Harnessing conformational dynamics in enzyme catalysis to achieve nature-like catalytic efficiencies: the shortest path map tool for computational enzyme redesign.

Enzymes exhibit diverse conformations, as represented in the free energy landscape (FEL). Such conformational diversity provides enzymes with the ability to evolve towards novel functions. The challenge lies in identifying mutations that enhance specific conformational changes, especially if located in distal sites from the active site cavity. The shortest path map (SPM) method, which we developed to address this challenge, constructs a graph based on the distances and correlated motions of residues observed in nanosecond timescale molecular dynamics (MD) simulations. We recently introduced a template based AlphaFold2 (tAF2) approach coupled with 10 nanosecond MD simulations to quickly estimate the conformational landscape of enzymes and assess how the FEL is shifted after mutation. In this study, we evaluate the potential of SPM when coupled with tAF2-MD in estimating conformational heterogeneity and identifying key conformationally-relevant positions. The selected model system is the beta subunit of tryptophan synthase (TrpB). We compare how the SPM pathways differ when integrating tAF2 with different MD simulation lengths from as short as 10 ns until 50 ns and considering two distinct Amber forcefield and water models (ff14SB/TIP3P versus ff19SB/OPC). The new methodology can more effectively capture the distal mutations found in laboratory evolution, thus showcasing the efficacy of tAF2-MD-SPM in rapidly estimating enzyme dynamics and identifying the key conformationally relevant hotspots for computational enzyme engineering.

The shortest path method (SPM) webserver for computational enzyme design.

SPMweb is the online webserver of the Shortest Path Map (SPM) tool for identifying the key conformationally-relevant positions of a given enzyme structure and dynamics. The server is built on top of the DynaComm.py code and enables the calculation and visualization of the SPM pathways. SPMweb is easy-to-use as it only requires three input files: the three-dimensional structure of the protein of interest, and the two matrices (distance and correlation) previously computed from a Molecular Dynamics simulation. We provide in this publication information on how to generate the files for SPM construction even for non-expert users and discuss the most relevant parameters that can be modified. The tool is extremely fast (it takes less than one minute per job), thus allowing the rapid identification of distal positions connected to the active site pocket of the enzyme. SPM applications expand from computational enzyme design, especially if combined with other tools to identify the preferred substitution at the identified position, but also to rationalizing allosteric regulation, and even cryptic pocket identification for drug discovery. The simple user interface and setup make the SPM tool accessible to the whole scientific community. SPMweb is freely available for academia at http://spmosuna.com/.

Designing Efficient Enzymes: Eight Predicted Mutations Convert a Hydroxynitrile Lyase into an Efficient Esterase.

Hydroxynitrile lyase from rubber tree (HbHNL) shares 45% identical amino acid residues with the homologous esterase from tobacco, SABP2, but the two enzymes catalyze different reactions. The x-ray structures reveal a serine-histidine-aspartate catalytic triad in both enzymes along with several differing amino acid residues within the active site. Previous exchange of three amino acid residues in the active site of HbHNL with the corresponding amino acid residue in SABP2 (T11G-E79H-K236M) created variant HNL3, which showed low esterase activity toward p-nitrophenyl acetate. Further structure comparison reveals additional differences surrounding the active site. HbHNL contains an improperly positioned oxyanion hole residue and differing solvation of the catalytic aspartate. We hypothesized that correcting these structural differences would impart good esterase activity on the corresponding HbHNL variant. To predict the amino acid substitutions needed to correct the structure, we calculated shortest path maps for both HbHNL and SABP2, which reveal correlated movements of amino acids in the two enzymes. Replacing four amino acid residues (C81L-N104T-V106F-G176S) whose movements are connected to the movements of the catalytic residues yielded variant HNL7TV (stabilizing substitution H103V was also added), which showed an esterase catalytic efficiency comparable to that of SABP2. The x-ray structure of an intermediate variant, HNL6V, showed an altered solvation of the catalytic aspartate and a partially corrected oxyanion hole. This dramatic increase in catalytic efficiency demonstrates the ability of shortest path maps to predict which residues outside the active site contribute to catalytic activity.

