Biology subjects

Thirunavukarasu, A. S.

Publications and source records attributed to Thirunavukarasu, A. S..

4 recordsLinked to original sources

bioRxiv2024

Benchmarking coarse-grained simulation methods for investigation of transport tunnels in enzymes

Enzymes are pivotal to numerous biological processes, often featuring buried active sites linked to the surrounding solvent through intricate and dynamic tunnels. These tunnels are vital for facilitating substrate access, enabling product release, and regulating solvent exchange, which collectively influence enzymatic function and efficiency. Consequently, knowledge of tunnels is key for a holistic understanding of the effect of mutations as well as predicting drug residence times. Unfortunately, most transport tunnels are transient, i.e., equipped by molecular gates, rendering their opening a rare event that is often notoriously hard to study with conventional molecular dynamics simulations. To overcome the sampling limitation of such simulations, this study investigated the efficacy of three different coarse-grained (CG) molecular dynamics simulation methods for inferring enzyme tunnel structure and dynamics. Here, we covered the Martini and SIRAH models with different restraint protocols providing stability to CG proteins while to some extent biasing the sampling towards a reference structure. By contrasting CG results with all-atom simulations, we benchmarked the ability of CG methods to replicate ensemble characteristics of complex tunnel networks in haloalkane dehalogenase LinB and two of its mutants with engineered tunnel networks. The assessed tunnel parameters are essential for prioritizing functionally relevant tunnels and delineating the effect of mutations on transport tunnels. Our findings reveal that while CG methods significantly enhance the efficiency of tunnel analyses, some of them, like Martini with Elastic network restraints, were limited in recapitulating all-atom tunnel dynamics due to the structural bias applied. In contrast, the Martini G[o] model even captured the intricate details of mutation perturbing tunnel dynamics. All studied CG methods performed well in capturing the geometry of tunnel ensembles in line with all-atom simulations. Additionally, the wider applicability of CG methods was verified by analyzing tunnel networks of nine enzymes from different combinations of structural and functional classes, demonstrating their potential to uncover new tunnel phenomena and validate their utility in broader biological and functional contexts. This comprehensive evaluation underscores the strengths and constraints of CG simulations in capturing enzyme tunnels and benefiting from their computational speed for studying huge datasets of enzymes. These insights are valuable for enzyme engineering, drug design, and understanding enzyme function while benefitting from the efficiency of coarse-grained models.

bioinformatics↗

bioRxiv2023

Water migration through enzyme tunnels is sensitive to choice of explicit water model

Understanding the utilization of tunnels and water transport within enzymes is crucial for the catalytic function of enzymes, as water molecules can stabilize bound substrates and help with unbinding processes of products and inhibitors. Since the choice of water models for molecular dynamics simulations was shown to determine the accuracy of various calculated properties of the bulk solvent and solvated proteins, we have investigated if and to what extent the water transport through the enzyme tunnels depends on the selection of the water model. Here, we have focused on simulating enzymes with various well-defined tunnel geometries. In a systematic investigation using haloalkane dehalogenase as a model system, we focused on the well-established TIP3P, OPC, and TIP4P-Ew water models to explore their impact on using tunnels for water molecules transport. The TIP3P water model showed significantly faster migration, resulting in the transport of approximately 2.5 times more water molecules in comparison to OPC and 2.0 times greater than the TIP4P-Ew. The increase in migration of TIP3P water molecules was mainly due to faster transit times, and in the case of narrower tunnels, greater concurrent transport was evident as well. We have observed similar behavior in two different enzymes with buried active sites and different tunnel network topologies, indicating that our findings are likely not restricted to a particular enzyme family. Our study emphasizes the critical importance of water models in comprehending the use of enzyme tunnels for small molecule transport. Given the significant role of water availability in various stages of the catalytic cycle and solvation of substrates, products, and drugs, choosing an appropriate water model might be crucial for accurate simulations of complex enzymatic reactions, rational enzyme design, and predicting drug residence times.

bioinformatics↗

bioRxiv2023

Water will find a way: transport through narrow tunnels in hydrolases

An aqueous environment is vital for life as we know it, and water is essential for nearly all biochemical processes at a molecular level. Proteins utilize water molecules in various ways. Consequently, proteins must transport water molecules across their internal network of tunnels to reach the desired action sites, either within them or functioning as molecular pipes to control cellular osmotic pressure. Despite water playing a crucial role in enzymatic activity and stability, its transport has been largely overlooked, with studies primarily focusing on water transport across membrane proteins. The transport of molecules through a proteins tunnel network is challenging to study experimentally, making molecular dynamics simulations the most popular approach for investigating such events. In this study, we focused on the transport of water molecules across three different /{beta}-hydrolases: haloalkane dehalogenase, epoxide hydrolase, and lipase. Using a 5 s adaptive simulation per system, we observed that only a few tunnels were responsible for the majority of water transport in dehalogenase, in contrast to a higher diversity of tunnels in other enzymes. Interestingly, water molecules could traverse narrow tunnels with sub-angstrom bottlenecks, which is surprising given the commonly accepted water molecule radius of 1.4 [A]. Our analysis of the transport events in such narrow tunnels revealed a markedly increased number of hydrogen bonds formed between the water molecules and the protein, likely compensating for the steric penalty of the process. Overall, these commonly disregarded narrow tunnels accounted for [~]20% of the total water transport observed, emphasizing the need to surpass the standard geometrical limits on the functional tunnels to properly account for relevant transport processes. Finally, we demonstrated how the obtained insights could be applied to explain the differences in a mutant of the human soluble epoxide hydrolase associated with a higher incidence of ischemic stroke.

bioinformatics↗

bioRxiv2021

TransportTools: a library for high-throughput analyses of internal voids in biomolecules and ligand transport through them

Information regarding pathways through voids in biomolecules and their roles in ligand transport is critical to our understanding of the function of many biomolecules. Recently, the advent of high-throughput molecular dynamics simulations has enabled the study of these pathways, and of rare transport events. However, the scale and intricacy of the data produced requires dedicated tools in order to conduct analyses efficiently and without excessive demand on users. To fill this gap, we developed the TransportTools, which allows the investigation of pathways and their utilization across large, simulated datasets. TransportTools also facilitates the development of custom-made analyses. TransportTools is implemented in Python3 and distributed as pip and conda packages. The source code is available at https://github.com/labbit-eu/transport_tools.

bioinformatics↗