Lessons from Hot Spot Analysis for Fragment-Based Drug Discovery

Fragment library screening by X-ray crystallography and binding site analysis on thioredoxin glutathione reductase of Schistosoma mansoni

Schistosomiasis is caused by parasites of the genus Schistosoma, which infect more than 200 million people. Praziquantel (PZQ) has been the main drug for controlling schistosomiasis for over four decades, but despite that it is ineffective against juvenile worms and size and taste issues with its pharmaceutical forms impose challenges for treating school-aged children. It is also important to note that PZQ resistant strains can be generated in laboratory conditions and observed in the field, hence its extensive use in mass drug administration programs raises concerns about resistance, highlighting the need to search for new schistosomicidal drugs. Schistosomes survival relies on the redox enzyme thioredoxin glutathione reductase (TGR), a validated target for the development of new anti-schistosomal drugs. Here we report a high-throughput fragment screening campaign of 768 compounds against S. mansoni TGR (SmTGR) using X-ray crystallography. We observed 49 binding events involving 35 distinct molecular fragments which were found to be distributed across 16 binding sites. Most sites are described for the first time within SmTGR, a noteworthy exception being the "doorstop pocket" near the NADPH binding site. We have compared results from hotspots and pocket druggability analysis of SmTGR with the experimental binding sites found in this work, with our results indicating only limited coincidence between experimental and computational results. Finally, we discuss that binding sites at the doorstop/NADPH binding site and in the SmTGR dimer interface, should be prioritized for developing SmTGR inhibitors as new antischistosomal drugs.

In Silico Exploration of the Trypanothione Reductase (TryR) of L. mexicana

Human leishmaniasis is a neglected tropical disease which affects nearly 1.5 million people every year, with Mexico being an important endemic region. One of the major defense mechanisms of these parasites is based in the polyamine metabolic pathway, as it provides the necessary compounds for its survival. Among the enzymes in this route, trypanothione reductase (TryR), an oxidoreductase enzyme, is crucial for the Leishmania genus' survival against oxidative stress. Thus, it poses as an attractive drug target, yet due to the size and features of its catalytic pocket, modeling techniques such as molecular docking focusing on that region is not convenient. Herein, we present a computational study using several structure-based approaches to assess the druggability of TryR from L. mexicana, the predominant Leishmania species in Mexico, beyond its catalytic site. Using this consensus methodology, three relevant pockets were found, of which the one we call σ-site promises to be the most favorable one. These findings may help the design of new drugs of trypanothione-related diseases.

Fragment-based drug discovery supports drugging 'undruggable' protein-protein interactions

Protein-protein interactions (PPIs) have important roles in various cellular processes, but are commonly described as 'undruggable' therapeutic targets due to their large, flat, featureless interfaces. Fragment-based drug discovery (FBDD) has achieved great success in modulating PPIs, with more than ten compounds in clinical trials. Here, we highlight the progress of FBDD in modulating PPIs for therapeutic development. Targeting hot spots that have essential roles in both fragment binding and PPIs provides a shortcut for the development of PPI modulators via FBDD. We highlight successful cases of cracking the 'undruggable' problems of PPIs using fragment-based approaches. We also introduce new technologies and future trends. Thus, we hope that this review will provide useful guidance for drug discovery targeting PPIs.

Development of potent inhibitors by fragment-linking strategies

Fragment-based drug discovery (FBDD) is a method of identifying small molecule hits that can be elaborated rationally through fragment growing, merging, and linking, to afford high affinity ligands for biological targets. Despite the promised theoretical potential of fragment linking, examples are still surprisingly sparse and remain overshadowed by the successes of fragment growing. The aim of this review is to outline a number of key examples of fragment linking strategies and discuss their strengths and limitations. Structure-based approaches including X-ray crystallography and in silico methods fragment optimisation are discussed, as well as fragment linking guided by NMR experiments. Target-guided approaches, exploiting the biological target to assemble its own inhibitors through dynamic combinatorial chemistry (DCC) and kinetic target-guided synthesis (KTGS), are identified as alternative efficient methods for fragment linking.

Deep Sequencing of a Systematic Peptide Library Reveals Conformationally-Constrained Protein Interface Peptides that Disrupt a Protein-Protein Interaction

Disrupting protein-protein interactions is difficult due to the large and flat interaction surfaces of the binding partners. The BLIP and BLIP-II proteins are unrelated in sequence and structure and yet each potently inhibit β-lactamases. High-throughput oligonucleotide synthesis was used to construct a 12,470-member library containing overlapping linear and cyclic peptides ranging in size from 6 to 21 amino acids that scan through the sequences of BLIP and BLIP-II. Phage display affinity selections and deep sequencing revealed that, despite the differences in interaction surfaces with β-lactamases, rapid enrichment of consensus peptide regions originating from both BLIP and BLIP-II contact residues in the binding interface occurred. BLIP and BLIP-II peptides that were enriched by affinity selection were shown to bind β-lactamases and disrupt the BLIP/β-lactamase interaction. The results suggest that peptides that bind at and disrupt PPI interfaces can be identified through systematic peptide library construction, affinity selection, and deep sequencing.

