Quantitative Structure-Activity Relationship Study For Different Peptides

Polypeptide drugs in the treatment of cancer,metabolic diseases,cardiovascular disease,infectious diseases,endocrine diseases,blood disease and pain relief and many other aspects have significant efficacy and wide application of the future.Compared with small molecular chemicals,peptide drugs are often more safe,less side effects,specificity,and rarely cause serious immune response.With the progress of chemistry and life sciences,in recent years,the development and listing of peptide drugs have gradually accelerated the trend.Quantitative structure activity relationship(QSAR)is a mathematical statistical method to quantitatively describe the relationship between the chemical structure information of a peptide drug or its analog and the specific peptide drug activity.The method of measuring the activity of peptide drugs is very costly and time consuming.Therefore,the QSAR of peptide drugs is of great significance in the development of peptide drugs.In the QSAR study,the most important is the characterization of the drug structure.Since the spatial structure and function information of the peptide drugs are mostly hidden in the primary structure amino acid sequence,the QSAR for the structural information and characterization of the amino acid in peptide drugs is essential.This paper includes the following three parts:Firstly,a new descriptor of amino acids-SVREW was derived from principal components analysis of 41 randic molecular profiles descriptors,44 eigenvalue-based indices descriptors and the matrix of 47 walk and path counts descriptors of amino acids.The structure of antimicrobial peptides,angiotensinconverting enzyme(ACE)inhibitors peptides,bitter tasting thresholds peptides,oxytocin,HLA-A*0201 restricted CTL epitope were characterized with SVREW.Using multiple linear regression(MLR)to establish a quantitative structureactivity relationship,at the same time,adopt the method of internal and external double verify the stability of the model.Studies showed that the MLR models constructed by SVREW descriptor had good fitting and predictive abilities.secondly,CoMFA,CoMSIA and HQSAR were used to explore the relationships between structures and activities of 150 angiotensin-converting enzyme(ACE).The results indicate that steric and electrostatic fields are main factors to inhibition performance.The mechanism of action of ACE and ACE enzyme inhibitory tri-peptides was studied by molecular docking.It showed that the activity of ACE enzyme inhibitory tri-peptides was mainly dependent on the steric and electrostatic.These information indicated that model generated form HQSAR,CoMSIA and CoMFA were reasonable,and had a good prediction ability.Which can guide the design of new potent inhibitors of ACE enzyme inhibitory peptides and express mechanism of mocular.In the end,by applying the three-dimensional holographic vector of atomic interaction field(3D-HoVAIF)to express the structure of bitter tasting threshold of dipeptide,the QSAR model was built by the MLR.The results show that 3DHoVAIF is superior to the traditional amino acid descriptor for bitter tasting threshold of dipeptides due to the high predictive ability.Thus,it can provide guidance for the new active peptide drug molecular design and modification.