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.
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.
The enzymatic activity of butyrylcholinesterase (BChE) in the brain increases with the progression of Alzheimer’s disease, thus classifying BChE as a promising drug target in advanced Alzheimer’s ...disease. We used structure-based drug discovery approaches to develop potent, selective, and reversible human BChE inhibitors. The most potent, compound 3, had a picomolar inhibition constant versus BChE due to strong cation−π interactions, as revealed by the solved crystal structure of its complex with human BChE. Additionally, compound 3 inhibits BChE ex vivo and is noncytotoxic. In vitro pharmacokinetic experiments show that compound 3 is highly protein bound, highly permeable, and metabolically stable. Finally, compound 3 crosses the blood–brain barrier, and it improves memory, cognitive functions, and learning abilities of mice in a scopolamine model of dementia. Compound 3 is thus a promising advanced lead compound for the development of drugs for alleviating symptoms of cholinergic hypofunction in patients with advanced Alzheimer’s disease.
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.
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•Synthesis and extensive SAR of a series of quinazolinone-based inhibitors of MurA.•Potent MurA inhibitors with IC50 in low micromolar range were discovered.•Some quinazolinone-based ...MurA inhibitors possess antibacterial activity.•Important compounds in the development of novel antimicrobial agents.
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.
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”.
The ProBiS H2O MD approach for identification of conserved waters and water sites of interest in macromolecular systems, which is becoming a typical step in a structure-based drug design or ...macromolecular study in general, is described. This work explores an extension of the ProBiS H2O approach introduced by Jukič et al. Indeed, water molecules are key players in the interaction mechanisms of macromolecules and small molecules and play structural roles. Our earlier developed approach, ProBiS H2O, is a simple and transparent workflow for conserved water detection. Here we have considered generalizing the idea by supplementing the experimental data with data derived from molecular dynamics to facilitate work on less known systems. Newly developed ProBiS H2O MD workflow uses trajectory data, extracts and identifies interesting water sites, and visualizes the results. ProBiS H2O MD can thus robustly process molecular dynamic trajectory snapshots, perform local superpositions, collect water location data, and perform density-based clustering to identify discrete sites with high conservation of water molecules. This is a new approach that uses experimental data in silico to identify interesting water sites. Methodology is fast and water-model or molecular dynamics software independent. Trends in the conservation of water molecules can be followed over a variety of trajectories, and our approach has been successfully validated using reported protein systems with experimentally observed conserved water molecules. ProBiS H2O MD is freely available as PyMOL plugin at http://insilab.org.
In this report we present a flow photochemical bromination of a 5-methyl-substituted pyrimidine precursor of rosuvastatin. The study demonstrated that the reaction productivity can be increased ...markedly with a flow-mode approach compared to a batch-mode synthesis. Indeed, reaction times can be significantly shortened from a range of hours to a range of minutes. Moreover, in addition to process intensification, the study demonstrated that significantly lower overall levels of side products are obtained when photochemical bromination is conducted in a flow mode.
We report the successful implementation of virtual screening in the discovery of new inhibitors of undecaprenyl pyrophosphate synthase (UppS) from
UppS is an essential enzyme in the biosynthesis of ...bacterial cell wall. It catalyzes the condensation of farnesyl pyrophosphate (FPP) with eight consecutive isopentenyl pyrophosphate units (IPP), in which new
-double bonds are formed, to generate undecaprenyl pyrophosphate. The latter serves as a lipid carrier for peptidoglycan synthesis, thus representing an important target in the antibacterial drug design. A pharmacophore model was designed on a known bisphosphonate
and used to prepare an enriched compound library that was further docked into UppS conformational ensemble generated by molecular dynamics experiment. The docking resulted in three anthranilic acid derivatives with promising inhibitory activity against UppS. Compound
displayed high inhibitory potency (IC
= 25 μM) and good antibacterial activity against
BW25113 Δ
strain (MIC = 0.5 μg/mL).
Advances in computer hardware and the availability of high-performance supercomputing platforms and parallel computing, along with artificial intelligence methods are successfully complementing ...traditional approaches in medicinal chemistry. In particular, machine learning is gaining importance with the growth of the available data collections. One of the critical areas where this methodology can be successfully applied is in the development of new antibacterial agents. The latter is essential because of the high attrition rates in new drug discovery, both in industry and in academic research programs. Scientific involvement in this area is even more urgent as antibacterial drug resistance becomes a public health concern worldwide and pushes us increasingly into the post-antibiotic era. In this review, we focus on the latest machine learning approaches used in the discovery of new antibacterial agents and targets, covering both small molecules and antibacterial peptides. For the benefit of the reader, we summarize all applied machine learning approaches and available databases useful for the design of new antibacterial agents and address the current shortcomings.
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