Automated Determination of Nuclear Magnetic Resonance Chemical Shift Perturbations in Ligand Screening Experiments: The PICASSO Web Server

Nuclear magnetic resonance (NMR) is an effective, commonly used experimental approach to screen small organic molecules against a protein target. A very popular method consists of monitoring the changes of the NMR chemical shifts of the protein nuclei upon addition of the small molecule to the free protein. Multidimensional NMR experiments allow the interacting residues to be mapped along the protein sequence. A significant amount of human effort goes into manually tracking the chemical shift variations, especially when many signals exhibit chemical shift changes and when many ligands are tested. Some computational approaches to automate the procedure are available, but none of them as a web server. Furthermore, some methods require the adoption of a fairly specific experimental setup, such as recording a series of spectra at increasing small molecule:protein ratios. In this work, we developed a tool requesting a minimal amount of experimental data from the user, implemented it as an open-source program, and made it available as a web application. Our tool compares two spectra, one of the free protein and one of the small molecule:protein mixture, based on the corresponding peak lists. The performance of the tool in terms of correct identification of the protein-binding regions has been evaluated on different protein targets, using experimental data from interaction studies already available in the literature. For a total of 16 systems, our tool achieved between 79% and 100% correct assignments, properly identifying the protein regions involved in the interaction.

Progress in Free Energy Perturbation: Options for Evolving Fragments

One of the remaining bottlenecks in fragment-based drug design (FBDD) is the initial exploration and optimization of the identified hit fragments. There is a growing interest in computational approaches that can guide these efforts by predicting the binding affinity of newly designed analogues. Among others, alchemical free energy (AFE) calculations promise high accuracy at a computational cost that allows their application during lead optimization campaigns. In this review, we discuss how AFE could have a strong impact in fragment evolution, and we raise awareness on the challenges that could be encountered applying this methodology in FBDD studies.

Non-Extensive Fragmentation of Natural Products and Pharmacophore-Based Virtual Screening as a Practical Approach to Identify Novel Promising Chemical Scaffolds

Fragment-based drug design (FBDD) and pharmacophore modeling have proven to be efficient tools to discover novel drugs. However, these approaches may become limited if the collection of fragments is highly repetitive, poorly diverse, or excessively simple. In this article, combining pharmacophore modeling and a non-classical type of fragmentation (herein called non-extensive) to screen a natural product (NP) library may provide fragments predicted as potent, diverse, and developable. Initially, we applied retrosynthetic combinatorial analysis procedure (RECAP) rules in two versions, extensive and non-extensive, in order to deconstruct a virtual library of NPs formed by the databases Traditional Chinese Medicine (TCM), AfroDb (African Medicinal Plants database), NuBBE (Nuclei of Bioassays, Biosynthesis, and Ecophysiology of Natural Products), and UEFS (Universidade Estadual de Feira de Santana). We then developed a virtual screening (VS) using two groups of natural-product-derived fragments (extensive and non-extensive NPDFs) and two overlapping pharmacophore models for each of 20 different proteins of therapeutic interest. Molecular weight, lipophilicity, and molecular complexity were estimated and compared for both types of NPDFs (and their original NPs) before and after the VS proceedings. As a result, we found that non-extensive NPDFs exhibited a much higher number of chemical entities compared to extensive NPDFs (45,355 vs. 11,525 compounds), accounting for the larger part of the hits recovered and being far less repetitive than extensive NPDFs. The structural diversity of both types of NPDFs and the NPs was shown to diminish slightly after VS procedures. Finally, and most interestingly, the pharmacophore fit score of the non-extensive NPDFs proved to be not only higher, on average, than extensive NPDFs (56% of cases) but also higher than their original NPs (69% of cases) when all of them were also recognized as hits after the VS. The findings obtained in this study indicated that the proposed cascade approach was useful to enhance the probability of identifying innovative chemical scaffolds, which deserve further development to become drug-sized candidate compounds. We consider that the knowledge about the deconstruction degree required to produce NPDFs of interest represents a good starting point for eventual synthesis, characterization, and biological activity studies.

Assessing the binding properties of CASP14 targets and models

An important question is how well the models submitted to CASP retain the properties of target structures. We investigate several properties related to binding. First we explore the binding of small molecules as probes, and count the number of interactions between each residue and such probes, resulting in a binding fingerprint. The similarity between two fingerprints, one for the X-ray structure and the other for a model, is determined by calculating their correlation coefficient. The fingerprint similarity weakly correlates with global measures of accuracy, and GDT_TS higher than 80 is a necessary but not sufficient condition for the conservation of surface binding properties. The advantage of this approach is that it can be carried out without information on potential ligands and their binding sites. The latter information was available for a few targets, and we explored whether the CASP14 models can be used to predict binding sites and to dock small ligands. Finally, we tested the ability of models to reproduce protein-protein interactions by docking both the X-ray structures and the models to their interaction partners in complexes. The analysis showed that in CASP14 the quality of individual domain models is approaching that offered by X-ray crystallography, and hence such models can be successfully used for the identification of binding and regulatory sites, as well as for assembling obligatory protein-protein complexes. Success of ligand docking, however, often depends on fine details of the binding interface, and thus may require accounting for conformational changes by simulation methods.

Exploring protein hotspots by optimized fragment pharmacophores

Fragment-based drug design has introduced a bottom-up process for drug development, with improved sampling of chemical space and increased effectiveness in early drug discovery. Here, we combine the use of pharmacophores, the most general concept of representing drug-target interactions with the theory of protein hotspots, to develop a design protocol for fragment libraries. The SpotXplorer approach compiles small fragment libraries that maximize the coverage of experimentally confirmed binding pharmacophores at the most preferred hotspots. The efficiency of this approach is demonstrated with a pilot library of 96 fragment-sized compounds (SpotXplorer0) that is validated on popular target classes and emerging drug targets. Biochemical screening against a set of GPCRs and proteases retrieves compounds containing an average of 70% of known pharmacophores for these targets. More importantly, SpotXplorer0 screening identifies confirmed hits against recently established challenging targets such as the histone methyltransferase SETD2, the main protease (3CLPro) and the NSP3 macrodomain of SARS-CoV-2.

