The integration of genomic and structural information in the development of high affinity plasmepsin inhibitors

The plasmepsins are key enzymes in the life cycle of the Plasmodium parasites responsible for malaria. Since plasmepsin inhibition leads to parasite death, these enzymes have been acknowledged to be important targets for the development of new antimalarial drugs. The development of effective plasmepsin inhibitors, however, is compounded by their genomic diversity which gives rise not to a unique target for drug development but to a family of closely related targets. Successful drugs will have to inhibit not one but several related enzymes with high affinity. Structure-based drug design against heterogeneous targets requires a departure from the classic 'lock-and-key' paradigm that leads to the development of conformationally constrained molecules aimed at a single target. Drug molecules designed along those principles are usually rigid and unable to adapt to target variations arising from naturally occurring genetic polymorphisms or drug-induced resistant mutations. Heterogeneous targets need adaptive drug molecules, characterised by the presence of flexible elements at specific locations that sustain a viable binding affinity against existing or expected polymorphisms. Adaptive ligands have characteristic thermodynamic signatures that distinguish them from their rigid counterparts. This realisation has led to the development of rigorous thermodynamic design guidelines that take advantage of correlations between the structure of lead compounds and the enthalpic and entropic components of the binding affinity. In this paper, we discuss the application of the thermodynamic approach to the development of high affinity (K(i) - pM) plasmepsin inhibitors. In particular, a family of allophenylnorstatine-based compounds is evaluated for their potential to inhibit a wide spectrum of plasmepsins.     

High-affinity inhibition of a family of Plasmodium falciparum proteases by a designed adaptive inhibitor

Drug development against viral or microbial targets is often compounded by the existence of naturally occurring polymorphisms or drug resistant mutations. In the case of Plasmodium falciparum, the etiological agent of malaria, four related and essential proteases, plasmepsin I, II, and IV and the histo-aspartyl protease (HAP), have been identified in the food vacuole of the parasite. Since all of these enzymes are involved in the hemoglobin degradation of infected victims, the simultaneous inhibition of the four enzymes can be expected to lead to a faster starvation of the parasite and to delay the onset of drug resistance, since four enzymes will need to mutate in a concerted fashion. This study describes the design of an adaptive inhibitor intended to inhibit the entire plasmepsin family. Adaptive inhibitors bind with extremely high affinity to a primary target within the family and maintain significant affinity against the remaining members. This objective is accomplished by engineering the strongest and most specific interactions of the inhibitor against conserved regions of the binding site and by accommodating target variations by means of flexible asymmetric functional groups. Using this approach, we have designed an inhibitor with subnanomolar affinity (0.5 nM) against the primary target, plasmepsin II, and with no loss or a very small loss of affinity against plasmepsin IV, I, and HAP (K(i) ratios of 0.4, 7.1, and 17.7, respectively). The core of the inhibitor is defined by an allophenylnorstatine scaffold. Adaptability is provided by an asymmetric amino indanol functional group facing one of the key variable regions in the binding site. Adaptive inhibitors, which display high affinity against several variations of a primary target, are expected to play an important role in the chemotherapy of infectious diseases.     

RNA as a small molecule druggable target

Small molecule drugs have readily been developed against many proteins in the human proteome, but RNA has remained an elusive target for drug discovery. Increasingly, we see that RNA, and to a lesser extent DNA elements, show a persistent tertiary structure responsible for many diverse and complex cellular functions. In this digest, we have summarized recent advances in screening approaches for RNA targets and outlined the discovery of novel, drug-like small molecules against RNA targets from various classes and therapeutic areas. The link of structure, function, and small-molecule Druggability validates now for the first time that RNA can be the targets of therapeutic agents.     

