Diabetic neuropathy: Molecular approach a treatment opportunity.

Diabetic neuropathy (DN) encompasses a group of clinical or subclinical manifestations involving a dysfunction in the peripheral nervous system. The cause of the dysfunction is the development of microvascular complications related to diabetes, a disease that affects about 381 million people worldwide. Approximately 50% of patients currently diagnosed with diabetes are expected to manifest DN in the next 10 years. The diagnosis can be made clinically by establishing a good patient history and delving into the symptoms to rule out other etiologies. Treatment of DN focuses on glycemic control and the use of medications to reduce pain, including NSAIDs, antidepressants and antiepileptic drugs. The pathogenesis is of multifactorial origin, associated with various metabolic, vascular, inflammatory and neurodegenerative disorders. The three fundamental cellular alterations participating in the development of DN are chronic inflammation, endothelial dysfunction and oxidative stress. Since the combination of all three is capable of giving rise to nerve ischemia and direct axonal injury, these factors play a key role in the development of polyneuropathy. However, neuronal and microvascular changes do not occur in the same way in all patients with DN, some of whom have no detectable blood abnormalities.

Chemical characterization (LC-MS-ESI), cytotoxic activity and intracellular localization of PAMAM G4 in leukemia cells.

Generation 4 of polyamidoamine dendrimer (G4-PAMAM) has several biological effects due to its tridimensional globular structure, repetitive branched amides, tertiary amines, and amino-terminal subunit groups liked to a common core. G4-PAMAM is cytotoxic due to its positive charges. However, its cytotoxicity could increase in cancer cells due to the excessive intracellular negative charges in these cells. Furthermore, this work reports G4-PAMAM chemical structural characterization using UHPLC-QTOF-MS/MS (LC-MS) by electrospray ionization to measure its population according to its positive charges. Additionally, the antiproliferative effects and intracellular localization were explored in the HMC-1 and K-562 cell lines by confocal microscopy. The LC-MS results show that G4-PAMAM generated multivalent mass spectrum values, and its protonated terminal amino groups produced numerous positive charges, which allowed us to determine its exact mass despite having a high molecular weight. Additionally, G4-PAMAM showed antiproliferative activity in the HMC-1 tumor cell line after 24 h (IC50 = 16.97 µM), 48 h (IC50 = 7.02 µM) and 72 h (IC50 = 5.98 µM) and in the K-562 cell line after 24 h (IC50 = 15.14 µM), 48 h (IC50 = 14.18 µM) and 72 h (IC50 = 9.91 µM). Finally, our results showed that the G4-PAMAM dendrimers were located in the cytoplasm and nucleus in both tumor cell lines studied.

Molecular modeling and LC-MS-based metabolomics of a glutamine-valproic acid (Gln-VPA) derivative on HeLa cells.

Glutaminase plays an important role in carcinogenesis and cancer cell growth. This biological target is interesting against cancer cells. Therefore, in this work, in silico [docking and molecular dynamics (MD) simulations] and in vitro methods (antiproliferative and LC-MS metabolomics) were employed to assay a hybrid compound derived from glutamine and valproic acid (Gln-VPA), which was compared with 6-diazo-5-oxo-L-norleucine (DON, a glutaminase inhibitor) and VPA (contained in Gln-VPA structure). Docking results from some snapshots retrieved from MD simulations show that glutaminase recognized Gln-VPA and DON. Additionally, Gln-VPA showed antiproliferative effects in HeLa cells and inhibited glutaminase activity. Finally, the LC-MS-based metabolomics studies on HeLa cells treated with either Gln-VPA (IC60 = 8 mM) or DON (IC50 = 3.5 mM) show different metabolomics behaviors, suggesting that they modulate different biological targets of the cell death mechanism. In conclusion, Gln-VPA is capable of interfering with more than one pharmacological target of cancer, making it an interesting drug that can be used to avoid multitherapy of classic anticancer drugs.

