Identifying Metal Binding Sites in Proteins Using Homologous Structures, the MADE Approach.

In order to identify the locations of metal ions in the binding sites of proteins, we have developed a method named the MADE (MAcromolecular DEnsity and Structure Analysis) approach. The MADE approach represents an evolution of our previous toolset, the ProBiS H2O (MD) methodology, for the identification of conserved water molecules. Our method uses experimental structures of proteins homologous to a query, which are subsequently superimposed upon it. Areas with a particular species present in a similar location among many homologous protein structures are identified using a clustering algorithm. Dense clusters likely represent positions containing species important to the query protein structure or function. We analyze well-characterized apo protein structures and show that the MADE approach can identify clusters corresponding to the expected positions of metal ions in their binding sites. The greatest advantage of our method lies in its generality. It can in principle be applied to any species found in protein records; it is not only limited to metal ions. We additionally demonstrate that the MADE approach can be successfully applied to predict the location of cofactors in computer-modeled structures, e.g., via AlphaFold. We also conduct a careful protein superposition method comparison and find our methodology robust and the results largely independent of the selected protein superposition algorithm. We postulate that with increasing structural data availability, additional applications of the MADE approach will be possible such as non-protein systems, water network identification, protein binding site elaboration, and analysis of binding events, all in a dynamic manner. We have implemented the MADE approach as a plugin for the PyMOL molecular visualization tool. The MADE plugin is available free of charge at https://gitlab.com/Jukic/made_software.

Naive Prediction of Protein Backbone Phi and Psi Dihedral Angles Using Deep Learning.

Protein structure prediction represents a significant challenge in the field of bioinformatics, with the prediction of protein structures using backbone dihedral angles recently achieving significant progress due to the rise of deep neural network research. However, there is a trend in protein structure prediction research to employ increasingly complex neural networks and contributions from multiple models. This study, on the other hand, explores how a single model transparently behaves using sequence data only and what can be expected from the predicted angles. To this end, the current paper presents data acquisition, deep learning model definition, and training toward the final protein backbone angle prediction. The method applies a simple fully connected neural network (FCNN) model that takes only the primary structure of the protein with a sliding window of size 21 as input to predict protein backbone ϕ and ψ dihedral angles. Despite its simplicity, the model shows surprising accuracy for the ϕ angle prediction and somewhat lower accuracy for the ψ angle prediction. Moreover, this study demonstrates that protein secondary structure prediction is also possible with simple neural networks that take in only the protein amino-acid residue sequence, but more complex models are required for higher accuracies.

In Vitro Bioaccessibility Assessment of Phenolic Compounds from Encapsulated Grape Pomace Extract by Ionic Gelation.

Grape pomace is a by-product of winemaking characterized by a rich chemical composition from which phenolics stand out. Phenolics are health-promoting agents, and their beneficial effects depend on their bioaccessibility, which is influenced by gastrointestinal digestion. The effect of encapsulating phenol-rich grape pomace extract (PRE) with sodium alginate (SA), a mixture of SA with gelatin (SA-GEL), and SA with chitosan (SA-CHIT) on the bioaccessibility index (BI) of phenolics during simulated digestion in vitro was studied. A total of 27 individual phenolic compounds (IPCs) were quantified by UHPLC. The addition of a second coating to SA improved the encapsulation efficiency (EE), and the highest EE was obtained for SA-CHIT microbeads (56.25%). Encapsulation affected the physicochemical properties (size, shape and texture, morphology, crystallinity) of the produced microbeads, which influenced the delivery of phenolics to the intestine and their BI. Thus, SA-GEL microbeads had the largest size parameters, as confirmed by scanning electron microscopy (SEM), and the highest BI for total phenolic compounds and IPCs (gallic acid, 3,4-dihydroxybenzoic acid and o-coumaric acid, epicatechin, and gallocatechin gallate) ranged from 96.20 to 1011.3%. The results suggest that encapsulated PRE has great potential to be used as a functional ingredient in products for oral administration.

Conserved Water Networks Identification for Drug Design Using Density Clustering Approaches on Positional and Orientational Data.

