamic approach. The PubChem database was used to perform the VS analysis by employing oseltamivir as query. Subsequently, the data reduction was carried out by employing molecular docking study. Furthermore, the screened lead molecules were analyzed with respect to the Lipinski rule of five, drug-likeness, toxicity profiles, and other physico-chemical properties of drugs by suitable software program. Final screening was carried out by normal mode analysis and molecular dynamic simulation approach. The result indicates that CID 25145634, deuterium-enriched oseltamivir, become a promising lead compound and be effective in treating oseltamivir sensitive as well as resistant influenza virus strains.

Identification of druggable targets for Acinetobacter baumannii via subtractive genomics and plausible inhibitors for MurA and MurB

Emergence of the multidrug-resistant pathogens has rendered the current therapies ineffective thereby, resulting in the need for new drugs and drug targets. The accumulating protein sequence data has initiated a drift from classical drug discovery protocols to structure-based drug designing. In the present study, in silico subtractive genomics approach was implemented to find a set of potential drug targets present in an opportunist bacterial pathogen, Acinetobacter baumannii (A. baumannii). Out of the 43 targets identified, further studies for protein model building and lead-inhibitor identification were carried out on two cell-essential targets, MurA and MurB enzymes (of A. baumannii designated as MurAAb and MurBAb) involved in the peptidoglycan biosynthesis pathway of bacteria. The homology model built for each of them was further refined and validated using various available programs like PROCHECK, Errat, ProSA energy plots, etc. Compounds showing activity against MurA and MurB enzymes of other organisms were collected from the literature and were docked into the active site of MurAAb and MurBAb enzymes. Three inhibitors namely, T6361, carbidopa, and aesculin, showed maximum Glide score, hydrogen bonding interactions with the key amino acid residues of both the enzymes and acceptable ADME properties. Furthermore, molecular dynamics simulation studies on MurAAb-T6361 and MurBAb-T6361 complexes suggested that the ligand has a high binding affinity with both the enzymes and the hydrogen bonding with the key residues were stable in the dynamic condition also. Therefore, these ligands have been propsed as dual inhibitors and promising lead compounds for the drug design against MurAAb and MurBAb enzymes.

Tumor necrosis factor receptor superfamily 10B (TNFRSF10B): an insight from structure modeling to virtual screening for designing drug against head and neck cancer

BACKGROUND

Head and neck cancer (HNC) belongs to a group of heterogeneous disease with distinct patterns of behavior and presentation. TNFRSF10B, a tumor suppressor gene mapped on chromosome 8. Mutation in candidate gene is responsible for the loss of chromosome p arm which is frequently observed in head and neck tumors. TNFRSF10B inhibits tumor formation through apoptosis but deregulation encourages metastasis, migration and invasion of tumor cell tissues.

RESULTS

Structural modeling was performed by employing MODELLER (9v10). A suitable template [2ZB9] was retrieved from protein databank with query coverage and sequence identity of 84% and 30% respectively. Predicted Model evaluation form Rampage revealed 93.2% residues in favoured region, 5.7% in allowed region while only 1 residue is in outlier region. ERRAT and ProSA demonstrated 51.85% overall quality with a -1.08 Z-score of predicted model. Molecular Evolutionary Genetics Analysis (MEGA 5) tool was executed to infer an evolutionary history of TNFRSF10B candidate gene. Orthologs and paralogs [TNFRSF10A & TNFRSF10D] protein sequences of TNFRSF10B gene were retrieved for developed ancestral relationship. Topology of tree presenting TNFRSF10A gene considered as outgroup. Human and gorilla shared more than 90% similarities with conserved amino acid sequence. Virtual screening approach was appliedfor identification of novel inhibitors. Library (Mcule) was screened for novel inhibitors and utilized the scrutinized lead compounds for protein ligand docking. Screened lead compounds were further investigated for molecular docking studies. STRING server was employed to explore protein-protein interactions of TNFRSF10B target protein. TNFSF10 protein showed highest 0.999 confidence score and selected protein-protein docking by utilizing GRAMM-X server. In-silico docking results revealed I-58, S-90 and A-62 as most active interacting residues of TNFRSF10B receptor protein with R-130, S-156 and R-130 of TNFSF10B ligand protein.

CONCLUSION

Current research may provide a backbone for understanding structural and functional insights of TNFRSF10B protein. The designed novel inhibitors and predicted interactions might serve to inhibit the disease. Effective in-vitro potent ligands are required which will be helpful in future to design a drug to against Head and neck cancer disease. There is an urgent need for affective drug designing of head and neck cancer and computational tools for examining candidate genes more efficiently and accurately are required.