Epigenetic Evaluation of N-(2-hydroxyphenyl)-2-Propylpentanamide, a Valproic Acid Aryl Derivative with Activity Against HeLa Cells.

BACKGROUND: Valproic acid (VPA) is an HDAC inhibitor (HDACI) with an anticancer activity, but is hepatotoxic. N-(2-hydroxyphenyl)-2-propylpentanamide (o-OH-VPA) is a VPA aryl derivative designed in silico as a selective inhibitor of HDAC8 with biological properties against HeLa, rhabdomyosarcoma and breast cancer cell cultures. OBJECTIVE: We studied the epigenetic mechanism of o-OH-VPA as an HDACI and evaluated whether it was toxic to normal cells. METHODS: HeLa cells and primary human fibroblasts were used for this study as carcinogenic and normal cells, respectively. Cell survival was evaluated by MTT assay, whereas viability and doubling time were determined by the Trypan-blue method. HDAC activity was tested using the colorimetric HDAC activity assay. The expression of p21 was analyzed by PCR and HDAC8 expression was also evaluated by real-time PCR. Cell cycle and caspase-3 activity were analyzed by flow cytometry and caspase-3 colorimetric assay, respectively. RESULTS: o-OH-VPA (IC50 = 0.1 mM) was fifty-eight times more effective than VPA (IC50 = 5.8 mM) to reduce HeLa cell survival. Furthermore, o-OH-VPA increased the doubling time of HeLa cells by 33% with respect to the control. o-OH-VPA acted as HDACI in HeLa cells without affecting the HDAC8 expression, arresting the cell cycle of HeLa cells in the G0/G1 phase due to the increase in p21 expression with the inhibition of caspase-3 activity without exhibiting toxicity toward normal cells. CONCLUSION: Our results revealed that o-OH-VPA is an HDACI with a selective effect against HeLa cells but without the known toxicity exerted by most pan-HDACIs on normal cells.

Molecular dynamics simulations reveal structural differences among wild-type NPC1 protein and its mutant forms.

NPC1 is a 25-exon gene located on the long arm of chromosome 18q11.2 and encodes NPC1, a transmembrane protein comprising 1278 amino acid residues. Mutations in the NPC1 gene can cause Niemann-Pick disease type C (NP-C), a rare autosomal-recessive neurovisceral disease. We assessed mutant protein folding using computer-based molecular dynamics (MD) simulations and molecular docking of the three most common NPC1 mutations, all of which result in changes in a cysteine-rich luminal loop region of the protein: a) I1061T is the most commonly detected variant in patients with NP-C worldwide; b) P1007A is the second most common variant, frequently detected in Portuguese, British and German patients; c) G992W occurs most often in patients of Acadian descent. Analyses of molecular structural information and related cellular physiological processes revealed that mutant NPC1 proteins exhibited altered function despite being far from the N-terminal domain cholesterol binding. MD simulations revealed that mutant I1061T protein shows remarkable instability in comparison the WT and also de other mutants, and interestingly this mutant has been identified as the most common variant. In the case of the mutant P1007A, it is presumed that this substitution promotes larger structural changes than proline due to their greater hydrophobic properties.Structural changes related to the G992W mutation may affect the physicochemical space of G992W variant protein because tryptophan induces hydrophobic interactions. Cholesterol docking studies focused on binding recognition showed differences in the binding positions of variants versus the wild-type protein that go some way to explaining the molecular pathogenesis.Communicated by Ramaswamy H. Sarma.

In vitro and in silico evaluation of fucosterol from Sargassum horridum as potential human acetylcholinesterase inhibitor.