This work describes the development and testing of a method for the identification and classification of conserved water molecules and their networks from molecular dynamics (MD) simulations. The conserved waters in the active sites of proteins influence protein-ligand binding. Recently, several groups have argued that a water network formed from conserved waters can be used to interpret the thermodynamic signature of the binding site. We implemented a novel methodology in which we apply the complex approach to categorize water molecules extracted from the MD simulation trajectories using clustering approaches. The main advantage of our methodology as compared to current state of the art approaches is the inclusion of the information on the orientation of hydrogen atoms to further inform the clustering algorithm and to classify the conserved waters into different subtypes depending on how strongly certain orientations are preferred. This information is vital for assessing the stability of water networks. The newly developed approach is described in detail as well as validated against known results from the scientific literature including comparisons with the experimental data on thermolysin, thrombin, and Haemophilus influenzae virulence protein SiaP as well as with the previous computational results on thermolysin. We observed excellent agreement with the literature and were also able to provide additional insights into the orientations of the conserved water molecules, highlighting the key interactions which stabilize them. The source code of our approach, as well as the utility tools used for visualization, are freely available on GitHub.

Comparative Analyses of Medicinal Chemistry and Cheminformatics Filters with Accessible Implementation in Konstanz Information Miner (KNIME).

High-throughput virtual screening (HTVS) is, in conjunction with rapid advances in computer hardware, becoming a staple in drug design research campaigns and cheminformatics. In this context, virtual compound library design becomes crucial as it generally constitutes the first step where quality filtered databases are essential for the efficient downstream research. Therefore, multiple filters for compound library design were devised and reported in the scientific literature. We collected the most common filters in medicinal chemistry (PAINS, REOS, Aggregators, van de Waterbeemd, Oprea, Fichert, Ghose, Mozzicconacci, Muegge, Egan, Murcko, Veber, Ro3, Ro4, and Ro5) to facilitate their open access use and compared them. Then, we implemented these filters in the open platform Konstanz Information Miner (KNIME) as a freely accessible and simple workflow compatible with small or large compound databases for the benefit of the readers and for the help in the early drug design steps.

Neuropilin (NRPs) Related Pathological Conditions and Their Modulators.

Neuropilin 1 (NRP1) represents one of the two homologous neuropilins (NRP, splice variants of neuropilin 2 are the other) found in all vertebrates. It forms a transmembrane glycoprotein distributed in many human body tissues as a (co)receptor for a variety of different ligands. In addition to its physiological role, it is also associated with various pathological conditions. Recently, NRP1 has been discovered as a coreceptor for the SARS-CoV-2 viral entry, along with ACE2, and has thus become one of the COVID-19 research foci. However, in addition to COVID-19, the current review also summarises its other pathological roles and its involvement in clinical diseases like cancer and neuropathic pain. We also discuss the diversity of native NRP ligands and perform a joint analysis. Last but not least, we review the therapeutic roles of NRP1 and introduce a series of NRP1 modulators, which are typical peptidomimetics or other small molecule antagonists, to provide the medicinal chemistry community with a state-of-the-art overview of neuropilin modulator design and NRP1 druggability assessment.

A Cross-Sectional Study of Psychiatric Comorbidity in Croatian Homeland War Veterans Who Were Held as Prisoners of War and Are Affected by Posttraumatic Stress Disorder.

BACKGROUND: As a extremely traumatic experience, captivity may cause other mental disorders in addition to posttraumatic stress disorder, which is highly prevalent among ex-prisoners of war, and which often occurs in comorbidity with at least one other mental disorder. This objective of this study is to identify the incidence of comorbid mental disorders in Homeland war veterans ex-prisoners of war affected by posttraumatic stress disorder, as well as to identify the factors that influenced psychiatric comorbidity. SUBJECTS AND METHODS: The study sample comprised 264 subjects, all of whom were Croatian Homeland War veterans with combat experience in the defence of the Republic of Croatia, and all of whom fulfilled clinical criteria for posttraumatic stress disorder at the time of the study. The subjects were divided into two groups: the experimental group was composed of ex-prisoners of war, and the control group of veterans who had never been prisoners of war. The methods of sociodemographic questionnaire, posttraumatic stress disorder self-report checklist and the Harvard Trauma Questionnaire were used in the study. Psychiatric comorbidity data were retrieved from the subjects' anamnesis and medical records. RESULTS: The results showed that ex-prisoners of war were exposed to a statistically much higher number of traumatic events, and had a significantly higher total number of psychiatric comorbidities (p<0.01) than the control group. The incidence of acute and transient psychotic disorders, generalized anxiety disorders and psychological and behavioural factors associated with disorders or diseases classified elsewhere was significantly higher among ex-prisoners of war. There was no statistically significant difference in overall posttraumatic stress disorder intensity between the two groups (p<0.05). CONCLUSIONS: The results of the study confirm our hypothesis that the incidence of psychiatric comorbidity is higher in ex-prisoners of war.