Virtual screening for oseltamivir-resistant a (H5N1) influenza neuraminidase from traditional Chinese medicine database: a combined molecular docking with molecular dynamics approach

The neuraminidase (NA) of the influenza virus is the target of antiviral drug, oseltamivir. Recently, cases are reported that Influenza virus becoming resistant to oseltamivir, necessitating the development of new long-acting antiviral compounds. Most importantly, H274Y mutation in neuraminidase exhibits high levels of resistance to oseltamivir. In this report, a novel class of lead molecule with potential NA inhibitory activity was found from the traditional Chinese medicine database (TCMD) using virtual screening approach. Initially ADME properties of the lead compounds were analyzed with respect to the Lipinski rule of five. Subsequently, the data reduction was carried out by employing molecular docking study. Final validation was done by means of molecular dynamic simulations. The toxicity profiles for the screened compound were also analyzed. The result indicates that neoglucobrassicin (a compound derived from TCMD) become a promising lead compound and be effective in treating oseltamivir-resistant influenza virus strains.

Diversity of nonribosomal peptide synthetase genes in the microbial metagenomes of marine sponges

Genomic mining revealed one major nonribosomal peptide synthetase (NRPS) phylogenetic cluster in 12 marine sponge species, one ascidian, an actinobacterial isolate and seawater. Phylogenetic analysis predicts its taxonomic affiliation to the actinomycetes and hydroxy-phenyl-glycine as a likely substrate. Additionally, a phylogenetically distinct NRPS gene cluster was discovered in the microbial metagenome of the sponge Aplysina aerophoba, which shows highest similarities to NRPS genes that were previously assigned, by ways of single cell genomics, to a Chloroflexi sponge symbiont. Genomic mining studies such as the one presented here for NRPS genes, contribute to on-going efforts to characterize the genomic potential of sponge-associated microbiota for secondary metabolite biosynthesis.

A Discovery Funnel for Nucleic Acid Binding Drug Candidates

Computational approaches are becoming increasingly popular for the discovery of drug candidates against a target of interest. Proteins have historically been the primary targets of many virtual screening efforts. While in silico screens targeting proteins has proven successful, other classes of targets, in particular DNA, remain largely unexplored using virtual screening methods. With the realization of the functional importance of many non-cannonical DNA structures such as G-quadruplexes, increased efforts are underway to discover new small molecules that can bind selectively to DNA structures. Here, we describe efforts to build an integrated in silico and in vitro platform for discovering compounds that may bind to a chosen DNA target. Millions of compounds are initially screened in silico for selective binding to a particular structure and ranked to identify several hundred best hits. An important element of our strategy is the inclusion of an array of possible competing structures in the in silico screen. The best hundred or so hits are validated experimentally for binding to the actual target structure by a high-throughput 96-well thermal denaturation assay to yield the top ten candidates. Finally, these most promising candidates are thoroughly characterized for binding to their DNA target by rigorous biophysical methods, including isothermal titration calorimetry, differential scanning calorimetry, spectroscopy and competition dialysis.This platform was validated using quadruplex DNA as a target and a newly discovered quadruplex binding compound with possible anti-cancer activity was discovered. Some considerations when embarking on virtual screening and in silico experiments are also discussed.

A mapping of drug space from the viewpoint of small molecule metabolism

Small molecule drugs target many core metabolic enzymes in humans and pathogens, often mimicking endogenous ligands. The effects may be therapeutic or toxic, but are frequently unexpected. A large-scale mapping of the intersection between drugs and metabolism is needed to better guide drug discovery. To map the intersection between drugs and metabolism, we have grouped drugs and metabolites by their associated targets and enzymes using ligand-based set signatures created to quantify their degree of similarity in chemical space. The results reveal the chemical space that has been explored for metabolic targets, where successful drugs have been found, and what novel territory remains. To aid other researchers in their drug discovery efforts, we have created an online resource of interactive maps linking drugs to metabolism. These maps predict the "effect space" comprising likely target enzymes for each of the 246 MDDR drug classes in humans. The online resource also provides species-specific interactive drug-metabolism maps for each of the 385 model organisms and pathogens in the BioCyc database collection. Chemical similarity links between drugs and metabolites predict potential toxicity, suggest routes of metabolism, and reveal drug polypharmacology. The metabolic maps enable interactive navigation of the vast biological data on potential metabolic drug targets and the drug chemistry currently available to prosecute those targets. Thus, this work provides a large-scale approach to ligand-based prediction of drug action in small molecule metabolism.