The fucosterol has been reported numerous biological activities. In this study, the activity in vitro of the fucosterol from Sargassum horridum as potential human acetylcholinesterase inhibitor was evaluated. The structural identification was obtained by nuclear magnetic resonance (NMR) spectroscopy and based on experimental data, we combined docking and molecular dynamics simulations coupled to the molecular-mechanics-generalized-born-surface-area approach to evaluating the structural and energetic basis for the molecular recognition of fucosterol and neostigmine at the binding site of acetylcholinesterase (AChE). In addition, the Lineweaver-Burk plot showed the nature of a non-competitive inhibition. The maximum velocity (Vmax) and the constant of Michaelis-Menten (Km) estimated for fucosterol (0.006 µM) were 0.015 1/Vo (ΔA/h and 6.399 1/[ACh] mM-1, respectively. While, for neostigmine (0.14 µM), the Vmax was 0.022 1/Vo (ΔA/h) and Km of 6.726 1/[ACh] mM-1, these results showed a more effective inhibition by fucosterol respect to neostigmine. Structural analysis revealed that neostigmine reaches the AChE binding site reported elsewhere, whereas fucosterol can act as a no-competitive and competitive acetylcholinesterase inhibitor, in agree with kinetic enzymatic experiments. Binding free energy calculations revealed that fucosterol reaches the acetylcholinesterase binding site with higher affinity than neostigmine, which is according to experimental results. Whereas the per-residue decomposition free energy analysis let us identify crucial residues involved in the molecular recognition of ligands by AChE. Results corroborate the ability of theoretical methods to provide crucial information at the atomic level about energetic and structural differences in the binding interaction and affinity from fucosterol with AChE. Communicated by Ramaswamy H. Sarma.

In vitro and in silico studies of terpenes, terpenoids and related compounds with larvicidal and pupaecidal activity against Culex quinquefasciatus Say (Diptera: Culicidae).

BACKGROUND: In order to develop new larvicidal agents derived from phytochemicals, the larvicidal activity of fifty molecules that are constituent of essential oils was evaluated against Culex quinquefasciatus Say. Terpenes, terpenoids and phenylpropanoids molecules were included in the in vitro evaluation, and QSAR models using genetic algorithms were built to identify molecular and structural properties of biological interest. Further, to obtain structural details on the possible mechanism of action, selected compounds were submitted to docking studies on sterol carrier protein-2 (SCP-2) as possible target. RESULTS: Results showed high larvicidal activity of carvacrol and thymol on the third and fourth larval stage with a median lethal concentration (LC50) of 5.5 and 11.1 µg/mL respectively. Myrcene and carvacrol were highly toxic for pupae, with LC50 values of 31.8 and 53.2 µg/mL. Structure-activity models showed that the structural property π-bonds is the largest contributor of larvicidal activity while ketone groups should be avoided. Similarly, property-activity models attributed to the molecular descriptor LogP the most contribution to larvicidal activity, followed by the absolute total charge (Qtot) and molar refractivity (AMR). The models were statistically significant; thus the information contributes to the design of new larvicidal agents. Docking studies show that all molecules tested have the ability to interact with the SCP-2 protein, wherein α-humulene and ß-caryophyllene were the compounds with higher binding energy. CONCLUSIONS: The description of the molecular properties and the structural characteristics responsible for larvicidal activity of the tested compounds were used for the development of mathematical models of structure-activity relationship. The identification of molecular and structural descriptors, as well as studies of molecular docking on the SCP-2 protein, provide insight on the mechanism of action of the active molecules, and the information can be used for the design of new structures for synthesis as potential new larvicidal agents.

Computational Study of the Binding Modes of Diverse DPN Analogues on Estrogen Receptors (ER) and the Biological Evaluation of a New Potential Antiestrogenic Ligand.

