Serine Hydroxymethyltransferase (SHMT) is an important drug target to fight malaria – one of the most devastating infectious diseases that accounted in 2016 with 216 million new cases and almost 450 thousand deaths. In this paper, computational studies were carried out to unveil the catalytic mechanism of SHMT using QM/MM methodologies. This enzyme is responsible for the extraordinary cyclisation of a tetrahydrofolate (THF) into 5,10-methylene-THF. This process is catalyzed by a pyridoxal-5’-phosphate (PLP) cofactor that binds L-serine and from which one molecule of L-glycine is produced. The results show that the catalytic process takes place in eight sequential steps that involve an α-elimination, the cyclization of the 5-hydroxymethyl-THF intermediate into 5,10-methylene-THF and the protonation of the quinonoid intermediate. According to the calculated energetic profile, the rate-limiting step of the full mechanism is the elimination of the hydroxymethyl group, from which results a formaldehyde intermediate that then becomes covalently bonded to the THF cofactor. The calculated barrier (DLPNO-CCSD(T)/CBS:ff99SB) for the rate-limiting step (18.0 kcal/mol) agrees very well with the experimental kinetic results (15.7-16.2 kcal/mol). The results also highlight the key role played by Glu57 during the full catalytic process and particularly in the first step of the mechanism that requires an anionic Glu57, contrasting with some proposals available in the literature for this step. It was also concluded that the cyclisation of THF must take place in the enzyme, rather than in solution as it has been proposed also in the past. All of these results together provide new knowledge and insight on the catalytic mechanism of SHMT that now can be used to develop new inhibitors targeting SHMT and therefore new anti-malaria drugs.
The molUP plugin, developed by Nuno Sousa Cerqueira and colleagues and described on page 1344, overcomes some of the most common problems in computational chemistry concerning the analysis of big data. MolUP was developed for use in the analysis of quantum chemistry (QM), QM/MM (molecular mechanics), and QM/QM calculations, molecular dynamics (MD) simulations, as well as the preparation of input files. MolUP also provides new tools to analyze and visualize existing computational chemistry information in a more userfriendly way that simplifies the current complex and time‐demanding practices used in the field. (DOI: 10.1002/jcc.25189)
The catalytic mechanism of histidine decarboxylase (HDC), a pyridoxal-5′-phosphate (PLP)-dependent enzyme, was studied by using a computational QM/MM approach following the scheme M06-2X/6–311++G(3df,2pd):Amber. The reaction involves two sequential steps: the decarboxylation of l-histidine and the protonation of the generated intermediate from which results histamine. The rate-limiting step is the first one (ΔG≠=17.6 kcal mol−1; ΔGr=13.7 kcal mol−1) and agrees closely with the available experimental kcat (1.73 s−1), which corresponds to an activation barrier of 17.9 kcal mol−1. In contrast, the second step is very fast (ΔG≠=1.9 kcal mol−1) and exergonic (ΔGr=−33.2 kcal mol−1). Our results agree with the available experimental data and allow us to explain the role played by several active site residues that are considered relevant according to site-directed mutagenesis studies, namely Tyr334B, Asp273A, Lys305A, and Ser354B. These results can provide insights regarding the catalytic mechanism of other enzymes belonging to family II of PLP-dependent decarboxylases.
oniomANALYSIS is a TCL script that allows an easy way to extract data and handling output files from Gaussian 09 calculations.
The script allows get informations about energy about low a high levels in hybrid systems (ONIOM). In this option, scripts generates two files:
Energy of all structures
Energy of all optimized structures
oniomANALYIS allows also extract the first and last structures and write them in a new input Gaussian files in order to run a following calculation recurring to a previous calculation. In this case two files will be generated:
Gaussian input file of first structure
Gaussian input file of last structure
Moreover, you could also extract PDB files from Gaussian output files:
PDB file with all structures
PDB file with all optimized structures
PDB file with last structure
PDB file with last optimized structure
How to use?
Insert follow command in shell:
tclsh oniomANALYSIS.tcl [A] [B]
[A] is a flag which defines what type of job is going to be perfomed: