Amino acid depletion in the blood serum is currently being exploited and explored for therapies in tumors or viral infections that are auxotrophic for a certain amino acid or have a metabolic defect and cannot produce it. The success of these treatments is because normal cells remain unaltered since they are less demanding and/or can synthesize these compounds in sufficient amounts for their needs by other mechanisms. Areas covered: This review is focused on amino acid depriving enzymes and their formulations that have been successfully used in the treatment of several types of cancer and viral infections. Particular attention will be given to the enzymes L-asparaginase, L-arginase, L-arginine deiminase, and L-methionine-γ-lyase. Expert opinion: The immunogenicity and other toxic effects are perhaps the major limitations of these therapies, but they have been successfully decreased either through the expression of these enzymes from other organisms, recombination processes, pegylation of the selected enzymes or by specific mutations in the proteins. In 2006, FDA has already approved the use of L-asparaginase in the treatment of acute lymphoblastic leukemia. Other enzymes and in particular L-arginase, L-arginine deiminase, and L-methioninase have been showing promising results in vitro and in vivo studies.

Quantum mechanics/molecular mechanics (QM/MM) methods are presently a well‐established alternative for the study of enzymatic reaction mechanisms. They enable the description of a small part of the enzyme, where reactions take place through QM, while the majority of the thousands of atoms that comprise these biomolecules are handled through MM. While different “flavors” and variations in the QM/MM field exist, this review will focus more on the application of the ONIOM methodology, presenting a fresh perspective on the application of this popular method in light of the growth in computational power and level of sophistication of the different methodologies that it can combine. In addition to a brief presentation of the basic principles behind these methods, this review will discuss different examples of applicability, common choices, practical considerations, and main problems involved, stemming from our experience in this field. Finally, a reflection on the future challenges for the next decade in the QM/MM modeling of enzymatic mechanisms is presented.

The notable advances obtained by computational (bio)chemistry provided its widespread use in many areas of science, in particular, in the study of reaction mechanisms. These studies involve a huge number of complex calculations, which are often carried out using the Gaussian suite of programs. The preparation of input files and the analysis of the output files are not easy tasks and often involve laborious and complex steps. Taking this into account, we developed molUP: a VMD plugin that offers a complete set of tools that enhance the preparation of QM and ONIOM (QM/MM, QM/QM, and QM/QM/MM) calculations. The starting structures for these calculations can be imported from different chemical formats. A set of tools is available to help the user to examine or modify any geometry parameter. This includes the definition of layers in ONIOM calculations, choosing fixed atoms during geometry optimizations, the recalculation or adjustment of the atomic charges, performing SCANs or IRC calculations, etc. molUP also extracts the geometries from the output files as well as the energies of each of them. All of these tasks are performed in an interactive GUI that is extremely helpful for the user. MolUP was developed to be easy to handle by inexperienced users, but simultaneously to be a fast and flexible graphical interface to allow the advanced users to take full advantage of this plugin. The program is available, free of charges, for macOS, Linux, and Windows at the PortoBioComp page https://www.fc.up.pt/PortoBioComp/database/doku.php?id=molup. © 2018 Wiley Periodicals, Inc.

Serine hydroxymethyltransferase (SHMT) is an important drug target to fight malaria, which is one of the most devastating infectious diseases, with 216 million cases cited and accounting for ∼450 000 deaths in 2016. In this paper, computational studies were performed to unveil the catalytic mechanism of SHMT using quantum mechanics/molecular mechanics (QM/ MM) methodologies. This enzyme is responsible for the extraordinary cyclization of a tetrahydrofolate (THF) into 5,10methylene−THF. This process is catalyzed by a pyridoxal-5′phosphate (PLP) cofactor that binds L-serine and, from this, one molecule of L-glycine is produced. The results show that the catalytic process occurs in eight sequential steps that involve an αelimination, the cyclization of the 5-hydroxymethyl−THF intermediate into 5,10-methylene−THF, and the protonation of the quinonoid intermediate. According to the calculated energetic profile, the rate-limiting step of the full mechanism is the elimination of the hydroxymethyl group, from which results a formaldehyde intermediate that then becomes covalently bonded to the THF cofactor. The calculated barrier (DLPNO−CCSD(T)/CBS:ff99SB) for the rate-limiting step (18.0 kcal/mol) agrees very well with the experimental kinetic results (15.7−16.2 kcal/mol). The results also highlight the key role played by Glu57 during the full catalytic process and particularly in the first step of the mechanism that requires an anionic Glu57, contrasting with some proposals available in the literature for this step. It was also concluded that the cyclization of THF must occur in the enzyme, rather than in solution, as it has been proposed also in the past. Together, all of these results provide knowledge and insight on the catalytic mechanism of SHMT, which can now be used to develop inhibitors targeting SHMT and, therefore, antimalaria drugs.

Herein we present the VMD Store, an open-source VMD plugin that simplifies the way that users browse, discover, install, update, and uninstall extensions for the Visual Molecular Dynamics (VMD) software. The VMD Store obtains data about all the indexed VMD extensions hosted on GitHub and presents a one-click mechanism to install and configure VMD extensions. This plugin arises in an attempt to aggregate all VMD extensions into a single platform. The VMD Store is available, free of charge, for Windows, macOS, and Linux at and requires VMD 1.9.3 (or later).

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiologic agent responsible for the recent coronavirus disease 2019 (COVID-19) pandemic. Productive SARS-CoV-2 infection relies on viral entry into cells expressing angiotensin-converting enzyme 2 (ACE2). Indeed, viral entry into cells is mostly mediated by the early interaction between the viral spike protein S and its ACE2 receptor. The S/ACE2 complex is, thus, the first contact point between the incoming virus and its cellular target; consequently, it has been considered an attractive therapeutic target. To further characterize this interaction and the cellular processes engaged in the entry step of the virus, we set up various in silico, in vitro and in cellulo approaches that allowed us to specifically monitor the S/ACE2 association. We report here a computational model of the SARS-CoV-2 S/ACE2 complex, as well as its biochemical and biophysical monitoring using pulldown, AlphaLISA and biolayer interferometry (BLI) binding assays. This led us to determine the kinetic parameters of the S/ACE2 association and dissociation steps. In parallel to these in vitro approaches, we developed in cellulo transduction assays using SARS-CoV-2 pseudotyped lentiviral vectors and HEK293T-ACE2 cell lines generated in-house. This allowed us to recapitulate the early replication stage of the infection mediated by the S/ACE2 interaction and to detect cell fusion induced by the interaction. Finally, a cell imaging system was set up to directly monitor the S/ACE2 interaction in a cellular context and a flow cytometry assay was developed to quantify this association at the cell surface. Together, these different approaches are available for both basic and clinical research, aiming to characterize the entry step of the original SARS-CoV-2 strain and its variants as well as to investigate the possible chemical modulation of this interaction. All these models will help in identifying new antiviral agents and new chemical tools for dissecting the virus entry step.

In this article, Quantum mechanical/molecular mechanical (QM/MM) methods were used to study the full catalytic mechanism of xanthine oxidase (XO). The XO catalyzes the conversion of xanthine (XAN) to uric...

No abstract