Estrogen (17ß-estradiol) is essential for normal growth and differentiation in the mammary gland. In the last three decades, previous investigations have revealed that Estrogen Receptor Alpha (ERα) plays a critical role in breast cancer. More recently, observations regarding the widespread expression of ERß-like proteins in normal and neoplastic mammary tissues have suggested that ERß is also involved in the mentioned pathology. Design of new drugs both steroidal and nonsteroidal that target any of these receptors represents a promise to treat breast cancer although it remains a challenge due to the sequence similarity between their catalytic domains. In this work, we propose a new set of compounds that could effectively target the estrogen receptors ERα and ERß. These ligands were designed based on the chemical structure of the ERß-selective agonist Diarylpropionitrile (DPN). The designed ligands were submitted to in silico ADMET studies, yielding in a filtered list of ligands that showed better drug-like properties. Molecular dynamics simulations of both estrogen receptors and docking analysis were carried-out employing the designed compounds, from which two were chosen due to their promising characteristics retrieved from theoretical results (docking analysis or targeting receptor predictions). They were chemically synthetized and during the process, two precursor ligands were also obtained. These four ligands were subjected to biological studies from which it could be detected that compound mol60b dislplayed inhibitory activity and its ability to activate the transcription via an estrogenic mechanism of action was also determined. Interestinly, this observation can be related to theoretical binding free energy calculations, where the complex: ERß-mol60b showed the highest energy ΔGbind value in comparison to others.

QSAR, DFT and molecular modeling studies of peptides from HIV-1 to describe their recognition properties by MHC-I.

Human immunodeficiency virus type-1 (HIV-1) has infected more than 40 million people around the world. HIV-1 treatment still has several side effects, and the development of a vaccine, which is another potential option for decreasing human infections, has faced challenges. This work presents a computational study that includes a quantitative structure activity relationship(QSAR) using density functional theory(DFT) for reported peptides to identify the principal quantum mechanics descriptors related to peptide activity. In addition, the molecular recognition properties of these peptides are explored on major histocompatibility complex I (MHC-I) through docking and molecular dynamics (MD) simulations accompanied by the Molecular Mechanics Generalized Born Surface Area (MMGBSA) approach for correlating peptide activity reported elsewhere vs. theoretical peptide affinity. The results show that the carboxylic acid and hydroxyl groups are chemical moieties that have an inverse relationship with biological activity. The number of sulfides, pyrroles and imidazoles from the peptide structure are directly related to biological activity. In addition, the HOMO orbital energy values of the total absolute charge and the Ghose-Crippen molar refractivity of peptides are descriptors directly related to the activity and affinity on MHC-I. Docking and MD simulation studies accompanied by an MMGBSA analysis show that the binding free energy without considering the entropic contribution is energetically favorable for all the complexes. Furthermore, good peptide interaction with the most affinity is evaluated experimentally for three proteins. Overall, this study shows that the combination of quantum mechanics descriptors and molecular modeling studies could help describe the immunogenic properties of peptides from HIV-1.

In Silico Studies Most Employed in the Discovery of New Antimicrobial Agents.

The present review summarizes the methods most used in drug search and design, which may help to keep pace with the growing antibiotic resistance among pathogens. The rate of reduction in the effectiveness of many antimicrobial medications, caused by this resistance, is faster than new drug development, thereby creating a worldwide public health threat. Among the scientific community, the urgency of finding new drugs is peaking interest in the use of in silico studies to explore the interaction of compounds with target receptors. With this approach, small molecules (designed or retrieved from data bases) are tested with computer-aided molecular simulation to explore their efficacy. That is, ligand-protein complexes are constructed and evaluated via virtual screening (VS), molecular dynamics (MD), and docking simulations with the data from the physical, chemical and pharmacological properties of such molecules. Additionally, the application of quantitative structure-activity relationship (QSAR), multi-target quantitative structure-activity relationship (mt- QSAR), and multi-tasking quantitative structure-biological effect (mtk-QSBER) can be enhanced by principal component analysis and systematic workflows. These types of studies aid in selecting a group of promising molecules with high potency and selectivity as well as low toxicity, thus making in vitro and in vivo (animal model) testing more efficient. Since knowledge of the receptor topography and receptor-ligand interactions has yielded promising compounds and effective drugs, there is now no doubt that the use of in silico tools can lead to more rapid validation of new potential drugs for preclinical studies and clinical trials.

Docking Studies of Glutamine Valproic Acid Derivative (S)-5- amino-2-(heptan-4-ylamino)-5-oxopentanoic Acid (Gln-VPA) on HDAC8 with Biological Evaluation in HeLa Cells.

