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Drug discovery and development is a very challenging, expensive and time-consuming process. Impressive technological advances in computer sciences and molecular biology have made it possible to use computer-aided drug design (CADD) methods in various stages of the drug discovery and development pipeline. Nowadays, CADD presents an efficacious and indispensable tool, widely used in medicinal chemistry, to lead rational drug design and synthesis of novel compounds. In this article, an overview of commonly used CADD approaches from hit identification to lead optimization was presented. Moreover, different aspects of design of multitarget ligands for neuropsychiatric and anti-inflammatory diseases were summarized. Apparently, designing multi-target directed ligands for treatment of various complex diseases may offer better efficacy, and fewer side effects. Antipsychotics that act through aminergic G protein-coupled receptors (GPCRs), especially Dopamine D2 and serotonin 5-HT2A receptors, are the best option for treatment of various symptoms associated with neuropsychiatric disorders. Furthermore, multi-target directed cyclooxygenase-2 (COX-2) and 5-lipoxygenase (5-LOX) inhibitors are also a successful approach to aid the discovery of new anti-inflammatory drugs with fewer side effects. Overall, employing CADD approaches in the process of rational drug design provides a great opportunity for future development, allowing rapid identification of compounds with the optimal polypharmacological profile.

Today, we are witnessing an explosion of scientific concepts in cancer chemotherapy. It has been considered for a long time that genetic instability in cancer should be treated with drugs that directly damage the DNA. Understanding the molecular basis of malignant diseases shed light on studying phenotypic plasticity. In the era of epigenetics, many efforts are being made to alter the aberrant homeostasis in cancer without modifying the DNA sequence. One such strategy is modulation of the lysine acetylome in human cancers. To remove the acetyl group from the histones, cells use the enzymes that are called histone deacetylases (HDACs). The disturbed equilibrium between acetylation and deacetylation on lysine residues of histones can be manipulated with histone deacetylase inhibitors (HDACi). Throughout the review, an effort will be made to present the mechanistic basis of targeting the HDAC isoforms, discovered selective HDAC inhibitors, and their therapeutical implications and expectations in modern drug discovery.

The importance of the activation of phosphatidylinositol-3-kinase (PI3K) in the processes of tumor cell formation and growth has brought great interest in the development of new antitumor drugs that inhibit the PI3K-Akt signaling pathway. Recent studies have shown that in most tumors the activity of p110α isoform of PI3K kinase has been altered, and today special emphasis is placed on developing specific PI3K-α inhibitors. In a series of 92 PI3K-α inhibitors, whose data on experimentally determined inhibitory activity were collected from literature, 3D quantitative structure-activity relationship studies (3D-QSAR) were carried out. All molecular structures were previously optimized using semiempirical PM3 and ab initio Hartree-Fock / 3- 21G methods, and modeling was performed using PLS regression analysis. Calculated parameters of internal (R2=0.84; Q2=0.67) and external (R2pred=0.681; r2m=0.594; Δr2m=0.00039)validation indicate on good reliability and predictive power of created 3D-QSAR model. The analysis of the variables enabled pharmacophore structure determination, which implies: presence of hydrogen bond donor and hydrogen bond acceptor at a distance of 18-18.4Å or 12- 12.4Å, presence of hydrophobic domain and hydrogen bond donor at a distance of 15.2-15.6Å, and presence of steric hotspot at optimal distance from hydrogen bond donor and acceptor. These results will have the relevance in selecting the lead compounds for targeted structural modifications in order to design new selective PI3K-α inhibitors as potential antitumor drugs.

