Artificial intelligence: Machine learning approach for screening large database and drug discovery

Recent research in drug discovery dealing with many faces difficulties, including development of new drugs during disease outbreak and drug resistance due to rapidly accumulating mutations. Virtual screening is the most widely used method in computer aided drug discovery. It has a prominent ability in screening drug targets from large molecular databases. Recently, a number of web servers have developed for quickly screening publicly accessible chemical databases. In a nutshell, deep learning algorithms and artificial neural networks have modernised the field. Several drug discovery processes have used machine learning and deep learning algorithms, including peptide synthesis, structure-based virtual screening, ligand-based virtual screening, toxicity prediction, drug monitoring and release, pharmacophore modelling, quantitative structure-activity relationship, drug repositioning, polypharmacology, and physiochemical activity. Although there are presently a wide variety of data-driven AI/ML tools available, the majority of these tools have, up to this point, been developed in the context of non-communicable diseases like cancer, and a number of obstacles have prevented the translation of these tools to the discovery of treatments against infectious diseases. In this review various aspects of AI and ML in virtual screening of large databases were discussed. Here, with an emphasis on antivirals as well as other disease, offers a perspective on the advantages, drawbacks, and hazards of AI/ML techniques in the search for innovative treatments.

Protein-protein interaction of LDH and CRP-1 with hematotoxin snake venom proteins of all species of snake: An in silico approach

Objective

Snake bite-induced elevation of serum LDH and CRP-1 is considered as useful biomarkers of hemotoxic. The snake venom contains proteins and may result in various envenomation such as bleeding, inflammation, and pain, cytotoxic, cardiotoxic, or neurotoxic effects. This in silico study was aimed to screen the snake venom proteins and to find out the most interactive hemotoxic venom protein against LDH and CRP-1 proteins as biomarkers.

Materials and Methods

To validate the hypothesis of the prospective interaction of snake venom proteins, molecular docking analysis was used in the current work by deploying a cutting-edge docking program. Snake venom peptides were screened from literature and both peptide as well as target protein were obtained from PDB. HDOCK online server was used for the molecular docking analysis of target proteins with hemotoxic snake venom peptides. Further, the toxicity properties of each docked complex of target proteins were subjected for ADME/T analysis.

Results

The selected snake venom peptides were subjected to molecular docking study and the results generated from computational-based approach reveals that all the hematotoxin snake venom proteins are interactive with LDH and CRP-1 peptide. Further, this study indicates that snake venom metalloproteinase (SVMPS) peptide may be considered as the best interactive protein with both LDH and CRP-1 proteins; also, ADME/T screening revealed that all docked complex are safe and follow toxicity properties.

Conclusion

This in silico study clearly shows that the greatest interaction of SVMPS peptide with LDH and CRP-1 may be due to strong binding in the active site of the target proteins LDH and CRP-1 with SVMPS. Results, further, confirmed LDH and CRP-1 as potential biomarkers against hemotoxic snake venoms. This study should be validated by in vitro and in vivo analysis as well as specific species snake venom should be assessed. For further studies, SVMPS can be consider as therapeutic point of view.

Effect of Mucuna pruriens on brain NMDA receptor and tau protein gene expression in cerebral ischemic rats

Present study aimed to assess effect of pre-treatment with Mucuna pruriens seed extract and its bioactive molecule(s) on NMDAR and Tau protein gene expression in cerebral ischemic rodent model. Methanol extract of M. pruriens seeds was characterized by HPLC, and β-sitosterol was isolated by flash chromatography. In vivo studies to observe the effect of pre-treatment (28 days) with methanol extract of M. pruriens seed and β-sitosterol on the unilateral cerebral ischemic rat model. Cerebral ischemia induced by left common carotid artery occlusion (LCCAO) for 75 min (on day 29) followed by reperfusion for 12 h. Rats (n = 48) divided into four groups. GroupI (control,Untreated + LCCAO)-No pre-treatment + cerebral ischemia; GroupII(β-sitosterol + Sham)-pre-treatment with β-sitosterol, 10 mg/kg/day + sham-operated; GroupIII(β-sitosterol + LCCAO)-pre-treatment with β-sitosterol, 10 mg/kg/day + cerebral ischemia; GroupIV(methanol extract + LCCAO)-pre-treatment with methanol extract of M. pruriens seeds, 50 mg/kg/day + cerebral ischemia. Neurological deficit score was assessed just before sacrifice. Experimental animals were sacrificed after 12 h reperfusion. Brain histopathology was performed. Gene expression of NMDAR and Tau protein of left cerebral hemisphere (occluded side) was performed by RT-PCR. Results revealed that the neurological deficit score was lower in groups III and IV compared to group I. NMDAR and tau protein mRNA expression in left cerebral hemisphere were upregulated in Group I, downregulated in groups III and IV. Histopathology of left cerebral hemisphere (occluded side) in Group I showed features of ischemic brain damage. Groups III and IV, left cerebral hemisphere showed less ischemic damage compared GroupI. Right cerebral hemisphere showed no areas of ischemia-induced brain changes. Pre-treatment with β-sitosterol and methanol extract of M. pruriens seeds may reduce ischemic brain injury following unilateral common carotid artery occlusion in rats.

Screening ,development of Transglutaminase-2 Inhibitors and its derivative as anti-lung cancer agent by insilico and invitro approach

AIM

Screening and development of TG2 inhibitors as anti lung cancer agent.

BACKGROUND

Transglutaminase 2 (TG2) is multifunctional and ubiquitously expressed protein from transglutaminase family. It takes part in various cellular processes and plays an important role in the pathogenesis of autoimmune, neurodegerative and also cancer.

OBJECTIVE

The of proposed study is to focused on screening of potent inhibitors of TG2 by in-silico method and synthesis its derivative as well as analysis of its activity by invitro approach.

MATERIAL AND METHODS

Molecular docking studies have been carried on the different classes of TG2 inhibitors against the target protein. Nearly thirty TG2 inhibitors were selected from literature and docking was performed against transglutaminase 2. The computational ADME property screening was also carried out to check their pharmacokinetic properties. The compounds which exhibited positive ADME properties with good interaction with possessing least binding energy were further validated for their anti-lung cancer inhibition property against A549 cell lines by cytotoxicity studies.

RESULTS

The results of present study indicate that the docked complex formed by cystamine showed better binding affinity towards target protein so, this derivative of cystamine is formed using 2,5 dihydrobenzoic acid. Invitro results revealed that both molecule proved good cytotoxic agent against A549 lung cancer (875.10, 553.22 µg/ml) respectively. Further its activity should be validated on TG2 expressing lung cancer.

CONCLUSION

Cystamine and its derivative can be act as potential therapeutic target for lung cancer but further its activity should be validated on TG2 expressing lung cancer.