Redefining the Limits of Functional Continuity in the Early Evolution of P-Loop NTPases.

At the heart of many nucleoside triphosphatases is a conserved phosphate-binding sequence motif. A current model of early enzyme evolution proposes that this 6-8 residue motif could have sparked the emergence of the very first nucleoside triphosphatases - a striking example of evolutionary continuity from simple beginnings, if true. To test this provocative model, seven disembodied Walker A-derived peptides were extensively computationally characterized.

Analysis of mutations in precision oncology using the automated, accurate, and user-friendly web tool PredictONCO.

Next-generation sequencing technology has created many new opportunities for clinical diagnostics, but it faces the challenge of functional annotation of identified mutations. Various algorithms have been developed to predict the impact of missense variants that influence oncogenic drivers. However, computational pipelines that handle biological data must integrate multiple software tools, which can add complexity and hinder non-specialist users from accessing the pipeline.

A computational workflow for analysis of missense mutations in precision oncology.

Every year, more than 19 million cancer cases are diagnosed, and this number continues to increase annually. Since standard treatment options have varying success rates for different types of cancer, understanding the biology of an individual's tumour becomes crucial, especially for cases that are difficult to treat. Personalised high-throughput profiling, using next-generation sequencing, allows for a comprehensive examination of biopsy specimens.

PredictONCO: a web tool supporting decision-making in precision oncology by extending the bioinformatics predictions with advanced computing and machine learning.

PredictONCO 1.0 is a unique web server that analyzes effects of mutations on proteins frequently altered in various cancer types. The server can assess the impact of mutations on the protein sequential and structural properties and apply a virtual screening to identify potential inhibitors that could be used as a highly individualized therapeutic approach, possibly based on the drug repurposing.

Loop dynamics and the evolution of enzyme activity.

In the early 2000s, Tawfik presented his 'New View' on enzyme evolution, highlighting the role of conformational plasticity in expanding the functional diversity of limited repertoires of sequences. This view is gaining increasing traction with increasing evidence of the importance of conformational dynamics in both natural and laboratory evolution of enzymes. The past years have seen several elegant examples of harnessing conformational (particularly loop) dynamics to successfully manipulate protein function.

Q-RepEx: A Python pipeline to increase the sampling of empirical valence bond simulations.

The exploration of chemical systems occurs on complex energy landscapes. Comprehensively sampling rugged energy landscapes with many local minima is a common problem for molecular dynamics simulations. These multiple local minima trap the dynamic system, preventing efficient sampling.

LoopGrafter: a web tool for transplanting dynamical loops for protein engineering.

The transplantation of loops between structurally related proteins is a compelling method to improve the activity, specificity and stability of enzymes. However, despite the interest of loop regions in protein engineering, the available methods of loop-based rational protein design are scarce. One particular difficulty related to loop engineering is the unique dynamism that enables them to exert allosteric control over the catalytic function of enzymes.

LoopGrafter: Visual Support for the Grafting Workflow of Protein Loops.

In the process of understanding and redesigning the function of proteins in modern biochemistry, protein engineers are increasingly focusing on the exploration of regions in proteins called loops. Analyzing various characteristics of these regions helps the experts to design the transfer of the desired function from one protein to another. This process is denoted as loop grafting.

Exploiting enzyme evolution for computational protein design.

Recent years have seen an explosion of interest in understanding the physicochemical parameters that shape enzyme evolution, as well as substantial advances in computational enzyme design. This review discusses three areas where evolutionary information can be used as part of the design process: (i) using ancestral sequence reconstruction (ASR) to generate new starting points for enzyme design efforts; (ii) learning from how nature uses conformational dynamics in enzyme evolution to mimic this process in silico; and (iii) modular design of enzymes from smaller fragments, again mimicking the process by which nature appears to create new protein folds. Using showcase examples, we highlight the importance of incorporating evolutionary information to continue to push forward the boundaries of enzyme design studies.

Virtual screening of potential anticancer drugs based on microbial products.

The development of microbial products for cancer treatment has been in the spotlight in recent years. In order to accelerate the lengthy and expensive drug development process, in silico screening tools are systematically employed, especially during the initial discovery phase. Moreover, considering the steadily increasing number of molecules approved by authorities for commercial use, there is a demand for faster methods to repurpose such drugs.

Engineering the protein dynamics of an ancestral luciferase.

Protein dynamics are often invoked in explanations of enzyme catalysis, but their design has proven elusive. Here we track the role of dynamics in evolution, starting from the evolvable and thermostable ancestral protein Anc which catalyses both dehalogenase and luciferase reactions. Insertion-deletion (InDel) backbone mutagenesis of Anc challenged the scaffold dynamics.

Screening of world approved drugs against highly dynamical spike glycoprotein of SARS-CoV-2 using CaverDock and machine learning.

The new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes pathological pulmonary symptoms. Most efforts to develop vaccines and drugs against this virus target the spike glycoprotein, particularly its S1 subunit, which is recognised by angiotensin-converting enzyme 2. Here we use the developed tool CaverDock to perform virtual screening against spike glycoprotein using a cryogenic electron microscopy structure (PDB-ID: 6VXX) and the representative structures of five most populated clusters from a previously published molecular dynamics simulation.

