In silico structure-based design of enhanced peptide inhibitors targeting RNA polymerase PAN-PB1C interaction

Developing antivirals for influenza A virus (FluA) has become more challenging due to high range of antigenic mutation and increasing numbers of drug-resistant viruses. Finding a selective inhibitor to target highly conserved region of protein-protein interactions interface, thereby increasing its efficiency against drug resistant virus could be highly beneficial. In this study, we used in silico approach to derive FluAPep1 from highly conserved region, PA_N-PB1_C interface and generated 121 FluAPep1 analogues. Interestingly, we found that the FluAPep1 interaction region in the PA_N domain are highly conserved in many FluA subtypes. Especially, FluAPep1 targets two pandemic FluA strains, H1N1/avian/2009 and H3N2/Victoria/1975. All of these FluA subtypes PA_N domain (H1N1/H3N2CAN/H3N2VIC/H7N1/H7N2) were superimposed with PA_N domain from H17N10 and the calculated root mean standards deviations were less than 3 Å. FlexPepDock analysis revealed that FluAPep1 exhibited higher binding affinity (score -246.155) with the PA_N domain. In addition, around 86% of non-hot spot mutated peptides (FluAPep28-122) showed enhanced binding affinity with PA_N domain. ToxinPred analysis confirmed that designed peptides were non-toxic. Thus, FluAPep1 and its analogues has potential to be further developed into an antiviral treatment against FluA infection.     

Mini-review: computational structure-based design of inhibitors that target protein surfaces

Finding drugs that inhibit protein-protein interactions is usually difficult. While computer-aided design is used widely to facilitate the drug discovery process for protein targets with well-defined binding pockets, its application to the design of inhibitors targeting a protein surface is very limited. In this mini-review we address two aspects of this issue: firstly, we overview the current state of design methodology for inhibitors specifically targeting protein surfaces, and secondly, we briefly outline recent advances in computational methods for structure-based drug design. These methods are closely related to protein docking and protein recognition, the difference being that in ligand design, ligands are built on a fragment-by-fragment basis. A novel scheme of computational combinatorial ligand design developed for the design of inhibitors that interfere with protein-protein interaction is described in detail. Current applications and limitations of this methodology, as well as its future prospects, are discussed.     

A structure-based design approach to advance the allyltyrosine-based series of HIV integrase inhibitors

As of mid-2017, only one structure of the human immunodeficiency virus (HIV) integrase core domain co-crystallised with an active site inhibitor was reported. In this structure (1QS4), integrase is complexed with a diketo-acid based strand-transfer inhibitor (INSTI). This structure has been a preferred platform for the structure-based design of INSTIs despite concerns relating to structural irregularities arising from crystallographic packing effects. A survey of the current pool of 297 reported integrase catalytic core structures indicated that the anatomy of the active site in the complex structure 1QS4 exhibits subtle variations relative to all other structures examined. Consequently, the 1QS4 structure was employed for docking studies. From the docking of twenty-seven allyltyrosine analogues, a 3-point inhibitor binding motif required for activity was established and successfully utilised in the development of a tripeptide displaying an EC₅₀ value of 10 ± 5 μM in HIV infected human T-cells. Additional docking of “in-house” compound libraries unearthed a methyl ester based nitrile derivative displaying an IC₅₀ value of 0.5 μM in a combined 3′-processing and strand-transfer assay.     

The structure-based design of Mdm2/Mdmx-p53 inhibitors gets serious

The p53 protein is the cell's principal bastion of defense against tumor-associated DNA damage. Commonly referred as a "guardian of the genome", p53 is responsible for determining the fate of the cell when the integrity of its genome is damaged. The development of tumors requires breaching this defense line. All known tumor cells either mutate the p53 gene, or in a similar number of cases, use internal cell p53 modulators, Mdm2 and Mdmx proteins, to disable its function. The release of functional p53 from the inhibition by Mdm2 and Mdmx should in principle provide an efficient, nongenotoxic means of cancer therapy. In recent years substantial progress has been made in developing novel p53-activating molecules thanks to several reported crystal structures of Mdm2/x in complex with p53-mimicking peptides and nonpeptidic drug candidates. Understanding the structural attributes of ligand binding holds the key to developing novel, highly effective, and selective drug candidates. Two low-molecular-weight compounds have just recently progressed into early clinical studies.     

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.     

