Sampling-Based Motion Planning for Tracking Evolution of Dynamic Tunnels in Molecular Dynamics Simulations

Assessing the role of deep eutectic solvents in Yarrowia lipolytica inhibition

Yarrowia lipolytica has gained recognition as a microorganism with biological relevance and extensive biotechnological applications. Some of its features include a high enzyme secretion capacity and a high cell-density fermentation mode. Hexokinase (YlHxk) is a vital enzyme in Y. lipolytica growth since it catalyzes glucose metabolism through phosphorylation in the glycolytic pathway. Given the potential application of deep eutectic solvents (DES) as novel solvents in biotechnological processes, this study evaluated the influence of eighteen DES on the growth of Y. lipolytica. Furthermore, this work examined the effects of individual ions on the YlHxk enzyme by analyzing its enzymatic tunnel structure, molecule transport, and molecular docking. The results revealed a significant reduction in yeast growth in the presence of most DES compared to the control (medium without DES), with the exception of the [N8881]Cl: hexanoic acid (1:1) DES. The growth varied between 11.95 ± 0.60 and 0.68 ± 0.17 g dry cell weight L-1. According to the enzymatic tunnel analysis, DES components associated with the lowest microbial growth values were transported through tunnel 1. On the other hand, DES components had their pathway facilitated through tunnel 2 ([N8881]+ and hexanoic acid) and showed growth values close to the control. Molecular docking analysis identified a similarity between all the ligands in this tunnel (including substrate and product), presenting binding interactions with the ASN273 amino acid of the YlHxk active site. Combining experimental results with computational tools provided promising insights at the molecular level, while also potentially reducing analysis costs and time, paving the way for similar approaches in broad biocatalytic reactions.

A New Tool to Study the Binding Behavior of Intrinsically Disordered Proteins

Understanding the binding behavior and conformational dynamics of intrinsically disordered proteins (IDPs) is crucial for unraveling their regulatory roles in biological processes. However, their lack of stable 3D structures poses challenges for analysis. To address this, we propose an algorithm that explores IDP binding behavior with protein complexes by extracting topological and geometric features from the protein surface model. Our algorithm identifies a geometrically favorable binding pose for the IDP and plans a feasible trajectory to evaluate its transition to the docking position. We focus on IDPs from Homo sapiens and Mus-musculus, investigating their interaction with the Plasmodium falciparum (PF) pathogen associated with malaria-related deaths. We compare our algorithm with HawkDock and HDOCK docking tools for quantitative (computation time) and qualitative (binding affinity) measures. Our results indicated that our method outperformed the compared methods in computation performance and binding affinity in experimental conformations.

In Silico Evaluation of Enzymatic Tunnels in the Biotransformation of α-Tocopherol Esters

Motivation: α-Tocopherol is a molecule obtained primarily from plant sources that are important for the pharmaceutical and cosmetics industry. However, this component has some limitations such as sensitivity to oxygen, presence of light, and high temperatures. For this molecule to become more widely used, it is important to carry out a structural modification so that there is better stability and thus it can carry out its activities. To carry out this structural modification, some modifications are carried out, including the application of biotransformation using enzymes as biocatalysts. Thus, the application of a computational tool that helps in understanding the transport mechanisms of molecules in the tunnels present in the enzymatic structures is of fundamental importance because it promotes a computational screening facilitating bench applications.

Objective: The aim of this work was to perform a computational analysis of the biotransformation of α-tocopherol into tocopherol esters, observing the tunnels present in the enzymatic structures as well as the energies which correspond to the transport of molecules.

Method: To carry out this work, 9 lipases from different organisms were selected; their structures were analyzed by identifying the tunnels (quantity, conformation, and possibility of transport) and later the calculations of substrate transport for the biotransformation reaction in the identified tunnels were carried out. Additionally, the transport of the product obtained in the reaction through the tunnels was also carried out.

Results: In this work, the quantity of existing tunnels in the morphological conformational characteristics in the lipases was verified. Thus, the enzymes with fewer tunnels were RML (3 tunnels), LBC and RNL (4 tunnels), PBLL (5 tunnels), CALB (6 tunnels), HLG (7 tunnels), and LCR and LTL (8 tunnels) and followed by the enzyme LPP with the largest number of tunnels (39 tunnels). However, the enzyme that was most likely to transport substrates in terms of α-tocopherol biotransformation (in relation to the E_max and E_a energies of ligands and products) was CALB, as it obtains conformational and transport characteristics of molecules with a particularity. The most conditions of transport analysis were α-tocopherol tunnel 3 (E_max: −4.6 kcal/mol; E_a: 1.1 kcal/mol), vinyl acetate tunnel 1 (E_max: −2.4 kcal/mol; E_a: 0.1 kcal/mol), and tocopherol acetate tunnel 2 (E_max: −3.7 kcal/mol; E_a: 2 kcal/mol).

An Algorithm for Computing Side Chain Conformational Variations of a Protein Tunnel/Channel

In this paper, a novel method to compute side chain conformational variations for a protein molecule tunnel (or channel) is proposed. From the conformational variations, we compute the flexibly deformed shapes of the initial tunnel, and present a way to compute the maximum size of the ligand that can pass through the deformed tunnel. By using the two types of graphs corresponding to amino acids and their side chain rotamers, the suggested algorithm classifies amino acids and rotamers which possibly have collisions. Based on the divide and conquer technique, local side chain conformations are computed first, and then a global conformation is generated by combining them. With the exception of certain cases, experimental results show that the algorithm finds up to 327,680 valid side chain conformations from 12⁸~12³³ conformation candidates within three seconds.