In this contribution, we focused on evaluating a novel compound developed by our group. This molecule, derived from glutamine (Gln) and valproic acid (VPA), denominated (S)- 5-amino-2-(heptan-4-ylamino)-5-oxopentanoic acid (Gln-VPA), was submitted to docking studies on histone deacetylase 8 (HDAC8) to explore its non-bonded interactions. The theoretical results were validated in HeLa cells as a cancer cell model and in human dermal fibroblasts as a normal cell model. The effects of Gln-VPA on HeLa and normal fibroblasts in terms of cell survival and the ability to inhibit HDAC activity in nude nuclear proteins and in nuclear proteins of whole cells treated for 24 h were analyzed. The HeLa cell cycle was analyzed after 24 and 48 h of treatment with Gln-VPA. The docking studies show that Gln-VPA can reach the catalytic site of HDAC8. Gln-VPA was organically synthesized with a purity greater than 97%, and its structure was validated using mass spectrometry, nuclear magnetic resonance and infrared spectroscopy. Gln-VPA showed a similar effect to VPA as an HDAC inhibitor but with less toxicity to fibroblasts. Although Gln-VPA was less efficient than VPA in reducing the survival of HeLa cells, it could be studied for use as a cancer cell sensitizer.

Molecular modeling studies demonstrate key mutations that could affect the ligand recognition by influenza AH1N1 neuraminidase.

The goal of this study was to identify neuraminidase (NA) residue mutants from human influenza AH1N1 using sequences from 1918 to 2012. Multiple alignment studies of complete NA sequences (5732) were performed. Subsequently, the crystallographic structure of the 1918 influenza (PDB ID: 3BEQ-A) was used as a wild-type structure and three-dimensional (3-D) template for homology modeling of the mutated selected NA sequences. The 3-D mutated NAs were refined using molecular dynamics (MD) simulations (50 ns). The refined 3-D models were used to perform docking studies using oseltamivir. Multiple sequence alignment studies showed seven representative mutations (A232V, K262R, V263I, T264V, S367L, S369N, and S369K). MD simulations applied to 3-D NAs showed that each NA had different active-site shapes according to structural surface visualization and docking results. Moreover, Cartesian principal component analyses (cPCA) show structural differences among these NA structures caused by mutations. These theoretical results suggest that the selected mutations that are located outside of the active site of NA could affect oseltamivir recognition and could be associated with resistance to oseltamivir.

Three-dimensional structure and molecular dynamics studies of prorrenin/renin receptor: description of the active site.

The recent finding of a specific receptor for prorrenin/renin (PRR) has brought new insights into the physiology of the renin-angiotensin-aldosterone system. No undoubtable role has been described for this receptor so far. Its role seems to be important in chronic illnesses such as hypertension, possibly participating in the cardiovascular remodeling process, and diabetes where participation in inflammation development has been described. It is not possible, however, to explore the PRR function using classical pharmacological approaches due to the lack of specific agonists or antagonists. Two synthetic peptides have been described to accomplish these roles, but no conclusive data have been provided. There are no X-ray crystallography studies available to describe the structure and potential sites for drug development. So, the aim of this work was to model and theoretically describe the PRR. We describe and characterize the whole receptor protein, its spatial conformation and the potential interactions of PRR with the synthetic peptides available, describing the amino acid residues responsible for these interactions. This information provides the basis for directed development of drugs, seeking to agonize or antagonize PRR activity and study its function in health and ill stages.

Deciphering the GPER/GPR30-agonist and antagonists interactions using molecular modeling studies, molecular dynamics, and docking simulations.