Computational drug design accommodating receptor flexibility: the relaxed complex scheme

A novel computational methodology for drug design that accommodates receptor flexibility is described. This "relaxed-complex" method recognizes that ligand may bind to conformations that occur only rarely in the dynamics of the receptor. We have shown that the ligand-enzyme binding modes are very sensitive to the enzyme conformations, and our approach is capable of finding the best ligand-enzyme complexes. This new method serves as the computational analog of the experimental "SAR by NMR" and "tether" methods, which permit a building block approach for constructing a very potent drug.     

A structure-based design approach for the identification of novel inhibitors: application to an alanine racemase

We report a new structure-based strategy for the identification of novel inhibitors. This approach has been applied to Bacillus stearothermophilus alanine racemase (AlaR), an enzyme implicated in the biosynthesis of the bacterial cell wall. The enzyme catalyzes the racemization of l- and d-alanine using pyridoxal 5-phosphate (PLP) as a cofactor. The restriction of AlaR to bacteria and some fungi and the absolute requirement for d-alanine in peptidoglycan biosynthesis make alanine racemase a suitable target for drug design. Unfortunately, known inhibitors of alanine racemase are not specific and inhibit the activity of other PLP-dependent enzymes, leading to neurological and other side effects.This article describes the development of a receptor-based pharmacophore model for AlaR, taking into account receptor flexibility (i.e. a `dynamic' pharmacophore model). In order to accomplish this, molecular dynamics (MD) simulations were performed on the full AlaR dimer from Bacillus stearothermophilus (PDB entry, 1sft) with a d-alanine molecule in one active site and the non-covalent inhibitor, propionate, in the second active site of this homodimer. The basic strategy followed in this study was to utilize conformations of the protein obtained during MD simulations to generate a dynamic pharmacophore model using the property mapping capability of the LigBuilder program. Compounds from the Available Chemicals Directory that fit the pharmacophore model were identified and have been submitted for experimental testing.The approach described here can be used as a valuable tool for the design of novel inhibitors of other biomolecular targets.     

The estrogen receptor: a structure-based approach to the design of new specific hormone-receptor combinations

Background: The specificity of hormone action arises from complementary steric and electronic interactions between a hormonal ligand and its cognate receptor. An analysis of such key ligand-receptor contact sites, often delineated by mutational mapping and X-ray crystallographic studies, can suggest ways in which hormone-receptor specificity might be altered.Results: We have altered the hormonal specificity of the estrogen receptor alpha (ER) by making 'coordinated' changes in the A-ring of the ligand estradiol and in the A-ring binding subpocket of ER. These changes were designed to maintain a favorable interaction when both E and ER are changed, but to disfavor interaction when only E or ER is changed. We have evaluated several of these altered ligand and receptor pairs in quantitative ligand binding and reporter gene assays.Conclusions: In best cases, the new interaction is sufficiently favorable and orthogonal so as to represent the creation of a new hormone specificity, which might be useful in the regulation of transgene activity.     

An improved relaxed complex scheme for receptor flexibility in computer-aided drug design

The interactions among associating (macro)molecules are dynamic, which adds to the complexity of molecular recognition. While ligand flexibility is well accounted for in computational drug design, the effective inclusion of receptor flexibility remains an important challenge. The relaxed complex scheme (RCS) is a promising computational methodology that combines the advantages of docking algorithms with dynamic structural information provided by molecular dynamics (MD) simulations, therefore explicitly accounting for the flexibility of both the receptor and the docked ligands. Here, we briefly review the RCS and discuss new extensions and improvements of this methodology in the context of ligand binding to two example targets: kinetoplastid RNA editing ligase 1 and the W191G cavity mutant of cytochrome c peroxidase. The RCS improvements include its extension to virtual screening, more rigorous characterization of local and global binding effects, and methods to improve its computational efficiency by reducing the receptor ensemble to a representative set of configurations. The choice of receptor ensemble, its influence on the predictive power of RCS, and the current limitations for an accurate treatment of the solvent contributions are also briefly discussed. Finally, we outline potential methodological improvements that we anticipate will assist future development. Rommie E. Amaro and Riccardo Baron contributed equally to this work.     

The process of structure-based drug design

The field of structure-based drug design is a rapidly growing area in which many successes have occurred in recent years. The explosion of genomic, proteomic, and structural information has provided hundreds of new targets and opportunities for future drug lead discovery. This review summarizes the process of structure-based drug design and includes, primarily, the choice of a target, the evaluation of a structure of that target, the pivotal questions to consider in choosing a method for drug lead discovery, and evaluation of the drug leads. Key principles in the field of structure-based drug design will be illustrated through a case study that explores drug design for AmpC beta-lactamase.     