Computational design of enzymes for biotechnological applications.

Enzymes are the natural catalysts that execute biochemical reactions upholding life. Their natural effectiveness has been fine-tuned as a result of millions of years of natural evolution. Such catalytic effectiveness has prompted the use of biocatalysts from multiple sources on different applications, including the industrial production of goods (food and beverages, detergents, textile, and pharmaceutics), environmental protection, and biomedical applications.

Transcription and Translation Inhibitors in Cancer Treatment.

Transcription and translation are fundamental cellular processes that govern the protein production of cells. These processes are generally up regulated in cancer cells, to maintain the enhanced metabolism and proliferative state of these cells. As such cancerous cells can be susceptible to transcription and translation inhibitors.

The impact of tunnel mutations on enzymatic catalysis depends on the tunnel-substrate complementarity and the rate-limiting step.

Transport of ligands between bulk solvent and the buried active sites is a critical event in the catalytic cycle of many enzymes. The rational design of transport pathways is far from trivial due to the lack of knowledge about the effect of mutations on ligand transport. The main and an auxiliary tunnel of haloalkane dehalogenase LinB have been previously engineered for improved dehalogenation of 1,2-dibromoethane (DBE).

Fast Screening of Inhibitor Binding/Unbinding Using Novel Software Tool CaverDock.

Protein tunnels and channels are attractive targets for drug design. Drug molecules that block the access of substrates or release of products can be efficient modulators of biological activity. Here, we demonstrate the applicability of a newly developed software tool CaverDock for screening databases of drugs against pharmacologically relevant targets.

Caver Web 1.0: identification of tunnels and channels in proteins and analysis of ligand transport.

Caver Web 1.0 is a web server for comprehensive analysis of protein tunnels and channels, and study of the ligands' transport through these transport pathways. Caver Web is the first interactive tool allowing both the analyses within a single graphical user interface.

Engineering enzyme access tunnels.

Enzymes are efficient and specific catalysts for many essential reactions in biotechnological and pharmaceutical industries. Many times, the natural enzymes do not display the catalytic efficiency, stability or specificity required for these industrial processes. The current enzyme engineering methods offer solutions to this problem, but they mainly target the buried active site where the chemical reaction takes place.

Trimethylphosphate and Dimethylphosphate Hydrolysis by Binuclear Cd , Mn , and Zn -Fe Promiscuous Organophosphate-Degrading Enzyme: Reaction Mechanisms.

Organophosphate-degrading enzyme from Agrobacterium radiobacter P230 exhibits promiscuity, not only in the reactions it catalyzes, but also in the metals it uses to catalyze those reactions. Here, three different binuclear metal centers were studied: di-Cd , di-Mn and Zn -Fe . This enzyme uses these metal centers for hydrolyzing trimethyl- and dimethyl-phosphates.

Establishing the catalytic mechanism of human pancreatic α-amylase with QM/MM methods.

In this work, we studied the catalytic mechanism of human pancreatic α-amylase (HPA). Our goal was to determine the catalytic mechanism of HPA with atomic detail using computational methods. We demonstrated that the HPA catalytic mechanism consists of two steps, the first of which (glycosylation step) involves breaking the glycosidic bond to culminate in the formation of a covalent intermediate.

New insights in the catalytic mechanism of tyrosine ammonia-lyase given by QM/MM and QM cluster models.

Tyrosine ammonia lyase (TAL) catalyzes the deamination of tyrosine to p-coumaric acid in purple phototropic bacteria and Actinomycetales. The enzyme is used in bioengineering and has the potential to be used industrially. It belongs to a family of enzymes that uses a 4-methylidene-imidazole-5-one (MIO) cofactor to catalyze the deamination amino acids.

Triesterase and promiscuous diesterase activities of a di-Co(II)-containing organophosphate degrading enzyme reaction mechanisms.

The reaction mechanism for the hydrolysis of trimethyl phosphate and of the obtained phosphodiester by the di-Co(II) derivative of organophosphate degrading enzyme from Agrobacterium radiobacter P230(OpdA), have been investigated at density functional level of theory in the framework of the cluster model approach. Both mechanisms proceed by a multistep sequence and each catalytic cycle begins with the nucleophilic attack by a metal-bound hydroxide on the phosphorus atom of the substrate, leading to the cleavage of the phosphate-ester bond. Four exchange-correlation functionals were used to derive the potential energy profiles in protein environments.

Comparative analysis of the performance of commonly available density functionals in the determination of geometrical parameters for copper complexes.

In this study, a set of 50 transition-metal complexes of Cu(I) and Cu(II), were used in the evaluation of 18 density functionals in geometry determination. In addition, 14 different basis sets were considered, including four commonly used Pople's all-electron basis sets; four basis sets including popular types of effective-core potentials: Los Alamos, Steven-Basch-Krauss, and Stuttgart-Dresden; and six triple-ζ basis sets. The results illustrate the performance of different methodological alternatives for the treatment of geometrical properties in relevant copper complexes, pointing out Double-Hybrid (DH) and Long-range Correction (LC) Generalized Gradient Approximation (GGA) methods as better descriptors of the geometry of the evaluated systems.