Potential Novel Thioether-Amide or Guanidine-Linker Class of SARS-CoV-2 Virus RNA-Dependent RNA Polymerase Inhibitors Identified by High-Throughput Virtual Screening Coupled to Free-Energy Calculations.

SARS-CoV-2, or severe acute respiratory syndrome coronavirus 2, represents a new pathogen from the family of Coronaviridae that caused a global pandemic of COVID-19 disease. In the absence of effective antiviral drugs, research of novel therapeutic targets such as SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) becomes essential. This viral protein is without a human counterpart and thus represents a unique prospective drug target. However, in vitro biological evaluation testing on RdRp remains difficult and is not widely available. Therefore, we prepared a database of commercial small-molecule compounds and performed an in silico high-throughput virtual screening on the active site of the SARS-CoV-2 RdRp using ensemble docking. We identified a novel thioether-amide or guanidine-linker class of potential RdRp inhibitors and calculated favorable binding free energies of representative hits by molecular dynamics simulations coupled with Linear Interaction Energy calculations. This innovative procedure maximized the respective phase-space sampling and yielded non-covalent inhibitors representing small optimizable molecules that are synthetically readily accessible, commercially available as well as suitable for further biological evaluation and mode of action studies.

Commercial SARS-CoV-2 Targeted, Protease Inhibitor Focused and Protein-Protein Interaction Inhibitor Focused Molecular Libraries for Virtual Screening and Drug Design.

Since December 2019, the new SARS-CoV-2-related COVID-19 disease has caused a global pandemic and shut down the public life worldwide. Several proteins have emerged as potential therapeutic targets for drug development, and we sought out to review the commercially available and marketed SARS-CoV-2-targeted libraries ready for high-throughput virtual screening (HTVS). We evaluated the SARS-CoV-2-targeted, protease-inhibitor-focused and protein-protein-interaction-inhibitor-focused libraries to gain a better understanding of how these libraries were designed. The most common were ligand- and structure-based approaches, along with various filtering steps, using molecular descriptors. Often, these methods were combined to obtain the final library. We recognized the abundance of targeted libraries offered and complimented by the inclusion of analytical data; however, serious concerns had to be raised. Namely, vendors lack the information on the library design and the references to the primary literature. Few references to active compounds were also provided when using the ligand-based design and usually only protein classes or a general panel of targets were listed, along with a general reference to the methods, such as molecular docking for the structure-based design. No receptor data, docking protocols or even references to the applied molecular docking software (or other HTVS software), and no pharmacophore or filter design details were given. No detailed functional group or chemical space analyses were reported, and no specific orientation of the libraries toward the design of covalent or noncovalent inhibitors could be observed. All libraries contained pan-assay interference compounds (PAINS), rapid elimination of swill compounds (REOS) and aggregators, as well as focused on the drug-like model, with the majority of compounds possessing their molecular mass around 500 g/mol. These facts do not bode well for the use of the reviewed libraries in drug design and lend themselves to commercial drug companies to focus on and improve.

Prioritisation of Compounds for 3CLpro Inhibitor Development on SARS-CoV-2 Variants.