RNAapt3D: RNA aptamer 3D-structural modeling database

RNA aptamers are oligonucleotides with high binding affinity and specificity for target molecules and are expected to be a new generation of therapeutic molecules and targeted delivery materials. The tertiary structure of RNA molecules and RNA-protein interaction sites are increasingly important as potential targets for new drugs. The pathological mechanisms of diseases must be understood in detail to guide drug design. In developing RNA aptamers as drugs, information about the interaction mechanisms and structures of RNA aptamer-target protein complexes are useful. We constructed a database, RNA aptamer 3D-structural modeling (RNAapt3D), consisting of RNA aptamer data that are potential drug candidates. The database includes RNA sequences and computationally predicted RNA tertiary structures based on secondary structures and implements methods that can be used to predict unknown structures of RNA aptamer-target molecule complexes. RNAapt3D should enable the design of RNA aptamers for target molecules and improve the efficiency and productivity of candidate drug selection. RNAapt3D can be accessed at https://rnaapt3d.medals.jp.     

SARS-CoV-2 Mutations and their Viral Variants

Mutations in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) occur spontaneously during replication. Thousands of mutations have accumulated and continue to since the emergence of the virus. As novel mutations continue appearing at the scene, naturally, new variants are increasingly observed.Since the first occurrence of the SARS-CoV-2 infection, a wide variety of drug compounds affecting the binding sites of the virus have begun to be studied. As the drug and vaccine trials are continuing, it is of utmost importance to take into consideration the SARS-CoV-2 mutations and their respective frequencies since these data could lead the way to multi-drug combinations. The lack of effective therapeutic and preventive strategies against human coronaviruses (hCoVs) necessitates research that is of interest to the clinical applications.The reason why the mutations in glycoprotein S lead to vaccine escape is related to the location of the mutation and the affinity of the protein. At the same time, it can be said that variations should occur in areas such as the receptor-binding domain (RBD), and vaccines and antiviral drugs should be formulated by targeting more than one viral protein.In this review, a literature survey in the scope of the increasing SARS-CoV-2 mutations and the viral variations is conducted. In the light of current knowledge, the various disguises of the mutant SARS-CoV-2 forms and their apparent differences from the original strain are examined as they could possibly aid in finding the most appropriate therapeutic approaches.     

An immuno-chemo-proteomics method for drug target deconvolution

Chemical proteomics is an emerging technique for drug target deconvolution and profiling the toxicity of known drugs. With the use of this technique, the specificity of a small molecule inhibitor toward its potential targets can be characterized and information thus obtained can be used in optimizing lead compounds. Most commonly, small molecules are immobilized on solid supports and used as affinity chromatography resins to bind targets. However, it is difficult to evaluate the effect of immobilization on the affinity of the compounds to their targets. Here, we describe the development and application of a soluble probe where a small molecule was coupled with a peptide epitope which was used to affinity isolate binding proteins from cell lysate. The soluble probe allowed direct verification that the compound after coupling with peptide epitope retained its binding characteristics. The PKC-alpha inhibitor Bisindolylmaleimide-III was coupled with a peptide containing the FLAG epitope. Following incubation with cellular lysates, the compound and associated proteins were affinity isolated using anti-FLAG antibody beads. Using this approach, we identified the known Bisindolylmaleimide-III targets, PKC-alpha, GSK3-beta, CaMKII, adenosine kinase, CDK2, and quinine reductase type 2, as well as previously unidentified targets PKAC-alpha, prohibitin, VDAC and heme binding proteins. This method was directly compared to the solid-phase method (small molecule was immobilized to a solid support) providing an orthogonal strategy to aid in target deconvolution and help to eliminate false positives originating from nonspecific binding of the proteins to the matrix.     