Ligand design by a combinatorial approach based on modeling and experiment: application to HLA-DR4

Combinatorial synthesis and large scale screening methods are being used increasingly in drug discovery, particularly for finding novel lead compounds. Although these "random" methods sample larger areas of chemical space than traditional synthetic approaches, only a relatively small percentage of all possible compounds are practically accessible. It is therefore helpful to select regions of chemical space that have greater likelihood of yielding useful leads. When three-dimensional structural data are available for the target molecule this can be achieved by applying structure-based computational design methods to focus the combinatorial library. This is advantageous over the standard usage of computational methods to design a small number of specific novel ligands, because here computation is employed as part of the combinatorial design process and so is required only to determine a propensity for binding of certain chemical moieties in regions of the target molecule. This paper describes the application of the Multiple Copy Simultaneous Search (MCSS) method, an active site mapping and de novo structure-based design tool, to design a focused combinatorial library for the class II MHC protein HLA-DR4. Methods for the synthesizing and screening the computationally designed library are presented; evidence is provided to show that binding was achieved. Although the structure of the protein-ligand complex could not be determined, experimental results including cross-exclusion of a known HLA-DR4 peptide ligand (HA) by a compound from the library. Computational model building suggest that at least one of the ligands designed and identified by the methods described binds in a mode similar to that of native peptides.

Thymidyl biosynthesis enzymes as antibiotic targets

The two long-known "classical" enzymes of uridyl-5-methylation, thymidylate synthase and ribothymidyl synthase, have been joined by two alternative methylation enzymes, flavin-dependent thymidylate synthase and folate-dependent ribothymidyl synthase. These two newly discovered enzymes have much in common: both contain flavin cofactors, utilize methylenetetrahydrofolate as a source of methyl group, and perform thymidylate synthesis via chemical pathways distinct from those of their classic counterparts. Several severe human pathogens (e.g., typhus, anthrax, tuberculosis, and more) depend on these "alternative" enzymes for reproduction. These and other distinctive properties make the alternative enzymes and their corresponding genes appealing targets for new antibiotics.

Antibacterial Agent Discovery Using Thymidylate Synthase Biolibrary Screening

Thymidylate synthase (TS, ThyA) catalyzes the reductive methylation of 2'-deoxyuridine 5'-monophosphate to 2'-deoxythymidine 5'-monophosphate, an essential precursor for DNA synthesis. A specific inhibition of this enzyme induces bacterial cell death. As a second round lead optimization design, new 1,2-naphthalein derivatives have been synthesized and tested against a TS-based biolibrary, including human thymidylate synthase (hTS). Docking studies have been performed to rationalize the experimentally observed affinity profiles of 1,2-naphthalein compounds toward Lactobacillus casei TS and hTS. The best TS inhibitors have been tested against a number of clinical isolates of Gram-positive-resistant bacterial strains. Compound 3,3-bis(3,5-dibromo-4-hydroxyphenyl)-1H,3H-naphtho[1,2-c]furan-1-one (5) showed significant antibacterial activity, no in vitro toxicity, and dose-response effects against Staphylococcus epidermidis (MIC=0.5-2.5 microg/mL) clinical isolate strains, which are resistant to at least 17 of the best known antibacterial agents, including vancomycin. So far this compound can be regarded as a leading antibacterial agent.

Harnessing the potential of communication-mediating domains for the biocombinatorial synthesis of nonribosomal peptides

The interaction between enzymes of a nonribosomal peptide synthetase (NRPS) complex relies on the interplay of compatible sets of donor and acceptor communication-mediating (COM) domains. Hence, these domains are essential for the formation of a defined biosynthetic template, thereby directing the synthesis of a specific peptide product. Without the selectivity provided by different sets of COM domains, NRPSs should form random biosynthetic templates, which would ultimately lead to combinatorial peptide synthesis. This study aimed to exploit this inherent combinatorial potential of COM domains. Based on sequence alignments between COM domains, the crosstalk between different biosynthetic systems was predicted and experimentally proven. Furthermore, key residues important for maintaining (or preventing) NRPS interaction were identified. Point mutation of one of these key residues within the acceptor COM domain of TycC1 was sufficient to shift its selectivity from the cognate donor COM of TycB3 toward the noncognate donor COM domain of TycB1. Finally, an artificial NRPS complex was constructed, constituted of enzymes derived from three different biosynthetic systems. By virtue of domain fusions, the interactions between all enzymes were established by the same set of COM domains. Because of the abrogated selectivity, this universal communication system was able to simultaneously form two biosynthetic complexes that catalyzed the combinatorial synthesis of different peptide products.

