Isocyanide Multicomponent Reactions on Solid-Phase-Coupled DNA Oligonucleotides for Encoded Library Synthesis

Isocyanide multicomponent reactions play a prominent role in drug discovery. This chemistry has hardly been investigated for compatibility with DNA-encoded combinatorial synthesis. The Ugi, Ugi-azide, and Groebke-Blackburn-Bienaymé reactions are well-tolerated by DNA on the solid phase and show a broad scope. However, an oxadiazole-forming variant of the Ugi reaction caused DNA depurination, requiring a more stable hexathymidine DNA for encoded library synthesis. Cheminformatic analysis revealed that isocyanide multicomponent-reaction-based encoded libraries cover a diverse chemical space

Massive X-ray screening reveals two allosteric drug binding sites of SARS-CoV-2 main protease

The coronavirus disease (COVID-19) caused by SARS-CoV-2 is creating tremendous health problems and economical challenges for mankind. To date, no effective drug is available to directly treat the disease and prevent virus spreading. In a search for a drug against COVID-19, we have performed a massive X-ray crystallographic screen of repurposing drug libraries containing 5953 individual compounds against the SARS-CoV-2 main protease (Mpro), which is a potent drug target as it is essential for the virus replication. In contrast to commonly applied X-ray fragment screening experiments with molecules of low complexity, our screen tested already approved drugs and drugs in clinical trials. From the three-dimensional protein structures, we identified 37 compounds binding to Mpro. In subsequent cell-based viral reduction assays, one peptidomimetic and five non-peptidic compounds showed antiviral activity at non-toxic concentrations. Interestingly, two compounds bind outside the active site to the native dimer interface in close proximity to the S1 binding pocket. Another compound binds in a cleft between the catalytic and dimerization domain of Mpro. Neither binding site is related to the enzymatic active site and both represent attractive targets for drug development against SARS-CoV-2. This X-ray screening approach thus has the potential to help deliver an approved drug on an accelerated time-scale for this and future pandemics

X-ray screening identifies active site and allosteric inhibitors of SARS-CoV-2 main protease

The coronavirus disease (COVID-19) caused by SARS-CoV-2 is creating tremendous human suffering. To date, no effective drug is available to directly treat the disease. In a search for a drug against COVID-19, we have performed a high-throughput X-ray crystallographic screen of two repurposing drug libraries against the SARS-CoV-2 main protease (M^(pro)), which is essential for viral replication. In contrast to commonly applied X-ray fragment screening experiments with molecules of low complexity, our screen tested already approved drugs and drugs in clinical trials. From the three-dimensional protein structures, we identified 37 compounds that bind to M^(pro). In subsequent cell-based viral reduction assays, one peptidomimetic and six non-peptidic compounds showed antiviral activity at non-toxic concentrations. We identified two allosteric binding sites representing attractive targets for drug development against SARS-CoV-2

