The empirical valence bond as an effective strategy for computer-aided enzyme design

Homology modeling of human GABA-AT and devise some novel and potent inhibitors via computer-aided drug design techniques

γ-aminobutyric acid aminotransferase (GABA-AT) is a pyridoxal 5'-phosphate (PLP)-dependent enzyme which degrades γ-aminobutyric (GABA) in the brain. GABA is an important inhibitory neurotransmitter that plays important neurological roles in the brain. Therefore, GABA-AT is an important drug target which regulates the GABA level. Novel and potent drug development to inhibit GABA-AT is still very challenging task. In this study, we aimed to devise novel and potent inhibitors against GABA-AT using computer-aided drug design (CADD) tools. However, the human GABA-AT crystal structure is not available yet, and we built the 3D structure of human GABA-AT based on the crystal structure of pig's liver (Sus Scrofa) enzyme as a template. The generated model was validated with numerous tools such as ProSA and PROCHECK. A set of selected well-known inhibitors have been tested against the modeled GABA-AT. Molecular docking studies have been accomplished via application of Genetic Optimization for Ligand Docking (GOLD), Vina and Autodock 4.2 software to search for potent inhibitors. The best two candidate inhibitors have been computationally examined for absorption, distribution, metabolism, elimination and toxicity descriptors (ADMET) and Lipinski's rule of 5. Lastly, molecular dynamics (MD) simulations were carried out to inspect the ligands' binding mode and stability of the active site of human GABA-AT over time. The top ranked ligands exhibited reliable stability throughout the MD simulation. The selected compounds are promising candidates and might be tested experimentally for the inhibition of human GABA-AT enzyme. Communicated by Ramaswamy H. Sarma.

Exploring the Development of Ground-State Destabilization and Transition-State Stabilization in Two Directed Evolution Paths of Kemp Eliminases

Computer-aided enzyme design presents a major challenge since in most cases it has not resulted in an impressive catalytic power. The reasons for the problems with computational design include the use of nonquantitative approaches, but they may also reflect other difficulties that are not completely obvious. Thus, it is very useful to try to learn from the trend in directed evolution experiments. Here we explore the nature of the refinement of Kemp eliminases by directed evolution, trying to gain an understanding of related requirements from computational design. The observed trend in the directed evolution refinement of KE07 and HG3 are reproduced, showing that in the case of KE07 the directed evolution leads to ground-state destabilization, whereas in the case of HG3 the directed evolution leads to transition-state stabilization. The nature of the different paths of the directed evolution is examined and discussed. The present study seems to indicate that computer-aided enzyme design may require more than calculations of the effect of single mutations and should be extended to calculations of the effect of simultaneous multiple mutations (that make a few residues preorganized effectively). However, the analysis of two known evolution paths can still be accomplished using the relevant sequences and structures. Thus, by comparing two directed evolution paths of Kemp eliminases we reached the important conclusion that the more effective path leads to transition-state stabilization.

Computer aided enzyme design and catalytic concepts

Gaining a deeper understanding of enzyme catalysis is of great practical and fundamental importance. Over the years it has become clear that despite advances made in experimental mutational studies, a quantitative understanding of enzyme catalysis will not be possible without the use of computer modeling approaches. While we believe that electrostatic preorganization is by far the most important catalytic factor, convincing the wider scientific community of this may require the demonstration of effective rational enzyme design. Here we make the point that the main current advances in enzyme design are basically advances in directed evolution and that computer aided enzyme design must involve approaches that can reproduce catalysis in well-defined test cases. Such an approach is provided by the empirical valence bond method.

Modeling catalytic promiscuity in the alkaline phosphatase superfamily

In recent years, it has become increasingly clear that promiscuity plays a key role in the evolution of new enzyme function. This finding has helped to elucidate fundamental aspects of molecular evolution. While there has been extensive experimental work on enzyme promiscuity, computational modeling of the chemical details of such promiscuity has traditionally fallen behind the advances in experimental studies, not least due to the nearly prohibitive computational cost involved in examining multiple substrates with multiple potential mechanisms and binding modes in atomic detail with a reasonable degree of accuracy. However, recent advances in both computational methodologies and power have allowed us to reach a stage in the field where we can start to overcome this problem, and molecular simulations can now provide accurate and efficient descriptions of complex biological systems with substantially less computational cost. This has led to significant advances in our understanding of enzyme function and evolution in a broader sense. Here, we will discuss currently available computational approaches that can allow us to probe the underlying molecular basis for enzyme specificity and selectivity, discussing the inherent strengths and weaknesses of each approach. As a case study, we will discuss recent computational work on different members of the alkaline phosphatase superfamily (AP) using a range of different approaches, showing the complementary insights they have provided. We have selected this particular superfamily, as it poses a number of significant challenges for theory, ranging from the complexity of the actual reaction mechanisms involved to the reliable modeling of the catalytic metal centers, as well as the very large system sizes. We will demonstrate that, through current advances in methodologies, computational tools can provide significant insight into the molecular basis for catalytic promiscuity, and, therefore, in turn, the mechanisms of protein functional evolution.