5,10-Methylene-5,6,7,8-tetrahydrofolate conformational transitions upon binding to thymidylate synthase: molecular mechanics and continuum solvent studies

We applied the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) approach to evaluate relative stability of the extended (flat) and C-shaped (bent) solution conformational forms of the 5,10-methylene-5,6,7,8-tetrahydrofolate (mTHF) molecule in aqueous solution. Calculations indicated that both forms have similar free energies in aqueous solution but detailed energy components are different. The bent solution form has lower intramolecular electrostatic and van der Waals interaction energies. The flat form has more favorable solvation free energy and lower contribution from the bond, angle and torsion angle molecular mechanical internal energies. We exploit these results and combine them with known crystallographic data to provide a model for the progressive binding of the mTHF molecule, a natural cofactor of thymidylate synthase (TS), to the complex forming in the TS-catalyzed reaction. We propose that at the time of initial weak binding in the open enzyme the cofactor molecule remains in a close balance between the flat and bent solution conformations, with neither form clearly favored. Later, thymidylate synthase undergoes conformational change leading to the closure of the active site and the mTHF molecule is withdrawn from the solvent. That effect shifts the thermodynamic equilibrium of the mTHF molecule toward the bent solution form. At the same time, burying the cofactor molecule in the closed active site produces numerous contacts between mTHF and protein that render change in the shape of the mTHF molecule. As a result, the bent solution conformer is converted to more strained L-shaped bent enzyme conformer of the mTHF molecule. The strain in the bent enzyme conformation allows for the tight binding of the cofactor molecule to the productive ternary complex that forms in the closed active site, and facilitates the protonation of the imidazolidine N10 atom, which promotes further reaction.

Hot Regions in Protein–Protein Interactions: The Organization and Contribution of Structurally Conserved Hot Spot Residues

Structurally conserved residues at protein-protein interfaces correlate with the experimental alanine-scanning hot spots. Here, we investigate the organization of these conserved, computational hot spots and their contribution to the stability of protein associations. We find that computational hot spots are not homogeneously distributed along the protein interfaces; rather they are clustered within locally tightly packed regions. Within the dense clusters, they form a network of interactions and consequently their contributions to the stability of the complex are cooperative; however the contributions of independent clusters are additive. This suggests that the binding free energy is not a simple summation of the single hot spot residue contributions. As expected, around the hot spot residues we observe moderately conserved residues, further highlighting the crucial role of the conserved interactions in the local densely packed environment. The conserved occurrence of these organizations suggests that they are advantageous for protein-protein associations. Interestingly, the total number of hydrogen bonds and salt bridges contributed by hot spots is as expected. Thus, H-bond forming residues may use a "hot spot for water exclusion" mechanism. Since conserved residues are located within highly packed regions, water molecules are easily removed upon binding, strengthening electrostatic contributions of charge-charge interactions. Hence, the picture that emerges is that protein-protein associations are optimized locally, with the clustered, networked, highly packed structurally conserved residues contributing dominantly and cooperatively to the stability of the complex. When addressing the crucial question of "what are the preferred ways of proteins to associate", these findings point toward a critical involvement of hot regions in protein-protein interactions.

Improving Specificity vs Bacterial Thymidylate Synthases throughN-Dansyl Modulation of Didansyltyrosine

N,O-Didansyl-L-tyrosine (DDT) represented the starting lead for further development of novel non-substrate-like inhibitors of bacterial thymidylate synthase. The N-dansyl structure modulation led to a submicromolar inhibitor of Lactobacillus casei TS (LcTS), which is highly specific with respect to human TS (hTS). Using molecular dynamics simulation, a binding mode for DDT vs LcTS was predicted, explaining activity and species-specificity along the series.

Computational analysis of ligand binding dynamics at the intermolecular hot spots with the aid of simulated tempering and binding free energy calculations

Equilibrium binding dynamics is studied for a panel of benzimidazole-containing compounds at the remodeled interface between human growth hormone (hGH) and the extracellular domain of its receptor (hGHbp), engineered by mutating to glycine hot spot residues T175 from the hormone and W104 from the receptor. Binding energetics is predicted in a good agreement with the experimental data for a panel of these small molecules that complement the engineered defect and restore the binding affinity of the wild-type hGH-hGHbp complex. The results of simulated tempering ligand dynamics at the protein-protein interface reveals a diversity of ligand binding modes that is consistent with the structural orientation of the benzimidazole ring which closely mimics the position of the mutated W104 hot spot residue in the wild-type hGH-hGHbp complex. This structural positioning of the benzimidazole core motif is shown to be a critical feature of the low-energy ligand conformations binding in the engineered cavity. The binding free energy analysis provides a plausible rationale behind the experimental dissociation constants and suggests a key role of ligand-protein van der Waals interactions in restoring binding affinity.