Fragment-based drug design facilitates selective kinase inhibitor discovery

Protein kinases (PKs) are important drug targets, but kinases selectivity poses a challenge to protein kinase inhibitors (PKIs) design. Fragment-based drug discovery (FBDD) has achieved great success in the discovery of highly specific PKIs. It makes full use of kinase-fragment interaction in target kinase subpockets to obtain promising selectivity. However, it's difficult to understand the complicated kinase-fragment interaction space, and systemic discussion of these interactions is still lacking. Herein, we introduce the advantages of the FBDD strategy in PKIs design. Key features of the selectivity of kinase-fragment interactions are summarized and analyzed. Some promising PKIs are introduced as case studies to help understand the fragment-to-lead (F2L) optimization process. Novel strategies and technologies for FBDD in PKIs discovery are also outlooked.

Conservation of binding properties in protein models

We study the models submitted to round 12 of the Critical Assessment of protein Structure Prediction (CASP) experiment to assess how well the binding properties are conserved when the X-ray structures of the target proteins are replaced by their models. To explore small molecule binding we generate distributions of molecular probes - which are fragment-sized organic molecules of varying size, shape, and polarity - around the protein, and count the number of interactions between each residue and the probes, resulting in a vector of interactions we call a binding fingerprint. The similarity between two fingerprints, one for the X-ray structure and the other for a model of the protein, is determined by calculating the correlation coefficient between the two vectors. The resulting correlation coefficients are shown to correlate with global measures of accuracy established in CASP, and the relationship yields an accuracy threshold that has to be reached for meaningful binding surface conservation. The clusters formed by the probe molecules reliably predict binding hot spots and ligand binding sites in both X-ray structures and reasonably accurate models of the target, but ensembles of models may be needed for assessing the availability of proper binding pockets. We explored ligand docking to the few targets that had bound ligands in the X-ray structure. More targets were available to assess the ability of the models to reproduce protein-protein interactions by docking both the X-ray structures and models to their interaction partners in complexes. It was shown that this application is more difficult than finding small ligand binding sites, and the success rates heavily depend on the local structure in the potential interface. In particular, predicted conformations of flexible loops are frequently incorrect in otherwise highly accurate models, and may prevent predicting correct protein-protein interactions.

Fragment-linking peptide design yields a high-affinity ligand for microtubule-based transport

Synthetic peptides are attractive candidates to manipulate protein-protein interactions inside the cell as they mimic natural interactions to compete for binding. However, protein-peptide interactions are often dynamic and weak. A challenge is to design peptides that make improved interactions with the target. Here, we devise a fragment-linking strategy-"mash-up" design-to deliver a high-affinity ligand, KinTag, for the kinesin-1 motor. Using structural insights from natural micromolar-affinity cargo-adaptor ligands, we have identified and combined key binding features in a single, high-affinity ligand. An X-ray crystal structure demonstrates interactions as designed and reveals only a modest increase in interface area. Moreover, when genetically encoded, KinTag promotes transport of lysosomes with higher efficiency than natural sequences, revealing a direct link between motor-adaptor binding affinity and organelle transport. Together, these data demonstrate a fragment-linking strategy for peptide design and its application in a synthetic motor ligand to direct cellular cargo transport.

Direct Keap1-kelch inhibitors as potential drug candidates for oxidative stress-orchestrated diseases: A review on In silico perspective

The recent outcry in the search for direct keap1 inhibitors requires a quicker and more effective drug discovery process which is an inherent property of the Computer Aided Drug Discovery (CADD) to bring drug candidates into the clinic for patient's use. This Keap1 (negative regulator of ARE master activator) is emerging as a therapeutic strategy to combat oxidative stress-orchestrated diseases. The advances in computer algorithm and compound databases require that we highlight the functionalities that this technology possesses that can be exploited to target Keap1-Nrf2 PPI. Therefore, in this review, we uncover the in silico approaches that had been exploited towards the identification of keap1 inhibition in the light of appropriate fitting with relevant amino acid residues, we found 3 and 16 other compounds that perfectly fit keap1 kelch pocket/domain. Our goal is to harness the parameters that could orchestrate keap1 surface druggability by utilizing hotspot regions for virtual fragment screening and identification of hotspot residues.

Mapping major SARS-CoV-2 drug targets and assessment of druggability using computational fragment screening: Identification of an allosteric small-molecule binding site on the Nsp13 helicase

The 2019 emergence of, SARS-CoV-2 has tragically taken an immense toll on human life and far reaching impacts on society. There is a need to identify effective antivirals with diverse mechanisms of action in order to accelerate preclinical development. This study focused on five of the most established drug target proteins for direct acting small molecule antivirals: Nsp5 Main Protease, Nsp12 RNA-dependent RNA polymerase, Nsp13 Helicase, Nsp16 2'-O methyltransferase and the S2 subunit of the Spike protein. A workflow of solvent mapping and free energy calculations was used to identify and characterize favorable small-molecule binding sites for an aromatic pharmacophore (benzene). After identifying the most favorable sites, calculated ligand efficiencies were compared utilizing computational fragment screening. The most favorable sites overall were located on Nsp12 and Nsp16, whereas the most favorable sites for Nsp13 and S2 Spike had comparatively lower ligand efficiencies relative to Nsp12 and Nsp16. Utilizing fragment screening on numerous possible sites on Nsp13 helicase, we identified a favorable allosteric site on the N-terminal zinc binding domain (ZBD) that may be amenable to virtual or biophysical fragment screening efforts. Recent structural studies of the Nsp12:Nsp13 replication-transcription complex experimentally corroborates ligand binding at this site, which is revealed to be a functional Nsp8:Nsp13 protein-protein interaction site in the complex. Detailed structural analysis of Nsp13 ZBD conformations show the role of induced-fit flexibility in this ligand binding site and identify which conformational states are associated with efficient ligand binding. We hope that this map of over 200 possible small-molecule binding sites for these drug targets may be of use for ongoing discovery, design, and drug repurposing efforts. This information may be used to prioritize screening efforts or aid in the process of deciphering how a screening hit may bind to a specific target protein.