Creation of a statistically reliable 3D-QSAR (Quantitative Structure Activity Relationships) model enables definition of the structure of the pharmacophore for antagonists of serotonin 5-HT2A receptors and selection of the key molecular determinants for the design of new antagonists. A 3D-QSAR study was applied on a series of 50 antagonists of 5-HT2A receptors. The data set is divided into the training set, composed of 33 compounds, and test set containing 14 molecules. The training set was used to build the 3D-QSAR model, while test set was used for model validation. This 3D-QSAR study was performed by use of the Pentacle 1.07 programs. Obtained statistical and validation parameters for training set (R²= 0.96; Q²=0.75, RMSEE= 0.211); and for test set (R²pred=0.51; RMSEP= 0.558); indicate on reliability and good predictive potential of the 3D-QSAR model. Based on the most influential variables of the selected 3D-QSAR model, the molecular determinants for the antagonistic effect on the 5-HT2A receptors were selected: hydrogen bond acceptor and hydrogen bond donor at a distance of 10.4A-10.8A (v495: O-N1); carbonyl oxygen and a steric hot spot at a distance of 14.8A-15.2A (v640: N1-TIP); hydrophobic domain and hydrogen bond acceptor at a distance of 3.2A-3.6A (v276: DRY-O); two steric hot spots at a distance of 18.8A-19.2A (v248: TIP-TIP) .

All tested compounds show agonistic activity onserotonin5-HT2areceptors, which activation causes neuronal excitations, behavioral changes and platelet aggregation. The main aims of this study were to create 3D-QSAR(3D-Quantitative structure-activity relationship)model, analyse 3D-structure of the pharmacophore, validate the 3D-QSARmodel, and propose structural modification for novel 5-HT2aagonists.3D-QSAR modeling was applied to 51 agonists of 5-HT2areceptors. Dominant forms at physiologic pHof the examined compounds were optimized using the PM3 method and used for QSAR modeling. Data set was divided in two groups, training set of38 compounds, and test set of 13 compounds. Training set was used to build 3D-QSAR model, while test set was examined for the model validation. PLS (Partial Least Square Regression)method was used to develop 3D-QSAR model. Statistical parameters of the created and validated 3D-QSAR model,R2= 0.93, Q2=0.72, RMSEE=0.178, RMSEP=0.190 and R2 pred=0.63, indicate good prognostic capacity of the model.The3D-QSAR model was applied to analyse pharmacophore and to predict activity of other agonists of serotonin 5-HT2areceptors. Information obtained from the 3D-QSAR study indicated that presence of hydrogen bond donor and steric hot spot at a distance 14.80-15.20Å (v477:O-TIP), hydrophobic region and hydrogen bond donor at a distance of 2.40-2.86Å (v226:DRY-O), hydrogen bond donor and hydrogen bond acceptor at a distance of 1.60-2.00Å (v389:O-N1) and two hydrophobic regions at a distance 9.20-9.60Å (v23:DRY-DRY) are essential for agonistic activity on 5-HT2aserotonin receptors.

Drug discovery based on development of selective ligands for a specific target intended to modulate its activity and revert pathophysiological process is now recognized as too simplistic to design effective agent for complex multifactorial diseases, characterized by diverse physiological dysfunctions caused by deregulations of complex networks of proteins. Major challenge in modern drug discovery is to rationally design multitarget drugs able to specifically modulate only a group of desired targets while minimizing interactions with off-targets. Multifactorial cerebral mechanisms implicated in mental (psychiatrics) and neurodegenerative diseases and interactions of the neurotransmitter systems are two main reasons for applying polypharmacology ('multi-target') strategy in drug discovery for these complex brain diseases. In this paper we review polypharmacological profile and potential therapeutic application of dopamine D1-like receptor antagonists.

Vitamin E comprises of two families of compounds, tocopherols and tocotrienols. It is well known for its antioxidant activity, but recently special attention is paid to the use of vitamin E and its derivatives in the prevention and the treatment of cancer. Various derivatives of vitamin E are synthesized, which exhibit antiproliferative activity. It has been shown that the α-tocopherol ester with the amino acid lysine exhibits improved antiproliferative activity on MCF-7 breast cancer cell line as compared to commercially available preparations. The first stage was the synthesis of α-tocopherol ester with di-Cbz-lysine. Synthesis of ester was monitored by thin layer chromatography (mobile phase: n-hexane-ethyl acetate 3: 1,2 v/v) and the purification of product was done by dry flash column chromatography and by preparative plate chromatography (mobile phase: n-hexane-ethyl acetate 3: 1,2 v/v). In the second stage, Cbz protecting groups were removed by catalytic hydrogenation. The final product α- tocopheryl-lysine ester was detected by TLC (mobile phase: dichloromethane-methanolammonia 9 : 0,9 : 0,1 v/v).