Virtual Screening Using Protein−Ligand Docking: Avoiding Artificial Enrichment

This study addresses a number of topical issues around the use of protein-ligand docking in virtual screening. We show that, for the validation of such methods, it is key to use focused libraries (containing compounds with one-dimensional properties, similar to the actives), rather than "random" or "drug-like" libraries to test the actives against. We also show that, to obtain good enrichments, the docking program needs to produce reliable binding modes. We demonstrate how pharmacophores can be used to guide the dockings and improve enrichments, and we compare the performance of three consensus-ranking protocols against ranking based on individual scoring functions. Finally, we show that protein-ligand docking can be an effective aid in the screening for weak, fragment-like binders, which has rapidly become a popular strategy for hit identification. All results presented are based on carefully constructed virtual screening experiments against four targets, using the protein-ligand docking program GOLD.

A molecular docking strategy identifies Eosin B as a non-active site inhibitor of protozoal bifunctional thymidylate synthase-dihydrofolate reductase

Protozoal parasites are unusual in that their thymidylate synthase (TS) and dihydrofolate reductase (DHFR) enzymes exist on a single polypeptide. In an effort to probe the possibility of substrate channeling between the TS and DHFR active sites and to identify inhibitors specific for bifunctional TS-DHFR, we used molecular docking to screen for inhibitors targeting the shallow groove connecting the two active sites. Eosin B is a 100 microm non-active site inhibitor of Leishmania major TS-DHFR identified by molecular docking. Eosin B slows both the TS and DHFR reaction rates. When Arg-283, a key residue to which eosin B is predicted to bind, is mutated to glutamate, however, eosin B only minimally inhibits the TS-DHFR reaction. Additionally, eosin B was found to be a 180 microm inhibitor of Toxoplasma gondii in both biochemical and cell culture assays.

Extended disordered proteins: targeting function with less scaffold

It has been estimated that a large fraction of cellular proteins are natively disordered. Current opinion largely holds that natively disordered proteins are more 'adaptive', leading to advantages in regulation and in binding diverse ligands. Here, we argue for another, simple, physically based reason. Disordered proteins often have large intermolecular interfaces, the size of which is dictated by protein function. For proteins to be stable as monomers with extensive interfaces, protein size would need to be 2-3 times larger. This would either increase cellular crowding or enlarge the size of the cell by 15-30%, owing to the increase in the sequence length. Smaller sizes of cells, proteins, DNA and RNA conserve energy. Thus, disordered proteins provide a simple yet elegant solution to having large intermolecular interfaces, but with smaller protein, genome and cell sizes.

Structure-based virtual screening: an overview

Enormous advances in genomics have resulted in a large increase in the number of potential therapeutic targets that are available for investigation. This growth in potential targets has increased the demand for reliable target validation, as well as technologies that can identify rapidly several quality lead candidates. Virtual screening, and in particular receptor-based virtual screening, has emerged as a reliable, inexpensive method for identifying leads. Although still an evolving method, advances in computational techniques have enabled virtual screening to have a positive impact on the discovery process. Here, the current strengths and weaknesses of the technology are discussed, and emphasis is placed on aspects of the work-flow of a virtual screening campaign, from preparation through to post-screening analysis.

Monte Carlo simulations of the peptide recognition at the consensus binding site of the constant fragment of human immunoglobulin G: the energy landscape analysis of a hot spot at the intermolecular interface

Monte Carlo simulations of molecular recognition at the consensus binding site of the constant fragment (Fc) of human immunoglobulin G (Ig) protein have been performed to analyze structural and thermodynamic aspects of binding for the 13-residue cyclic peptide DCAWHLGELVWCT. The energy landscape analysis of a hot spot at the intermolecular interface using alanine scanning and equilibrium-simulated tempering dynamics with the simplified, knowledge-based energy function has enabled the role of the protein hot spot residues in providing the thermodynamic stability of the native structure to be determined. We have found that hydrophobic interactions between the peptide and the Met-252, Ile-253, His-433, and His-435 protein residues are critical to guarantee the thermodynamic stability of the crystallographic binding mode of the complex. Binding free energy calculations, using a molecular mechanics force field and a solvation energy model, combined with alanine scanning have been conducted to determine the energetic contribution of the protein hot spot residues in binding affinity. The conserved Asn-434, Ser-254, and Tyr-436 protein residues contribute significantly to the binding affinity of the peptide-protein complex, serving as an energetic hot spot at the intermolecular interface. The results suggest that evolutionary conserved hot spot protein residues at the intermolecular interface may be partitioned in fulfilling thermodynamic stability of the native binding mode and contributing to the binding affinity of the complex.