COVID-19 represents a new potentially life-threatening illness caused by severe acute respiratory syndrome coronavirus 2 or SARS-CoV-2 pathogen. In 2021, new variants of the virus with multiple key mutations have emerged, such as B.1.1.7, B.1.351, P.1 and B.1.617, and are threatening to render available vaccines or potential drugs ineffective. In this regard, we highlight 3CLpro, the main viral protease, as a valuable therapeutic target that possesses no mutations in the described pandemically relevant variants. 3CLpro could therefore provide trans-variant effectiveness that is supported by structural studies and possesses readily available biological evaluation experiments. With this in mind, we performed a high throughput virtual screening experiment using CmDock and the "In-Stock" chemical library to prepare prioritisation lists of compounds for further studies. We coupled the virtual screening experiment to a machine learning-supported classification and activity regression study to bring maximal enrichment and available structural data on known 3CLpro inhibitors to the prepared focused libraries. All virtual screening hits are classified according to 3CLpro inhibitor, viral cysteine protease or remaining chemical space based on the calculated set of 208 chemical descriptors. Last but not least, we analysed if the current set of 3CLpro inhibitors could be used in activity prediction and observed that the field of 3CLpro inhibitors is drastically under-represented compared to the chemical space of viral cysteine protease inhibitors. We postulate that this methodology of 3CLpro inhibitor library preparation and compound prioritisation far surpass the selection of compounds from available commercial "corona focused libraries".

Mouse genetics identifies unique and overlapping functions of fibroblast growth factor receptors in keratinocytes.

Fibroblast growth factors (FGFs) are key regulators of tissue development, homeostasis and repair, and abnormal FGF signalling is associated with various human diseases. In human and murine epidermis, FGF receptor 3 (FGFR3) activation causes benign skin tumours, but the consequences of FGFR3 deficiency in this tissue have not been determined. Here, we show that FGFR3 in keratinocytes is dispensable for mouse skin development, homeostasis and wound repair. However, the defect in the epidermal barrier and the resulting inflammatory skin disease that develops in mice lacking FGFR1 and FGFR2 in keratinocytes were further aggravated upon additional loss of FGFR3. This caused fibroblast activation and fibrosis in the FGFR1/FGFR2 double-knockout mice and even more in mice lacking all three FGFRs, revealing functional redundancy of FGFR3 with FGFR1 and FGFR2 for maintaining the epidermal barrier. Taken together, our study demonstrates that FGFR1, FGFR2 and FGFR3 act together to maintain epidermal integrity and cutaneous homeostasis, with FGFR2 being the dominant receptor.

Ensemble Docking Coupled to Linear Interaction Energy Calculations for Identification of Coronavirus Main Protease (3CLpro) Non-Covalent Small-Molecule Inhibitors.

SARS-CoV-2, or severe acute respiratory syndrome coronavirus 2, represents a new strain of Coronaviridae. In the closing 2019 to early 2020 months, the virus caused a global pandemic of COVID-19 disease. We performed a virtual screening study in order to identify potential inhibitors of the SARS-CoV-2 main viral protease (3CLpro or Mpro). For this purpose, we developed a novel approach using ensemble docking high-throughput virtual screening directly coupled with subsequent Linear Interaction Energy (LIE) calculations to maximize the conformational space sampling and to assess the binding affinity of identified inhibitors. A large database of small commercial compounds was prepared, and top-scoring hits were identified with two compounds singled out, namely 1-[(R)-2-(1,3-benzimidazol-2-yl)-1-pyrrolidinyl]-2-(4-methyl-1,4-diazepan-1-yl)-1-ethanone and [({(S)-1-[(1H-indol-2-yl)methyl]-3-pyrrolidinyl}methyl)amino](5-methyl-2H-pyrazol-3-yl)formaldehyde. Moreover, we obtained a favorable binding free energy of the identified compounds, and using contact analysis we confirmed their stable binding modes in the 3CLpro active site. These compounds will facilitate further 3CLpro inhibitor design.

α-Unsaturated 3-Amino-1-carboxymethyl-ß-lactams as Bacterial PBP Inhibitors: Synthesis and Biochemical Assessment.