Fragment-based covalent ligand discovery

Targeted covalent inhibitors have regained widespread attention in drug discovery and have emerged as powerful tools for basic biomedical research. Fueled by considerable improvements in mass spectrometry sensitivity and sample processing, chemoproteomic strategies have revealed thousands of proteins that can be covalently modified by reactive small molecules. Fragment-based drug discovery, which has traditionally been used in a target-centric fashion, is now being deployed on a proteome-wide scale thereby expanding its utility to both the discovery of novel covalent ligands and their cognate protein targets. This powerful approach is allowing ‘high-throughput’ serendipitous discovery of cryptic pockets leading to the identification of pharmacological modulators of proteins previously viewed as “undruggable”. The reactive fragment toolkit has been enabled by recent advances in the development of new chemistries that target residues other than cysteine including lysine and tyrosine. Here, we review the emerging area of covalent fragment-based ligand discovery, which integrates the benefits of covalent targeting and fragment-based medicinal chemistry. We discuss how the two strategies synergize to facilitate the efficient discovery of new pharmacological modulators of established and new therapeutic target proteins.

Covalent fragment-based ligand discovery greatly facilitates the discovery of useful fragments for drug discovery and helps unveil chemical-tractable biological targets in native biological systems.

Hsp90 chaperones have an energetic hot-spot for binding inhibitors

Although Hsp90-family chaperones have been extensively targeted with ATP-competitive inhibitors, it is unknown whether high affinity is achieved from a few highly stabilizing contacts or from many weaker contacts within the ATP-binding pocket. A large-scale analysis of Hsp90α:inhibitor structures shows that inhibitor hydrogen-bonding to a conserved aspartate (D93 in Hsp90α) stands out as most universal among Hsp90 inhibitors. Here we show that the D93 region makes a dominant energetic contribution to inhibitor binding for both cytosolic and organelle-specific Hsp90 paralogs. For inhibitors in the resorcinol family, the D93:inhibitor hydrogen-bond is pH-dependent because the associated inhibitor hydroxyl group is titratable, rationalizing a linked-protonation event previously observed by the Matulis group. The inhibitor hydroxyl group pKa associated with the D93 hydrogen-bond is therefore critical for optimizing the affinity of resorcinol derivatives, and we demonstrate that spectrophotometric measurements can determine this pKa value. Quantifying the energetic contribution of the D93 hotspot is best achieved with the mitochondrial Hsp90 paralog, yielding 3-6 kcal/mol of stabilization (35-60% of the total binding energy) for a diverse set of inhibitors. The Hsp90 Asp93➔Asn substitution has long been known to abolish nucleotide binding, yet puzzlingly, native sequences of structurally similar ATPases, such as Topoisomerasese II, have an asparagine at this same crucial site. While aspartate and asparagine sidechains can both act as hydrogen bond acceptors, we show that a steric clash prevents the Hsp90 Asp93➔Asn sidechain from adopting the necessary rotamer, whereas this steric restriction is absent in Topoisomerasese II.

Identification of Alternative Allosteric Sites in Glycolytic Enzymes for Potential Use as Species-Specific Drug Targets

Three allosteric glycolytic enzymes, phosphofructokinase, glyceraldehyde-3 phosphate dehydrogenase and pyruvate kinase, associated with bacterial, parasitic and human species, were explored to identify potential allosteric sites that would be used as prime targets for species-specific drug design purposes using a newly developed approach which incorporates solvent mapping, elastic network modeling, sequence and structural alignments. The majority of binding sites detected by solvent mapping overlapped with the interface regions connecting the subunits, thus appeared as promising target sites for allosteric regulation. Each binding site was then evaluated by its ability to alter the global dynamics of the receptor defined by the percentage change in the frequencies of the lowest-frequency modes most significantly and as anticipated, the most effective ones were detected in the vicinity of the well-reported catalytic and allosteric sites. Furthermore, some of our proposed regions intersected with experimentally resolved sites which are known to be critical for activity regulation, which further validated our approach. Despite the high degree of structural conservation encountered between bacterial/parasitic and human glycolytic enzymes, the majority of the newly presented allosteric sites exhibited a low degree of sequence conservation which further increased their likelihood to be used as species-specific target regions for drug design studies.

Interaction Energetics and Druggability of the Protein-Protein Interaction between Kelch-like ECH-Associated Protein 1 (KEAP1) and Nuclear Factor Erythroid 2 Like 2 (Nrf2)

Development of small molecule inhibitors of protein-protein interactions (PPIs) is hampered by our poor understanding of the druggability of PPI target sites. Here, we describe the combined application of alanine-scanning mutagenesis, fragment screening, and FTMap computational hot spot mapping to evaluate the energetics and druggability of the highly charged PPI interface between Kelch-like ECH-associated protein 1 (KEAP1) and nuclear factor erythroid 2 like 2 (Nrf2), an important drug target. FTMap identifies four binding energy hot spots at the active site. Only two of these are exploited by Nrf2, which alanine scanning of both proteins shows to bind primarily through E79 and E82 interacting with KEAP1 residues S363, R380, R415, R483, and S508. We identify fragment hits and obtain X-ray complex structures for three fragments via crystal soaking using a new crystal form of KEAP1. Combining these results provides a comprehensive and quantitative picture of the origins of binding energy at the interface. Our findings additionally reveal non-native interactions that might be exploited in the design of uncharged synthetic ligands to occupy the same site on KEAP1 that has evolved to bind the highly charged DEETGE binding loop of Nrf2. These include π-stacking with KEAP1 Y525 and interactions at an FTMap-identified hot spot deep in the binding site. Finally, we discuss how the complementary information provided by alanine-scanning mutagenesis, fragment screening, and computational hot spot mapping can be integrated to more comprehensively evaluate PPI druggability.