Identifying Novel Drug Targets by iDTPnd: A Case Study of Kinase Inhibitors

Current FDA-approved kinase inhibitors cause diverse adverse effects, some of which are due to the mechanism-independent effects of these drugs. Identifying these mechanism-independent interactions could improve drug safety and support drug repurposing. Here, we develop iDTPnd (integrated Drug Target Predictor with negative dataset), a computational approach for large-scale discovery of novel targets for known drugs. For a given drug, we construct a positive structural signature as well as a negative structural signature that captures the weakly conserved structural features of drug-binding sites. To facilitate assessment of unintended targets, iDTPnd also provides a docking-based interaction score and its statistical significance. We confirm the interactions of sorafenib, imatinib, dasatinib, sunitinib, and pazopanib with their known targets at a sensitivity of 52% and a specificity of 55%. We also validate 10 predicted novel targets by using in vitro experiments. Our results suggest that proteins other than kinases, such as nuclear receptors, cytochrome P450, and MHC class I molecules, can also be physiologically relevant targets of kinase inhibitors. Our method is general and broadly applicable for the identification of protein–small molecule interactions, when sufficient drug–target 3D data are available. The code for constructing the structural signatures is available at https://sfb.kaust.edu.sa/Documents/iDTP.zip.     

Novel putative drugs and key initiating genes for neurodegenerative disease determined using network-based genetic integrative analysis

Understanding the genetic causes of neurodegenerative disease (ND) can be useful for their prevention and treatment. Among the genetic variations responsible for ND, heritable germline variants have been discovered in genome-wide association studies (GWAS), and nonheritable somatic mutations have been discovered in sequencing projects. Distinguishing the important initiating genes in ND and comparing the importance of heritable and nonheritable genetic variants for treating ND are important challenges. In this study, we analysed GWAS results, somatic mutations and drug targets of ND from large databanks by performing directed network-based analysis considering a randomised network hypothesis testing procedure. A disease-associated biological network was created in the context of the functional interactome, and the nonrandom topological characteristics of directed-edge classes were interpreted. Hierarchical network analysis indicated that drug targets tend to lie upstream of somatic mutations and germline variants. Furthermore, using directed path length information and biological explanations, we provide information on the most important genes in these created node classes and their associated drugs. Finally, we identified nine germline variants overlapping with drug targets for ND, seven somatic mutations close to drug targets from the hierarchical network analysis and six crucial genes in controlling other genes from the network analysis. Based on these findings, some drugs have been proposed for treating ND via drug repurposing. Our results provide new insights into the therapeutic actionability of GWAS results and somatic mutations for ND. The interesting properties of each node class and the existing relationships between them can broaden our knowledge of ND.     

Rapid and accurate structure-based therapeutic peptide design using GPU accelerated thermodynamic integration

Peptide-based therapeutics are an alternative to small molecule drugs as they offer superior specificity, lower toxicity, and easy synthesis. Here we present an approach that leverages the dramatic performance increase afforded by the recent arrival of GPU accelerated thermodynamic integration (TI). GPU TI facilitates very fast, highly accurate binding affinity optimization of peptides against therapeutic targets. We benchmarked TI predictions using published peptide binding optimization studies. Prediction of mutations involving charged side-chains was found to be less accurate than for non-charged, and use of a more complex 3-step TI protocol was found to boost accuracy in these cases. Using the 3-step protocol for non-charged side-chains either had no effect or was detrimental. We use the benchmarked pipeline to optimize a peptide binding to our recently discovered cancer target: EME1. TI calculations predict beneficial mutations using both canonical and non-canonical amino acids. We validate these predictions using fluorescence polarization and confirm that binding affinity is increased. We further demonstrate that this increase translates to a significant reduction in pancreatic cancer cell viability.     