Structure-based studies on species-specific inhibition of thymidylate synthase

Thymidylate synthase (TS) is a well-recognized target for anticancer chemotherapy. Due to its key role in the sole de novo pathway for thymidylate synthesis and, hence, DNA synthesis, it is an essential enzyme in all life forms. As such, it has been recently recognized as a valuable new target against infectious diseases. There is also a pressing need for new antimicrobial agents that are able to target strains that are drug resistant toward currently used drugs. In this context, species specificity is of crucial importance to distinguish between the invading microorganism and the human host, yet thymidylate synthase is among the most highly conserved enzymes. We combine structure-based drug design with rapid synthetic techniques and mutagenesis, in an iterative fashion, to develop novel antifolates that are not derived from the substrate and cofactor, and to understand the molecular basis for the observed species specificity. The role of structural and computational studies in the discovery of nonanalog antifolate inhibitors of bacterial TS, naphthalein and dansyl derivatives, and in the understanding of their biological activity profile, are discussed.

Principles of docking: An overview of search algorithms and a guide to scoring functions

The docking field has come of age. The time is ripe to present the principles of docking, reviewing the current state of the field. Two reasons are largely responsible for the maturity of the computational docking area. First, the early optimism that the very presence of the "correct" native conformation within the list of predicted docked conformations signals a near solution to the docking problem, has been replaced by the stark realization of the extreme difficulty of the next scoring/ranking step. Second, in the last couple of years more realistic approaches to handling molecular flexibility in docking schemes have emerged. As in folding, these derive from concepts abstracted from statistical mechanics, namely, populations. Docking and folding are interrelated. From the purely physical standpoint, binding and folding are analogous processes, with similar underlying principles. Computationally, the tools developed for docking will be tremendously useful for folding. For large, multidomain proteins, domain docking is probably the only rational way, mimicking the hierarchical nature of protein folding. The complexity of the problem is huge. Here we divide the computational docking problem into its two separate components. As in folding, solving the docking problem involves efficient search (and matching) algorithms, which cover the relevant conformational space, and selective scoring functions, which are both efficient and effectively discriminate between native and non-native solutions. It is universally recognized that docking of drugs is immensely important. However, protein-protein docking is equally so, relating to recognition, cellular pathways, and macromolecular assemblies. Proteins function when they are bound to other molecules. Consequently, we present the review from both the computational and the biological points of view. Although large, it covers only partially the extensive body of literature, relating to small (drug) and to large protein-protein molecule docking, to rigid and to flexible. Unfortunately, when reviewing these, a major difficulty in assessing the results is the non-uniformity in the formats in which they are presented in the literature. Consequently, we further propose a way to rectify it here.

Complexity and simplicity of ligand-macromolecule interactions: the energy landscape perspective

The energy landscape approach has contributed to recent progress in understanding the complexity and simplicity of ligand-macromolecule interactions. Significant advances in computational structure prediction of ligand-protein complexes have been made using approaches that include the effects of protein flexibility and incorporate a hierarchy of energy functions. The results suggest that the complexity of structure prediction in molecular recognition may be determined by low-resolution properties of the underlying binding energy landscapes and by the nature of the energy funnels near the native structures of the complexes.

Multiple diverse ligands binding at a single protein site: a matter of pre-existing populations

Here, we comment on the steadily increasing body of data showing that proteins with specificity actually bind ligands of diverse shapes, sizes, and composition. Such a phenomenon is not surprising when one considers that binding is a dynamic process with populations in equilibrium and that the shape of the binding site is strongly influenced by the molecular partner. It derives implicitly from the concept of populations. All proteins, specific and nonspecific, exist in ensembles of substates. If the library of ligands in solution is large enough, favorably matching ligands with altered shapes and sizes can be expected to bind, with a redistribution of the protein populations. Point mutations at spatially distant sites may exert large conformational rearrangements and hinge effects, consistent with mutations away from the binding site leading to population shifts and (cross-)drug resistance. A similar effect is observed in protein superfamilies, in which different sequences with similar topologies display similar large-scale dynamic motions. The hinges are frequently at analogous sites, yet with different substrate specificity. Similar topologies yield similar conformational isomers, although with different distributions of population times, owing to the change in the conditions, that is, the change in the sequences. In turn, different distributions relate to binding of different sizes and shapes. Hence, the binding site shape and size are defined by the ligand. They are not independent entities of fixed proportions and cannot be analyzed independently of the binding partner. Such a proposition derives from viewing proteins as dynamic distributions, presenting to the incoming ligands a range of binding site shapes. It illustrates how presumably specific binding molecules can bind multiple ligands. In terms of drug design, the ability of a single receptor to recognize many dissimilar ligands shows the need to consider more diverse molecules. It provides a rationale for higher affinity inhibitors that are not derived from substrates at their transition states and indicates flexible docking schemes.