Acrosin structure-based design,synthesis and biological activities of 7-azaindol derivatives as new acrosin inhibitors

A series of 7-azaindol derivatives were designed based on the homologous 3D model of human acrosin.These compounds were synthesized and evaluated for their human acrosin inhibitory activities in vitro.Compounds 7a,7i,7j,7k and 7n showed highly inhibitory activity against human acrosin.The three-dimensional structure-activity relationship was investigated through a CoMFA model,which provided valuable information to further study of potential human acrosin inhibitors.     

Nonpeptide inhibitors of cathepsin G: optimization of a novel beta-ketophosphonic acid lead by structure-based drug design

The serine protease cathepsin G (EC 3.4.21.20; Cat G), which is stored in the azurophilic granules of neutrophils (polymorphonuclear leukocytes) and released on degranulation, has been implicated in various pathological conditions associated with inflammation. By employing high-throughput screening, we identified beta-ketophosphonic acid 1 as a moderate inhibitor of Cat G (IC(50) = 4.1 microM). We were fortunate to obtain a cocrystal of 1 with Cat G and solve its structure by X-ray crystallography (3.5 A). Structural details from the X-ray analysis of 1.Cat G served as a platform for optimization of this lead compound by structure-based drug design. With the aid of molecular modeling, substituents were attached to the 3-position of the 2-naphthyl ring of 1, which occupies the S1 pocket of Cat G, to provide an extension into the hydrophobic S3 region. Thus, we arrived at analogue 7 with an 80-fold potency improvement over 1 (IC(50) = 53 nM). From these results, it is evident that the beta-ketophosphonic acid unit can form the basis for a novel class of serine protease inhibitors.     

Identification of cylin-dependent kinase 1 inhibitors of a new chemical type by structure-based design and database searching

We have selected cyclin-dependent kinase 1 (CDK1), an enzyme participating in the regulation of the cell cycle, as a target in our efforts to discover new antitumor agents. By exploiting available structural information, we designed an ATP-site directed ligand scaffold that allowed us to identify 4-(3-methyl-1,4-dioxo-1,4-dihydro-naphthalen-2-ylamino)-benzenesulfonamide as a new potent inhibitor of CDK1 in a subsequent database search. The synthesis and testing of some analogues confirmed the interest of this class of compounds as novel CDK1 inhibitors.     

Generation and selection of novel estrogen receptor ligands using the de novo structure-based design tool, SkelGen

A de novo design approach to generating novel estrogen receptor (ER) ligands is described. The SkelGen program was used to generate ligands in the active sites of seven crystal structures of ERalpha. Seventeen high-scoring, diverse structures were selected from the SkelGen output and synthesized without introducing any modifications to the structures. Five ligands, four of which are novel, showed < or = 25 microM affinity, with the best compound displaying an IC50 of 340 nM. SkelGen can, therefore, be a powerful tool for designing active molecules.     

Limiting assumptions in structure-based design: binding entropy

In order to deal with the complexity of biological systems at the atomic level, limiting assumptions are often made which do not reflect the reality of the system under study. One example is the assumption that the entropy of binding of the macromolecule is not influenced significantly by the different ligands. Recent experimental data on ligands binding to HIV-1 protease challenge this assumption.     

Impact of mobility on structure-based drug design for the MMPs

Structure-based approaches for drug design generally do not incorporate solvent effects and dynamic information to predict inhibitor-binding affinity because of practical limitations. The matrix metalloproteinases (MMPs) have previously been demonstrated to exhibit significant mobility in their active sites. This dynamic characteristic significantly complicates the drug design process based on static structures, which was clearly observed for a class of hydroxamic acids containing a butynyl moiety. Compound 1 was expected to be selective against MMP-1 based on predicted steric clashes between the butynyl P1' group and the S1' pocket, but the observation of complex inhibitor dynamics in the NMR structure of MMP-1:1 provides an explanation for the low nanomolar binding to MMP-1.     

