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DNA double strand-breaks (DSBs) are the most deleterious lesions that can affect the genome of living beings and are lethal if not quickly and properly repaired. Recently, N-phenyl ureidobenzenesulfonates (PUB-SOs) as tubulin inhibitors that are blocking the cells cycle progression in S-phase and inducing DNA DSBs is discovered. Here, a set of PUB-SOs derivatives were applied to quantitative structural activity relationship (QSAR) analysis. A series of chemometrics methods like MLR, FA- MLR, PCR and partial least squared included in variable selection genetic algorithm (GA-PLS) were used for relations between structural features of these compounds and their anti-proliferative activity against MCF-7 cell line. New potent lead compounds were also designed based on new structural patterns using in silico-screening study. Molecular docking studies of these compounds on DNA and tubulin were conducted. The results obtained from validated docking protocol indicate that the important amino acids inside the active site cavity that are in charge of essential interactions with tubulin are Ala30, Lys B254, Asn B258, Met B259, Asn A101, Glu A183, Thr A179, Leu B255, Ser A178 and Gln B247. And the most important base pairs inside the minor groove of DNA being responsible for essential interclation with DNA are G2, G4, G10, G12, A5, A6, C9 and C11 base pairs.

DNA double strand-breaks (DSBs) are the most deleterious lesions that can affect the genome of living beings and are lethal if not quickly and properly repaired. Recently, N-phenyl ureidobenzenesulfonates (PUB-SOs) as tubulin inhibitors that are blocking the cells cycle progression in S-phase and inducing DNA DSBs is discovered. Here, a set of PUB-SOs derivatives were applied to quantitative structural activity relationship (QSAR) analysis. A series of chemometrics methods like MLR, FA- MLR, PCR and partial least squared included in variable selection genetic algorithm (GA-PLS) were used for relations between structural features of these compounds and their anti-proliferative activity against MCF-7 cell line. New potent lead compounds were also designed based on new structural patterns using in silico-screening study. Molecular docking studies of these compounds on DNA and tubulin were conducted. The results obtained from validated docking protocol indicate that the important amino acids inside the active site cavity that are in charge of essential interactions with tubulin are Ala30, Lys B254, Asn B258, Met B259, Asn A101, Glu A183, Thr A179, Leu B255, Ser A178 and Gln B247. And the most important base pairs inside the minor groove of DNA being responsible for essential interclation with DNA are G2, G4, G10, G12, A5, A6, C9 and C11 base pairs.

Proper docking protocols were presented for three known enzyme structures, human betasecretase (BACE1), Aromatase and pyruvate dehydogenase kinase (PDHK) using Autodock4.2 and Vina softwares. The validity of docking protocols was verified using a set of known active ligands and decoys for all three enzymes. Different energy minimization algorithms were performed prior to docking of each ligand in order to find out by which method a more reasonable correlation between binding energy and corresponding experimental activity of the compounds was obtained. The highest ROCAUC value was 0.916, 0.914 and 0. 833 when MM+-PM3 methods were applied as minimization method, whereas without minimization it was 0.127, 0.187, and 0.51 for PDHK, BACE-1 and aromatase, respectively. So a combination of molecular mechanics (MM+) and a semi-empirical method (PM3 or AM1) could promote the docking protocol in case of all targets. Protein ligand interaction studies using self-organizing map (SOM) were also conducted in order to reveal the validity of docking protocol and to evaluate its predictive ability in terms of distinguishing between ligands and decoys.

Proper docking protocols were presented for three known enzyme structures, human betasecretase (BACE1), Aromatase and pyruvate dehydogenase kinase (PDHK) using Autodock4.2 and Vina softwares. The validity of docking protocols was verified using a set of known active ligands and decoys for all three enzymes. Different energy minimization algorithms were performed prior to docking of each ligand in order to find out by which method a more reasonable correlation between binding energy and corresponding experimental activity of the compounds was obtained. The highest ROCAUC value was 0.916, 0.914 and 0. 833 when MM+-PM3 methods were applied as minimization method, whereas without minimization it was 0.127, 0.187, and 0.51 for PDHK, BACE-1 and aromatase, respectively. So a combination of molecular mechanics (MM+) and a semi-empirical method (PM3 or AM1) could promote the docking protocol in case of all targets. Protein ligand interaction studies using self-organizing map (SOM) were also conducted in order to reveal the validity of docking protocol and to evaluate its predictive ability in terms of distinguishing between ligands and decoys.

Dichloroacetate (DCA) is a pyruvate mimetic compound that stimulates the activity of the enzyme pyruvate dehydrogenase (PDH) through inhibition of the enzyme pyruvate dehydrogenase kinases (PDK1-4). DCA works by turning on the apoptosis which is suppressed in tumor cells, hence let them to die on their own. Here, in this paper a series of DCA analogues were applied to quantitative structure–activity relationship (QSAR) analysis. A collection of chemometrics methods such as multiple linear regression (MLR), factor analysis–based multiple linear regression (FA-MLR), principal component regression (PCR), simple Free-Wilson analysis (FWA) and partial least squared combined with genetic algorithm for variable selection (GA-PLS) were conducted to make relations between structural features and cytotoxic activities of a variety of DCA derivatives. The best multiple linear regression equation obtained from genetic algorithms partial least squares which predict 91% of variances. On the basis of the produced model, an in silico-screening study was also employed and new potent lead compounds based on new structural patterns were suggested. Docking studies of these compounds were also investigated and promising results were obtained. The docking results were also conducted to protein ligand interaction fingerprints (PLIF) studies using self-organizing map (SOM) in order to evaluate the predictive ability in suggesting new potent compounds and some compounds were introduced as a good candidates for synthesis.

Dichloroacetate (DCA) is a pyruvate mimetic compound that stimulates the activity of the enzyme pyruvate dehydrogenase (PDH) through inhibition of the enzyme pyruvate dehydrogenase kinases (PDK1-4). DCA works by turning on the apoptosis which is suppressed in tumor cells, hence let them to die on their own. Here, in this paper a series of DCA analogues were applied to quantitative structure–activity relationship (QSAR) analysis. A collection of chemometrics methods such as multiple linear regression (MLR), factor analysis–based multiple linear regression (FA-MLR), principal component regression (PCR), simple Free-Wilson analysis (FWA) and partial least squared combined with genetic algorithm for variable selection (GA-PLS) were conducted to make relations between structural features and cytotoxic activities of a variety of DCA derivatives. The best multiple linear regression equation obtained from genetic algorithms partial least squares which predict 91% of variances. On the basis of the produced model, an in silico-screening study was also employed and new potent lead compounds based on new structural patterns were suggested. Docking studies of these compounds were also investigated and promising results were obtained. The docking results were also conducted to protein ligand interaction fingerprints (PLIF) studies using self-organizing map (SOM) in order to evaluate the predictive ability in suggesting new potent compounds and some compounds were introduced as a good candidates for synthesis.