Predicting and harnessing protein flexibility in the design of species-specific inhibitors of thymidylate synthase

BACKGROUND

Protein plasticity in response to ligand binding abrogates the notion of a rigid receptor site. Thus, computational docking alone misses important prospective drug design leads. Bacterial-specific inhibitors of an essential enzyme, thymidylate synthase (TS), were developed using a combination of computer-based screening followed by in-parallel synthetic elaboration and enzyme assay [Tondi et al. (1999) Chem. Biol. 6, 319-331]. Specificity was achieved through protein plasticity and despite the very high sequence conservation of the enzyme between species.

RESULTS

The most potent of the inhibitors synthesized, N,O-didansyl-L-tyrosine (DDT), binds to Lactobacillus casei TS (LcTS) with 35-fold higher affinity and to Escherichia coli TS (EcTS) with 24-fold higher affinity than to human TS (hTS). To reveal the molecular basis for this specificity, we have determined the crystal structure of EcTS complexed with DDT and 2'-deoxyuridine-5'-monophosphate (dUMP). The 2.0 A structure shows that DDT binds to EcTS in a conformation not predicted by molecular docking studies and substantially differently than other TS inhibitors. Binding of DDT is accompanied by large rearrangements of the protein both near and distal to the enzyme's active site with movement of C alpha carbons up to 6 A relative to other ternary complexes. This protein plasticity results in novel interactions with DDT including the formation of hydrogen bonds and van der Waals interactions to residues conserved in bacterial TS but not hTS and which are hypothesized to account for DDT's specificity. The conformation DDT adopts when bound to EcTS explains the activity of several other LcTS inhibitors synthesized in-parallel with DDT suggesting that DDT binds to the two enzymes in similar orientations.

CONCLUSIONS

Dramatic protein rearrangements involving both main and side chain atoms play an important role in the recognition of DDT by EcTS and highlight the importance of incorporating protein plasticity in drug design. The crystal structure of the EcTS/dUMP/DDT complex is a model system to develop more selective TS inhibitors aimed at pathogenic bacterial species. The crystal structure also suggests a general formula for identifying regions of TS and other enzymes that may be treated as flexible to aid in computational methods of drug discovery.

High-throughput docking for lead generation

Recent improvements in flexible docking technology may lead to a bigger role for computational methods in lead discovery. Although fast and accurate computational prediction of binding affinities for an arbitrary molecule is still beyond the limits of current methods, the docking and screening procedures can select small sets of likely lead candidates from large libraries of either commercially or synthetically available compounds.

Structure-based design and in-parallel synthesis of inhibitors of AmpC beta-lactamase

BACKGROUND

Group I beta-lactamases are a major cause of antibiotic resistance to beta-lactams such as penicillins and cephalosporins. These enzymes are only modestly affected by classic beta-lactam-based inhibitors, such as clavulanic acid. Conversely, small arylboronic acids inhibit these enzymes at sub-micromolar concentrations. Structural studies suggest these inhibitors bind to a well-defined cleft in the group I beta-lactamase AmpC; this cleft binds the ubiquitous R1 side chain of beta-lactams. Intriguingly, much of this cleft is left unoccupied by the small arylboronic acids.

RESULTS

To investigate if larger boronic acids might take advantage of this cleft, structure-guided in-parallel synthesis was used to explore new inhibitors of AmpC. Twenty-eight derivatives of the lead compound, 3-aminophenylboronic acid, led to an inhibitor with 80-fold better binding (2; K(i) 83 nM). Molecular docking suggested orientations for this compound in the R1 cleft. Based on the docking results, 12 derivatives of 2 were synthesized, leading to inhibitors with K(i) values of 60 nM and with improved solubility. Several of these inhibitors reversed the resistance of nosocomial Gram-positive bacteria, though they showed little activity against Gram-negative bacteria. The X-ray crystal structure of compound 2 in complex with AmpC was subsequently determined to 2.1 A resolution. The placement of the proximal two-thirds of the inhibitor in the experimental structure corresponds with the docked structure, but a bond rotation leads to a distinctly different placement of the distal part of the inhibitor. In the experimental structure, the inhibitor interacts with conserved residues in the R1 cleft whose role in recognition has not been previously explored.