The G-protein coupled estrogen receptor 1 GPER/GPR30 is a transmembrane seven-helix (7TM) receptor involved in the growth and proliferation of breast cancer. Due to the absence of a crystal structure of GPER/GPR30, in this work, molecular modeling studies have been carried out to build a three-dimensional structure, which was subsequently refined by molecular dynamics (MD) simulations (up to 120 ns). Furthermore, we explored GPER/GPR30's molecular recognition properties by using reported agonist ligands (G1, estradiol (E2), tamoxifen, and fulvestrant) and the antagonist ligands (G15 and G36) in subsequent docking studies. Our results identified the E2 binding site on GPER/GPR30, as well as other receptor cavities for accepting large volume ligands, through GPER/GPR30 π-π, hydrophobic, and hydrogen bond interactions. Snapshots of the MD trajectory at 14 and 70 ns showed almost identical binding motifs for G1 and G15. It was also observed that C107 interacts with the acetyl oxygen of G1 (at 14 ns) and that at 70 ns the residue E275 interacts with the acetyl group and with the oxygen from the other agonist whereas the isopropyl group of G36 is oriented toward Met141, suggesting that both C107 and E275 could be involved in the protein activation. This contribution suggest that GPER1 has great structural changes which explain its great capacity to accept diverse ligands, and also, the same ligand could be recognized in different binding pose according to GPER structural conformations.

Targeting a cluster of arginine residues of neuraminidase to avoid oseltamivir resistance in influenza A (H1N1): a theoretical study.

Following the influenza A (H1N1) pandemic in Mexico and around the world in 2009, the numbers of oseltamivir-resistant clinical cases have increased through a mechanism that remains unclear. In this work, we focus on studying the mutated NA structures ADA71175 (GenBank) and 3CKZ (PDB ID). Recently crystallized NA (PDB ID: 3NSS) was used as a wild-type structure and template to construct the three-dimensional (3D) structure of ADA71175. Then, the NA mutants and 3NSS natives as well as their refined monomer structures as determined through MD simulations (snapshots at 50 ns) were used as models to perform a docking study using a set of aryl-oseltamivir derivatives. These aryl-oseltamivir derivatives have better recognition properties than oseltamivir because of cation-π interactions with a cluster of Arg residues (118, 292, and 371) at the binding site. This cluster of Arg residues represents a potential binding site for aryl-oseltamivir derivatives that are potentially new NA inhibitors.

QSAR, docking, dynamic simulation and quantum mechanics studies to explore the recognition properties of cholinesterase binding sites.

A set of 84 known N-aryl-monosubstituted derivatives (42 amides: series 1 and 2, and 42 imides: series 3 an 4, from maleic and succinic anhydrides, respectively) that display inhibitory activity toward both acetylcholinesterase and butyrylcholinesterase (ChEs) was considered for Quantitative structure-activity relationship (QSAR) studies. These QSAR studies employed docking data from both ChEs that were previously submitted to molecular dynamics (MD) simulations. Donepezil and galanthamine stereoisomers were included to analyze their quantum mechanics properties and for validating the docking procedure. Quantum parameters such as frontier orbital energies, dipole moment, molecular volume, atomic charges, bond length and reactivity parameters were measured, as well as partition coefficients, molar refractivity and polarizability were also analyzed. In order to evaluate the obtained equations, four compounds: 1a (4-oxo-4-(phenylamino)butanoic acid), 2a ((2Z)-4-oxo-4-(phenylamino)but-2-enoic acid), 3a (2-phenylcyclopentane-1,3-dione) and 4a (2-phenylcyclopent-4-ene-1,3-dione) were employed as independent data set, using only equations with r(m(test))²>0.5. It was observed that residual values gave low value in almost all series, excepting in series 1 for compounds 3a and 4a, and in series 4 for compounds 1a, 2a and 3a, giving a low value for 4a. Consequently, equations seems to be specific according to the structure of the evaluated compound, that means, series 1 fits better for compound 1a, series 3 or 4 fits better for compounds 3a or 4a. Same behavior was observed in the butyrylcholinesterase (BChE). Therefore, obtained equations in this QSAR study could be employed to calculate the inhibition constant (Ki) value for compounds having a similar structure as N-aryl derivatives described here. The QSAR study showed that bond lengths, molecular electrostatic potential and frontier orbital energies are important in both ChE targets. Docking studies revealed that despite the multiple conformations obtained through MD simulations on both ChEs, the ligand recognition properties were conserved. In fact, the complex formed between ChEs and the best N-aryl compound reproduced the binding mode experimentally reported, where the ligand was coupled into the choline-binding site and stabilized through π-π interactions with Trp82 or Trp86 for BChE and AChE, respectively, suggesting that this compound could be an efficient inhibitor and supporting our model.