The use of genomic variants to drive drug repurposing for chronic hepatitis B

BackgroundOne of the main challenges in personalized medicine is to establish and apply a large number of variants from genomic databases into clinical diagnostics and further facilitate genome-driven drug repurposing. By utilizing biological chronic hepatitis B infection (CHB) risk genes, our study proposed a systematic approach to use genomic variants to drive drug repurposing for CHB.MethodThe genomic variants were retrieved from the Genome-Wide Association Study (GWAS) and Phenome-Wide Association Study (PheWAS) databases. Then, the biological CHB risk genes crucial for CHB progression were prioritized based on the scoring system devised with five strict functional annotation criteria. A score of ≥ 2 were categorized as the biological CHB risk genes and further shed light on drug target genes for CHB treatments. Overlapping druggable targets were identified using two drug databases (DrugBank and Drug-Gene Interaction Database (DGIdb)).ResultsA total of 44 biological CHB risk genes were screened based on the scoring system from five functional annotation criteria. Interestingly, we found 6 druggable targets that overlapped with 18 drugs with status of undergoing clinical trials for CHB, and 9 druggable targets that overlapped with 20 drugs undergoing preclinical investigations for CHB. Eight druggable targets were identified, overlapping with 25 drugs that can potentially be repurposed for CHB. Notably, CD40 and HLA-DPB1 were identified as promising targets for CHB drug repurposing based on the target scores.ConclusionThrough the integration of genomic variants and a bioinformatic approach, our findings suggested the plausibility of CHB genomic variant-driven drug repurposing for CHB.     

Deep Sequencing-guided Design of a High Affinity Dual Specificity Antibody to Target Two Angiogenic Factors in Neovascular Age-related Macular Degeneration

The development of dual targeting antibodies promises therapies with improved efficacy over mono-specific antibodies. Here, we engineered a Two-in-One VEGF/angiopoietin 2 antibody with dual action Fab (DAF) as a potential therapeutic for neovascular age-related macular degeneration. Crystal structures of the VEGF/angiopoietin 2 DAF in complex with its two antigens showed highly overlapping binding sites. To achieve sufficient affinity of the DAF to block both angiogenic factors, we turned to deep mutational scanning in the complementarity determining regions (CDRs). By mutating all three CDRs of each antibody chain simultaneously, we were able not only to identify affinity improving single mutations but also mutation pairs from different CDRs that synergistically improve both binding functions. Furthermore, insights into the cooperativity between mutations allowed us to identify fold-stabilizing mutations in the CDRs. The data obtained from deep mutational scanning reveal that the majority of the 52 CDR residues are utilized differently for the two antigen binding function and permit, for the first time, the engineering of several DAF variants with sub-nanomolar affinity against two structurally unrelated antigens. The improved variants show similar blocking activity of receptor binding as the high affinity mono-specific antibodies against these two proteins, demonstrating the feasibility of generating a dual specificity binding surface with comparable properties to individual high affinity mono-specific antibodies.     

Evaluation of novel Saquinavir analogs for resistance mutation compatibility and potential as an HIV-Protease inhibitor drug

A fundamental issue related to therapy of HIV-1 infection is the emergence of viral mutations which severely limits the long term efficiency of the HIV-protease (HIV-PR) inhibitors. Development of new drugs is therefore continuously needed. Chemoinformatics enables to design and discover novel molecules analogous to established drugs using computational tools and databases. Saquinavir, an anti-HIV Protease drug is administered for HIV therapy. In this work chemoinformatics tools were used to design structural analogs of Saquinavir as ligand and molecular dockings at AutoDock were performed to identify potential HIV-PR inhibitors. The analogs S1 and S2 when docked with HIV-PR had binding energies of -4.08 and -3.07 kcal/mol respectively which were similar to that for Saquinavir. The molecular docking studies revealed that the changes at N2 of Saquinavir to obtain newly designed analogs S1 (having N2 benzoyl group at N1) and S2 (having 3-oxo-3phenyl propanyl group at N2) were able to dock with HIV-PR with similar affinity as that of Saquinavir. Docking studies and computationally derived pharmacodynamic and pharmacokinetic properties׳ comparisons at ACD/I-lab establish that analog S2 has more potential to evade the problem of drug resistance mutation against HIV-1 PR subtype-A. S2 can be further developed and tested clinically as a real alternative drug for HIV-1 PR across the clades in future.     