C-H Bonds as Functional Groups: Simultaneous Generation of Multiple Stereocenters by Enantioselective Hydroxylation at Unactivated Tertiary C-H Bonds.

Enantioselective C-H oxidation is a standing chemical challenge foreseen as a powerful tool to transform readily available organic molecules into precious oxygenated building blocks. Here, we describe a catalytic enantioselective hydroxylation of tertiary C-H bonds in cyclohexane scaffolds with H2O2, an evolved manganese catalyst that provides structural complementary to the substrate similarly to the lock-and-key recognition operating in enzymatic active sites. Theoretical calculations unveil that enantioselectivity is governed by the precise fitting of the substrate scaffold into the catalytic site, through a network of complementary weak non-covalent interactions. Stereoretentive C(sp3)-H hydroxylation results in a single-step generation of multiple stereogenic centers (up to 4) that can be orthogonally manipulated by conventional methods providing rapid access, from a single precursor to a variety of chiral scaffolds.

AlphaFold2 and Deep Learning for Elucidating Enzyme Conformational Flexibility and Its Application for Design.

The recent success of AlphaFold2 (AF2) and other deep learning (DL) tools in accurately predicting the folded three-dimensional (3D) structure of proteins and enzymes has revolutionized the structural biology and protein design fields. The 3D structure indeed reveals key information on the arrangement of the catalytic machinery of enzymes and which structural elements gate the active site pocket. However, comprehending enzymatic activity requires a detailed knowledge of the chemical steps involved along the catalytic cycle and the exploration of the multiple thermally accessible conformations that enzymes adopt when in solution. In this Perspective, some of the recent studies showing the potential of AF2 in elucidating the conformational landscape of enzymes are provided. Selected examples of the key developments of AF2-based and DL methods for protein design are discussed, as well as a few enzyme design cases. These studies show the potential of AF2 and DL for allowing the routine computational design of efficient enzymes.

Estimating conformational heterogeneity of tryptophan synthase with a template-based Alphafold2 approach.

The three-dimensional structure of the enzymes provides very relevant information on the arrangement of the catalytic machinery and structural elements gating the active site pocket. The recent success of the neural network Alphafold2 in predicting the folded structure of proteins from the primary sequence with high levels of accuracy has revolutionized the protein design field. However, the application of Alphafold2 for understanding and engineering function directly from the obtained single static picture is not straightforward. Indeed, understanding enzymatic function requires the exploration of the ensemble of thermally accessible conformations that enzymes adopt in solution. In the present study, we evaluate the potential of Alphafold2 in assessing the effect of the mutations on the conformational landscape of the beta subunit of tryptophan synthase (TrpB). Specifically, we develop a template-based Alphafold2 approach for estimating the conformational heterogeneity of several TrpB enzymes, which is needed for enhanced stand-alone activity. Our results show the potential of Alphafold2, especially if combined with molecular dynamics simulations, for elucidating the changes induced by mutation in the conformational landscapes at a rather reduced computational cost, thus revealing its plausible application in computational enzyme design.

Epoxide Hydrolase Conformational Heterogeneity for the Resolution of Bulky Pharmacologically Relevant Epoxide Substrates.

The conformational landscape of Bacillus megaterium epoxide hydrolase (BmEH) and how it is altered by mutations that confer the enzyme the ability to accept bulky epoxide substrates has been investigated. Extensive molecular dynamics (MD) simulations coupled to active site volume calculations have unveiled relevant features of the enzyme conformational dynamics and function. Our long-timescale MD simulations identify key conformational states not previously observed by means of X-ray crystallography and short MD simulations that present the loop containing one of the catalytic residues, Asp239, in a wide-open conformation, which is likely involved in the binding of the epoxide substrate. Introduction of mutations M145S and F128A dramatically alters the conformational landscape of the enzyme. These singly mutated variants can accept bulky epoxide substrates due to the disorder induced by mutation in the α-helix containing the catalytic Tyr144 and some parts of the lid domain. These changes impact the enzyme active site, which is substantially wider and more complementary to the bulky pharmacologically relevant epoxide substrates.