Computational modeling and simulation of the Bcl-2 family: paving the way for rational drug design.

Bcl-2 (B-cell lymphoma 2) family proteins have been studied intensively due to their association with cancer and other human diseases. These proteins were originally associated with the regulation of outer mitochondrial membrane integrity and apoptosis. However, there is experimental evidence that suggests that several members of this family play instrumental roles in other cellular pathways including autophagy, endoplasmic reticulum signaling, mitochondrial morphology and synaptic activity among others. Bcl-2 family proteins have been explored using diverse experimental and theoretical methods to obtain structural information that can provide valuable insight for drug development. This review is focused on computational studies related to Bcl-2 family proteins. Different strategies are described and evaluated, such as Molecular Dynamics simulations, docking, and rational drug design with the aim of demonstrating the importance of structural details of either ligands or proteins. The relevance of the knowledge obtained using these tools to drug design is discussed.

Give boron a chance: boron containing compounds reach ionotropic and metabotropic transmembrane receptors.

The ligand-gated ion channels and seven transmembrane domain receptors are the greatest families of transmembrane receptors (TMR) expressed in mammalians and the major target of current available drugs. Recently, boron containing compounds (BCC) have shown capability of acting as ligands on these targets. This mini-review is focused on the description of BCC that target TMR which were evaluated under experimental models. The results in experimental models are related with the theoretical interaction studies of these ligands on the target proteins as 3D-models in order to explore the biological effects of BCC in molecular detail.

In silico methods to assist drug developers in acetylcholinesterase inhibitor design.

Alzheimer's disease (AD) is a neurodegenerative disease characterized by a low acetylcholine (ACh) concentration in the hippocampus and cortex. ACh is a neurotransmitter hydrolyzed by acetylcholinesterase (AChE). Therefore, it is not surprising that AChE inhibitors (AChEIs) have shown better results in the treatment of AD than any other strategy. To improve the effects of AD, many researchers have focused on designing and testing new AChEIs. One of the principal strategies has been the use of computational methods (structural bioinformatics or in silico methods). In this review, we summarize the in silico methods used to enhance the understanding of AChE, particularly at the binding site, to design new AChEIs. Several computational methods have been used, such as docking approaches, molecular dynamics studies, quantum mechanical studies, electronic properties, hindrance effects, partition coefficients (Log P) and molecular electrostatic potentials surfaces, among other physicochemical methods that exhibit quantitative structure-activity relationships.

Molecular modeling applied to anti-cancer drug development.

In the past, anti-cancer drugs were identified and developed without focusing on a particular macromolecular target. Currently, the fields of molecular biochemistry, molecular biology, genetics and pharmacology, among other disciplines, have grown considerably in their ability to identify biological targets. These disciplines are now searching for specific targets to treat cancer. These targets exist in different cellular compartments (membrane, cytoplasm, nucleus) as proteins, glycoproteins, nucleic acids, etc. Computational tools have recently been used to explore such targets and to corroborate previously obtained experimental data. These methods have also been used to design new drugs with the aim of decreasing illness and the economic resources needed to discover drug candidates. Some of these computational methods include quantum mechanics (ab initio and density functional theories) and molecular mechanics (docking, molecular dynamics, and protein folding). Docking and molecular dynamics are the most commonly used computational tools for elucidating cancer targets. Using these tools, one can identify the recognition processes between ligands and targets at the atomic level. In addition, one can identify the affinity and conformational changes of these molecular complexes. In conclusion, we propose that the use of such tools is necessary in order to identify new anti-cancer drugs.