Computational protein engineering: bridging the gap between rational design and laboratory evolution

Enzymes are tremendously proficient catalysts, which can be used as extracellular catalysts for a whole host of processes, from chemical synthesis to the generation of novel biofuels. For them to be more amenable to the needs of biotechnology, however, it is often necessary to be able to manipulate their physico-chemical properties in an efficient and streamlined manner, and, ideally, to be able to train them to catalyze completely new reactions. Recent years have seen an explosion of interest in different approaches to achieve this, both in the laboratory, and in silico. There remains, however, a gap between current approaches to computational enzyme design, which have primarily focused on the early stages of the design process, and laboratory evolution, which is an extremely powerful tool for enzyme redesign, but will always be limited by the vastness of sequence space combined with the low frequency for desirable mutations. This review discusses different approaches towards computational enzyme design and demonstrates how combining newly developed screening approaches that can rapidly predict potential mutation “hotspots” with approaches that can quantitatively and reliably dissect the catalytic step can bridge the gap that currently exists between computational enzyme design and laboratory evolution studies.

Examining the promiscuous phosphatase activity of Pseudomonas aeruginosa arylsulfatase: a comparison to analogous phosphatases

Pseudomonas aeruginosa arylsulfatase (PAS) is a bacterial sulfatase capable of hydrolyzing a range of sulfate esters. Recently, it has been demonstrated to also show very high proficiency for phosphate ester hydrolysis. Such proficient catalytic promiscuity is significant, as promiscuity has been suggested to play an important role in enzyme evolution. Additionally, a comparative study of the hydrolyses of the p-nitrophenyl phosphate and sulfate monoesters in aqueous solution has demonstrated that despite superficial similarities, the two reactions proceed through markedly different transition states with very different solvation effects, indicating that the requirements for the efficient catalysis of the two reactions by an enzyme will also be very different (and yet they are both catalyzed by the same active site). This work explores the promiscuous phosphomonoesterase activity of PAS. Specifically, we have investigated the identity of the most likely base for the initial activation of the unusual formylglycine hydrate nucleophile (which is common to many sulfatases), and demonstrate that a concerted substrate-as-base mechanism is fully consistent with the experimentally observed data. This is very similar to other related systems, and suggests that, as far as the phosphomonoesterase activity of PAS is concerned, the sulfatase behaves like a "classical" phosphatase, despite the fact that such a mechanism is unlikely to be available to the native substrate (based on pK(a) considerations and studies of model systems). Understanding such catalytic versatility can be used to design novel artificial enzymes that are far more proficient than the current generation of designer enzymes.

On catalytic preorganization in oxyanion holes: highlighting the problems with the gas-phase modeling of oxyanion holes and illustrating the need for complete enzyme models

Oxyanion holes play a major role in catalyzing enzymatic reactions, yet the corresponding energetics is frequently misunderstood. The main problem may be associated with the nontrivial nature of the electrostatic preorganization effect, without following the relevant formulation. That is, although the energetics of oxyanion holes have been fully quantified in early studies (which include both the enzymatic and reference solution reactions), the findings of these studies are sometimes overlooked, and, in some cases, it is assumed that gas-phase calculations with a fixed model of an oxyanion hole are sufficient for assessing the corresponding effect in the protein. Herein, we present a systematic analysis of this issue, clarifying the problems associated with modeling oxyanions by means of two fixed water molecules (or related constructs). We then re-emphasize the point that the effect of the oxyanion hole is mainly due to the fact that the relevant dipoles are already set in an orientation that stabilizes the TS charges, whereas the corresponding dipoles in solution are randomly oriented, resulting in the need to pay a very large reorganization energy. Simply calculating interaction energies with relatively fixed species cannot capture this crucial point, and considering it may help in advancing rational enzyme design.