Innovative monocyclic ß-lactam entities create opportunities in the battle against resistant bacteria because of their PBP acylation potential, intrinsically high ß-lactamase stability and compact scaffold. α-Benzylidene-substituted 3-amino-1-carboxymethyl-ß-lactams were recently shown to be potent PBP inhibitors and constitute eligible anchor points for synthetic elaboration of the chemical space around the central ß-lactam ring. The present study discloses a 12-step synthesis of ten α-arylmethylidenecarboxylates using a microwave-assisted Wittig olefination as the crucial reaction step. The library was designed aiming at enhanced ß-lactam electrophilicity and extended electron flow after enzymatic attack. Additionally, increased ß-lactamase stability and intermolecular target interaction were envisioned by tackling both the substitution pattern of the aromatic ring and the ß-lactam C4-position. The significance of α-unsaturation was validated and the R39/PBP3 inhibitory potency shown to be augmented the most through decoration of the aromatic ring with electron-withdrawing groups. Furthermore, ring cleavage by representative ß-lactamases was ruled out, providing new insights in the SAR landscape of monocyclic ß-lactams as eligible PBP or ß-lactamase inhibitors.

Reaching toward underexplored targets in antibacterial drug design.

The increase of antimicrobial resistance necessitates the renewal and strong research involvement in antibacterial drug design. In the following work, we comment on the key approaches used in development of new antibacterials, focusing on intracellular therapeutic targets that have been so far mostly underexplored: the enzymes of the Mur pathway MurA to MurF. We identify common obstacles observed during research on MurA, MurB, and Mur ligases inhibitors and their development into potential antibacterial compounds, and discern several approaches and solutions to tackle the whole-cell activity of designed compounds. Furthermore, we consolidate recent literature reports and encourage the further research on Mur enzymes.

Antibacterial and ß-Lactamase Inhibitory Activity of Monocyclic ß-Lactams.

Due to the widespread emergence of resistant bacterial strains, an urgent need for the development of new antibacterial agents with novel modes of action has emerged. The discovery of naturally occurring monocyclic ß-lactams in the late 1970s, mainly active against aerobic Gram-negative bacteria, has introduced a new approach in the design and development of novel antibacterial ß-lactam agents. The main goal was the derivatization of the azetidin-2-one core in order to improve their antibacterial potency, broaden their spectrum of activity, and enhance their ß-lactamase stability. In that respect, our review covers the updates in the field of monocyclic ß-lactam antibiotics during the last three decades, taking into account an extensive collection of references. An overview of the relationships between the structural features of these monocyclic ß-lactams, classified according to their N-substituent, and the associated antibacterial or ß-lactamase inhibitory activities is provided. The different paragraphs disclose a number of well-established classes of compounds, such as monobactams, monosulfactams, monocarbams, monophosphams, nocardicins, as well as other known representative classes. Moreover, this review draws attention to some less common but, nevertheless, possibly important types of monocyclic ß-lactams and concludes by highlighting the recent developments on siderophore-conjugated classes of monocyclic ß-lactams.

In Silico Design and Enantioselective Synthesis of Functionalized Monocyclic 3-Amino-1-carboxymethyl-ß-lactams as Inhibitors of Penicillin-Binding Proteins of Resistant Bacteria.

As a complement to the renowned bicyclic ß-lactam antibiotics, monocyclic analogues provide a breath of fresh air in the battle against resistant bacteria. In that framework, the present study discloses the in silico design and unprecedented ten-step synthesis of eleven nocardicin-like enantiomerically pure 2-{3-[2-(2-aminothiazol-4-yl)-2-(methoxyimino)acetamido]-2-oxoazetidin-1-yl}acetic acids starting from serine as a readily accessible precursor. The capability of this novel class of monocyclic 3-amino-ß-lactams to inhibit penicillin-binding proteins (PBPs) of various (resistant) bacteria was assessed, revealing the potential of α-benzylidenecarboxylates as interesting leads in the pursuit of novel PBP inhibitors. No deactivation by representative enzymes belonging to the four ß-lactamase classes was observed, while weak inhibition of class C ß-lactamase P99 was demonstrated.

Synthesis and structure-activity relationship study of novel quinazolinone-based inhibitors of MurA.