Rational structure-based design of a novel carboxypeptidase R inhibitor

A novel carboxypeptidase R (CPR) inhibitor, related to potato carboxypeptidase inhibitor (PCI), was designed using rational structure-based strategies, incorporating two principle facts: CPR has a strong affinity for basic amino acids, and the two lysine and arginine residues of PCI are orientated in the same direction and held in close spatial proximity by three disulfide bonds. Initially, a disulfide-bonded fragment of PCI was synthesized showing weak competitive inhibitory activity against CPR. Subsequently, a smaller linear 9-mer peptide, designated CPI-2KR, was designed/synthesized and found to be a more efficient competitive inhibitor of CPR, without affecting the activity of the other plasma carboxypeptidase, carboxypeptidase N. In vitro studies showed that, together with tissue plasminogen activator, CPI-2KR synergistically accelerated fibrinolysis, representing a lead compound for the design of smaller organic molecules for use in thrombolytic therapy.     

Protein flexibility and species specificity in structure-based drug discovery: dihydrofolate reductase as a test system

In structure-based drug discovery, researchers would like to identify all possible scaffolds for a given target. However, techniques that push the boundaries of chemical space could lead to many false positives or inhibitors that lack specificity for the target. Is it possible to broadly identify the appropriate chemical space for the inhibitors and yet maintain target specificity? To address this question, we have turned to dihydrofolate reductase (DHFR), a well-studied metabolic enzyme of pharmacological relevance. We have extended our multiple protein structure (MPS) method for receptor-based pharmacophore models to use multiple X-ray crystallographic structures. Models were created for DHFR from human and Pneumocystis carinii. These models incorporate a fair degree of protein flexibility and are highly selective for known DHFR inhibitors over drug-like non-inhibitors. Despite sharing a highly conserved active site, the pharmacophore models reflect subtle differences between the human and P. carinii forms, which identify species-specific, high-affinity inhibitors. We also use structures of DHFR from Candida albicans as a counter example. The available crystal structures show little flexibility, and the resulting models give poorer performance in identifying species-specific inhibitors. Therapeutic success for this system may depend on achieving species specificity between the related human host and these key fungal targets. The MPS technique is a promising advance for structure-based drug discovery for DHFR and other proteins of biomedical interest.     

An integrated approach to ligand- and structure-based drug design: development and application to a series of serine protease inhibitors

A novel approach was developed to rationally interface structure- and ligand-based drug design through the rescoring of docking poses and automated generation of molecular alignments for 3D quantitative structure-activity relationship investigations. The procedure was driven by a genetic algorithm optimizing the value of a novel fitness function, accounting simultaneously for best regressions among binding-energy docking scores and affinities and for minimal geometric deviations from properly established crystal-based binding geometry. The GRID/CPCA method, as implemented in GOLPE, was used to feature molecular determinants of ligand binding affinity for each molecular alignment. In addition, unlike standard procedures, a novel multipoint equation was adopted to predict the binding affinity of ligands in the prediction set. Selectivity was investigated through square plots reporting experimental versus recalculated binding affinities on the targets under examination. The application of our approach to the modeling of affinity data of a large series of 3-amidinophenylalanine inhibitors of thrombin, trypsin, and factor Xa generated easily interpretable and independent models with robust statistics. As a further validation study, our approach was successfully applied to a series of 3,4,7-substituted coumarins, acting as selective MAO-B inhibitors.     

Exploring experimental sources of multiple protein conformations in structure-based drug design

Receptor flexibility must be incorporated into structure-based drug design in order to portray a more accurate representation of a protein in solution. Our approach is to generate pharmacophore models based on multiple conformations of a protein and is very similar to solvent mapping of hot spots. Previously, we had success using computer-generated conformations of apo human immunodeficiency virus-1 protease (HIV-1p). Here, we examine the use of an NMR ensemble versus a collection of crystal structures, and we compare back to our previous study based on computer-generated conformations. To our knowledge, this is the first direct comparison of an NMR ensemble and a collection of crystal structures to incorporate protein flexibility in structure-based drug design. To provide an accurate comparison between the experimental sources, we used bound structures for our multiple protein structure (MPS) pharmacophore models. The models from an NMR ensemble and a collection of crystal structures were both able to discriminate known HIV-1p inhibitors from decoy molecules and displayed superior performance over models created from single conformations of the protein. Although the active-site conformations were already predefined by bound ligands, the use of MPS allows us to overcome the cross-docking problem and generate a model that does not simply reproduce the chemical characteristics of a specific ligand class. We show that there is more structural variation between 28 structures in an NMR ensemble than 90 crystal structures bound to a variety of ligands. MPS models from both sources performed well, but the model determined using the NMR ensemble appeared to be the most general yet accurate representation of the active site. This work encourages the use of NMR models in structure-based design.