适配体结合蛋白质靶标的亲和力表征方法及其在疾病诊断中的应用

核酸适配体是通过体外指数富集配体系统进化（SELEX）技术筛选获得,并能够和蛋白质靶标高特异性、高亲和力结合的单链寡核苷酸。核酸适配体不但具有抗体的识别特性,而且具有自己独特的优良性能,目前已应用于分析检验、食品安全和生物医药等各个领域。蛋白质具有多种多样的生物功能以及临床诊断价值。因此,核酸适配体针对蛋白质靶标并在蛋白质相关的基础研究领域受到广泛的关注。核酸适配体应用性能的优劣取决于与其靶标蛋白质的亲和力与特异性。本文主要综述核酸适配体对蛋白质靶标的亲和力表征方法,以及在药物研发、肿瘤检测、生物成像以及生物传感器方面的应用。     

Analysis of HIV-1 CRF_01 A/E protease inhibitor resistance: structural determinants for maintaining sensitivity and developing resistance to atazanavir

A series of HIV-1 protease mutants has been designed in an effort to analyze the contribution to drug resistance provided by natural polymorphisms as well as therapy-selective (active and non-active site) mutations in the HIV-1 CRF_01 A/E (AE) protease when compared to that of the subtype B (B) protease. Kinetic analysis of these variants using chromogenic substrates showed differences in substrate specificity between pretherapy B and AE proteases. Inhibition analysis with ritonavir, indinavir, nelfinavir, amprenavir, saquinavir, lopinavir, and atazanavir revealed that the natural polymorphisms found in A/E can influence inhibitor resistance. It was also apparent that a high level of resistance in the A/E protease, as with B protease, is due to it aquiring a combination of active site and non-active site mutations. Structural analysis of atazanavir bound to a pretherapy B protease showed that the ability of atazanavir to maintain its binding affinity for variants containing some resistance mutations is due to its unique interactions with flap residues. This structure also explains why the I50L and I84V mutations are important in decreasing the binding affinity of atazanavir.     

Aptamers as tools for target validation

Synthetic nucleic acid ligands, called aptamers, bind to protein targets with high specificity and affinity. They are very potent inhibitors of protein function and their application can greatly enhance the process of target validation and drug development. An important benefit of this technology is the recent development of rapidly identifying these sophisticated ligands for almost any target molecule in multi-parallel, automated workstations. The aptamer technology is thus well-suited to addressing the growing demand for high-throughput analysis and functional validation of potential drug targets. Numerous examples have shown the potency of aptamers in inhibiting the function of proteins in cell culture and in vivo models. The technology is complementary to genetic knockout or siRNA approaches as it provides highly valuable information at the proteomic level. In addition, the aptamer technology has recently been extended to developing aptamer drugs and identifying functionally equivalent small molecule leads.     

Developing hybrid molecule therapeutics for diverse enzyme inhibitory action: Active role of coumarin-based structural leads in drug discovery

Hybrid drugs featuring two or more potentially bioactive pharmacophores have been recognized as advanced and superior chemical entities to simultaneously modulate multiple drug targets of multifactorial diseases, thus overcoming the severe side effects associated with a single drug molecule. The selection of these chemical moieties to produce hybrid structures with druggable properties is generally facilitated by the observed and/or anticipated synergistic pharmacological activities of the individual molecules. In this perspective, coumarin template has extensively been studied in pursuit of structurally diverse leads for drug development due to high affinity and specificity to different molecular targets. This review highlights the most commonly exploited approaches conceptualizing the design and construction of hybrid molecules by coupling two or more individual fragments with or without an appropriate linker. In addition to the design strategies, this review also summarizes and reflects on the therapeutic potential of these hybrid molecules for diverse enzyme inhibitory action as well as their observed structure-activity relationship (SAR). Several key features of the synthesized hybrid structures that assert a profound impact on the inhibitory function have also been discussed alongside computational investigations, inhibitor molecular diversity and selectivity toward multiple drug targets. Finally, these drug discovery and development efforts should serve as a handy reference aiming to provide a useful platform for the exploration of new coumarin-based compounds with enhanced enzyme inhibitory profile.     