Protein binding site comparison

The aim of the present study was the identification of novel hit compounds for the inhibition of trypanothione synthetase (TryS) from organisms of the genus Leishmania. They are the causative agents of the so-called neglected diseases. There is an urgent need for novel therapeutics for these diseases as the current treatment methods are not sufficiently reliable when compared to the medical management for diseases prevalent in developed high-income countries. The basic idea of this work was to set up a structure-based drug repurposing workflow based on similarities between the ATP binding sites of TryS from Leishmania major and protein kinases. The latter enzymes are well characterised, and this approach benefits from the huge knowledge of drug-like small molecule inhibitors of protein kinases. However, the establishment of such a workflow requires the reliable interplay of multiple software methods for in silico structure-based modelling. The chosen workflow includes the comparative modelling of the enzymes under investigation, MD simulation studies, an in-depth analysis of pocket properties, the comparison of binding sites of TryS and kinases, and a subsequent molecular docking of known inhibitors of protein kinases which are most similar to TryS with respect to the ATP binding site properties. The breakneck developments in the field of in silico hit identification led to the emergence of a myriad of available methods to meet similar targets. Current state-of-the-art methods evolved for often applied structure-based methods such as molecular docking or pharmacophore searches. Unfortunately, methods for the prediction, analysis, and comparison of binding sites are less frequently applied. This led to the parallel development of numerous methods which differ in multiple aspects. This diversity necessitates reliable comparison and benchmark analyses to elucidate the most suitable approaches for a pre-defined scientific question. In consequence, a main part of the present work is dedicated to the comprehensive evaluation of developed software for the prediction and comparison of binding sites. The analyses shed light on the major strengths and restrictions of the methods under investigation. The results ensure that only the most reliable methods are chosen for the problem under investigation. For binding site prediction methods, we can pinpoint a restricted set of exceptionally reliable methods. The case is different for binding site comparison tools. We must finally conclude that the establishment of a consensus approach might be the most appropriate way to identify binding site similarities. Besides the comparison of binding sites based on physicochemical and shape properties, an alternative approach was tested for its applicability for the presented project. Based on the observation that some less closely related proteins binding to similar scaffolds share a common arrangement of SSEs in the ligand binding sites, it was hypothesised that finding similar arrangements of SSEs in unrelated proteins might facilitate the search for novel promising scaffold for yet unexplored enzymes. This so-called “ligand-sensing cores” approach was adopted for the comparison of ATP binding sites of TryS and kinases. However, the results for this case study indicate not only that it is difficult to pinpoint specific and unique secondary structure element arrangements in protein binding sites, but also that the success in establishing a novel method rises and falls with the availability of proper optimisation datasets and the reliability of secondary structure assignment methods. We tried to solve at least the latter part of the problem by developing the novel secondary structure assignment tool SCOT which classifies geometrically uniform helices and strands. But especially with respect to parameter optimisation, further developments of SSE comparison methods and the generation of suitable datasets will be necessary. However, with respect to the target of this study, we could show that well-established methods for the comparison of protein binding sites are perfectly suitable to pinpoint similarities between the nucleotide binding sites of TryS and protein kinases. Known inhibitors of protein kinases with the most significant similarities to the target and structurally related compounds were investigated. Finally, we could propose promising molecules for addressing the ATP binding site of TryS which must now be evaluated experimentally for their potential to inhibit TryS from Leishmania

A benchmark driven guide to binding site comparison: An exhaustive evaluation using tailor-made data sets (ProSPECCTs).

The automated comparison of protein-ligand binding sites provides useful insights into yet unexplored site similarities. Various stages of computational and chemical biology research can benefit from this knowledge. The search for putative off-targets and the establishment of polypharmacological effects by comparing binding sites led to promising results for numerous projects. Although many cavity comparison methods are available, a comprehensive analysis to guide the choice of a tool for a specific application is wanting. Moreover, the broad variety of binding site modeling approaches, comparison algorithms, and scoring metrics impedes this choice. Herein, we aim to elucidate strengths and weaknesses of binding site comparison methodologies. A detailed benchmark study is the only possibility to rationalize the selection of appropriate tools for different scenarios. Specific evaluation data sets were developed to shed light on multiple aspects of binding site comparison. An assembly of all applied benchmark sets (ProSPECCTs-Protein Site Pairs for the Evaluation of Cavity Comparison Tools) is made available for the evaluation and optimization of further and still emerging methods. The results indicate the importance of such analyses to facilitate the choice of a methodology that complies with the requirements of a specific scientific challenge

A benchmark driven guide to binding site comparison: an exhaustive evaluation using tailor-made data sets (ProSPECCTs)

The automated comparison of protein-ligand binding sites provides useful insights into yet unexplored site similarities. Various stages of computational and chemical biology research can benefit from this knowledge. The search for putative off-targets and the establishment of polypharmacological effects by comparing binding sites led to promising results for numerous projects. Although many cavity comparison methods are available, a comprehensive analysis to guide the choice of a tool for a specific application is wanting. Moreover, the broad variety of binding site modeling approaches, comparison algorithms, and scoring metrics impedes this choice. Herein, we aim to elucidate strengths and weaknesses of binding site comparison methodologies. A detailed benchmark study is the only possibility to rationalize the selection of appropriate tools for different scenarios. Specific evaluation data sets were developed to shed light on multiple aspects of binding site comparison. An assembly of all applied benchmark sets (ProSPECCTs–Protein Site Pairs for the Evaluation of Cavity Comparison Tools) is made available for the evaluation and optimization of further and still emerging methods. The results indicate the importance of such analyses to facilitate the choice of a methodology that complies with the requirements of a specific scientific challenge