Photoinduced synthesis and antitumor activity of a phakellistatin 18 analog with an isoindolinone fragment

Photoinduced synthesis and antitumor activity of a phakellistatin 18 analog with an isoindolinone fragment.

Pharmmaker: Pharmacophore modeling and hit identification based on druggability simulations

Recent years have seen progress in druggability simulations, that is, molecular dynamics simulations of target proteins in solutions containing drug‐like probe molecules to characterize their drug‐binding abilities, if any. An important consecutive step is to analyze the trajectories to construct pharmacophore models (PMs) to use for virtual screening of libraries of small molecules. While considerable success has been observed in this type of computer‐aided drug discovery, a systematic tool encompassing multiple steps from druggability simulations to pharmacophore modeling, to identifying hits by virtual screening of libraries of compounds, has been lacking. We address this need here by developing a new tool, Pharmmaker, building on the DruGUI module of our ProDy application programming interface. Pharmmaker is composed of a suite of steps: (Step 1) identification of high affinity residues for each probe molecule type; (Step 2) selecting high affinity residues and hot spots in the vicinity of sites identified by DruGUI; (Step 3) ranking of the interactions between high affinity residues and specific probes; (Step 4) obtaining probe binding poses and corresponding protein conformations by collecting top‐ranked snapshots; and (Step 5) using those snapshots for constructing PMs. The PMs are then used as filters for identifying hits in structure‐based virtual screening. Pharmmaker, accessible online at http://prody.csb.pitt.edu/pharmmaker/, can be used in conjunction with other tools available in ProDy.

Structure-Based Analysis of Cryptic-Site Opening

Many proteins in their unbound structures have cryptic sites that are not appropriately sized for drug binding. We consider here 32 proteins from the recently published CryptoSite set with validated cryptic sites, and study whether the sites remain cryptic in all available X-ray structures of the proteins solved without any ligand bound near the sites. It was shown that only few of these proteins have binding pockets that never form without ligand binding. Sites that are cryptic in some structures but spontaneously form in others are also rare. In most proteins the forming of pockets is affected by mutations or ligand binding at locations far from the cryptic site. To further explore these mechanisms, we applied adiabatic biased molecular dynamics simulations to guide the proteins from their ligand-free structures to ligand-bound conformations, and studied the distribution of druggability scores of the pockets located at the cryptic sites.

An Integrated System Biology Approach Yields Drug Repositioning Candidates for the Treatment of Heart Failure

Identifying effective pharmacological treatments for heart failure (HF) patients remains critically important. Given that the development of drugs de novo is expensive and time consuming, drug repositioning has become an increasingly important branch. In the present study, we propose a two-step drug repositioning pipeline and investigate the novel therapeutic effects of existing drugs approved by the US Food and Drug Administration to discover potential therapeutic drugs for HF. In the first step, we compared the gene expression pattern of HF patients with drug-induced gene expression profiles to obtain preliminary candidates. In the second step, we performed a systems biology approach based on the known protein–protein interaction information and targets of drugs to narrow down preliminary candidates to obtain final candidates. Drug set enrichment analysis and literature search were applied to assess the performance of our repositioning approach. We also constructed a mode of action network for each candidate and performed pathway analysis for each candidate using genes contained in their mode of action network to uncover pathways that potentially reflect the mechanisms of candidates’ therapeutic efficacy to HF. We discovered numerous preliminary candidates, some of which are used in clinical practice and supported by the literature. The final candidates contained nearly all of the preliminary candidates supported by previous studies. Drug set enrichment analysis and literature search support the validity of our repositioning approach. The mode of action network for each candidate not only displayed the underlying mechanisms of drug efficacy but also uncovered potential biomarkers and therapeutic targets for HF. Our two-step drug repositioning approach is efficient to find candidates with potential therapeutic efficiency to HF supported by the literature and might be of particular use in the discovery of novel effective pharmacological therapies for HF.

Analysis of single amino acid variations in singlet hot spots of protein-protein interfaces

Motivation

Single amino acid variations (SAVs) in protein-protein interaction (PPI) sites play critical roles in diseases. PPI sites (interfaces) have a small subset of residues called hot spots that contribute significantly to the binding energy, and they may form clusters called hot regions. Singlet hot spots are the single amino acid hot spots outside of the hot regions. The distribution of SAVs on the interface residues may be related to their disease association.

Results

We performed statistical and structural analyses of SAVs with literature curated experimental thermodynamics data, and demonstrated that SAVs which destabilize PPIs are more likely to be found in singlet hot spots rather than hot regions and energetically less important interface residues. In contrast, non-hot spot residues are significantly enriched in neutral SAVs, which do not affect PPI stability. Surprisingly, we observed that singlet hot spots tend to be enriched in disease-causing SAVs, while benign SAVs significantly occur in non-hot spot residues. Our work demonstrates that SAVs in singlet hot spot residues have significant effect on protein stability and function.

Availability and implementation

The dataset used in this paper is available as Supplementary Material. The data can be found at http://prism.ccbb.ku.edu.tr/data/sav/ as well.

Supplementary information

Supplementary data are available at Bioinformatics online.