MurA is an intracellular bacterial enzyme that is essential for peptidoglycan biosynthesis, and is therefore an important target for antibacterial drug discovery. We report the synthesis, in silico studies and extensive structure-activity relationships of a series of quinazolinone-based inhibitors of MurA from Escherichia coli. 3-Benzyloxyphenylquinazolinones showed promising inhibitory potencies against MurA, in the low micromolar range, with an IC50 of 8µM for the most potent derivative (58). Furthermore, furan-substituted quinazolinones (38, 46) showed promising antibacterial activities, with MICs from 1µg/mL to 8µg/mL, concomitant with their MurA inhibitory potencies. These data represent an important step towards the development of novel antimicrobial agents to combat increasing bacterial resistance.

Identification of Conserved Water Sites in Protein Structures for Drug Design.

Identification of conserved waters in protein structures is a challenging task with applications in molecular docking and protein stability prediction. As an alternative to computationally demanding simulations of proteins in water, experimental cocrystallized waters in the Protein Data Bank (PDB) in combination with a local structure alignment algorithm can be used for reliable prediction of conserved water sites. We developed the ProBiS H2O approach based on the previously developed ProBiS algorithm, which enables identification of conserved water sites in proteins using experimental protein structures from the PDB or a set of custom protein structures available to the user. With a protein structure, a binding site, or an individual water molecule as a query, ProBiS H2O collects similar proteins from the PDB and performs local or binding site-specific superimpositions of the query structure with similar proteins using the ProBiS algorithm. It collects the experimental water molecules from the similar proteins and transposes them to the query protein. Transposed waters are clustered by their mutual proximity, which enables identification of discrete sites in the query protein with high water conservation. ProBiS H2O is a robust and fast new approach that uses existing experimental structural data to identify conserved water sites on the interfaces of protein complexes, for example protein-small molecule interfaces, and elsewhere on the protein structures. It has been successfully validated in several reported proteins in which conserved water molecules were found to play an important role in ligand binding with applications in drug design.

Chlorocarbonylsulfenyl Chloride Cyclizations Towards Piperidin-3-yl-oxathiazol-2-ones as Potential Covalent Inhibitors of Threonine Proteases.

Using rescaffolding approach, we designed piperidine compounds decorated with an electrophilic oxathiazol-2-one moiety that is known to confer selectivity towards threonine proteases. Our efforts to prepare products according to the published procedures were not successful. Furthermore we identified major side products containing nitrile functional group, resulting from carboxamide dehydration. We systematically optimized reaction conditions towards our desired products to identify heating of carboxamides with chlorocarbonylsulfenyl chloride and sodium carbonate as base in dioxane at 100 °C. Our efforts culminated in the preparation of a small series of piperidin-3-yl-oxathiazol-2-ones that are suitable for further biological evaluation.

Postoperative pain in complex ophthalmic surgical procedures: comparing practice with guidelines.

OBJECTIVE: To analyze the management of postoperative pain after complex ophthalmic surgery and to compare it to the guidelines. DESIGN: A retrospective study. SETTING: University Hospital Split, Croatia. SUBJECTS: Patients (N = 447) who underwent complex ophthalmic surgical procedures from 2008 to 2012. METHODS: The following data were extracted from patient medical records: age, gender, type and dosage of premedication, preoperative patient's physical status, type of procedure, duration of procedure-surgical and anesthesia time, type and dosage of anesthesia, the type and dosage of postoperative analgesia for each postoperative day. RESULTS: None of the patients had information about pain intensity in their records. There were 90% patients who did not receive any medication the night before surgery, 54% did not receive any premedication immediately before surgery, 19% did not receive any pain medication after the surgery in the operating room and 46% of patients did not receive any analgesics after being released to the ophthalmology department. Among those who received analgesia after surgery, 98% received only one dose of an analgesic, and 93% of patients received analgesia only on the day of the surgery. Furthermore, patients were returned to the department immediately after surgery, without intensive monitoring. During the analyzed five years there were no educational session organized by anesthesiologist to the ophthalmic surgeons. CONCLUSIONS: Postoperative pain management and perioperative care of patients undergoing major ophthalmic surgery indicates lack of attention towards pain intensity and postoperative analgesia. Appropriate interventions should be employed to improve postoperative pain management, to facilitate patient recovery.