Optimization and Evaluation Datasets for PiMine

The protein-protein interface comparison software PiMine was developed to provide fast comparisons against databases of known protein-protein complex structures. Its application domains range from the prediction of interfaces and potential interaction partners to the identification of potential small molecule modulators of protein-protein interactions.[1] The protein-protein evaluation datasets are a collection of five datasets that were used for the parameter optimization (ParamOptSet), enrichment assessment (Dimer597 set, Keskin set, PiMineSet), and runtime analyses (RunTimeSet) of protein-protein interface comparison tools. The evaluation datasets contain pairs of interfaces of protein chains that either share sequential and structural similarities or are even sequentially and structurally unrelated. They enable comparative benchmark studies for tools designed to identify interface similarities. Data Set description: The ParamOptSet was designed based on a study on improving the benchmark datasets for the evaluation of protein-protein docking tools [2]. It was used to optimize and fine-tune the geometric search parameters of PiMine. The Dimer597 [3] and Keskin [4] sets were developed earlier. We used them to evaluate PiMine’s performance in identifying structurally and sequentially related interface pairs as well as interface pairs with prominent similarity whose constituting chains are sequentially unrelated. The PiMine set [1] was constructed to assess different quality criteria for reliable interface comparison. It consists of similar pairs of protein-protein complexes of which two chains are sequentially and structurally highly related while the other two chains are unrelated and show different folds. It enables the assessment of the performance when the interfaces of apparently unrelated chains are available only. Furthermore, we could obtain reliable interface-interface alignments based on the similar chains which can be used for alignment performance assessments. Finally, the RunTimeSet [1] comprises protein-protein complexes from the PDB that were predicted to be biologically relevant. It enables the comparison of typical run times of comparison methods and represents also an interesting dataset to screen for interface similarities. References: [1] Graef, J.; Ehrt, C.; Reim, T.; Rarey, M. Database-driven identification of structurally similar protein-protein interfaces (submitted) [2] Barradas-Bautista, D.; Almajed, A.; Oliva, R.; Kalnis, P.; Cavallo, L. Improving classification of correct and incorrect protein-protein docking models by augmenting the training set. Bioinform. Adv. 2023, 3, vbad012. [3] Gao, M.; Skolnick, J. iAlign: a method for the structural comparison of protein–protein interfaces. Bioinformatics 2010, 26, 2259-2265. [4] Keskin, O.; Tsai, C.-J.; Wolfson, H.; Nussinov, R. A new, structurally nonredundant, diverse data set of protein–protein interfaces and its implications. Protein Sci. 2004, 13, 1043-1055

Impact of Binding Site Comparisons on Medicinal Chemistry and Rational Molecular Design

Modern rational drug design not only deals with the search for ligands binding to interesting and promising validated targets but also aims to identify the function and ligands of yet uncharacterized proteins having impact on different diseases. Additionally, it contributes to the design of inhibitors with distinct selectivity patterns and the prediction of possible off-target effects. The identification of similarities between binding sites of various proteins is a useful approach to cope with those challenges. The main scope of this perspective is to describe applications of different protein binding site comparison approaches to outline their applicability and impact on molecular design. The article deals with various substantial application domains and provides some outstanding examples to show how various binding site comparison methods can be applied to promote in silico drug design workflows. In addition, we will also briefly introduce the fundamental principles of different protein binding site comparison methods

Alteration of Protein Binding Affinities by Aqueous Two-Phase Systems Revealed by Pressure Perturbation

Interactions between proteins and ligands, which are fundamental to many biochemical processes essential to life, are mostly studied at dilute buffer conditions. The effects of the highly crowded nature of biological cells and the effects of liquid-liquid phase separation inducing biomolecular droplet formation as a means of membrane-less compartmentalization have been largely neglected in protein binding studies. We investigated the binding of a small ligand (ANS) to one of the most multifunctional proteins, bovine serum albumin (BSA) in an aqueous two-phase system (ATPS) composed of PEG and Dextran. Also, aiming to shed more light on differences in binding mode compared to the neat buffer data, we examined the effect of high hydrostatic pressure (HHP) on the binding process. We observe a marked effect of the ATPS on the binding characteristics of BSA. Not only the binding constants change in the ATPS system, but also the integrity of binding sites is partially lost, which is most likely due to soft enthalpic interactions of the BSA with components in the dense droplet phase of the ATPS. Using pressure modulation, differences in binding sites could be unravelled by their different volumetric and hydration properties. Regarding the vital biological relevance of the study, we notice that extreme biological environments, such as HHP, can markedly affect the binding characteristics of proteins. Hence, organisms experiencing high-pressure stress in the deep sea need to finely adjust the volume changes of their biochemical reactions in cellulo