CONCLUSIONS

Combining structure-based design with in-parallel synthesis allowed for the rapid exploration of inhibitor functionality in the R1 cleft of AmpC. The resulting inhibitors differ considerably from beta-lactams but nevertheless inhibit the enzyme well. The crystal structure of 2 (K(i) 83 nM) in complex with AmpC may guide exploration of a highly conserved, largely unexplored cleft, providing a template for further design against AmpC beta-lactamase.

Protein functional epitopes: hot spots, dynamics and combinatorial libraries

Recent studies increasingly point to the importance of structural flexibility and plasticity in proteins, highlighting the evolutionary advantage. There are an increasing number of cases in which given, presumably specific, binding sites have been shown to bind a range of ligands with different compositions and shapes. These studies have also revealed that evolution tends to find convergent solutions for stable intermolecular associations, largely via conservation of polar residues as hot spots of binding energy. On the other hand, the ability to bind multiple ligands at a given site is largely derived from hinge-based motions. The consideration of these two factors in functional epitopes allows more realism and robustness in the description of protein binding surfaces and, as such, in applications to mutants, modeled structures and design. Efficient multiple structure comparison and hinge-bending structure comparison tools enable the construction of combinatorial binding epitope libraries.

Docking molecules by families to increase the diversity of hits in database screens: computational strategy and experimental evaluation

Molecular docking programs screen chemical databases for novel ligands that fit protein binding sites. When one compound fits the site well, close analogs typically do the same. Therefore, many of the compounds that are found in such screens resemble one another. This reduces the variety and novelty of the compounds suggested. In an attempt to increase the diversity of docking hit lists, the Available Chemicals Directory was grouped into families of related structures. All members of every family were docked and scored, but only the best scoring molecule of a high-ranking family was allowed in the hit list. The identity and scores of the other members of these families were recorded as annotations to the best family member, but they were not independently ranked. This family-based docking method was compared with molecule-by-molecule docking in screens against the structures of thymidylate synthase, dihydrofolate reductase (DHFR), and the cavity site of the mutant T4 lysozyme Leu99 --> Ala (L99A). In each case, the diversity of the hit list increased, and more families of known ligands were found. To investigate whether the newly identified hits were sensible, we tested representative examples experimentally for binding to L99A and DHFR. Of the six compounds tested against L99A, five bound to the internal cavity. Of the seven compounds tested against DHFR, six inhibited the enzyme with apparent K(i) values between 0.26 and 100 microM. The segregation of potential ligands into families of related molecules is a simple technique to increase the diversity of candidates suggested by database screens. The general approach should be applicable to most docking methods. Proteins 2001;42:279-293.

Efficient identification of inhibitors targeting the closed active site conformation of the HPRT from Trypanosoma cruzi

BACKGROUND

Currently, only two drugs are recommended for treatment of infection with Trypanosoma cruzi, the etiologic agent of Chagas' disease. These compounds kill the trypomastigote forms of the parasite circulating in the bloodstream, but are relatively ineffective against the intracellular stage of the parasite life cycle. Neither drug is approved by the FDA for use in the US. The hypoxanthine phosphoribosyltransferase (HPRT) from T. cruzi is a possible new target for antiparasite chemotherapy. The crystal structure of the HPRT in a conformation approximating the transition state reveals a closed active site that provides a well-defined target for computational structure-based drug discovery.

RESULTS

A flexible ligand docking program incorporating a desolvation correction was used to screen the Available Chemicals Directory for inhibitors targeted to the closed conformation of the trypanosomal HPRT. Of 22 potential inhibitors identified, acquired and tested, 16 yielded K(i)'s between 0.5 and 17 microM versus the substrate phosphoribosylpyrophosphate. Surprisingly, three of eight compounds tested were effective in inhibiting the growth of parasites in infected mammalian cells.

CONCLUSIONS

This structure-based docking method provided a remarkably efficient path for the identification of inhibitors targeting the closed conformation of the trypanosomal HPRT. The inhibition constants of the lead inhibitors identified are unusually favorable, and the trypanostatic activity of three of the compounds in cell culture suggests that they may provide useful starting points for drug design for the treatment of Chagas' disease.