Kinase Atlas: Druggability Analysis of Potential Allosteric Sites in Kinases

The inhibition of kinases has been pursued by the pharmaceutical industry for over 20 years. While the locations of the sites that bind type II and III inhibitors at or near the adenosine 5'-triphosphate binding sites are well defined, the literature describes 10 different regions that were reported as regulatory hot spots in some kinases and thus are potential target sites for type IV inhibitors. Kinase Atlas is a systematic collection of binding hot spots located at the above ten sites in 4910 structures of 376 distinct kinases available in the Protein Data Bank. The hot spots are identified by FTMap, a computational analogue of experimental fragment screening. Users of Kinase Atlas ( https://kinase-atlas.bu.edu ) may view summarized results for all structures of a particular kinase, such as which binding sites are present and how druggable they are, or they may view hot spot information for a particular kinase structure of interest.

Why Some Targets Benefit from beyond Rule of Five Drugs

Beyond rule-of-five (bRo5) compounds are increasingly used in drug discovery. Here we analyze 37 target proteins that have bRo5 drugs or clinical candidates. Targets can benefit from bRo5 drugs if they have "complex" hot spot structure with four or more hots spots, including some strong ones. Complex I targets show positive correlation between binding affinity and molecular weight. These targets are conventionally druggable, but reaching additional hot spots enables improved pharmaceutical properties. Complex II targets, mostly protein kinases, also have strong hot spots but show no correlation between affinity and ligand molecular weight, and the primary motivation for creating larger drugs is to increase selectivity. Each target considered as complex III has some specific reason for requiring bRo5 drugs. Finally, targets with "simple" hot spot structure, i.e., three or fewer weak hot spots, must use larger compounds that interact with surfaces beyond the hot spot region to achieve acceptable affinity.

Analysis of tractable allosteric sites in G protein-coupled receptors

Allosteric modulation of G protein-coupled receptors represent a promising mechanism of pharmacological intervention. Dramatic developments witnessed in the structural biology of membrane proteins continue to reveal that the binding sites of allosteric modulators are widely distributed, including along protein surfaces. Here we restrict consideration to intrahelical and intracellular sites together with allosteric conformational locks, and show that the protein mapping tools FTMap and FTSite identify 83% and 88% of such experimentally confirmed allosteric sites within the three strongest sites found. The methods were also able to find partially hidden allosteric sites that were not fully formed in X-ray structures crystallized in the absence of allosteric ligands. These results confirm that the intrahelical sites capable of binding druglike allosteric modulators are among the strongest ligand recognition sites in a large fraction of GPCRs and suggest that both FTMap and FTSite are useful tools for identifying allosteric sites and to aid in the design of such compounds in a range of GPCR targets.

Fragment Hits: What do They Look Like and How do They Bind?

A “fragment hit”, a molecule of low molecular weight that has been validated to bind to a target protein, can be an effective chemical starting point for a drug discovery project. Our ability to find and progress fragment hits could potentially be improved by enhancing our understanding of their binding properties, which to date has largely been based on tacit knowledge and reports from individual projects. In the work reported here, we systematically analyzed the molecular and binding properties of fragment hits using 489 published protein–fragment complexes. We identified a number of notable features that these hits tend to have in common, including preferences in buried surface area upon binding, hydrogen bonding and other directional interactions with the protein targets, structural topology, functional-group occurrence, and degree of carbon saturation. In the future, taking account of these preferences in designing and selecting fragments to screen against protein targets may increase the chances of success in fragment screening campaigns.

Defining and Exploiting Hypersensitivity Hotspots to Facilitate Abscisic Acid Agonist Optimization

Pyrabactin resistance 1 (PYR1) and related abscisic acid (ABA) receptors are new targets for manipulating plant drought tolerance. Here, we identify and use PYR1 hypersensitive mutants to define ligand binding hotspots and show that these can guide improvements in agonist potency. One hotspot residue defined, A160, is part of a pocket that is occupied by ABA's C6 methyl or by the toluyl methyl of the synthetic agonist quinabactin (QB). A series of QB analogues substituted at the toluyl position were synthesized and provide up to 10-fold gain in activity in vitro. Furthermore, we demonstrate that hypersensitive receptors can be used to improve the sensitivity of a previously described mammalian cell ABA-regulated transcriptional circuit by three orders of magnitude. Collectively, our data show that the systematic mapping of hypersensitivity sites in a ligand-binding pocket can help guide ligand optimization and tune the sensitivity of engineered receptors.

Crystallographic screening using ultra-low-molecular-weight ligands to guide drug design

We present a novel crystallographic screening methodology (MiniFrags) that employs high-concentration aqueous soaks with a chemically diverse and ultra-low-molecular-weight library (heavy atom count 5-7) to identify ligand-binding hot and warm spots on proteins. We propose that MiniFrag screening represents a highly effective method for guiding optimisation of fragment-derived lead compounds or chemical tools and that the high screening hit rates reflect enhanced sampling of chemical space.

Methods for Discovering and Targeting Druggable Protein-Protein Interfaces and Their Application to Repurposing

Drug repurposing is a creative and resourceful approach to increase the number of therapies by exploiting available and approved drugs. However, identifying new protein targets for previously approved drugs is challenging. Although new strategies have been developed for drug repurposing, there is broad agreement that there is room for further improvements. In this chapter, we review protein-protein interaction (PPI) interface-targeting strategies for drug repurposing applications. We discuss certain features, such as hot spot residue and hot region prediction and their importance in drug repurposing, and illustrate common methods used in PPI networks to identify drug off-targets. We also collect available online resources for hot spot prediction, binding pocket identification, and interface clustering which are effective resources in polypharmacology. Finally, we provide case studies showing the significance of protein interfaces and hot spots in drug repurposing.