Thermodynamic rules for the design of high affinity HIV-1 protease inhibitors with adaptability to mutations and high selectivity towards unwanted targets

Protease inhibitors are key components in the chemotherapy of HIV-1 infection. However, the long term efficacy of antiretroviral therapies is hampered by issues of patient compliance often associated with the presence of severe side effects, and above all by the appearance of drug resistance. The development of new protease inhibitors with high potency, low susceptibility to mutations and minimal affinity for unwanted targets is an urgent goal. The engineering of these adaptive inhibitors requires identification of the critical determinants of affinity, adaptability, and selectivity. Analysis of the binding database for existing clinical and experimental inhibitors has allowed us to address the following questions in a quantitative fashion: (1) Is there an optimal binding affinity? Or, are the highest affinity inhibitors necessarily the best inhibitors? (2) What is the dependence of optimal affinity on adaptability and selectivity? (3) What are the determinants of adaptability to mutations associated with drug resistance? (4) How selectivity against unwanted targets can be improved? It is shown that the optimal affinity is a function of the effective target concentration and the desired adaptability and selectivity factors. Furthermore, knowledge of the enthalpic and entropic contributions to the binding affinity to the wild type provides a way of anticipating the response of an inhibitor to mutations associated with drug resistance, and therefore, a valuable guideline for optimization.     

Effect of sequence polymorphism and drug resistance on two HIV-1 Gag processing sites.

The HIV-1 proteinase (PR) has proved to be a good target for antiretroviral therapy of AIDS, and various PR inhibitors are now in clinical use. However, there is a rapid selection of viral variants bearing mutations in the proteinase that are resistant to clinical inhibitors. Drug resistance also involves mutations of the nucleocapsid/p1 and p1/p6 cleavage sites of Gag, both in vitro and in vivo. Cleavages at these sites have been shown to be rate limiting steps for polyprotein processing and viral maturation. Furthermore, these sites show significant sequence polymorphism, which also may have an impact on virion infectivity. We have studied the hydrolysis of oligopeptides representing these cleavage sites with representative mutations found as natural variations or that arise as resistant mutations. Wild-type and five drug resistant PRs with mutations within or outside the substrate binding site were tested. While the natural variations showed either increased or decreased susceptibility of peptides toward the proteinases, the resistant mutations always had a beneficial effect on catalytic efficiency. Comparison of the specificity changes obtained for the various substrates suggested that the maximization of the van der Waals contacts between substrate and PR is the major determinant of specificity: the same effect is crucial for inhibitor potency. The natural nucleocapsid/p1 and p1/p6 sites do not appear to be optimized for rapid hydrolysis. Hence, mutation of these rate limiting cleavage sites can partly compensate for the reduced catalytic activity of drug resistant mutant HIV-1 proteinases.     

以完整细胞为靶子的SELEX技术研究进展

指数富集的配体系统进化（SELEX）是一种从大容量寡核苷酸文库中经反复分离扩增步骤得到针对靶分子的高亲和力、高特异性核酸配基——适配体的体外筛选技术。自1990年以来,SELEX技术得到了迅猛发展,筛选的靶分子已由最初的单一物质发展到完整的动物细胞、细菌病原体等复杂靶子。以完整细胞为靶子的SELEX技术有其独特的技术优势,可以在筛选细胞上特定靶分子未知的情况下进行筛选,为药物筛选、临床诊断、疾病治疗和基础医学研究等带来了新的思路和方法。随着对适配体研究的深入,尤其是纳米材料与其相结合应用,该技术将在肿瘤诊断治疗及微生物检测领域具有更为广泛的应用前景。