trans-AUCB kinase Dihydrofolate reductase DHFR is an excelle
Dihydrofolate reductase (DHFR) is an excellent molecular target for this study because it has been and is currently studied by using different molecular modeling techniques , , , . Kerrigan et al. have reported an interesting review about recent progress in molecular dynamics simulations of DHFR  and they conclude that “molecular mechanics calculations can work well to model the initial binding step of an inhibitor or substrate with DHFR. However, DHFR continues to be a challenge for free trans-AUCB kinase estimation methods and caution is recommended when interpreting these results”.
It should be noted that there are very few simulations specifically focused in the molecular interactions involved in the formation of the L-R complexes. Thus, interesting details about the intricacies of molecular interactions of DHFR interacting with its inhibitors remain unknown. Recently, we reported some molecular modeling studies using reduced models for the binding pockets , , , , , . This approach allows performing more accurate quantum mechanical calculations, as well as to obtain a detailed electronic analysis by using the method of Quantum Theory of Atoms in Molecules (QTAIM).
The main objective of this work is to find a way that allows us to differentiate between ligands possessing similar affinities for the DHFR. To achieve this goal, different calculations techniques have been used either alone or in combination in order to find a molecular descriptor that allows getting such differentiation. Thus, the present study was carried out at different stages. In the first step, seven new compounds were synthesized and then they were evaluated for their inhibitory activities against human DHFR. These results were added to thirteen compounds reported by Gangjee et al. (1–13) , two compounds reported in our earlier work (14a and 15a)  and two new compounds (14e and 15f) recently reported in Ref.  in order to have a more complete and representative number of compounds (25 molecules in the complete series (Fig. 1 and Table 1)). In the next step, we performed MD simulations, QM calculations (using different levels of theory) and QTAIM analysis with the aim to obtain a correlation which allows the discrimination between compounds possessing similar affinities by the enzyme. The conclusions are presented at the end.
Methods of calculations The results of this work have been compared with those recently reported in the Ref. ; therefore all calculations and molecular simulations have been performed using the same techniques previously used.
Results and discussion We recently reported two new DHFR inhibitors: compounds 14a and 15a . In order to have a more extensive series and based on these two structures, we decide to synthesize seven novel derivatives from 2,4,5-triamino-6-methoxypyrimidine with diverse aryl aldehydes to render well compounds 14b-d (structurally related to 14a) or compounds 15b-e (structurally related to compound 15a), which were prepared in a two-step one-pot procedure (Scheme 1 and Table 1). In the next step we tested the inhibitory effect of these compounds; such results are summarized in Table 1. As we can see from Table 1 some of these compounds displayed a relatively significant activity, such as compound 15b which shows inhibitory effect at concentrations of 27.87 μM. As it was stated above the main objective of this work is to obtain a correlation between the binding energies of these compounds and their respective IC50. Therefore MD simulations and quantum mechanical calculations were performed for all the L-R complexes. To try to use a sample as representative as possible of different types of ligands, we also include in this analysis the sixteen compounds reported in our previous work , thus forming a complete set of 25 compounds (Fig. 1). As we expected the general results obtained from MD simulations were very similar to those previously reported for compounds 14a and 15a . A highly conserved glutamic acid (Glu30) is functioning as an anchoring point. In the present study, all the simulated compounds were docked into the receptor with the N1 and 2-amino group near to Glu30. After 5 ns of MD simulations, the ligands moved slightly but in a different form compared with the initial position. However, the strong interaction with Glu30 was maintained for all the complexes. Other important MI stabilizing the different complexes are: π … π stacking interactions with Phe31 and Phe34, and hydrophobic interactions with Ile7 and Val115.