Hybrid Imidazole-Pyridine Derivatives: An Approach to Novel Anticancer DNA Intercalators

Lack of specificity and subsequent therapeutic effectiveness of antimicrobial and antitumoral drugs is a common difficulty in therapy. The aim of this study is to investigate, both by experimental and computational methods, the antitumoral and antimicrobial properties of a series of synthesized imidazole-pyridine derivatives. Interaction with three targets was discussed: Dickerson-Drew dodecamer (PDB id 2ADU), G-quadruplex DNA string (PDB id 2F8U) and DNA strain in complex with dioxygenase (PDB id 3S5A). Docking energies were computed and represented graphically. On them, a QSAR model was developed in order to further investigate the structure-activity relationship. Results showed that synthesized compounds have antitumoral and antimicrobial properties. Computational results agreed with the experimental data.

Exploring the structural origins of cryptic sites on proteins

Molecular dynamics (MD) simulations of proteins reveal the existence of many transient surface pockets; however, the factors determining what small subset of these represent druggable or functionally relevant ligand binding sites, called "cryptic sites," are not understood. Here, we examine multiple X-ray structures for a set of proteins with validated cryptic sites, using the computational hot spot identification tool FTMap. The results show that cryptic sites in ligand-free structures generally have a strong binding energy hot spot very close by. As expected, regions around cryptic sites exhibit above-average flexibility, and close to 50% of the proteins studied here have unbound structures that could accommodate the ligand without clashes. Nevertheless, the strong hot spot neighboring each cryptic site is almost always exploited by the bound ligand, suggesting that binding may frequently involve an induced fit component. We additionally evaluated the structural basis for cryptic site formation, by comparing unbound to bound structures. Cryptic sites are most frequently occluded in the unbound structure by intrusion of loops (22.5%), side chains (19.4%), or in some cases entire helices (5.4%), but motions that create sites that are too open can also eliminate pockets (19.4%). The flexibility of cryptic sites frequently leads to missing side chains or loops (12%) that are particularly evident in low resolution crystal structures. An interesting observation is that cryptic sites formed solely by the movement of side chains, or of backbone segments with fewer than five residues, result only in low affinity binding sites with limited use for drug discovery.

NMR-Fragment Based Virtual Screening: A Brief Overview

Fragment-based drug discovery (FBDD) using NMR has become a central approach over the last twenty years for development of small molecule inhibitors against biological macromolecules, to control a variety of cellular processes. Yet, several considerations should be taken into account for obtaining a therapeutically relevant agent. In this review, we aim to list the considerations that make NMR fragment screening a successful process for yielding potent inhibitors. Factors that may govern the competence of NMR in fragment based drug discovery are discussed, as well as later steps that involve optimization of hits obtained by NMR-FBDD.

Photo-induced synthesis of chiral galaxamide analogs and the biological activities against human tumor cells

Two chiral analogs of galaxamide were synthesized by a photoinduced cyclization reaction.

Computational characterization of the selective inhibition of human norepinephrine and serotonin transporters by an escitalopram scaffold

Selective inhibition of human norepinephrine and serotonin transporters has been studied by computational approaches. 4 warm spots in hNET and 4 in hSERT were found to exert a pronounced effect on inhibition by the studied ligands.

A Computational Investigation of Small-Molecule Engagement of Hot Spots at Protein-Protein Interaction Interfaces

The binding affinity of a protein-protein interaction is concentrated at amino acids known as hot spots. It has been suggested that small molecules disrupt protein-protein interactions by either (i) engaging receptor protein hot spots or (ii) mimicking hot spots of the protein ligand. Yet, no systematic studies have been done to explore how effectively existing small-molecule protein-protein interaction inhibitors mimic or engage hot spots at protein interfaces. Here, we employ explicit-solvent molecular dynamics simulations and end-point MM-GBSA free energy calculations to explore this question. We select 36 compounds for which high-quality binding affinity and cocrystal structures are available. Five complexes that belong to three classes of protein-protein interactions (primary, secondary, and tertiary) were considered, namely, BRD4•H4, XIAP•Smac, MDM2•p53, Bcl-xL•Bak, and IL-2•IL-2Rα. Computational alanine scanning using MM-GBSA identified hot-spot residues at the interface of these protein interactions. Decomposition energies compared the interaction of small molecules with individual receptor hot spots to those of the native protein ligand. Pharmacophore analysis was used to investigate how effectively small molecules mimic the position of hot spots of the protein ligand. Finally, we study whether small molecules mimic the effects of the native protein ligand on the receptor dynamics. Our results show that, in general, existing small-molecule inhibitors of protein-protein interactions do not optimally mimic protein-ligand hot spots, nor do they effectively engage protein receptor hot spots. The more effective use of hot spots in future drug design efforts may result in smaller compounds with higher ligand efficiencies that may lead to greater success in clinical trials.

The Ligand Binding Landscape of Diacylglycerol Kinases

Diacylglycerol kinases (DGKs) are integral components of signal transduction cascades that regulate cell biology through ATP-dependent phosphorylation of the lipid messenger diacylglycerol. Methods for direct evaluation of DGK activity in native biological systems are lacking and needed to study isoform-specific functions of these multidomain lipid kinases. Here, we utilize ATP acyl phosphate activity-based probes and quantitative mass spectrometry to define, for the first time, ATP and small-molecule binding motifs of representative members from all five DGK subtypes. We use chemical proteomics to discover an unusual binding mode for the DGKα inhibitor, ritanserin, including interactions at the atypical C1 domain distinct from the ATP binding region. Unexpectedly, deconstruction of ritanserin yielded a fragment compound that blocks DGKα activity through a conserved binding mode and enhanced selectivity against the kinome. Collectively, our studies illustrate the power of chemical proteomics to profile protein-small molecule interactions of lipid kinases for fragment-based lead discovery.

Targeting YAP/TAZ-TEAD protein-protein interactions using fragment-based and computational modeling approaches

The Hippo signaling pathway, which is implicated in the regulation of organ size, has emerged as a potential target for the development of cancer therapeutics. YAP, TAZ (transcription co-activators) and TEAD (transcription factor) are the downstream transcriptional machinery and effectors of the pathway. Formation of the YAP/TAZ-TEAD complex leads to transcription of growth-promoting genes. Conversely, disrupting the interactions of the complex decreases cell proliferation. Herein, we screened a 1000-member fragment library using Thermal Shift Assay and identified a hit fragment. We confirmed its binding at the YAP/TAZ-TEAD interface by X-ray crystallography, and showed that it occupies the same hydrophobic pocket as a conserved phenylalanine of YAP/TAZ. This hit fragment serves as a scaffold for the development of compounds that have the potential to disrupt YAP/TAZ-TEAD interactions. Structure-activity relationship studies and computational modeling were also carried out to identify more potent compounds that may bind at this validated druggable binding site.

Orally Absorbed Cyclic Peptides

Peptides and proteins are not orally bioavailable in mammals, although a few peptides are intestinally absorbed in small amounts. Polypeptides are generally too large and polar to passively diffuse through lipid membranes, while most known active transport mechanisms facilitate cell uptake of only very small peptides. Systematic evaluations of peptides with molecular weights above 500 Da are needed to identify parameters that influence oral bioavailability. Here we describe 125 cyclic peptides containing four to thirty-seven amino acids that are orally absorbed by mammals. Cyclization minimizes degradation in the gut, blood, and tissues by removing cleavable N- and C-termini and by shielding components from metabolic enzymes. Cyclization also folds peptides into bioactive conformations that determine exposure of polar atoms to solvation by water and lipids and therefore can influence oral bioavailability. Key chemical properties thought to influence oral absorption and bioavailability are analyzed, including molecular weight, octanol-water partitioning, hydrogen bond donors/acceptors, rotatable bonds, and polar surface area. The cyclic peptides violated to different degrees all of the limits traditionally considered to be important for oral bioavailability of drug-like small molecules, although fewer hydrogen bond donors and reduced flexibility generally favored oral absorption.

On the Integration of In Silico Drug Design Methods for Drug Repurposing

Drug repurposing has become an important branch of drug discovery. Several computational approaches that help to uncover new repurposing opportunities and aid the discovery process have been put forward, or adapted from previous applications. A number of successful examples are now available. Overall, future developments will greatly benefit from integration of different methods, approaches and disciplines. Steps forward in this direction are expected to help to clarify, and therefore to rationally predict, new drug–target, target–disease, and ultimately drug–disease associations.

Selective targeting of epigenetic reader domains

INTRODUCTION

Epigenetic regulators including writers, erasers, and readers of chromatin marks have been implicated in numerous diseases and are therefore subject of intense academic and pharmaceutical research. While several small-molecule inhibitors targeting writers or erasers are either approved drugs or are currently being evaluated in clinical trials, the targeting of epigenetic readers has lagged behind. Proof-of-principle that epigenetic readers are also relevant drug targets was provided by landmark discoveries of selective inhibitors targeting the BET family of acetyl-lysine readers. More recently, high affinity chemical probes for non-BET acetyl- and methyl-lysine reader domains have also been developed. Areas covered: This article covers recent advances with the identification and validation of inhibitors and chemical probes targeting epigenetic reader domains. Issues related to epigenetic reader druggability, quality requirements for chemical probes, interpretation of cellular action, unexpected cross-talk, and future challenges are also discussed. Expert opinion: Chemical probes provide a powerful means to unravel biological functions of epigenetic readers and evaluate their potential as drug targets. To yield meaningful results, potency, selectivity, and cellular target engagement of chemical probes need to be stringently validated. Future chemical probes will probably need to fulfil additional criteria such as strict target specificity or the targeting of readers within protein complexes.

Targeting tuberculosis using structure-guided fragment-based drug design

Fragment-based drug discovery is now widely used in academia and industry to obtain small molecule inhibitors for a given target and is established for many fields of research including antimicrobials and oncology. Many molecules derived from fragment-based approaches are already in clinical trials and two - vemurafenib and venetoclax - are on the market, but the approach has been used sparsely in the tuberculosis field. Here, we describe the progress of our group and others, and examine the most recent successes and challenges in developing compounds with antimycobacterial activity.

Comparing atom-based with residue-based descriptors in predicting binding site similarity: do backbone atoms matter?

AIM

We question the level of detail required in protein 3D-representation to detect site similarity which is relevant for polypharmacology prediction.

RESULTS

We modified the in-house program SiteAlign to replace generic pharmacophoric descriptors of cavity-lining amino acids by descriptors accounting for solvent exposure. Benchmarking the novel, atom-based, method (SiteAlign2) revealed no global improvement of performance. However, in the rare cases of no sequence or global structure similarities between the compared proteins, SiteAlign2 was more successful if backbone atoms are key determinants of ligand binding.

CONCLUSION

SiteAlign suits the comparison of binding sites for close or distant homologs. SiteAlign2 provides a better insight into the physical model of site similarity between nonhomologs, but at the expense of an increased sensitivity to atomic coordinates.

Systematic Targeting of Protein-Protein Interactions

Over the past decade, protein-protein interactions (PPIs) have gone from being neglected as 'undruggable' to being considered attractive targets for the development of therapeutics. Recent advances in computational analysis, fragment-based screening, and molecular design have revealed promising strategies to address the basic molecular recognition challenge: how to target large protein surfaces with specificity. Several systematic and complementary workflows have been developed to yield successful inhibitors of PPIs. Here we review the major contemporary approaches utilized for the discovery of inhibitors and focus on a structure-based workflow, from the selection of a biological target to design.